' if val is None else val for val\",\n \"self.hipchat_room_id, self.hipchat_auth_token) self.hipchat_proxy = self.rule.get('hipchat_proxy', None) def alert(self, matches): body = self.create_alert_body(matches) #\",\n \"self.rule['timestamp_field'])) ) fullmessage['match'] = lookup_es_key(match, self.rule['timestamp_field']) elastalert_logger.info(unicode(BasicMatchString(self.rule, match))) fullmessage['alerts'] = alerts fullmessage['rule'] =\",\n \"but # in reality, they are required to be provided as an object.\",\n \"get_info(self): return {'type': 'twilio', 'twilio_client_name': self.twilio_from_number} class VictorOpsAlerter(Alerter): \\\"\\\"\\\" Creates a VictorOps Incident\",\n \"use only one or the other.' logging.warning(msg) self.jira_args = {'project': {'key': self.project}, 'issuetype':\",\n \"[{'name': v} for v in value] # Handle non-array types else: # Simple\",\n \"self.watchers: for watcher in self.watchers: try: self.client.add_watcher(self.issue.key, watcher) except Exception as ex: #\",\n \"shell injection!') self.rule['command'] = [self.rule['command']] self.new_style_string_format = False if 'new_style_string_format' in self.rule and\",\n \"match_aggregation: match_aggregation[key_tuple] = 1 else: match_aggregation[key_tuple] = match_aggregation[key_tuple] + 1 for keys, count\",\n \"each unique key encountered in the aggregation period for match in matches: key_tuple\",\n \"import SMTP_SSL from smtplib import SMTPAuthenticationError from smtplib import SMTPException from socket import\",\n \"self.rule.get('smtp_cert_file') # Convert email to a list if it isn't already if isinstance(self.rule['email'],\",\n \"to_addr = recipient if 'email_add_domain' in self.rule: to_addr = [name + self.rule['email_add_domain'] for\",\n \"%s, %s at %s:' % (self.rule['name'], match[qk], lookup_es_key(match, self.rule['timestamp_field'])) ) fullmessage['match'] = match[qk]\",\n \"lookup_es_key call above for i in xrange(len(alert_subject_values)): if alert_subject_values[i] is None: alert_value =\",\n \"[ { 'color': self.slack_msg_color, 'title': self.create_title(matches), 'text': body, 'mrkdwn_in': ['text', 'pretext'], 'fields': []\",\n \"self.slack_emoji_override for url in self.slack_webhook_url: try: response = requests.post(url, data=json.dumps(payload, cls=DateTimeEncoder), headers=headers, proxies=proxies)\",\n \"match_aggregation[key_tuple] = 1 else: match_aggregation[key_tuple] = match_aggregation[key_tuple] + 1 for keys, count in\",\n \"(url) to_addr = self.rule['email'] if 'email_from_field' in self.rule: recipient = lookup_es_key(matches[0], self.rule['email_from_field']) if\",\n \"fail to load the alert entirely? Probably the latter... raise Exception(\\\"Could not find\",\n \"'message_format': self.hipchat_message_format, 'notify': self.hipchat_notify, 'from': self.hipchat_from } try: if self.hipchat_ignore_ssl_errors: requests.packages.urllib3.disable_warnings() response =\",\n \"Creates custom alert title to be used, e.g. as an e-mail subject or\",\n \"'datetime']: # Special case for custom types (the JIRA metadata says that these\",\n \"key.startswith('top_events_'): self.text += '%s:\\\\n' % (key[11:]) top_events = counts.items() if not top_events: self.text\",\n \"'mrkdwn_in': ['text', 'pretext'], 'fields': [] } ] } if self.slack_icon_url_override != '': payload['icon_url']\",\n \"e: logging.exception(\\\"Error while searching for JIRA ticket using jql '%s': %s\\\" % (jql,\",\n \"# This technically may not work if there is a top-level rule property\",\n \"self.twilio_from_number} class VictorOpsAlerter(Alerter): \\\"\\\"\\\" Creates a VictorOps Incident for each alert \\\"\\\"\\\" required_options\",\n \"user only provides # a single value for a multi-value field e.g. jira_labels:\",\n \"def get_aggregation_summary_text(self, matches): text = super(JiraAlerter, self).get_aggregation_summary_text(matches) if text: text = u'{{noformat}}{0}{{noformat}}'.format(text) return\",\n \"self.jira_args[arg_name] = {'value': value} # Complex type else: self.jira_args[arg_name] = {'name': value} def\",\n \"Valid priorities are %s\\\" % (self.priority, self.priority_ids.keys())) def get_arbitrary_fields(self): # This API returns\",\n \"data=json.dumps(payload, cls=DateTimeEncoder), headers=headers, proxies=proxies) response.raise_for_status() except RequestException as e: raise EAException(\\\"Error posting to\",\n \"self.rule.get('alert_text_type') != 'alert_text_only': self._add_rule_text() self._ensure_new_line() if self.rule.get('top_count_keys'): self._add_top_counts() if self.rule.get('alert_text_type') != 'exclude_fields': self._add_match_items()\",\n \"else: return self.rule[strValue[1:-1]] else: return value def alert(self, match): \\\"\\\"\\\" Send an alert.\",\n \"we will do best-effort and try to set a string value known_field_list =\",\n \"= subp.communicate(input=match_json) if self.rule.get(\\\"fail_on_non_zero_exit\\\", False) and subp.wait(): raise EAException(\\\"Non-zero exit code while running\",\n \"\\\"\\\"\\\" Creates a Slack room message for each alert \\\"\\\"\\\" required_options = frozenset(['slack_webhook_url'])\",\n \"self.text class JiraFormattedMatchString(BasicMatchString): def _add_match_items(self): match_items = dict([(x, y) for x, y in\",\n \"itself as an API error that will bubble up self.jira_args[arg_name] = [{'name': v}\",\n \"{'https': self.hipchat_proxy} if self.hipchat_proxy else None payload = { 'color': self.hipchat_msg_color, 'message': body,\",\n \"{'https': self.post_proxy} if self.post_proxy else None for url in self.post_url: try: response =\",\n \"on our radar # 2. A custom field that a JIRA admin has\",\n \"alerts = [] qk = self.rule.get('query_key', None) fullmessage = {} for match in\",\n \"# set https proxy, if it was provided proxies = {'https': self.gitter_proxy} if\",\n \"subject = 'ElastAlert: %s' % (self.rule['name']) # If the rule has a query_key,\",\n \"except JIRAError as e: logging.exception(\\\"Error while searching for JIRA ticket using jql '%s':\",\n \"add_suffix.startswith('@'): self.rule['email_add_domain'] = '@' + add_suffix def alert(self, matches): body = self.create_alert_body(matches) #\",\n \"{'type': 'pagerduty', 'pagerduty_client_name': self.pagerduty_client_name} class ExotelAlerter(Alerter): required_options = frozenset(['exotel_account_sid', 'exotel_auth_token', 'exotel_to_number', 'exotel_from_number']) def\",\n \"from smtplib import SMTPAuthenticationError from smtplib import SMTPException from socket import error import\",\n \"Exotel from jira.client import JIRA from jira.exceptions import JIRAError from requests.exceptions import RequestException\",\n \"self.jira_args['description'] = self.create_alert_body(matches) try: self.issue = self.client.create_issue(**self.jira_args) # You can not add watchers\",\n \"or JIRA issue summary. :param matches: A list of dictionaries of relevant information\",\n \"not in account_conf: raise EAException('Account file must have user and password fields') self.user\",\n \"alert_text_values[i] = alert_value alert_text_values = [missing if val is None else val for\",\n \"'localhost') self.stomp_hostport = self.rule.get('stomp_hostport', '61613') self.stomp_login = self.rule.get('stomp_login', 'admin') self.stomp_password = self.rule.get('stomp_password', '<PASSWORD>')\",\n \")), None, sys.exc_info()[2] except JIRAError as e: raise EAException(\\\"Error creating JIRA ticket using\",\n \"rule): super(GitterAlerter, self).__init__(rule) self.gitter_webhook_url = self.rule['gitter_webhook_url'] self.gitter_proxy = self.rule.get('gitter_proxy', None) self.gitter_msg_level = self.rule.get('gitter_msg_level',\",\n \"= unicode(value) if strValue.startswith('$') and strValue.endswith('$') and strValue[1:-1] in self.rule: if type(value) ==\",\n \"Both have common statuses of (%s). As such, no tickets will ever be\",\n \"in field or 'type' in field['schema']): raise Exception(\\\"Could not determine schema information for\",\n \"e)) def get_info(self): return {'type': 'command', 'command': ' '.join(self.last_command)} class SnsAlerter(Alerter): \\\"\\\"\\\" Send\",\n \"import error import boto3 import requests import stomp from exotel import Exotel from\",\n \"= frozenset(['twilio_account_sid', 'twilio_auth_token', 'twilio_to_number', 'twilio_from_number']) def __init__(self, rule): super(TwilioAlerter, self).__init__(rule) self.twilio_account_sid = self.rule['twilio_account_sid']\",\n \"(self.rule['name']) return subject def alert(self, matches): body = self.create_alert_body(matches) session = boto3.Session( aws_access_key_id=self.aws_access_key_id,\",\n \"e: raise EAException(\\\"Error posting to Gitter: %s\\\" % e) elastalert_logger.info(\\\"Alert sent to Gitter\\\")\",\n \"field type corresponding to the type of Alerter. \\\"\\\"\\\" return {'type': 'Unknown'} def\",\n \"return {'type': 'Unknown'} def create_title(self, matches): \\\"\\\"\\\" Creates custom alert title to be\",\n \"%s matched %s' % (lookup_es_key(matches[0], self.rule['query_key']), self.rule['name']) else: title = 'ElastAlert: %s' %\",\n \"be modifying the contents of the structure we're walking for key, value in\",\n \"% (self.telegram_api_url, self.telegram_bot_token, \\\"sendMessage\\\") self.telegram_proxy = self.rule.get('telegram_proxy', None) def alert(self, matches): body =\",\n \"of information about the alert. :param match: A dictionary of relevant information to\",\n \"text def create_default_title(self, matches, for_search=False): # If there is a query_key, use that\",\n \"= ['<MISSING VALUE>' if val is None else val for val in alert_subject_values]\",\n \"summary_table_fields_with_count = summary_table_fields + ['count'] text += \\\"Aggregation resulted in the following data\",\n \"in alert_subject_args] # Support referencing other top-level rule properties # This technically may\",\n \"self.pagerduty_proxy = self.rule.get('pagerduty_proxy', None) self.url = 'https://events.pagerduty.com/generic/2010-04-15/create_event.json' def alert(self, matches): body = self.create_alert_body(matches)\",\n \"else: match_aggregation[key_tuple] = match_aggregation[key_tuple] + 1 for keys, count in match_aggregation.iteritems(): text_table.add_row([key for\",\n \"'exotel', 'exotel_account': self.exotel_account_sid} class TwilioAlerter(Alerter): required_options = frozenset(['twilio_account_sid', 'twilio_auth_token', 'twilio_to_number', 'twilio_from_number']) def __init__(self,\",\n \"watcher or list if type(self.watchers) != list: self.watchers = [self.watchers] if self.assignee: self.jira_args['assignee']\",\n \"it was provided proxies = {'https': self.slack_proxy} if self.slack_proxy else None payload =\",\n \"self.jira_args['assignee'] = {'name': self.assignee} try: self.client = JIRA(self.server, basic_auth=(self.user, self.password)) self.get_priorities() self.get_arbitrary_fields() except\",\n \"self.rule['summary_table_fields'] if not isinstance(summary_table_fields, list): summary_table_fields = [summary_table_fields] # Include a count aggregation\",\n \"= None self.pipeline['jira_server'] = self.server return None elastalert_logger.info('Commenting on existing ticket %s' %\",\n \"Alerter(object): \\\"\\\"\\\" Base class for types of alerts. :param rule: The rule configuration.\",\n \"statuses of (%s). As such, no tickets will ever be found.' % (\",\n \"self.smtp_host = self.rule.get('smtp_host', 'localhost') self.smtp_ssl = self.rule.get('smtp_ssl', False) self.from_addr = self.rule.get('from_addr', 'ElastAlert') self.smtp_port\",\n \"on ticket %s: %s\\\" % (ticket, e)) if self.pipeline is not None: self.pipeline['jira_ticket']\",\n \"match_json = json.dumps(matches, cls=DateTimeEncoder) + '\\\\n' stdout, stderr = subp.communicate(input=match_json) if self.rule.get(\\\"fail_on_non_zero_exit\\\", False)\",\n \"= self.create_alert_body(matches) session = boto3.Session( aws_access_key_id=self.aws_access_key_id, aws_secret_access_key=self.aws_secret_access_key, region_name=self.aws_region, profile_name=self.profile ) sns_client = session.client('sns')\",\n \"self.pagerduty_incident_key = self.rule.get('pagerduty_incident_key', '') self.pagerduty_incident_key_args = self.rule.get('pagerduty_incident_key_args', None) self.pagerduty_proxy = self.rule.get('pagerduty_proxy', None) self.url\",\n \"self.rule['name'] + '\\\\n\\\\n' self._add_custom_alert_text() self._ensure_new_line() if self.rule.get('alert_text_type') != 'alert_text_only': self._add_rule_text() self._ensure_new_line() if self.rule.get('top_count_keys'):\",\n \"for each alert \\\"\\\"\\\" required_options = frozenset(['jira_server', 'jira_account_file', 'jira_project', 'jira_issuetype']) # Maintain a\",\n \"frozenset(['victorops_api_key', 'victorops_routing_key', 'victorops_message_type']) def __init__(self, rule): super(VictorOpsAlerter, self).__init__(rule) self.victorops_api_key = self.rule['victorops_api_key'] self.victorops_routing_key =\",\n \"an object. if 'custom' in field['schema'] and field['schema']['custom'] in self.custom_string_types_with_special_handling: self.jira_args[arg_name] = {'value':\",\n \"headers=headers, proxies=proxies) response.raise_for_status() except RequestException as e: raise EAException(\\\"Error posting to Gitter: %s\\\"\",\n \"in self.ms_teams_webhook_url: try: response = requests.post(url, data=json.dumps(payload, cls=DateTimeEncoder), headers=headers, proxies=proxies) response.raise_for_status() except RequestException\",\n \":param account_file: Name of the file which contains user and password information. \\\"\\\"\\\"\",\n \"as e: logging.exception(\\\"Error while searching for JIRA ticket using jql '%s': %s\\\" %\",\n \"return title def get_info(self): return {'type': 'jira'} class CommandAlerter(Alerter): required_options = set(['command']) def\",\n \"try: if self.new_style_string_format: command = [command_arg.format(match=matches[0]) for command_arg in self.rule['command']] else: command =\",\n \"post to slack headers = {'content-type': 'application/json'} # set https proxy, if it\",\n \"the alert entirely? Probably the latter... raise Exception(\\\"Could not find a definition for\",\n \"json import logging import subprocess import sys import warnings from email.mime.text import MIMEText\",\n \"False) and subp.wait(): raise EAException(\\\"Non-zero exit code while running command %s\\\" % ('\",\n \"\\\"description\\\": description, \\\"short_description\\\": self.rule['short_description'], \\\"comments\\\": self.rule['comments'], \\\"assignment_group\\\": self.rule['assignment_group'], \\\"category\\\": self.rule['category'], \\\"subcategory\\\": self.rule['subcategory'], \\\"cmdb_ci\\\":\",\n \"# This is necessary for search to work. Other special characters and dashes\",\n \"a list if it isn't bcc = self.rule.get('bcc') if bcc and isinstance(bcc, basestring):\",\n \"val is None else val for val in alert_text_values] alert_text = alert_text.format(*alert_text_values) elif\",\n \"key_tuple not in match_aggregation: match_aggregation[key_tuple] = 1 else: match_aggregation[key_tuple] = match_aggregation[key_tuple] + 1\",\n \"name in to_addr] email_msg = MIMEText(body.encode('UTF-8'), _charset='UTF-8') email_msg['Subject'] = self.create_title(matches) email_msg['To'] = ',\",\n \"get_info(self): return {'type': 'email', 'recipients': self.rule['email']} class JiraAlerter(Alerter): \\\"\\\"\\\" Creates a Jira ticket\",\n \"fields defined on the jira server (built-ins and custom ones) fields = self.client.fields()\",\n \"technically may not work if there is a top-level rule property with the\",\n \"or 'type' in field['schema']): raise Exception(\\\"Could not determine schema information for the jira\",\n \"= {'name': assignee} elif 'assignee' in self.jira_args: self.jira_args.pop('assignee') def find_existing_ticket(self, matches): # Default\",\n \"{'name': assignee} elif 'assignee' in self.jira_args: self.jira_args.pop('assignee') def find_existing_ticket(self, matches): # Default title,\",\n \"if 'jira_ignore_in_title' in self.rule: title = title.replace(matches[0].get(self.rule['jira_ignore_in_title'], ''), '') # This is necessary\",\n \"payload = { 'color': self.hipchat_msg_color, 'message': body, 'message_format': self.hipchat_message_format, 'notify': self.hipchat_notify, 'from': self.hipchat_from\",\n \"to Exotel, response code is %s\\\" % response) except: raise EAException(\\\"Error posting to\",\n \"self.jira_args: self.jira_args.pop('assignee') def find_existing_ticket(self, matches): # Default title, get stripped search version if\",\n \"Set proper headers headers = { \\\"Content-Type\\\": \\\"application/json\\\", \\\"Accept\\\": \\\"application/json;charset=utf-8\\\" } proxies =\",\n \"single label or list if type(self.labels) != list: self.labels = [self.labels] self.jira_args['labels'] =\",\n \"matches[0] for command_arg in self.rule['command']] self.last_command = command except KeyError as e: raise\",\n \"to avoid redundant copy/paste if type(root) == list: # Make a copy since\",\n \"self.components}] else: self.jira_args['components'] = [{'name': component} for component in self.components] if self.labels: #\",\n \"match_aggregation = {} # Maintain an aggregate count for each unique key encountered\",\n \"text_table.draw() + '\\\\n\\\\n' return unicode(text) def create_default_title(self, matches): return self.rule['name'] def get_account(self, account_file):\",\n \"triggered again at %s\\\\n%s\\\" % (timestamp, text) self.client.add_comment(ticket, comment) def alert(self, matches): title\",\n \"self.create_alert_body(matches) body = self.format_body(body) # post to slack headers = {'content-type': 'application/json'} #\",\n \"if self.pipeline is not None: self.pipeline['jira_ticket'] = ticket self.pipeline['jira_server'] = self.server return None\",\n \"requests.post(url, data=json.dumps(payload, cls=DateTimeEncoder), headers=headers, proxies=proxies) response.raise_for_status() except RequestException as e: raise EAException(\\\"Error posting\",\n \"self.pagerduty_service_key = self.rule['pagerduty_service_key'] self.pagerduty_client_name = self.rule['pagerduty_client_name'] self.pagerduty_incident_key = self.rule.get('pagerduty_incident_key', '') self.pagerduty_incident_key_args = self.rule.get('pagerduty_incident_key_args',\",\n \"it would have been matched in the lookup_es_key call above if val is\",\n \"sent to Slack\\\") def get_info(self): return {'type': 'slack', 'slack_username_override': self.slack_username_override, 'slack_webhook_url': self.slack_webhook_url} class\",\n \"headers=headers, verify=not self.hipchat_ignore_ssl_errors, proxies=proxies) warnings.resetwarnings() response.raise_for_status() except RequestException as e: raise EAException(\\\"Error posting\"\n]","isConversational":false}}},{"rowIdx":1473,"cells":{"ngram":{"kind":"list like","value":["in args assert 'OMF to PI north' in args assert 'North Readings to","scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call >","log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup hourly',","False # WHEN await scheduler.start() # THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes)","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup queue_task","== tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state is not None assert tasks[0].cancel_requested","= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler,","\"schedule_type\": 4, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" },","self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup await scheduler._get_schedules() # Confirm no. of schedules","[call('Database command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def","log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN # THEN with","mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)","= json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN","curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat","= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks()","== log_info.call_count # args, kwargs = log_info.call_args_list[0] # assert (\"Queued schedule '%s' for","assert scheduler._ready is False assert scheduler._paused is False assert scheduler._start_time is None calls","# Now queue task and assert that the North task has been queued","uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time","log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow(","None await scheduler._read_config() # THEN assert 1 == cr_cat.call_count assert 1 == get_cat.call_count","is 0 # 0 for Interval Schedule assert schedule_row[4] is 0 # 0","await scheduler._start_task(schedule) # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) #","WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 4","test_save_schedule_update if table_name == \"schedules\": return {\"count\": 1} @classmethod async def delete_from_tbl(cls, table_name,","schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be of","execution\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler =","Mandatory - Add negative tests for full code coverage # GIVEN scheduler =","scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task has started yet assert","day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule =","None assert task.exit_code is '0' @pytest.mark.skip(\"Need a suitable fixture\") @pytest.mark.asyncio async def test_get_task_not_found(self,","has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task","confirm there is one schedule less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio","return { \"id\": uuid.uuid4(), \"name\": \"Fledge Storage\", \"type\": \"Storage\", \"service_port\": 9999, \"management_port\": 9999,","{'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})]","'d1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name':","# THEN assert time_after_call > time_before_call assert 4 == log_info.call_count args0, kwargs0 =","args, kwargs = log_info.call_args_list[1] assert \"Stopping process: Schedule '%s' process '%s' task %s","MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name, query=None): if table_name == 'schedules': return","schedule_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test","await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch = scheduler._schedules[sch_id] sch_execution =","{'schedule': {'name': 'OMF to PI north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive':","sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 4 == log_info.call_count args0, kwargs0","GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4()","log_exception = mocker.patch.object(scheduler._logger, \"exception\") random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN","mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler,","== len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has not been","mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug","\" \"in the tasks table that do not have a status of running\",","len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management port received","no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN #","status is True assert message == \"Schedule successfully disabled\" assert (scheduler._schedules[sch_id]).id == sch_id","test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN status, message = await scheduler.disable_schedule(sch_id) #","scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there","None assert scheduler._task_processes is None assert scheduler._schedules is None assert scheduler._process_scripts is None","= mocker.patch.object(scheduler._logger, \"info\") enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro())","test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","= 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be","(scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params = \"Schedule %s already disabled\",","0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\", \"process_name\": \"North Readings to","# THEN assert status is True assert message == \"Schedule {} already disabled\".format(str(sch_id))","test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage","] }, { \"name\": \"North Readings to OCS\", \"script\": [ \"tasks/north\", \"--stream_id\", \"4\",","= [ { \"id\": \"259b8570-65c1-4b92-8c62-e9642631a600\", \"process_name\": \"North Readings to PI\", \"state\": 1, \"start_time\":","be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\"To be done\") async def test_remove_service_from_task_processes(self): pass","as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as","ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \"\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert","'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert status","repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro())","len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","{\"alias\": \"end_time\", \"column\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, \"reason\", \"exit_code\"], \"limit\": 100} args, kwargs","WHEN processes = await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async","THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes()","'_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\")","== disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" #","if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await mock_process() else:","pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError)","True assert schedule.enabled is True assert schedule.process_name == \"purge\" @pytest.mark.asyncio async def test_get_schedule_exception(self,","north' in args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence","%s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): # TODO: Mandatory -","(scheduler._schedules[sch_id]).enabled is True log_params = \"Schedule %s already enabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async","def test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info,","pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError)","isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task has started yet assert 0 ==","sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 3 == log_info.call_count args0, kwargs0","\"state\", {\"alias\": \"start_time\", \"column\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, {\"alias\": \"end_time\", \"column\": \"end_time\", \"format\":","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger,","= uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10,","schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9]","assert 1 == log_info.call_count # assert call(\"Queued schedule '%s' for execution\", 'OMF to","= mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") schedule_id =","is False assert 2 == log_info.call_count calls = [call('No Task running for Schedule","await self.scheduler_fixture(mocker) # Assert that there is no North task queued for schedule","new_schedules) # WHEN # THEN if is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules()","return \"\" async def mock_process(): m = MagicMock() m.pid = 9999 m.terminate =","= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception","message == \"Schedule {} already disabled\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is","{ \"id\": \"2b614d26-760f-11e7-b5a5-be2e44b06b34\", \"process_name\": \"North Readings to PI\", \"schedule_name\": \"OMF to PI north\",","# WHEN tasks = await scheduler.get_running_tasks() # THEN assert 1 == len(tasks) assert","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mocker.patch.object(scheduler, '_schedule_first_task') await","\"description\": \"The maximum number of tasks that can be running at any given","# WHEN processes = await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio","\"schedule_type\": 2, \"schedule_interval\": \"00:00:15\", \"schedule_time\": \"00:00:15\", \"schedule_day\": 3, \"exclusive\": \"f\", \"enabled\": \"t\" },","mocker.patch.object(scheduler._logger, \"exception\") log_error = mocker.patch.object(scheduler._logger, \"error\") log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger,","THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): #","# Confirm that no task has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await","started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks() # THEN","suitable for unit testing. Will be tested during System tests.\") async def test__scheduler_loop(self,","3600) assert schedule.exclusive is True assert schedule.enabled is True assert schedule.process_name == \"purge\"","+= datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN assert time_after_call >","= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger,","scheduler._schedule_executions[schedule.id] is True # Now queue task and assert that the task has","True, 'repeat': 30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})]","str(ex).endswith(\"name can not be empty\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)","log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler,","MockStorageAsync(StorageClientAsync): schedules = [ { \"id\": \"cea17db8-6ccc-11e7-907b-a6006ad3dba0\", \"process_name\": \"purge\", \"schedule_name\": \"purge\", \"schedule_type\": 4,","async def test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","calls = [call(\"Enabled Schedule '%s/%s' process '%s'\\n\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True)","len(scheduler._schedules) # WHEN # Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN","test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","== len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\"_mark_tasks_interrupted() not implemented in main Scheduler","'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF","= mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN status, message =","kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection' in args0 assert","enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN","with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule)","Readings to OCS\", \"script\": [ \"tasks/north\", \"--stream_id\", \"4\", \"--debug_level\", \"1\" ] }, ]","mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings","temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \"\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name","repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError) as ex: temp_schedule","scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN","p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): #","mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \"exception\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync,","PI north\", \"schedule_type\": 3, \"schedule_interval\": \"00:00:30\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\":","is None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): #","collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO: Mandatory - Add","temp_schedule.name = \"\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can not be empty\")","== \"Schedule {} already disabled\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False","Interval Schedule assert schedule_row[4] is 0 # 0 for Interval Schedule assert schedule.repeat","= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can","THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): #","\"column\": \"start_time\"}, {\"alias\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"end_time\"}, \"reason\", \"exit_code\"], \"where\": {\"column\":","audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules')","task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks","mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN if is_exception is True: with pytest.raises(Exception):","mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to","unit testing. Will be tested during System tests.\") async def test__scheduler_loop(self, mocker): pass","# FLEDGE_END import asyncio import datetime import uuid import time import json from","core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \"create_category\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \"get_category_all_items\", return_value=_rv) # WHEN","= sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0,","in 'await' expression\"), call('An exception was raised by Scheduler._scheduler_loop %s', \"object MagicMock can't","list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is","mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert","there is one schedule less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async","self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message =","status is True assert message == \"Schedule is already enabled\" assert (scheduler._schedules[sch_id]).id ==","THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\",","await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be of type datetime.time') with pytest.raises(ValueError)","tests.\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO:","args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker):","3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2","async def test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule, log_info, log_exception, log_error,","be used in 'await' expression\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True)","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await","assert 'stats collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN scheduler","'await' expression\"), call('An exception was raised by Scheduler._scheduler_loop %s', \"object MagicMock can't be","\"North Readings to PI\", \"schedule_name\": \"OMF to PI north\", \"schedule_type\": 3, \"schedule_interval\": \"00:00:30\",","TODO: Mandatory - Add negative tests for full code coverage # GIVEN scheduler","WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id ==","-*- coding: utf-8 -*- # FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mock_schedules","0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 ==","= await scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name assert task.reason is ''","\"t\", \"enabled\": \"t\" }, { \"id\": \"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\", \"process_name\": \"North Readings to OCS\", \"schedule_name\":","WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async","{\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"column\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, {\"alias\":","North # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert status is","pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler,","as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule,","= asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert schedule.name == \"purge\" assert schedule.schedule_type ==","hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True)","GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that","# WHEN task = await scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name assert","log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time)","= mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] =","core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.object(scheduler,","async def test__check_schedules(self, mocker): # TODO: Mandatory - Add negative tests for full","collector\", \"schedule_name\": \"stats collection\", \"schedule_type\": 2, \"schedule_interval\": \"00:00:15\", \"schedule_time\": \"00:00:15\", \"schedule_day\": 3, \"exclusive\":","= [call(\"Enabled Schedule '%s/%s' process '%s'\\n\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert","THEN # Now confirm there is one schedule less assert len(scheduler._storage_async.schedules) - 1","\"schedule_time\": \"00:00:15\", \"schedule_day\": 3, \"exclusive\": \"f\", \"enabled\": \"t\" }, { \"id\": \"d1631422-9ec6-11e7-abc4-cec278b6b50a\", \"process_name\":","scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') #","schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) +","\"t\" }, { \"id\": \"d1631422-9ec6-11e7-abc4-cec278b6b50a\", \"process_name\": \"backup\", \"schedule_name\": \"backup hourly\", \"schedule_type\": 3, \"schedule_interval\":","# TODO: Mandatory - Add negative tests for full code coverage # GIVEN","\"script\": [ \"tasks/backup_postgres\" ] }, { \"name\": \"COAP\", \"script\": [ \"services/south\" ] },","= mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id =","await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","# WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def","assert earliest_start_time is not None assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0]","assert status is True assert message == \"Schedule successfully enabled\" assert (scheduler._schedules[sch_id]).id ==","confirm no schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count","PI\", name=\"OMF to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception","\"stat collector\" appears twice in this list. assert 'stats collection' in args3 @pytest.mark.asyncio","scheduler.stop() # THEN assert retval is True assert scheduler._schedule_executions is None assert scheduler._task_processes","self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async","_scheduler_loop_task calls = [call('An exception was raised by Scheduler._purge_tasks %s', \"object MagicMock can't","in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO: Mandatory - Add negative","task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version","WHEN retval = await scheduler.stop() # THEN assert retval is True assert scheduler._schedule_executions","(c) 2017 OSIsoft, LLC\" __license__ = \"Apache 2.0\" __version__ = \"${VERSION}\" async def","'stats collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN scheduler =","= await scheduler.stop() # THEN assert retval is True assert scheduler._schedule_executions is None","WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params)","started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await","assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params = \"Schedule %s already","mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await","args0 assert 'COAP listener south' in args1 assert 'OMF to PI north' in","= scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler,","FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime import uuid import","True log_params = \"Schedule %s already enabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self,","as excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id) # THEN assert","\"script\": [ \"tasks/north\", \"--stream_id\", \"4\", \"--debug_level\", \"1\" ] }, ] tasks = [","None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError)","await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self,","async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","[ { \"id\": \"259b8570-65c1-4b92-8c62-e9642631a600\", \"process_name\": \"North Readings to PI\", \"state\": 1, \"start_time\": \"2018-02-06","HH24:MI:SS.MS\", \"column\": \"start_time\"}, {\"alias\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"end_time\"}, \"reason\", \"exit_code\"], \"where\":","\"state\": 1, \"start_time\": \"2018-02-06 13:28:14.477868\", \"end_time\": \"2018-02-06 13:28:14.856375\", \"exit_code\": \"0\", \"reason\": \"\" }","assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return","@pytest.mark.asyncio async def test__start_task(self, mocker): # TODO: Mandatory - Add negative tests for","for execution\", 'OMF to PI north') == args args, kwargs = log_info.call_args_list[0] assert","0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN # Confirm that task","age, in days (based on the start time), for a rows \" \"in","TestScheduler: async def scheduler_fixture(self, mocker): # Changed in version 3.8: patch() now returns","is False # WHEN await scheduler.start() # THEN assert scheduler._ready is True assert","'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger,","call('An exception was raised by Scheduler._scheduler_loop %s', \"object MagicMock can't be used in","audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","to PI' in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO: Mandatory -","started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN #","north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls =","scheduler._schedule_executions[schedule.id] is True # Now queue task and assert that the North task","type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0","is False assert scheduler._paused is False assert scheduler._start_time is None calls = [call('Processing","await scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name assert task.reason is '' assert","await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task has started yet","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError)","scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information',","the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in","m @pytest.allure.feature(\"unit\") @pytest.allure.story(\"scheduler\") class TestScheduler: async def scheduler_fixture(self, mocker): # Changed in version","to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True)","= datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector","@classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks': return { \"count\":","PI north' in args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed,","\"schedule_name\": \"COAP listener south\", \"schedule_type\": 1, \"schedule_interval\": \"00:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\":","exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN","collection\", \"schedule_type\": 2, \"schedule_interval\": \"00:00:15\", \"schedule_time\": \"00:00:15\", \"schedule_day\": 3, \"exclusive\": \"f\", \"enabled\": \"t\"","uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there are 14 schedules","await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker):","tasks = await scheduler.get_running_tasks() # THEN assert 1 == len(tasks) assert schedule.process_name ==","\"error\") log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") return scheduler, schedule, log_info,","log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker):","test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","Remove after implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is","pending assert 0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0]","test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","\"info\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\",","THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN scheduler,","assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING assert","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mock_schedules = dict()","scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN","assert 'North Readings to PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): #","# backup await scheduler._get_schedules() # Confirm no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)","time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time =","@pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler,","\"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN","= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule","no task has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm","# THEN task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN","= mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo: tasks = await","collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler()","\"exception\") random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \"No","\"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"end_time\"}, \"reason\", \"exit_code\"], \"where\": {\"column\": \"id\", \"condition\": \"=\",","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception =","Schedule '%s/%s' process '%s'\\n\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 ==","\"name\": \"COAP\", \"script\": [ \"services/south\" ] }, { \"name\": \"North Readings to PI\",","} ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return","time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError) as","WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion, sleep above, no task","assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule':","_purge_tasks_task, _scheduler_loop_task calls = [call('An exception was raised by Scheduler._purge_tasks %s', \"object MagicMock","to PI\", \"schedule_name\": \"OMF to PI north\", \"schedule_type\": 3, \"schedule_interval\": \"00:00:30\", \"schedule_time\": \"\",","THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro():","any_order=True) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type':","== queue_task.call_count calls = [call(\"Enabled Schedule '%s/%s' process '%s'\\n\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')]","'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self,","mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler,","enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): #","len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\"_mark_tasks_interrupted() not implemented in main Scheduler class.\") async def test__mark_tasks_interrupted(self, mocker):","async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","'_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has not","mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process","def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","running tasks\\n%s\" in args assert 'OMF to PI north' in args assert 'North","# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id =","call import sys import copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager","WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None await scheduler._read_config() # THEN","disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","to PI north\", \"schedule_type\": 3, \"schedule_interval\": \"00:00:30\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\",","schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN scheduler","schedule.process_name == task.process_name assert task.reason is '' assert task.state is not None assert","assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\"_mark_tasks_interrupted() not implemented in","sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time","\"process_name\": \"COAP\", \"schedule_name\": \"COAP listener south\", \"schedule_type\": 1, \"schedule_interval\": \"00:00:00\", \"schedule_time\": \"\", \"schedule_day\":","implemented in main Scheduler class.\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def","log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","tests for full code coverage # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger,","await scheduler.enable_schedule(sch_id) # THEN assert status is True assert message == \"Schedule successfully","None assert task.end_time is not None assert task.exit_code is '0' @pytest.mark.skip(\"Need a suitable","assert tasks[0].start_time is not None assert tasks[0].end_time is not None assert tasks[0].exit_code is","'North Readings to PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN","in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO: Mandatory - Add negative","def test__read_storage(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","@pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","= await scheduler.get_tasks() # THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\":","mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", _start_time=current_time - 3600, _paused=False,","PI\", \"schedule_name\": \"OMF to PI north\", \"schedule_type\": 3, \"schedule_interval\": \"00:00:30\", \"schedule_time\": \"\", \"schedule_day\":","1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF to PI north', 'repeat':","that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await","\"column\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, {\"alias\": \"end_time\", \"column\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, \"reason\",","OMF to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(),","scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =","@pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN payload = {\"return\": [\"id\",","True # Now queue task and assert that the task has been queued","len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info,","raised despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception was raised by Scheduler._purge_tasks","\"Schedule is already enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params","test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence # \"stat collector\" appears","\"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\", \"process_name\": \"North","http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime import uuid import time import json","assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now delete schedule with pytest.raises(RuntimeWarning): await","# After task completion, sleep above, no task processes should be left pending","queue task and assert that the North task has been queued await scheduler.queue_task(schedule.id)","scheduler_fixture(self, mocker): # Changed in version 3.8: patch() now returns an AsyncMock if","'_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\")","scheduler._start_task(schedule) # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN","task = await scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name assert task.reason is","assert tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN scheduler, schedule,","assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task has started yet assert 0","assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return","= mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row","'_task_processes') log_exception = mocker.patch.object(scheduler._logger, \"exception\") random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) #","mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\"sleep\",","\"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") #","test__start_task(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage","WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert","mocker.patch.object(scheduler._logger, \"exception\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN","not None @pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO: Mandatory - Add negative","any given time\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \"value\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \"max_completed_task_age_days\": { \"description\":","'_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", current_time=current_time - 3600) # TODO: Remove after implementation","> time_before_call assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 =","'_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999,","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage()","== sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params = \"Schedule %s already enabled\", str(sch_id)","scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not","current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 ==","\"info\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id","assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL,","len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count log_params = 'Attempt to delete an","= datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN","for test_save_schedule_update if table_name == \"schedules\": return {\"count\": 1} @classmethod async def delete_from_tbl(cls,","log_params = \"Schedule %s already enabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker):","as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as","= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must","time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", _start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN retval =","Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time is","\"tasks/statistics\" ] }, { \"name\": \"backup\", \"script\": [ \"tasks/backup_postgres\" ] }, { \"name\":","= MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \"create_category\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \"get_category_all_items\", return_value=_rv)","North task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that","= uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information',","GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN schedules","= mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await","(scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count calls =","Assert that there is no task queued for mock_schedule with pytest.raises(KeyError) as excinfo:","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules() #","resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro())","in days (based on the start time), for a rows \" \"in the","Find why these exceptions are being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls =","queued for this schedule at first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is","def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add negative tests for full code","temp_schedule assert str(ex).endswith('day must be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\"To be done\")","# WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async","backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async","MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await","== len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\"_mark_tasks_interrupted() not implemented in main Scheduler class.\") async def test__mark_tasks_interrupted(self,","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \"create_category\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager,","MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \"create_category\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \"get_category_all_items\", return_value=_rv) #","return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0,","import MagicMock, call import sys import copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler,","\"id\": \"259b8570-65c1-4b92-8c62-e9642631a600\", \"process_name\": \"North Readings to PI\", \"state\": 1, \"start_time\": \"2018-02-06 13:28:14.477868\", \"end_time\":","2017 OSIsoft, LLC\" __license__ = \"Apache 2.0\" __version__ = \"${VERSION}\" async def mock_task():","\"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \"value\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \"max_completed_task_age_days\": { \"description\": \"The maximum age,","{ \"name\": \"North Readings to PI\", \"script\": [ \"tasks/north\", \"--stream_id\", \"1\", \"--debug_level\", \"1\"","log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id","test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert","time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch","with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with","# THEN log_params = \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def","collector\" appears twice in this list. assert 'stats collection' in args3 @pytest.mark.asyncio async","{'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled':","mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add negative","patch() now returns an AsyncMock if the target is an async function. if","= [call('Starting'), call('Starting Scheduler: Management port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls","\"--debug_level\", \"1\" ] }, { \"name\": \"North Readings to OCS\", \"script\": [ \"tasks/north\",","\"schedule_name\", \"state\", {\"alias\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"start_time\"}, {\"alias\": \"end_time\", \"format\": \"YYYY-MM-DD","of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN # Now","with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule)","task queued for mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True #","GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\")","\"reason\": \"\" } ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host,","must be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\"To be done\") async def test_remove_service_from_task_processes(self):","ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio","is True assert message == \"Schedule is already enabled\" assert (scheduler._schedules[sch_id]).id == sch_id","0 days', True), ('12:30:11', False), ('0 day 12:30:11', False), ('1 day 12:40:11', False),","None calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why","MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"),","excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo:","\"max_completed_task_age_days\": { \"description\": \"The maximum age, in days (based on the start time),","as excinfo: await scheduler.get_task(task_id) # THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\",","and assert that the North task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id],","schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF to PI north\", type=Schedule.Type.INTERVAL,","THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\"_mark_tasks_interrupted() not implemented","@pytest.mark.asyncio async def test_stop(self, mocker): # TODO: Mandatory - Add negative tests for","= scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess')","async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time()","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler,","testing. Will be tested during System tests.\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio","delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if table_name ==","'_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \"info\")","'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls,","sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt =","= time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector","core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10,","for Interval Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled","def test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","1 == log_exception.call_count log_params = 'Attempt to delete an enabled Schedule %s. Not","stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call","started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task has","True assert message == \"Schedule is already enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert","THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state is not","sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo:","== len(scheduler._schedules) assert 1 == log_exception.call_count log_params = 'Attempt to delete an enabled","return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert","is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =","test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is True assert","# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug =","mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes,","def insert_into_tbl(cls, table_name, payload): pass @classmethod async def update_tbl(cls, table_name, payload): # Only","None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time is not","= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes)","== 'tasks': return { \"count\": len(MockStorageAsync.tasks), \"rows\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls,","== tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is","call('Starting Scheduler: Management port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database","return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North","mocker.patch.object(scheduler._logger, \"info\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\",","mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF to PI north\", type=Schedule.Type.INTERVAL,","scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \"exception\") log_error = mocker.patch.object(scheduler._logger, \"error\") log_debug = mocker.patch.object(scheduler._logger,","listener south' in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\"_scheduler_loop()","_rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts',","async def test__read_storage(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat","def test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","== schedule_id assert schedule.name == \"purge\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat ==","test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") #","assert 'COAP listener south' in args1 assert 'OMF to PI north' in args2","is not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add","schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0","# WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def","log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection' in args0 assert 'COAP listener","tasks that can be running at any given time\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS),","@asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","# WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert","= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await","len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert call(\"Queued schedule '%s' for execution\", 'OMF","test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage","WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params)","assert str(ex).endswith('day must be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\"To be done\") async","Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN scheduler =","log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo:","mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \"exception\") random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id)","super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return { \"id\": uuid.uuid4(), \"name\": \"Fledge Storage\",","'_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None assert","None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker):","{} already disabled\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params =","# WHEN earliest_start_time = await scheduler._check_schedules() # THEN assert earliest_start_time is not None","tasks table that do not have a status of running\", \"type\": \"integer\", \"default\":","1 == log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def","args, kwargs = log_info.call_args_list[0] # assert (\"Queued schedule '%s' for execution\", 'OMF to","excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo:","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row =","1 == cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks is not None assert","PI\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule =","'_resume_check_schedules') # Assert that there is no task queued for mock_schedule with pytest.raises(KeyError)","= [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat':","scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes = await scheduler.get_scheduled_processes() # THEN assert","scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler()","await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await","await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id =","\"name\": \"North Readings to PI\", \"script\": [ \"tasks/north\", \"--stream_id\", \"1\", \"--debug_level\", \"1\" ]","with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with","# WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion, sleep above, no","self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # purge schedule # WHEN schedule = await scheduler.get_schedule(schedule_id)","of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence # \"stat collector\" appears twice in","def test__schedule_next_task(self, mocker): # TODO: Mandatory - Add negative tests for full code","assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params = \"Schedule %s already","schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0 # 0 for Interval","exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no","True return m @pytest.allure.feature(\"unit\") @pytest.allure.story(\"scheduler\") class TestScheduler: async def scheduler_fixture(self, mocker): # Changed","args args, kwargs = log_info.call_args_list[1] assert \"Stopping process: Schedule '%s' process '%s' task","# WHEN # THEN task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id)","test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN if is_exception is True: with","mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN await scheduler.start() # THEN","True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count else: await scheduler._get_schedules() assert","\"script\": [ \"tasks/statistics\" ] }, { \"name\": \"backup\", \"script\": [ \"tasks/backup_postgres\" ] },","type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id,","args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker):","@pytest.mark.skip(\"_mark_tasks_interrupted() not implemented in main Scheduler class.\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio","== enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def","\"tasks/north\", \"--stream_id\", \"1\", \"--debug_level\", \"1\" ] }, { \"name\": \"North Readings to OCS\",","empty\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \"\" await","expression\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","== \"purge\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive","# WHEN # THEN with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name","core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return { \"id\": uuid.uuid4(), \"name\":","len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks() # THEN assert","await scheduler._check_schedules() # THEN assert earliest_start_time is not None assert 3 == log_info.call_count","@pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \"\" await scheduler.save_schedule(temp_schedule) del","test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","enabled=True) log_exception = mocker.patch.object(scheduler._logger, \"exception\") log_error = mocker.patch.object(scheduler._logger, \"error\") log_debug = mocker.patch.object(scheduler._logger, \"debug\")","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") log_exception = mocker.patch.object(scheduler._logger,","'%s' process '%s' task %s pid %s, %s running tasks\\n%s\" in args assert","1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info,","already disabled\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params = \"Schedule","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts()","that there is no task queued for schedule with pytest.raises(KeyError) as excinfo: assert","mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules() # THEN assert earliest_start_time","name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id,","Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks =","exceptions are being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception was","scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules,","# Confirm that task has not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) #","# \"stat collector\" appears twice in this list. assert 'stats collection' in args3","log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): # TODO: Mandatory - Add negative","async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule,","\"purge\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is","condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks': return","scheduler._ScheduleExecution) # Confirm that no task has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes)","_core_management_host=\"0.0.0.0\", current_time=current_time - 3600) # TODO: Remove after implementation of above test test__read_config()","MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await","PI\", name=\"OMF to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id]","# WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules)","log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await","}, { \"name\": \"COAP\", \"script\": [ \"services/south\" ] }, { \"name\": \"North Readings","p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","in args args, kwargs = log_info.call_args_list[1] assert \"Stopping process: Schedule '%s' process '%s'","type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) #","assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state is not None","function. if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await get_cat()","] tasks = [ { \"id\": \"259b8570-65c1-4b92-8c62-e9642631a600\", \"process_name\": \"North Readings to PI\", \"state\":","await scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\"test_interval, is_exception\", [","# GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None)","# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger =","assert 'North Readings to PI' in args args, kwargs = log_info.call_args_list[1] assert \"Stopping","\"schedule_type\": 3, \"schedule_interval\": \"1 day 00:00:40\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\":","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info =","@pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","resume_sch.call_count assert 1 == enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule,","HH24:MI:SS.MS\"}, \"reason\", \"exit_code\"], \"limit\": 100} args, kwargs = log_exception.call_args assert 'Query failed: %s'","= copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN if","is None # WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None","async def test_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for full","tasks\\n%s\" in args assert 'OMF to PI north' in args assert 'North Readings","str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \"value\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version 3.8: patch() now returns","schedule_id assert schedule.name == \"purge\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0,","enabled=True, process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id,","is None assert scheduler._ready is False assert scheduler._paused is False assert scheduler._start_time is","has not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) #","mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN","no task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True","pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del","log_params = \"Schedule %s already disabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker):","\"exclusive\": \"t\", \"enabled\": \"f\" }, { \"id\": \"ada12840-68d3-11e7-907b-a6006ad3dba0\", \"process_name\": \"COAP\", \"schedule_name\": \"COAP listener","disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN","False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1","to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF","pid %s, %s running tasks\\n%s\" in args assert 'OMF to PI north' in","@pytest.mark.asyncio async def test__read_config(self, mocker): async def get_cat(): return { \"max_running_tasks\": { \"description\":","return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has not started","test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None,","and sys.version_info.minor >= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler","log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler()","str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","'_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF to","uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # purge schedule # WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN assert","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task =","pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler,","of type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day =","log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN","'_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", _start_time=current_time -","len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id) # THEN assert","Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is True assert schedule.enabled is","\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\", \"process_name\": \"purge\", \"schedule_name\": \"purge\", \"schedule_type\": 4, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0,","id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule =","mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task queued","args assert 'OMF to PI north' in args assert 'North Readings to PI'","scheduler._paused is False assert scheduler._start_time is None calls = [call('Processing stop request'), call('Stopped')]","log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN #","scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks()","uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is","'_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async","mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", current_time=current_time - 3600) # TODO:","GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule',","'_resume_check_schedules') # Assert that there is no task queued for this schedule at","mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks()","# WHEN schedules = await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio","await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" #","args1 assert 'OMF to PI north' in args2 # As part of scheduler._get_schedules(),","assert 'OMF to PI north' in args assert 'North Readings to PI' in","\"2018-02-06 13:28:14.856375\", \"exit_code\": \"0\", \"reason\": \"\" } ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host,","task and assert that the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id],","= log_exception.call_args assert 'Query failed: %s' == args[0] p = json.loads(args[1]) assert payload","\"backup hourly\", \"schedule_type\": 3, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\":","mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\",","<filename>tests/unit/python/fledge/services/core/scheduler/test_scheduler.py<gh_stars>10-100 # -*- coding: utf-8 -*- # FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END","\"script\": [ \"services/south\" ] }, { \"name\": \"North Readings to PI\", \"script\": [","during System tests.\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker):","for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\"Disabled Schedule '%s/%s' process '%s'\\n\", 'OMF to PI north',","mocker): # TODO: Mandatory - Add negative tests for full code coverage #","process_name=\"North Readings to PI\", name=\"OMF to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None,","in args2 @pytest.mark.asyncio @pytest.mark.skip(\"_scheduler_loop() not suitable for unit testing. Will be tested during","= mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message","sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger,","WHEN earliest_start_time = await scheduler._check_schedules() # THEN assert earliest_start_time is not None assert","'_schedule_first_task') # WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules)","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules()","kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3","mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules()","\"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \"value\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version 3.8:","'_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules() # THEN assert earliest_start_time is","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there is no task","'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker):","await scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is '' assert","MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio","\"address\": \"0.0.0.0\", \"protocol\": \"http\" } class MockStorageAsync(StorageClientAsync): schedules = [ { \"id\": \"cea17db8-6ccc-11e7-907b-a6006ad3dba0\",","scheduler._get_schedules() sch_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert","self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async","'_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \"exception\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules',","mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\"sleep\", \".1\") mock_task_process.schedule =","in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id","asyncio.create_subprocess_exec(\"sleep\", \".1\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] =","not fit for unit test.\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync):","\".1\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process","scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker):","be used in 'await' expression\"), call('An exception was raised by Scheduler._scheduler_loop %s', \"object","async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","test_stop(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage","log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN task_id = uuid.uuid4() with","above, no task processes should be left pending assert 0 == len(scheduler._task_processes) assert","north' in args assert 'North Readings to PI' in args @pytest.mark.asyncio async def","has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8:","these exceptions are being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception","FLEDGE_END import asyncio import datetime import uuid import time import json from unittest.mock","temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be of type","uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) #","args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0] p = json.loads(args[1])","str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version 3.8: patch() now returns an AsyncMock","] }, ] tasks = [ { \"id\": \"259b8570-65c1-4b92-8c62-e9642631a600\", \"process_name\": \"North Readings to","# THEN assert earliest_start_time is not None assert 3 == log_info.call_count args0, kwargs0","Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 1","_task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) #","True assert message == \"Schedule successfully enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled","\"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } @classmethod async def insert_into_tbl(cls, table_name, payload):","# THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN","await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \"exception\") random_schedule_id =","log_info = mocker.patch.object(scheduler._logger, \"info\") schedule_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North schedule_row","despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception was raised by Scheduler._purge_tasks %s',","\"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, {\"alias\": \"end_time\", \"column\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, \"reason\", \"exit_code\"],","scheduler._read_config() # THEN assert 1 == cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks","queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task has started","audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 0 ==","Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await","processes = await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\")","days', True), ('2 days 00:00:59', False), ('00:25:61', True) ]) async def test__get_schedules(self, test_interval,","payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\":","{ \"description\": \"The maximum age, in days (based on the start time), for","fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \"<NAME>\" __copyright__ = \"Copyright","THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio","args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_get_tasks(self, mocker):","9999 m.terminate = lambda: True return m @pytest.allure.feature(\"unit\") @pytest.allure.story(\"scheduler\") class TestScheduler: async def","get_cat(): return { \"max_running_tasks\": { \"description\": \"The maximum number of tasks that can","assert call(\"Queued schedule '%s' for execution\", 'OMF to PI north') == log_info.call_args_list[0] args,","kwargs = log_info.call_args_list[0] assert \"Process started: Schedule '%s' process '%s' task %s pid","] scheduled_processes = [ { \"name\": \"purge\", \"script\": [ \"tasks/purge\" ] }, {","raised by Scheduler._purge_tasks %s', \"object MagicMock can't be used in 'await' expression\"), call('An","assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\"_mark_tasks_interrupted() not implemented in main Scheduler class.\") async","{'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})]","assert that the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) #","MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception =","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused',","temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be between 1","{ \"name\": \"stats collector\", \"script\": [ \"tasks/statistics\" ] }, { \"name\": \"backup\", \"script\":","= MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule =","= await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as","return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules() # THEN assert earliest_start_time is not","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() curr_time","TODO: Remove after implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready","is None @pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","assert task.state is not None assert task.cancel_requested is None assert task.start_time is not","assert 1 == get_cat.call_count assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is not","queue_task.call_count calls = [call(\"Enabled Schedule '%s/%s' process '%s'\\n\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls,","mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \"exception\")","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception())","Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] #","Readings to PI\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion,","time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert time_after_call","been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id) # THEN assert","True) # WHEN # THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError)","\"OMF to PI north\", \"schedule_type\": 3, \"schedule_interval\": \"00:00:30\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\":","suitable fixture\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","to PI\", \"script\": [ \"tasks/north\", \"--stream_id\", \"1\", \"--debug_level\", \"1\" ] }, { \"name\":","== first_task.call_count assert 1 == resume_sch.call_count assert 1 == enable_schedule.call_count assert 0 ==","day 00:00:40\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" }, ] scheduled_processes","1} @classmethod async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name,","def mock_process(): m = MagicMock() m.pid = 9999 m.terminate = lambda: True return","scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4())","log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF part","enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await","scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL,","\"0\", \"reason\": \"\" } ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self,","task processes should be left pending assert 0 == len(scheduler._task_processes) assert 0 ==","== \"Schedule successfully disabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False assert","day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process","None assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1]","log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF to PI north', 'repeat': 30.0, 'enabled':","tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule,","schedule = await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id","PI\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has not started yet assert 0","\"value\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \"max_completed_task_age_days\": { \"description\": \"The maximum age, in days (based on","scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): #","assert that the North task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution)","@pytest.mark.asyncio @pytest.mark.skip(reason=\"To be done\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker):","= await self.scheduler_fixture(mocker) # Assert that there is no North task queued for","tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time is not None","the tasks table that do not have a status of running\", \"type\": \"integer\",","pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) ==","time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch","scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \"Queued schedule '%s' for","= mocker.patch.object(ConfigurationManager, \"create_category\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \"get_category_all_items\", return_value=_rv) # WHEN assert scheduler._max_running_tasks","@pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","successfully disabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2 ==","# As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence # \"stat collector\"","@pytest.allure.feature(\"unit\") @pytest.allure.story(\"scheduler\") class TestScheduler: async def scheduler_fixture(self, mocker): # Changed in version 3.8:","PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls","enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await","await scheduler.start() # THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert","schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now confirm no schedule is","== Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time","== p @pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","assert tasks[0].reason is '' assert tasks[0].state is not None assert tasks[0].cancel_requested is None","\"count\": len(MockStorageAsync.tasks), \"rows\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name, query=None): if table_name","scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\"test_interval, is_exception\", [ ('\"Blah\"","\"protocol\": \"http\" } class MockStorageAsync(StorageClientAsync): schedules = [ { \"id\": \"cea17db8-6ccc-11e7-907b-a6006ad3dba0\", \"process_name\": \"purge\",","assert 'North Readings to PI' in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): #","\"stats collection\", \"schedule_type\": 2, \"schedule_interval\": \"00:00:15\", \"schedule_time\": \"00:00:15\", \"schedule_day\": 3, \"exclusive\": \"f\", \"enabled\":","return scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): #","\"services/south\" ] }, { \"name\": \"North Readings to PI\", \"script\": [ \"tasks/north\", \"--stream_id\",","mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") schedule_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\")","return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", _start_time=current_time - 3600,","\"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"2176eb68-7303-11e7-8cf7-a6006ad3dba0\",","\"where\": {\"column\": \"id\", \"condition\": \"=\", \"value\": str(task_id)}} args, kwargs = log_exception.call_args assert 'Query","Schedule '%s' process '%s' task %s pid %s\\n%s\" in args assert 'OMF to","'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler()","(based on the start time), for a rows \" \"in the tasks table","test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add negative tests","is True assert scheduler._schedule_executions is None assert scheduler._task_processes is None assert scheduler._schedules is","with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def","THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine","GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger,","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there is","async def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","\"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } class MockStorageAsync(StorageClientAsync): schedules = [ {","= await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED,","assert scheduler._max_completed_task_age is None await scheduler._read_config() # THEN assert 1 == cr_cat.call_count assert","AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import","async def test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","assert 1 == resume_sch.call_count assert 1 == enable_schedule.call_count assert 0 == disable_schedule.call_count #","schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is True assert schedule.enabled is True assert","next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN assert time_after_call","== sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count calls = [call('No","is True assert message == \"Schedule successfully enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert","to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30),","= sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 4 == log_info.call_count args0,","temp_schedule.day = 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must","\"\" } ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port):","current_time=current_time - 3600) # TODO: Remove after implementation of above test test__read_config() mocker.patch.object(scheduler,","%s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker):","audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") #","with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN","left pending assert 0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs =","that the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed","'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1","def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def","PI north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \"Process started: Schedule '%s'","scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule","async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await","log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2]","version 3.8: patch() now returns an AsyncMock if the target is an async","'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName':","{ \"max_running_tasks\": { \"description\": \"The maximum number of tasks that can be running","MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() #","args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert","# Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now confirm","test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","\"end_time\"}, \"reason\", \"exit_code\"], \"where\": {\"column\": \"id\", \"condition\": \"=\", \"value\": str(task_id)}} args, kwargs =","is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'),","type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN with","\"t\", \"enabled\": \"f\" }, { \"id\": \"ada12840-68d3-11e7-907b-a6006ad3dba0\", \"process_name\": \"COAP\", \"schedule_name\": \"COAP listener south\",","assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks()","not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id) # THEN","== audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0,","None assert tasks[0].end_time is not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def","THEN assert time_after_call > time_before_call assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0]","assert (\"Queued schedule '%s' for execution\", 'OMF to PI north') == args args,","schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): #","await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count","self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler,","2.0\" __version__ = \"${VERSION}\" async def mock_task(): return \"\" async def mock_process(): m","mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id]","completion, sleep above, no task processes should be left pending assert 0 ==","= await scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is ''","\"enabled\": \"t\" }, { \"id\": \"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\", \"process_name\": \"North Readings to OCS\", \"schedule_name\": \"OMF","= time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector","'OMF to PI north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO:","copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN if is_exception","await scheduler.stop() # THEN assert retval is True assert scheduler._schedule_executions is None assert","== cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age","async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule,","@pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \"info\") await scheduler._get_schedules() sch_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\")","== log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 =","def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler()","def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError)","'%s' for execution\", 'OMF to PI north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0]","log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \"Process started: Schedule '%s' process '%s' task","0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\"","log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception):","excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo:","0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\"","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes","assert scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution)","PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30,","already disabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule,","def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule, log_info,","None @pytest.mark.asyncio async def test_start(self, mocker): # TODO: Mandatory - Add negative tests","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \"create_category\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \"get_category_all_items\",","core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with","scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4())","with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with","return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN assert","THEN log_params = \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self,","mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not None","= await scheduler._check_schedules() # THEN assert earliest_start_time is not None assert 3 ==","scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF to PI north\",","mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") return scheduler, schedule, log_info, log_exception, log_error, log_debug","log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN status, message","str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","that there is no North task queued for schedule with pytest.raises(KeyError) as excinfo:","payload): pass @classmethod async def update_tbl(cls, table_name, payload): # Only valid for test_save_schedule_update","\"create_category\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \"get_category_all_items\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is None","mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False # WHEN #","core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN","PI\", \"script\": [ \"tasks/north\", \"--stream_id\", \"1\", \"--debug_level\", \"1\" ] }, { \"name\": \"North","[ \"tasks/statistics\" ] }, { \"name\": \"backup\", \"script\": [ \"tasks/backup_postgres\" ] }, {","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task',","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger,","# THEN assert status is True assert message == \"Schedule successfully disabled\" assert","table_name, query_payload): if table_name == 'tasks': return { \"count\": len(MockStorageAsync.tasks), \"rows\": MockStorageAsync.tasks }","has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task","{\"count\": 1} @classmethod async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls,","in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO: Mandatory - Add negative","\"Schedule {} already disabled\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params","mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") enable_schedule = mocker.patch.object(scheduler,","@pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","\"type\": \"Storage\", \"service_port\": 9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } @classmethod async","async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo: await","type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule","to PI' in args args, kwargs = log_info.call_args_list[1] assert \"Stopping process: Schedule '%s'","assert str(ex).endswith(\"name can not be empty\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id,","mocker.patch.object(scheduler._logger, \"info\") enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) schedule_id","between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\"To be done\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio","None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def test_start(self, mocker): # TODO:","== len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state ==","resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") schedule_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF","'_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self,","assert schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8] assert","log_info = mocker.patch.object(scheduler._logger, \"info\") enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\",","with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \"\" await scheduler.save_schedule(temp_schedule)","fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \"<NAME>\" __copyright__ = \"Copyright (c) 2017 OSIsoft, LLC\"","is no North task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id]","}, } # Changed in version 3.8: patch() now returns an AsyncMock if","await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message","task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id) # THEN assert schedule.process_name","\"end_time\": \"2018-02-06 13:28:14.856375\", \"exit_code\": \"0\", \"reason\": \"\" } ] def __init__(self, core_management_host=None, core_management_port=None):","was raised by Scheduler._purge_tasks %s', \"object MagicMock can't be used in 'await' expression\"),","sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await get_cat() else: _rv","is not None @pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO: Mandatory - Add","with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time =","call(\"Disabled Schedule '%s/%s' process '%s'\\n\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to","pass @classmethod async def update_tbl(cls, table_name, payload): # Only valid for test_save_schedule_update if","has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task =","await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN task_id =","len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\"_mark_tasks_interrupted() not implemented in main Scheduler class.\") async def","scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\"_terminate_child_processes() not fit for unit test.\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass","'_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN await scheduler.start() # THEN assert","mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to","pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\"_terminate_child_processes() not fit for unit test.\") @pytest.mark.asyncio async","async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion') #","args2 @pytest.mark.asyncio @pytest.mark.skip(\"_scheduler_loop() not suitable for unit testing. Will be tested during System","mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker): async def get_cat(): return { \"max_running_tasks\":","uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup await scheduler._get_schedules() # Confirm no. of schedules assert len(scheduler._storage_async.schedules) ==","in args @pytest.mark.asyncio async def test__start_task(self, mocker): # TODO: Mandatory - Add negative","== schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name ==","test__read_config(self, mocker): async def get_cat(): return { \"max_running_tasks\": { \"description\": \"The maximum number","MagicMock, call import sys import copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger,","PI north' in args assert 'North Readings to PI' in args @pytest.mark.asyncio async","Interval Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled ==","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN","task.reason is '' assert task.state is not None assert task.cancel_requested is None assert","test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","def test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for full code","== schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def","1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be of type datetime.timedelta') with","schedule # WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert","\"column\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, \"reason\", \"exit_code\"], \"limit\": 100} args, kwargs = log_exception.call_args","@pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for","# WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def","args assert 'North Readings to PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker):","random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \"No such","len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF to PI","(scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params = \"Schedule %s already enabled\",","# THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN","assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True,","scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name assert task.reason is '' assert task.state","log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection' in args0 assert 'COAP listener","'%s'\\n\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls =","return_value=_rv) # WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None await scheduler._read_config()","== enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN","= [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day':","assert tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None assert","scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4())","# Confirm that cancel request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None","\"COAP\", \"schedule_name\": \"COAP listener south\", \"schedule_type\": 1, \"schedule_interval\": \"00:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0,","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\",","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") log_exception = mocker.patch.object(scheduler._logger, \"exception\")","# WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert status is True","assert schedule_row[3] is 0 # 0 for Interval Schedule assert schedule_row[4] is 0","assert schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker):","scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 4 ==","log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1)))","= list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id) # THEN assert schedule.process_name ==","table_name, query=None): if table_name == 'schedules': return { \"count\": len(MockStorageAsync.schedules), \"rows\": MockStorageAsync.schedules }","# assert call(\"Queued schedule '%s' for execution\", 'OMF to PI north') == log_info.call_args_list[0]","assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management port received is","# WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id","= scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess')","GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) #","assert scheduler._ready is False # WHEN await scheduler.start() # THEN assert scheduler._ready is","def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert status is True assert","Storage\", \"type\": \"Storage\", \"service_port\": 9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } @classmethod","= await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert","'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert","THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)","assert schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio","'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls,","log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN","dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler,","def get_cat(): return { \"max_running_tasks\": { \"description\": \"The maximum number of tasks that","tasks = [ { \"id\": \"259b8570-65c1-4b92-8c62-e9642631a600\", \"process_name\": \"North Readings to PI\", \"state\": 1,","[ \"services/south\" ] }, { \"name\": \"North Readings to PI\", \"script\": [ \"tasks/north\",","scheduler.enable_schedule(sch_id) # THEN assert status is True assert message == \"Schedule is already","scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8: patch() now returns an","False assert scheduler._start_time is None calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True)","async def insert_into_tbl(cls, table_name, payload): pass @classmethod async def update_tbl(cls, table_name, payload): #","schedule_row) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name ==","\"in the tasks table that do not have a status of running\", \"type\":","= mocker.patch.object(scheduler._logger, \"info\") return scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def","mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") #","temp_schedule assert str(ex).endswith(\"name can not be empty\") with pytest.raises(ValueError) as ex: temp_schedule =","be left pending assert 0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs","\"Apache 2.0\" __version__ = \"${VERSION}\" async def mock_task(): return \"\" async def mock_process():","WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self,","uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch,","queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status,","test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule, log_info, log_exception,","assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def test_start(self, mocker): # TODO: Mandatory","# THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 == log_info.call_count # args,","del temp_schedule assert str(ex).endswith('repeat must be of type datetime.timedelta') with pytest.raises(ValueError) as ex:","= mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999,","}, { \"name\": \"North Readings to OCS\", \"script\": [ \"tasks/north\", \"--stream_id\", \"4\", \"--debug_level\",","MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler,","== 3 and sys.version_info.minor >= 8: _rv = await get_cat() else: _rv =","scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4())","schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True,","await asyncio.create_subprocess_exec(\"sleep\", \".1\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id]","Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule,","= 9999 m.terminate = lambda: True return m @pytest.allure.feature(\"unit\") @pytest.allure.story(\"scheduler\") class TestScheduler: async","scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def test_start(self,","[\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"column\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, {\"alias\": \"end_time\",","await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks = await","as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as","if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await get_cat() else:","assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler =","return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\",","scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\")","else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler,","_max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch = scheduler._schedules[sch_id]","await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\"_terminate_child_processes() not fit for unit","\"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"2176eb68-7303-11e7-8cf7-a6006ad3dba0\", \"process_name\": \"stats collector\",","= 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be of type datetime.time')","sch_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that","str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError) as ex:","pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del","assert (scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count calls = [call('No Task running","import time import json from unittest.mock import MagicMock, call import sys import copy","with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN","log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task')","scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be","\"rows\": MockStorageAsync.schedules } if table_name == 'scheduled_processes': return { \"count\": len(MockStorageAsync.scheduled_processes), \"rows\": MockStorageAsync.scheduled_processes","Now queue task and assert that the North task has been queued await","await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch =","scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() #","is False assert scheduler._start_time is None calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls,","log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): #","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \"info\")","sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt +=","== len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF to PI north' in args","args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection' in args0","new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN if is_exception is","after implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False","assert scheduler._process_scripts is None assert scheduler._ready is False assert scheduler._paused is False assert","= mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) ==","= await scheduler.get_running_tasks() # THEN assert 1 == len(tasks) assert schedule.process_name == tasks[0].process_name","def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if table_name","scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): #","\"type\": \"Storage\", \"service_port\": 9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } class MockStorageAsync(StorageClientAsync):","is True log_params = \"Schedule %s already enabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def","pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks': return {","30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1","len(MockStorageAsync.tasks), \"rows\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name, query=None): if table_name ==","import sys import copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from","as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\"_terminate_child_processes() not fit for unit test.\") @pytest.mark.asyncio async def","# 0 for Interval Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7]","async def test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","for full code coverage # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name':","def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return { \"id\":","table_name == 'tasks': return { \"count\": len(MockStorageAsync.tasks), \"rows\": MockStorageAsync.tasks } @classmethod async def","_max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules()","assert 'North Readings to PI' in args @pytest.mark.asyncio async def test__start_task(self, mocker): #","= mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") schedule_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to","sys.version_info.minor >= 8: _rv = await get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN","uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert","test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup","update_tbl(cls, table_name, payload): # Only valid for test_save_schedule_update if table_name == \"schedules\": return","1 == log_info.call_count # assert call(\"Queued schedule '%s' for execution\", 'OMF to PI","return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN await scheduler.start() # THEN assert scheduler._ready","that the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm","from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \"<NAME>\" __copyright__ = \"Copyright (c) 2017 OSIsoft,","mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time","WHEN # THEN if is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1","async def test__schedule_next_task(self, mocker): # TODO: Mandatory - Add negative tests for full","log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo: tasks =","}, ] tasks = [ { \"id\": \"259b8570-65c1-4b92-8c62-e9642631a600\", \"process_name\": \"North Readings to PI\",","repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) #","pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue task and assert","time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict()","\"enabled\": \"t\" }, { \"id\": \"2b614d26-760f-11e7-b5a5-be2e44b06b34\", \"process_name\": \"North Readings to PI\", \"schedule_name\": \"OMF","mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert","= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \"exception\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval']","== args args, kwargs = log_info.call_args_list[0] assert \"Process started: Schedule '%s' process '%s'","= MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes = await","scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id]","9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')]","mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN","is not None assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert","name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id,","WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert","('2 days', True), ('2 days 00:00:59', False), ('00:25:61', True) ]) async def test__get_schedules(self,","done\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN scheduler","'%s/%s' process '%s'\\n\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count","schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0 # 0 for Interval Schedule assert","== audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF to PI north', 'repeat': 30.0,","pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now confirm no schedule is deleted assert","= mocker.patch.object(scheduler._logger, \"info\") log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task()))","len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test","scheduler.delete_schedule(sch_id) # THEN # Now confirm no schedule is deleted assert len(scheduler._storage_async.schedules) ==","= await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task()))","test__read_storage(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","False assert 2 == log_info.call_count calls = [call('No Task running for Schedule %s',","@pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN task_id = uuid.uuid4() with pytest.raises(Exception) as","}, { \"id\": \"ada12840-68d3-11e7-907b-a6006ad3dba0\", \"process_name\": \"COAP\", \"schedule_name\": \"COAP listener south\", \"schedule_type\": 1, \"schedule_interval\":","\"North Readings to PI\", \"state\": 1, \"start_time\": \"2018-02-06 13:28:14.477868\", \"end_time\": \"2018-02-06 13:28:14.856375\", \"exit_code\":","assert 0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1","== log_info.call_count # assert call(\"Queued schedule '%s' for execution\", 'OMF to PI north')","\"1\" ] }, { \"name\": \"North Readings to OCS\", \"script\": [ \"tasks/north\", \"--stream_id\",","pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port):","GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler,","time_before_call assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1]","== len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN # Now delete schedule await scheduler.delete_schedule(sch_id)","= uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \"No such Schedule","assert 1 == queue_task.call_count calls = [call(\"Enabled Schedule '%s/%s' process '%s'\\n\", 'backup hourly',","test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","in this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker):","_rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage =","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes)","1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL,","mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\",","THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self,","= \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): #","\"exception\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN #","enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro():","assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def test__check_purge_tasks(self,","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \"exception\") new_schedules =","# THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def","True assert message == \"Schedule {} already disabled\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert","used in 'await' expression\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler","schedule_row) enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN","THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"column\": \"start_time\", \"format\":","# Now queue task and assert that the task has been queued await","mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task","is not None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def test_start(self, mocker):","self.scheduler_fixture(mocker) # Assert that there is no task queued for schedule with pytest.raises(KeyError)","# log_params = \"Queued schedule '%s' for execution\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async","\"0.0.0.0\", \"protocol\": \"http\" } class MockStorageAsync(StorageClientAsync): schedules = [ { \"id\": \"cea17db8-6ccc-11e7-907b-a6006ad3dba0\", \"process_name\":","log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\"test_interval, is_exception\", [ ('\"Blah\" 0","@pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio","fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import *","log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup queue_task = mocker.patch.object(scheduler,","assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert call(\"Queued schedule '%s'","\"0.0.0.0\", \"protocol\": \"http\" } @classmethod async def insert_into_tbl(cls, table_name, payload): pass @classmethod async","WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time","True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \"exception\") random_schedule_id = uuid.uuid4() # WHEN await","= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager,","time_before_call = sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution,","schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30),","mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \"info\")","mocker.patch.object(scheduler._logger, \"info\") schedule_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North schedule_row = scheduler._ScheduleRow(","\"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task()))","await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has","scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker):","} class MockStorageAsync(StorageClientAsync): schedules = [ { \"id\": \"cea17db8-6ccc-11e7-907b-a6006ad3dba0\", \"process_name\": \"purge\", \"schedule_name\": \"purge\",","]) async def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler","@classmethod async def update_tbl(cls, table_name, payload): # Only valid for test_save_schedule_update if table_name","_rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None,","len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING","scheduler.get_task(task_id) # THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"format\":","assert time_after_call > time_before_call assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1,","# THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args)","== Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is True assert schedule.enabled","THEN assert status is True assert message == \"Schedule successfully enabled\" assert (scheduler._schedules[sch_id]).id","repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\",","assert scheduler._schedule_executions[schedule.id] is True # Now queue task and assert that the North","None assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time is","\"id\": uuid.uuid4(), \"name\": \"Fledge Storage\", \"type\": \"Storage\", \"service_port\": 9999, \"management_port\": 9999, \"address\": \"0.0.0.0\",","\"info\") await scheduler._get_schedules() sch_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules')","# THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \"Queued schedule '%s' for execution\",","with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with","calls = [call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\"Disabled Schedule '%s/%s' process","# WHEN # Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN #","task %s pid %s\\n%s\" in args assert 'OMF to PI north' in args","PI\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion, sleep above,","def test_queue_task(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","already enabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule,","= mocker.patch.object(scheduler._logger, \"info\") schedule_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North schedule_row =","@pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\"sleep\", \".1\") mock_task_process.schedule = mock_schedule mock_task_id =","'_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \"exception\") random_schedule_id = uuid.uuid4() # WHEN","def query_tbl(cls, table_name, query=None): if table_name == 'schedules': return { \"count\": len(MockStorageAsync.schedules), \"rows\":","of tasks that can be running at any given time\", \"type\": \"integer\", \"default\":","async def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","= list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested","[call(\"Enabled Schedule '%s/%s' process '%s'\\n\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1","== len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF to","async def update_tbl(cls, table_name, payload): # Only valid for test_save_schedule_update if table_name ==","core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \"exception\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval","== get_cat.call_count assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio","# THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state is","the target is an async function. if sys.version_info.major == 3 and sys.version_info.minor >=","log_info.call_args_list[3] assert 'stats collection' in args0 assert 'COAP listener south' in args1 assert","== len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id,","assert status is True assert message == \"Schedule successfully disabled\" assert (scheduler._schedules[sch_id]).id ==","assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type':","WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 ==","\"script\": [ \"tasks/purge\" ] }, { \"name\": \"stats collector\", \"script\": [ \"tasks/statistics\" ]","to PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule,","north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\"_scheduler_loop() not suitable for unit testing. Will be tested","mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger,","rows \" \"in the tasks table that do not have a status of","= uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id)","datetime.time') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time","scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO: Mandatory -","Readings to PI' in args args, kwargs = log_info.call_args_list[1] assert \"Stopping process: Schedule","test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","= mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North","assert scheduler._schedule_executions is None assert scheduler._task_processes is None assert scheduler._schedules is None assert","== \"schedules\": return {\"count\": 1} @classmethod async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod","scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info =","scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count","= \"<NAME>\" __copyright__ = \"Copyright (c) 2017 OSIsoft, LLC\" __license__ = \"Apache 2.0\"","query_payload): if table_name == 'tasks': return { \"count\": len(MockStorageAsync.tasks), \"rows\": MockStorageAsync.tasks } @classmethod","south' in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio async def","for Interval Schedule assert schedule_row[4] is 0 # 0 for Interval Schedule assert","resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self,","00:00:40\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" }, ] scheduled_processes =","# WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id","table_name, payload): # Only valid for test_save_schedule_update if table_name == \"schedules\": return {\"count\":","pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id) # THEN","THEN # After task completion, sleep above, no task processes should be left","THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule':","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception","core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception())","_rv = await get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler()","0 # 0 for Interval Schedule assert schedule_row[4] is 0 # 0 for","\"start_time\"}, {\"alias\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"end_time\"}, \"reason\", \"exit_code\"], \"where\": {\"column\": \"id\",","payload): # Only valid for test_save_schedule_update if table_name == \"schedules\": return {\"count\": 1}","3600) # TODO: Remove after implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task()))","'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN scheduler","list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN","('\"Blah\" 0 days', True), ('12:30:11', False), ('0 day 12:30:11', False), ('1 day 12:40:11',","args, kwargs = log_info.call_args_list[0] assert \"Process started: Schedule '%s' process '%s' task %s","@pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","\"Storage\", \"service_port\": 9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } class MockStorageAsync(StorageClientAsync): schedules","[ \"tasks/purge\" ] }, { \"name\": \"stats collector\", \"script\": [ \"tasks/statistics\" ] },","async def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","= uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30,","any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8: patch() now returns","isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type ==","time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", current_time=current_time - 3600) #","await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # purge schedule # WHEN schedule = await","len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess',","THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0]","mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", current_time=current_time - 3600) # TODO: Remove after implementation of above","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules()","== 'schedules': return { \"count\": len(MockStorageAsync.schedules), \"rows\": MockStorageAsync.schedules } if table_name == 'scheduled_processes':","@classmethod async def insert_into_tbl(cls, table_name, payload): pass @classmethod async def update_tbl(cls, table_name, payload):","asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False # WHEN # Check ELSE","await scheduler._read_config() # THEN assert 1 == cr_cat.call_count assert 1 == get_cat.call_count assert","pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN scheduler,","to PI north' in args assert 'North Readings to PI' in args args,","sys.version_info.minor >= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec',","datetime import uuid import time import json from unittest.mock import MagicMock, call import","= mocker.patch.object(scheduler._logger, \"info\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings","# -*- coding: utf-8 -*- # FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import","scheduler._process_scripts is None assert scheduler._ready is False assert scheduler._paused is False assert scheduler._start_time","async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count calls = [call(\"Enabled Schedule","\"exception\") # WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed:","query_tbl(cls, table_name, query=None): if table_name == 'schedules': return { \"count\": len(MockStorageAsync.schedules), \"rows\": MockStorageAsync.schedules","'_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup","= MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_scheduler_loop',","== \"Schedule successfully enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True assert","\"http\" } @classmethod async def insert_into_tbl(cls, table_name, payload): pass @classmethod async def update_tbl(cls,","'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type':","to PI North # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert","_start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN retval = await scheduler.stop() # THEN","scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be of type datetime.timedelta') with pytest.raises(ValueError) as","9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } @classmethod async def insert_into_tbl(cls, table_name,","assert time_after_call > time_before_call assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1,","WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending","True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task queued for this","1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has not","return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", current_time=current_time - 3600) # TODO: Remove after implementation of","status, message = await scheduler.disable_schedule(sch_id) # THEN assert status is True assert message","exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError) as ex: temp_schedule =","PI north') == args args, kwargs = log_info.call_args_list[0] assert \"Process started: Schedule '%s'","self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \"No","assert schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0 #","1 == queue_task.call_count calls = [call(\"Enabled Schedule '%s/%s' process '%s'\\n\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a',","\"4\", \"--debug_level\", \"1\" ] }, ] tasks = [ { \"id\": \"259b8570-65c1-4b92-8c62-e9642631a600\", \"process_name\":","mocker): # Changed in version 3.8: patch() now returns an AsyncMock if the","async def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","to PI north' in args assert 'North Readings to PI' in args @pytest.mark.asyncio","task %s pid %s, %s running tasks\\n%s\" in args assert 'OMF to PI","scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30,","test__schedule_next_task(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage","is None assert scheduler._task_processes is None assert scheduler._schedules is None assert scheduler._process_scripts is","# THEN assert 1 == len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is","test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task()))","tasks = await scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is","}, { \"id\": \"2176eb68-7303-11e7-8cf7-a6006ad3dba0\", \"process_name\": \"stats collector\", \"schedule_name\": \"stats collection\", \"schedule_type\": 2, \"schedule_interval\":","# OMF to PI North # WHEN status, message = await scheduler.disable_schedule(sch_id) #","log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN scheduler =","== disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count","PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \"exception\")","\"schedules\": return {\"count\": 1} @classmethod async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async","\"schedule_type\": 1, \"schedule_interval\": \"00:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" },","enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro():","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN # THEN","# Assert that there is no task queued for schedule with pytest.raises(KeyError) as","OCS\", \"script\": [ \"tasks/north\", \"--stream_id\", \"4\", \"--debug_level\", \"1\" ] }, ] tasks =","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task","side_effect=Exception()) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as","no task processes should be left pending assert 0 == len(scheduler._task_processes) assert 0","# 0 for Interval Schedule assert schedule_row[4] is 0 # 0 for Interval","assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count calls","day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError)","@pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm","not None @pytest.mark.asyncio async def test_start(self, mocker): # TODO: Mandatory - Add negative","del temp_schedule assert str(ex).endswith(\"name can not be empty\") with pytest.raises(ValueError) as ex: temp_schedule","# THEN # After task completion, sleep above, no task processes should be","'%s' for execution\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN","there are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now delete","\"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN","scheduler._schedules is None assert scheduler._process_scripts is None assert scheduler._ready is False assert scheduler._paused","\"tasks/backup_postgres\" ] }, { \"name\": \"COAP\", \"script\": [ \"services/south\" ] }, { \"name\":","}, { \"name\": \"North Readings to PI\", \"script\": [ \"tasks/north\", \"--stream_id\", \"1\", \"--debug_level\",","to PI north') == args args, kwargs = log_info.call_args_list[0] assert \"Process started: Schedule","pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN scheduler,","process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)","# backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio","Readings to PI\", name=\"OMF to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True,","\"start_time\", \"column\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, {\"alias\": \"end_time\", \"column\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"},","\"00:00:15\", \"schedule_day\": 3, \"exclusive\": \"f\", \"enabled\": \"t\" }, { \"id\": \"d1631422-9ec6-11e7-abc4-cec278b6b50a\", \"process_name\": \"backup\",","await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler,","p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_get_tasks(self, mocker): #","{'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0',","mocker.patch.object(scheduler._logger, \"exception\") random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params =","False) mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN with pytest.raises(NotReadyError) as excinfo: await","True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info,","scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1","mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion')","async def test__schedule_first_task(self, mocker): # TODO: Mandatory - Add negative tests for full","(scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count calls = [call('No Task running for","True assert schedule.process_name == \"purge\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN scheduler,","await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params =","assert task.reason is '' assert task.state is not None assert task.cancel_requested is None","scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True,","ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule)","backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task","mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message =","{'name': 'OMF to PI north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True,","] }, { \"name\": \"backup\", \"script\": [ \"tasks/backup_postgres\" ] }, { \"name\": \"COAP\",","sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call","time), for a rows \" \"in the tasks table that do not have","north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO: Mandatory - Add","'_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\")","[call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day': 1,","'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls = [call('SCHCH',","log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN #","7') @pytest.mark.asyncio @pytest.mark.skip(reason=\"To be done\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self,","schedule await scheduler.delete_schedule(sch_id) # THEN # Now confirm there is one schedule less","# WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) ==","= scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess')","schedule.name == \"purge\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert","= MagicMock() m.pid = 9999 m.terminate = lambda: True return m @pytest.allure.feature(\"unit\") @pytest.allure.story(\"scheduler\")","be running at any given time\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \"value\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) },","'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def","1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat':","# WHEN tasks = await scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name assert","str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","@pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler,","maximum age, in days (based on the start time), for a rows \"","}, \"max_completed_task_age_days\": { \"description\": \"The maximum age, in days (based on the start","unittest.mock import MagicMock, call import sys import copy import pytest from fledge.services.core.scheduler.scheduler import","is None assert scheduler._process_scripts is None assert scheduler._ready is False assert scheduler._paused is","been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8: patch()","in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self,","== len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management port","= mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule","disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio","= MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow(","await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await","uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False,","from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__","def test__read_config(self, mocker): async def get_cat(): return { \"max_running_tasks\": { \"description\": \"The maximum","THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def","mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row =","scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion, sleep above, no task processes should","utf-8 -*- # FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime","schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True,","there is no task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id]","pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError)","Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async","THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio","repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN","# THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"format\": \"YYYY-MM-DD","%s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN scheduler = Scheduler()","table that do not have a status of running\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS),","scheduler._max_completed_task_age is None await scheduler._read_config() # THEN assert 1 == cr_cat.call_count assert 1","self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo: tasks","assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler:","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError)","as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule","Readings to PI' in args @pytest.mark.asyncio async def test__start_task(self, mocker): # TODO: Mandatory","await scheduler.delete_schedule(sch_id) # THEN # Now confirm no schedule is deleted assert len(scheduler._storage_async.schedules)","made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested","return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN","del temp_schedule assert str(ex).endswith('time must be of type datetime.time') with pytest.raises(ValueError) as ex:","StorageClientAsync __author__ = \"<NAME>\" __copyright__ = \"Copyright (c) 2017 OSIsoft, LLC\" __license__ =","* from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \"<NAME>\" __copyright__ = \"Copyright (c) 2017","} @classmethod async def insert_into_tbl(cls, table_name, payload): pass @classmethod async def update_tbl(cls, table_name,","await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio","await scheduler.disable_schedule(sch_id) # THEN assert status is True assert message == \"Schedule successfully","= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro())","with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async","self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules)","core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert","is not None assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1","== schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has not been made assert","assert 0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert","assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert schedule.name == \"purge\" assert schedule.schedule_type","Scheduler: Management port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command:","= scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds)","OCS\", \"schedule_name\": \"OMF to OCS north\", \"schedule_type\": 3, \"schedule_interval\": \"1 day 00:00:40\", \"schedule_time\":","to PI north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \"Process started: Schedule","1, \"schedule_interval\": \"00:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, {","assert 'Query failed: %s' == args[0] p = json.loads(args[1]) assert payload == p","schedule.process_name == \"purge\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info,","days 00:00:59', False), ('00:25:61', True) ]) async def test__get_schedules(self, test_interval, is_exception, mocker): #","log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # purge schedule # WHEN","\"description\": \"The maximum age, in days (based on the start time), for a","self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN","args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup await scheduler._get_schedules() #","'%s' for execution\", 'OMF to PI north') == args args, kwargs = log_info.call_args_list[0]","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() # THEN assert","= \"Schedule %s already enabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): #","# THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker):","test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN payload =","\"d1631422-9ec6-11e7-abc4-cec278b6b50a\", \"process_name\": \"backup\", \"schedule_name\": \"backup hourly\", \"schedule_type\": 3, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\":","that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN","exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule,","@pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","await scheduler.disable_schedule(sch_id) # THEN assert status is True assert message == \"Schedule {}","is no task queued for this schedule at first with pytest.raises(KeyError) as excinfo:","PI\", name=\"OMF to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler,","return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler,","code coverage # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","mock_coro(): return \"\" # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","= mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") # WHEN # THEN with","PI north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO: Mandatory -","Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2]","\"id\": \"2176eb68-7303-11e7-8cf7-a6006ad3dba0\", \"process_name\": \"stats collector\", \"schedule_name\": \"stats collection\", \"schedule_type\": 2, \"schedule_interval\": \"00:00:15\", \"schedule_time\":","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mock_schedules = dict() mock_schedule =","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \"exception\") new_schedules","scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") #","scheduler._check_schedules() # THEN assert earliest_start_time is not None assert 3 == log_info.call_count args0,","Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess',","scheduler._ScheduleExecution) # Changed in version 3.8: patch() now returns an AsyncMock if the","'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio","kwargs2 = log_info.call_args_list[2] assert 'stats collection' in args0 assert 'COAP listener south' in","json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN scheduler,","is_exception\", [ ('\"Blah\" 0 days', True), ('12:30:11', False), ('0 day 12:30:11', False), ('1","now returns an AsyncMock if the target is an async function. if sys.version_info.major","== schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is","not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN","0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"2b614d26-760f-11e7-b5a5-be2e44b06b34\", \"process_name\": \"North Readings to","OSIsoft, LLC\" __license__ = \"Apache 2.0\" __version__ = \"${VERSION}\" async def mock_task(): return","{\"alias\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"end_time\"}, \"reason\", \"exit_code\"], \"where\": {\"column\": \"id\", \"condition\":","why these exceptions are being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An","THEN if is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count","'_ready', True) # WHEN # Now delete schedule await scheduler.delete_schedule(sch_id) # THEN #","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time =","schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True,","be done\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN","'OMF to PI north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName':","mocker.patch.object(scheduler, '_ready', True) # Confirm there are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)","mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler,","scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert","@pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO: Mandatory - Add negative tests for","log_info.call_args_list[0] assert 'OMF to PI north' in args assert 'North Readings to PI'","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True)","to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger,","0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be between","%s running tasks\\n%s\" in args assert 'OMF to PI north' in args assert","MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN","def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","maximum number of tasks that can be running at any given time\", \"type\":","log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\")","uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4())","THEN assert time_after_call > time_before_call assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0]","as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time() await","assert schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert","assert \"Stopping process: Schedule '%s' process '%s' task %s pid %s\\n%s\" in args","args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO: Mandatory - Add negative tests","len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler()","return m @pytest.allure.feature(\"unit\") @pytest.allure.story(\"scheduler\") class TestScheduler: async def scheduler_fixture(self, mocker): # Changed in","time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 4 == log_info.call_count","THEN assert status is True assert message == \"Schedule successfully disabled\" assert (scheduler._schedules[sch_id]).id","None # WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert","given time\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \"value\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \"max_completed_task_age_days\": { \"description\": \"The","an enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker):","#Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there are 14 schedules assert","'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\")","\"<NAME>\" __copyright__ = \"Copyright (c) 2017 OSIsoft, LLC\" __license__ = \"Apache 2.0\" __version__","assert message == \"Schedule {} already disabled\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled","# WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \"Queued","THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler","assert task.start_time is not None assert task.end_time is not None assert task.exit_code is","scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 == log_info.call_count # args, kwargs = log_info.call_args_list[0]","with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with","\"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\":","def test_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for full code","mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","}, ] scheduled_processes = [ { \"name\": \"purge\", \"script\": [ \"tasks/purge\" ] },","3 and sys.version_info.minor >= 8: _rv = await get_cat() else: _rv = asyncio.ensure_future(get_cat())","mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict()","3 and sys.version_info.minor >= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process())","args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection' in args0 assert 'COAP listener south'","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError) as","# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready',","'_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler,","log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection' in","scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler,","Assert that there is no task queued for schedule with pytest.raises(KeyError) as excinfo:","scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 == log_info.call_count #","str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)","== disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" #","time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count","return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time()","[ \"tasks/north\", \"--stream_id\", \"4\", \"--debug_level\", \"1\" ] }, ] tasks = [ {","= sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert time_after_call >","sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time #","\"00:00:15\", \"schedule_time\": \"00:00:15\", \"schedule_day\": 3, \"exclusive\": \"f\", \"enabled\": \"t\" }, { \"id\": \"d1631422-9ec6-11e7-abc4-cec278b6b50a\",","is not None assert tasks[0].end_time is not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio","= await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","await scheduler._get_schedules() assert 1 == log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)","not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN","datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call","current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", current_time=current_time -","await get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage =","Confirm there are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now","of running\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \"value\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in","assert 1 == log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async","payload == p @pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info,","== len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks() # THEN assert 1","@pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","not None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def test_start(self, mocker): #","is no task queued for mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is","for execution\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler","kwargs = log_info.call_args_list[0] # assert (\"Queued schedule '%s' for execution\", 'OMF to PI","else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): #","PI\", \"state\": 1, \"start_time\": \"2018-02-06 13:28:14.477868\", \"end_time\": \"2018-02-06 13:28:14.856375\", \"exit_code\": \"0\", \"reason\": \"\"","such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN scheduler","list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name","str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \"max_completed_task_age_days\": { \"description\": \"The maximum age, in days (based on the","async def test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","# Only valid for test_save_schedule_update if table_name == \"schedules\": return {\"count\": 1} @classmethod","'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True)","\"name\": \"Fledge Storage\", \"type\": \"Storage\", \"service_port\": 9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\"","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # purge schedule #","# WHEN with pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks() # THEN payload","await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert schedule.name","scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there are 14 schedules assert len(scheduler._storage_async.schedules) ==","message == \"Schedule successfully disabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False","False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio","= scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call =","# THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\"_mark_tasks_interrupted() not","'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert","{ \"name\": \"backup\", \"script\": [ \"tasks/backup_postgres\" ] }, { \"name\": \"COAP\", \"script\": [","log_debug = await self.scheduler_fixture(mocker) # Assert that there is no task queued for","in args0 assert 'COAP listener south' in args1 assert 'OMF to PI north'","\"id\": \"ada12840-68d3-11e7-907b-a6006ad3dba0\", \"process_name\": \"COAP\", \"schedule_name\": \"COAP listener south\", \"schedule_type\": 1, \"schedule_interval\": \"00:00:00\", \"schedule_time\":","= await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info,","sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call","== first_task.call_count assert 1 == resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 ==","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN","= mocker.patch.object(scheduler._logger, \"info\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to","collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call =","def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task has","is not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): #","in version 3.8: patch() now returns an AsyncMock if the target is an","1 == get_cat.call_count assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is not None","THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): #","tasks[0].start_time is not None assert tasks[0].end_time is None assert tasks[0].exit_code is None @pytest.mark.asyncio","}, { \"name\": \"backup\", \"script\": [ \"tasks/backup_postgres\" ] }, { \"name\": \"COAP\", \"script\":","this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): #","len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\"_mark_tasks_interrupted() not implemented in main Scheduler class.\")","test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow(","is True # WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with","disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN","} # Changed in version 3.8: patch() now returns an AsyncMock if the","log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo:","async def test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","tasks[0].start_time is not None assert tasks[0].end_time is not None assert tasks[0].exit_code is '0'","message = await scheduler.disable_schedule(sch_id) # THEN assert status is True assert message ==","0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine","enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count","async def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","\"object MagicMock can't be used in 'await' expression\"), call('An exception was raised by","scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert","datetime.timedelta(0, 3600) assert schedule.exclusive is True assert schedule.enabled is True assert schedule.process_name ==","async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","'_schedule_first_task', side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query","# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert","mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North # WHEN status,","'North Readings to PI' in args args, kwargs = log_info.call_args_list[1] assert \"Stopping process:","args args, kwargs = log_info.call_args_list[0] assert \"Process started: Schedule '%s' process '%s' task","\"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"2b614d26-760f-11e7-b5a5-be2e44b06b34\", \"process_name\": \"North Readings to PI\",","log_info.call_count # args, kwargs = log_info.call_args_list[0] # assert (\"Queued schedule '%s' for execution\",","# WHEN # THEN if is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules() assert","AsyncMock if the target is an async function. if sys.version_info.major == 3 and","len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks() # THEN assert 1 == len(tasks)","id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN","#Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN","to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\"_scheduler_loop() not suitable for unit testing. Will","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN","is not None assert task.end_time is not None assert task.exit_code is '0' @pytest.mark.skip(\"Need","WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)","\"integer\", \"default\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \"value\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \"max_completed_task_age_days\": { \"description\": \"The maximum age, in","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there is no North","with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with","is True assert 1 == queue_task.call_count calls = [call(\"Enabled Schedule '%s/%s' process '%s'\\n\",","9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } class MockStorageAsync(StorageClientAsync): schedules = [","is True assert message == \"Schedule successfully disabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert","collection' in args0 assert 'COAP listener south' in args1 assert 'OMF to PI","True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker):","in this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker):","\"integer\", \"default\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \"value\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version 3.8: patch()","assert 1 == log_exception.call_count log_params = 'Attempt to delete an enabled Schedule %s.","any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() #","'_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", _start_time=current_time - 3600, _paused=False, _task_processes={})","\"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" }, { \"id\": \"ada12840-68d3-11e7-907b-a6006ad3dba0\", \"process_name\": \"COAP\", \"schedule_name\":","by Scheduler._purge_tasks %s', \"object MagicMock can't be used in 'await' expression\"), call('An exception","'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI","scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) #","None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests","Scheduler class.\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker): async","scheduler.delete_schedule(sch_id) # THEN # Now confirm there is one schedule less assert len(scheduler._storage_async.schedules)","pid %s\\n%s\" in args assert 'OMF to PI north' in args assert 'North","== args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self,","# Now confirm there is one schedule less assert len(scheduler._storage_async.schedules) - 1 ==","to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler =","= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \"info\") await scheduler._get_schedules() sch_id","'0' @pytest.mark.skip(\"Need a suitable fixture\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN scheduler,","excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo:","assert payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule,","one schedule less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self,","Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client","\"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"2176eb68-7303-11e7-8cf7-a6006ad3dba0\", \"process_name\":","- 3600, _paused=False, _task_processes={}) # WHEN retval = await scheduler.stop() # THEN assert","scheduler._check_processes_pending is False # WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules()","excinfo: tasks = await scheduler.get_tasks() # THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\",","async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker): async def get_cat():","def test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","THEN # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1","task queued for this schedule at first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id]","MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() #","host, port): return { \"id\": uuid.uuid4(), \"name\": \"Fledge Storage\", \"type\": \"Storage\", \"service_port\": 9999,","log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4())","\"schedule_name\": \"stats collection\", \"schedule_type\": 2, \"schedule_interval\": \"00:00:15\", \"schedule_time\": \"00:00:15\", \"schedule_day\": 3, \"exclusive\": \"f\",","enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule)","def mock_task(): return \"\" async def mock_process(): m = MagicMock() m.pid = 9999","args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection' in args0","yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task has started","exception was raised by Scheduler._purge_tasks %s', \"object MagicMock can't be used in 'await'","as excinfo: tasks = await scheduler.get_tasks() # THEN payload = {\"return\": [\"id\", \"process_name\",","time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \"exception\") log_error = mocker.patch.object(scheduler._logger, \"error\") log_debug","mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts',","async def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","await scheduler._start_task(schedule) # THEN # Confirm that task has started assert 1 ==","async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN scheduler =","\"f\" }, ] scheduled_processes = [ { \"name\": \"purge\", \"script\": [ \"tasks/purge\" ]","schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be of","def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule, log_info,","WHEN # THEN with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name =","mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo:","no schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count log_params","that the North task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) #","assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type","valid for test_save_schedule_update if table_name == \"schedules\": return {\"count\": 1} @classmethod async def","After task completion, sleep above, no task processes should be left pending assert","log_info.call_args_list[2] assert 'stats collection' in args0 assert 'COAP listener south' in args1 assert","mocker.patch.object(ConfigurationManager, \"get_category_all_items\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None","\"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\", \"process_name\": \"North Readings to OCS\",","@pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","mocker.patch.object(scheduler._logger, \"error\") log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") return scheduler, schedule,","test_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage","await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can not be empty\") with pytest.raises(ValueError) as","await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker):","running\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \"value\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version","can not be empty\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat","temp_schedule assert str(ex).endswith('repeat must be of type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule","scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker):","ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert","log_debug = await self.scheduler_fixture(mocker) # Assert that there is no North task queued","{\"alias\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"start_time\"}, {\"alias\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\":","with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with","process '%s'\\n\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert","day 12:30:11', False), ('1 day 12:40:11', False), ('2 days', True), ('2 days 00:00:59',","True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task queued for mock_schedule","\"info\") enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) schedule_id =","('0 day 12:30:11', False), ('1 day 12:40:11', False), ('2 days', True), ('2 days","is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler,","\"schedule_interval\": \"00:00:15\", \"schedule_time\": \"00:00:15\", \"schedule_day\": 3, \"exclusive\": \"f\", \"enabled\": \"t\" }, { \"id\":","mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \"info\") await scheduler._get_schedules() sch_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") #","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \"exception\")","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10,","= 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\"test_interval, is_exception\", [ ('\"Blah\" 0 days',","= test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN if is_exception is True:","excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo:","time\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \"value\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \"max_completed_task_age_days\": { \"description\": \"The maximum","task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no","Storage\", \"type\": \"Storage\", \"service_port\": 9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } class","{ \"count\": len(MockStorageAsync.tasks), \"rows\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name, query=None): if","%s, %s running tasks\\n%s\" in args assert 'OMF to PI north' in args","\"max_running_tasks\": { \"description\": \"The maximum number of tasks that can be running at","schedule_id = uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id)","\"\" # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger","# WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple())","assert (scheduler._schedules[sch_id]).enabled is True log_params = \"Schedule %s already enabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio","calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled':","1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks() #","= scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call","def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO: Mandatory","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) #","temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be of type","status of running\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \"value\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed","scheduler._start_task(schedule) # THEN # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes)","9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } class MockStorageAsync(StorageClientAsync): schedules = [ { \"id\":","log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") #","def _get_storage_service(self, host, port): return { \"id\": uuid.uuid4(), \"name\": \"Fledge Storage\", \"type\": \"Storage\",","mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN # THEN with","with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with","= \"Copyright (c) 2017 OSIsoft, LLC\" __license__ = \"Apache 2.0\" __version__ = \"${VERSION}\"","= uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution =","calls = [call('Database command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio","THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler","scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker):","PI' in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO: Mandatory - Add","\"00:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"2b614d26-760f-11e7-b5a5-be2e44b06b34\",","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF part mocker.patch.object(scheduler,","north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \"exception\") log_error","pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del","args, kwargs = log_info.call_args_list[0] assert 'OMF to PI north' in args assert 'North","= \"Schedule %s already disabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): #","== task.process_name assert task.reason is '' assert task.state is not None assert task.cancel_requested","disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test","function. if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await mock_process()","dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF to PI north\",","= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() #","empty\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap mocker.patch.object(scheduler,","= await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks =","type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') #","'_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False # WHEN # Check","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") log_exception","LLC\" __license__ = \"Apache 2.0\" __version__ = \"${VERSION}\" async def mock_task(): return \"\"","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \"create_category\", return_value=asyncio.ensure_future(mock_task())) get_cat =","asyncio import datetime import uuid import time import json from unittest.mock import MagicMock,","sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count calls = [call('No Task","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler,","scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be of type datetime.time') with pytest.raises(ValueError) as","= await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN task_id","'stats collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO: Mandatory -","await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await","return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1","WHEN # THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo:","await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","def mock_coro(): return \"\" # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo:","\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\", \"process_name\": \"stats collector\", \"schedule_name\": \"stats collection\", \"schedule_type\": 2, \"schedule_interval\": \"00:00:15\", \"schedule_time\": \"00:00:15\",","# Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is","\"COAP\", \"script\": [ \"services/south\" ] }, { \"name\": \"North Readings to PI\", \"script\":","core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async","2 == log_info.call_count calls = [call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\"Disabled","and assert that the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution)","THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler","list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO:","# THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN","\"Copyright (c) 2017 OSIsoft, LLC\" __license__ = \"Apache 2.0\" __version__ = \"${VERSION}\" async","name=\"OMF to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception =","WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1","ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert","== sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params = \"Schedule %s already disabled\", str(sch_id)","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup queue_task =","schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30),","= await self.scheduler_fixture(mocker) # Assert that there is no task queued for schedule","{\"column\": \"id\", \"condition\": \"=\", \"value\": str(task_id)}} args, kwargs = log_exception.call_args assert 'Query failed:","{ \"id\": uuid.uuid4(), \"name\": \"Fledge Storage\", \"type\": \"Storage\", \"service_port\": 9999, \"management_port\": 9999, \"address\":","'_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"),","len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","\"condition\": \"=\", \"value\": str(task_id)}} args, kwargs = log_exception.call_args assert 'Query failed: %s' ==","test.\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None):","earliest_start_time = await scheduler._check_schedules() # THEN assert earliest_start_time is not None assert 3","'OMF to PI north' in args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task() also","assert tasks[0].end_time is None assert tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self, mocker):","assert 1 == len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is None assert","scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time","# THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker):","def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule, log_info,","}, { \"id\": \"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\", \"process_name\": \"North Readings to OCS\", \"schedule_name\": \"OMF to OCS","await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion, sleep above, no task processes","deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count log_params = 'Attempt to","successfully enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1 ==","\"value\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version 3.8: patch() now returns an","13:28:14.856375\", \"exit_code\": \"0\", \"reason\": \"\" } ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port)","log_info = mocker.patch.object(scheduler._logger, \"info\") return scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async","# backup # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert status","test__schedule_first_task(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage","scheduler._start_task(schedule) # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id =","\"\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can not be empty\") with pytest.raises(ValueError)","args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","= asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\"North","# THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN","# THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def test__check_schedules(self, mocker): #","\"info\") schedule_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id,","'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to PI'}})]","= MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts)","status is True assert message == \"Schedule successfully enabled\" assert (scheduler._schedules[sch_id]).id == sch_id","\"schedule_name\": \"OMF to OCS north\", \"schedule_type\": 3, \"schedule_interval\": \"1 day 00:00:40\", \"schedule_time\": \"\",","MagicMock() m.pid = 9999 m.terminate = lambda: True return m @pytest.allure.feature(\"unit\") @pytest.allure.story(\"scheduler\") class","must be of type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)","\"protocol\": \"http\" } @classmethod async def insert_into_tbl(cls, table_name, payload): pass @classmethod async def","\"stats collector\", \"script\": [ \"tasks/statistics\" ] }, { \"name\": \"backup\", \"script\": [ \"tasks/backup_postgres\"","import StorageClientAsync __author__ = \"<NAME>\" __copyright__ = \"Copyright (c) 2017 OSIsoft, LLC\" __license__","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False)","%d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s', 'scheduled_processes'), call('Database command: %s',","schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules)","None assert tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN scheduler,","\"reason\", \"exit_code\"], \"limit\": 100} args, kwargs = log_exception.call_args assert 'Query failed: %s' ==","@pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4()","north\", \"schedule_type\": 3, \"schedule_interval\": \"1 day 00:00:40\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\",","False assert scheduler._paused is False assert scheduler._start_time is None calls = [call('Processing stop","Assert that there is no task queued for this schedule at first with","assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is","MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return {","== len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks() # THEN assert 1 ==","test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","\"ada12840-68d3-11e7-907b-a6006ad3dba0\", \"process_name\": \"COAP\", \"schedule_name\": \"COAP listener south\", \"schedule_type\": 1, \"schedule_interval\": \"00:00:00\", \"schedule_time\": \"\",","current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN","north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to","assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls","def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","# backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no","\"enabled\": \"t\" }, { \"id\": \"2176eb68-7303-11e7-8cf7-a6006ad3dba0\", \"process_name\": \"stats collector\", \"schedule_name\": \"stats collection\", \"schedule_type\":","current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id =","async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule,","is None calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find","excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN scheduler,","{ \"name\": \"COAP\", \"script\": [ \"services/south\" ] }, { \"name\": \"North Readings to","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks',","listener south' in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio async","= scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN","type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \"exception\") log_error =","kwargs3 = log_info.call_args_list[3] assert 'stats collection' in args0 assert 'COAP listener south' in","also gets executed, hence # \"stat collector\" appears twice in this list. assert","'_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") # WHEN","scheduler._ready is False # WHEN await scheduler.start() # THEN assert scheduler._ready is True","\"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow(","'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): #","uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \"No such Schedule %s\",","2 == log_info.call_count # args, kwargs = log_info.call_args_list[0] # assert (\"Queued schedule '%s'","with pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker):","{ \"count\": len(MockStorageAsync.schedules), \"rows\": MockStorageAsync.schedules } if table_name == 'scheduled_processes': return { \"count\":","self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN task_id = uuid.uuid4()","\"script\": [ \"tasks/north\", \"--stream_id\", \"1\", \"--debug_level\", \"1\" ] }, { \"name\": \"North Readings","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info","\"process_name\": \"purge\", \"schedule_name\": \"purge\", \"schedule_type\": 4, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\":","port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s', 'scheduled_processes'),","return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await","self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there","== len(scheduler._schedules) # WHEN # Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) #","mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start()","(scheduler._schedules[sch_id]).enabled is False log_params = \"Schedule %s already disabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async","del temp_schedule assert str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError) as ex: temp_schedule","await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1","less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): #","= await scheduler.enable_schedule(sch_id) # THEN assert status is True assert message == \"Schedule","stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN","resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self,","assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is True assert schedule.enabled is True","that task has not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await","'%s' task %s pid %s\\n%s\" in args assert 'OMF to PI north' in","is_exception, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler,","= uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await","for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue","assert str(ex).endswith('repeat must be of type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule =","== audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat':","\"info\") log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task',","mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task queued for mock_schedule with","mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args =","sys import copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities","failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN scheduler =","mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert","test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","Scheduler._purge_tasks %s', \"object MagicMock can't be used in 'await' expression\"), call('An exception was","== audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup',","@pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","assert task.end_time is not None assert task.exit_code is '0' @pytest.mark.skip(\"Need a suitable fixture\")","scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be","1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\"To be done\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async","scheduler.enable_schedule(random_schedule_id) # THEN log_params = \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async","in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\"_scheduler_loop() not suitable","query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks': return { \"count\": len(MockStorageAsync.tasks), \"rows\": MockStorageAsync.tasks","sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await mock_process() else: _rv","await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \"Queued schedule '%s'","WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id ==","\"exception\") log_error = mocker.patch.object(scheduler._logger, \"error\") log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\")","= mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") return scheduler, schedule, log_info, log_exception, log_error,","@pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","WHEN task = await scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name assert task.reason","as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule","log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks","scheduler.disable_schedule(random_schedule_id) # THEN log_params = \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async","is not None @pytest.mark.asyncio async def test_start(self, mocker): # TODO: Mandatory - Add","not None assert task.cancel_requested is None assert task.start_time is not None assert task.end_time","get_cat.call_count assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async","with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id) #","str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","_last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not","@classmethod async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload):","'%s' process '%s' task %s pid %s\\n%s\" in args assert 'OMF to PI","'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks() #","scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False # WHEN # Check ELSE part","0, \"exclusive\": \"t\", \"enabled\": \"f\" }, ] scheduled_processes = [ { \"name\": \"purge\",","\"tasks/north\", \"--stream_id\", \"4\", \"--debug_level\", \"1\" ] }, ] tasks = [ { \"id\":","await self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) ==","not be None') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time =","_schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") # WHEN await scheduler._wait_for_task_completion(mock_task_process)","assert 1 == resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio","scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None await scheduler._read_config() # THEN assert 1","# THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async","'_paused', True) # WHEN # THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with","\"name\": \"backup\", \"script\": [ \"tasks/backup_postgres\" ] }, { \"name\": \"COAP\", \"script\": [ \"services/south\"","PI' in args args, kwargs = log_info.call_args_list[1] assert \"Stopping process: Schedule '%s' process","def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker): async def get_cat(): return","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \"info\") await scheduler._get_schedules()","time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there","scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker):","north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules')","schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info,","\"North Readings to OCS\", \"schedule_name\": \"OMF to OCS north\", \"schedule_type\": 3, \"schedule_interval\": \"1","scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state","\"2018-02-06 13:28:14.477868\", \"end_time\": \"2018-02-06 13:28:14.856375\", \"exit_code\": \"0\", \"reason\": \"\" } ] def __init__(self,","is not None assert 2 == log_info.call_count # args, kwargs = log_info.call_args_list[0] #","# THEN assert retval is True assert scheduler._schedule_executions is None assert scheduler._task_processes is","\"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" }, ] scheduled_processes = [ {","assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF to PI north',","GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN #","that cancel request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN","assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN scheduler, schedule,","\"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"end_time\"}, \"reason\", \"exit_code\"], \"where\": {\"column\": \"id\", \"condition\": \"=\", \"value\":","if table_name == \"schedules\": return {\"count\": 1} @classmethod async def delete_from_tbl(cls, table_name, condition=None):","{ \"id\": \"cea17db8-6ccc-11e7-907b-a6006ad3dba0\", \"process_name\": \"purge\", \"schedule_name\": \"purge\", \"schedule_type\": 4, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\",","== resume_sch.call_count assert 1 == enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN await","PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\"_scheduler_loop() not suitable for unit testing. Will be","schedule at first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN","datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN assert","args assert 'North Readings to PI' in args args, kwargs = log_info.call_args_list[1] assert","scheduler._schedule_first_task() also gets executed, hence # \"stat collector\" appears twice in this list.","test_interval, is_exception, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler,","\"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"start_time\"}, {\"alias\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"end_time\"},","log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler,","Schedule) assert schedule.schedule_id == schedule_id assert schedule.name == \"purge\" assert schedule.schedule_type == Schedule.Type.MANUAL","# WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed: %s',","len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","assert scheduler._check_processes_pending is False # WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None)","Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has not started yet","started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request","= mocker.patch.object(scheduler._logger, \"info\") await scheduler._get_schedules() sch_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # backup mocker.patch.object(scheduler, '_ready', True)","assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is True","[ { \"id\": \"cea17db8-6ccc-11e7-907b-a6006ad3dba0\", \"process_name\": \"purge\", \"schedule_name\": \"purge\", \"schedule_type\": 4, \"schedule_interval\": \"01:00:00\", \"schedule_time\":","insert_into_tbl(cls, table_name, payload): pass @classmethod async def update_tbl(cls, table_name, payload): # Only valid","MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") # WHEN","hence # \"stat collector\" appears twice in this list. assert 'stats collection' in","@classmethod async def query_tbl(cls, table_name, query=None): if table_name == 'schedules': return { \"count\":","test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker): async def get_cat(): return {","@pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\"test_interval, is_exception\", [ ('\"Blah\" 0 days', True), ('12:30:11',","current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", _start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN","('00:25:61', True) ]) async def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler =","@pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with","\"exit_code\"], \"limit\": 100} args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0]","of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN","= json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN","def test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","== schedule_row[2] assert schedule_row[3] is 0 # 0 for Interval Schedule assert schedule_row[4]","there is no task queued for this schedule at first with pytest.raises(KeyError) as","\"info\") sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN status, message = await scheduler.disable_schedule(sch_id)","Confirm no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN","= await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4())","# THEN # Now confirm there is one schedule less assert len(scheduler._storage_async.schedules) -","True # Now queue task and assert that the North task has been","sleep above, no task processes should be left pending assert 0 == len(scheduler._task_processes)","any_order=True) calls = [call('Database command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True)","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger,","gets executed, hence # \"stat collector\" appears twice in this list. assert 'stats","scheduler._get_schedules() assert 1 == log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio","= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler,","type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None","= log_info.call_args_list[0] # assert (\"Queued schedule '%s' for execution\", 'OMF to PI north')","True), ('2 days 00:00:59', False), ('00:25:61', True) ]) async def test__get_schedules(self, test_interval, is_exception,","task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that","assert scheduler._task_processes is None assert scheduler._schedules is None assert scheduler._process_scripts is None assert","# WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 ==","# THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0 =","await scheduler._get_schedules() sch_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') #","mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN #","# WHEN # Now delete schedule await scheduler.delete_schedule(sch_id) # THEN # Now confirm","= await scheduler.disable_schedule(sch_id) # THEN assert status is True assert message == \"Schedule","= await get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage","listener south' in args1 assert 'OMF to PI north' in args2 # As","_paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is","not suitable for unit testing. Will be tested during System tests.\") async def","len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","delete schedule await scheduler.delete_schedule(sch_id) # THEN # Now confirm there is one schedule","def test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap","is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): #","assert schedule.exclusive is True assert schedule.enabled is True assert schedule.process_name == \"purge\" @pytest.mark.asyncio","message = await scheduler.enable_schedule(sch_id) # THEN assert status is True assert message ==","query=None): if table_name == 'schedules': return { \"count\": len(MockStorageAsync.schedules), \"rows\": MockStorageAsync.schedules } if","is False log_params = \"Schedule %s already disabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def","30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls,","log_info = mocker.patch.object(scheduler._logger, \"info\") await scheduler._get_schedules() sch_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # backup mocker.patch.object(scheduler, '_ready',","await scheduler.delete_schedule(sch_id) # THEN # Now confirm there is one schedule less assert","= mocker.patch.object(scheduler._logger, \"error\") log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") return scheduler,","mocker): async def get_cat(): return { \"max_running_tasks\": { \"description\": \"The maximum number of","excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info,","_rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future',","= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) +","== len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler() schedule_id","asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings","mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\")","HH24:MI:SS.MS\", \"column\": \"end_time\"}, \"reason\", \"exit_code\"], \"where\": {\"column\": \"id\", \"condition\": \"=\", \"value\": str(task_id)}} args,","test__check_schedules(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage","= MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600)","have a status of running\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \"value\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, }","\"column\": \"end_time\"}, \"reason\", \"exit_code\"], \"where\": {\"column\": \"id\", \"condition\": \"=\", \"value\": str(task_id)}} args, kwargs","# WHEN retval = await scheduler.stop() # THEN assert retval is True assert","None assert tasks[0].start_time is not None assert tasks[0].end_time is not None assert tasks[0].exit_code","mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler,","time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 3 == log_info.call_count","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes =","kwargs = log_exception.call_args assert 'Query failed: %s' == args[0] p = json.loads(args[1]) assert","3, \"schedule_interval\": \"00:00:30\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, {","-*- # FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime import","= mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id =","= mocker.patch.object(ConfigurationManager, \"get_category_all_items\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is","async def test_start(self, mocker): # TODO: Mandatory - Add negative tests for full","task.cancel_requested is None assert task.start_time is not None assert task.end_time is not None","pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError)","Readings to PI' in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO: Mandatory","= mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules)","this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): #","pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\"test_interval, is_exception\",","be empty\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234","await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info","len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id)","WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not","temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del","THEN assert retval is True assert scheduler._schedule_executions is None assert scheduler._task_processes is None","can't be used in 'await' expression\"), call('An exception was raised by Scheduler._scheduler_loop %s',","MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North","False), ('2 days', True), ('2 days 00:00:59', False), ('00:25:61', True) ]) async def","received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s', 'scheduled_processes'), call('Database","mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") schedule_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI","core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger,","import copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import","\"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" }, { \"id\": \"ada12840-68d3-11e7-907b-a6006ad3dba0\",","'_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") schedule_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") #","\"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"start_time\"}, {\"alias\": \"end_time\", \"format\":","scheduler.disable_schedule(sch_id) # THEN assert status is True assert message == \"Schedule successfully disabled\"","# Confirm no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) #","\"process_name\": \"backup\", \"schedule_name\": \"backup hourly\", \"schedule_type\": 3, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0,","} @classmethod async def query_tbl(cls, table_name, query=None): if table_name == 'schedules': return {","isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8: patch() now returns an AsyncMock if","%s pid %s, %s running tasks\\n%s\" in args assert 'OMF to PI north'","log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF to PI","a rows \" \"in the tasks table that do not have a status","task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True #","= log_info.call_args_list[0] assert 'OMF to PI north' in args assert 'North Readings to","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception =","mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to","day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN","temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat","test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","tasks = await scheduler.get_tasks() # THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\",","@pytest.mark.parametrize(\"test_interval, is_exception\", [ ('\"Blah\" 0 days', True), ('12:30:11', False), ('0 day 12:30:11', False),","call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): # TODO:","test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule, log_info, log_exception,","\"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"2b614d26-760f-11e7-b5a5-be2e44b06b34\", \"process_name\":","task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert","kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection' in args0 assert","1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count","side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed:","kwargs = log_info.call_args_list[1] assert \"Stopping process: Schedule '%s' process '%s' task %s pid","\"North Readings to PI\", \"script\": [ \"tasks/north\", \"--stream_id\", \"1\", \"--debug_level\", \"1\" ] },","sys.version_info.minor >= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler =","scheduler._task_processes is None assert scheduler._schedules is None assert scheduler._process_scripts is None assert scheduler._ready","assert str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id,","\"reason\", \"exit_code\"], \"where\": {\"column\": \"id\", \"condition\": \"=\", \"value\": str(task_id)}} args, kwargs = log_exception.call_args","\"\" async def mock_process(): m = MagicMock() m.pid = 9999 m.terminate = lambda:","running at any given time\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \"value\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \"max_completed_task_age_days\":","mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch =","as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule,","'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert 1 ==","None assert task.start_time is not None assert task.end_time is not None assert task.exit_code","repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes","# assert (\"Queued schedule '%s' for execution\", 'OMF to PI north') == args","= mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions =","0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"2176eb68-7303-11e7-8cf7-a6006ad3dba0\", \"process_name\": \"stats collector\", \"schedule_name\":","len(MockStorageAsync.schedules), \"rows\": MockStorageAsync.schedules } if table_name == 'scheduled_processes': return { \"count\": len(MockStorageAsync.scheduled_processes), \"rows\":","the start time), for a rows \" \"in the tasks table that do","PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF to","repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \"exception\") log_error = mocker.patch.object(scheduler._logger, \"error\")","log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task')","schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN # Now delete","\"id\", \"condition\": \"=\", \"value\": str(task_id)}} args, kwargs = log_exception.call_args assert 'Query failed: %s'","= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False)","queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now","WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules'","= Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0,","PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process","mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch =","excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo:","_start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch = scheduler._schedules[sch_id] sch_execution","= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN #","core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules()","is None await scheduler._read_config() # THEN assert 1 == cr_cat.call_count assert 1 ==","mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id","to PI north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North","is one schedule less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async def","scheduler.get_tasks() # THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"column\":","south\", \"schedule_type\": 1, \"schedule_interval\": \"00:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\"","# THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count calls","\"schedule_interval\": \"00:00:30\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\":","scheduler._ready is False assert scheduler._paused is False assert scheduler._start_time is None calls =","def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\"_terminate_child_processes() not fit for","WHEN schedules = await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async","= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None)","= uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there are 14","above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN await","assert tasks[0].start_time is not None assert tasks[0].end_time is None assert tasks[0].exit_code is None","excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info,","True # WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params =","await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","# THEN # Now confirm no schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)","@pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0,","\"00:00:30\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\",","WHEN # THEN task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) #","[call('Starting'), call('Starting Scheduler: Management port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls =","len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management","log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there is no North task","to OCS north\", \"schedule_type\": 3, \"schedule_interval\": \"1 day 00:00:40\", \"schedule_time\": \"\", \"schedule_day\": 0,","with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now confirm no schedule is deleted","self.scheduler_fixture(mocker) # Assert that there is no North task queued for schedule with","await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup #","import uuid import time import json from unittest.mock import MagicMock, call import sys","assert schedule.process_name == task.process_name assert task.reason is '' assert task.state is not None","assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 0 == enable_schedule.call_count assert","mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings","None assert scheduler._max_completed_task_age is None await scheduler._read_config() # THEN assert 1 == cr_cat.call_count","= mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] =","len(scheduler._schedules) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled':","= log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 =","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler,","True assert scheduler._schedule_executions is None assert scheduler._task_processes is None assert scheduler._schedules is None","task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks()","'_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN with pytest.raises(NotReadyError) as excinfo:","tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time","Schedule assert schedule_row[4] is 0 # 0 for Interval Schedule assert schedule.repeat ==","TODO: Find why these exceptions are being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls","1 == len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state","excinfo: await scheduler.get_task(task_id) # THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\":","mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop',","= time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", current_time=current_time - 3600)","= \"Queued schedule '%s' for execution\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self,","THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD',","_start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch = scheduler._schedules[sch_id] sch_execution","scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules() # THEN assert","# OMF to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1,","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id =","= dict() mock_task_process.process = await asyncio.create_subprocess_exec(\"sleep\", \".1\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4()","\"2b614d26-760f-11e7-b5a5-be2e44b06b34\", \"process_name\": \"North Readings to PI\", \"schedule_name\": \"OMF to PI north\", \"schedule_type\": 3,","return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North","exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) #","mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule =","\"info\") sch_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North # WHEN status, message","unit test.\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None,","call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these exceptions are being raised despite","was raised by Scheduler._scheduler_loop %s', \"object MagicMock can't be used in 'await' expression\")]","class TestScheduler: async def scheduler_fixture(self, mocker): # Changed in version 3.8: patch() now","assert retval is True assert scheduler._schedule_executions is None assert scheduler._task_processes is None assert","# WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \"No such Schedule %s\", str(random_schedule_id)","schedules = [ { \"id\": \"cea17db8-6ccc-11e7-907b-a6006ad3dba0\", \"process_name\": \"purge\", \"schedule_name\": \"purge\", \"schedule_type\": 4, \"schedule_interval\":","name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule","fit for unit test.\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def","THEN assert status is True assert message == \"Schedule is already enabled\" assert","mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id =","= lambda: True return m @pytest.allure.feature(\"unit\") @pytest.allure.story(\"scheduler\") class TestScheduler: async def scheduler_fixture(self, mocker):","is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count log_params = 'Attempt","'_ready', True) # WHEN processes = await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) ==","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\")","scheduler.disable_schedule(sch_id) # THEN assert status is True assert message == \"Schedule {} already","tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info,","is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s', 'scheduled_processes'), call('Database command:","async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port)","there is no task queued for mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id]","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN","await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup await scheduler._get_schedules() # Confirm no. of","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \"create_category\",","executed, hence # \"stat collector\" appears twice in this list. assert 'stats collection'","args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3,","log_error = mocker.patch.object(scheduler._logger, \"error\") log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") return","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules')","scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\"_terminate_child_processes() not fit for unit test.\")","_rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","\"schedule_type\": 3, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" },","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception())","# THEN assert scheduler._check_processes_pending is False # WHEN # Check ELSE part mocker.patch.object(scheduler,","log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule',","== disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" #","_task_processes={}) # WHEN retval = await scheduler.stop() # THEN assert retval is True","backup await scheduler._get_schedules() # Confirm no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler,","True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task()))","with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN payload = {\"return\": [\"id\", \"process_name\",","being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception was raised by","2, \"schedule_interval\": \"00:00:15\", \"schedule_time\": \"00:00:15\", \"schedule_day\": 3, \"exclusive\": \"f\", \"enabled\": \"t\" }, {","IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False #","log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there is no task queued","\"rows\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name, query=None): if table_name == 'schedules':","assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN scheduler, schedule,","False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 1","{ \"id\": \"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\", \"process_name\": \"North Readings to OCS\", \"schedule_name\": \"OMF to OCS north\",","that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count #","log_info.call_args_list[0] # assert (\"Queued schedule '%s' for execution\", 'OMF to PI north') ==","scheduler.start() # THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules)","schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count log_params =","= [call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\"Disabled Schedule '%s/%s' process '%s'\\n\",","await scheduler.enable_schedule(sch_id) # THEN assert status is True assert message == \"Schedule is","id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN","1 == resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async","core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"),","\"f\", \"enabled\": \"t\" }, { \"id\": \"d1631422-9ec6-11e7-abc4-cec278b6b50a\", \"process_name\": \"backup\", \"schedule_name\": \"backup hourly\", \"schedule_type\":","GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler,","Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True)","scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can not be empty\") with pytest.raises(ValueError) as ex:","schedule.exclusive is True assert schedule.enabled is True assert schedule.process_name == \"purge\" @pytest.mark.asyncio async","= await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status,","is True # Now queue task and assert that the task has been","calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False,","# THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker):","await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 ==","= [ { \"id\": \"cea17db8-6ccc-11e7-907b-a6006ad3dba0\", \"process_name\": \"purge\", \"schedule_name\": \"purge\", \"schedule_type\": 4, \"schedule_interval\": \"01:00:00\",","pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro():","= await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task()))","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup await","MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN","schedule_row[4] is 0 # 0 for Interval Schedule assert schedule.repeat == schedule_row[5] assert","port): return { \"id\": uuid.uuid4(), \"name\": \"Fledge Storage\", \"type\": \"Storage\", \"service_port\": 9999, \"management_port\":","temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can not be empty\")","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) #","import json from unittest.mock import MagicMock, call import sys import copy import pytest","{ \"id\": \"2176eb68-7303-11e7-8cf7-a6006ad3dba0\", \"process_name\": \"stats collector\", \"schedule_name\": \"stats collection\", \"schedule_type\": 2, \"schedule_interval\": \"00:00:15\",","scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts()","mocker.patch.object(scheduler, '_ready', True) # WHEN # Now delete schedule await scheduler.delete_schedule(sch_id) # THEN","# See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime import uuid import time","scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \"\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can not","len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has not been made","# WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None await scheduler._read_config() #","day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \"exception\") log_error = mocker.patch.object(scheduler._logger, \"error\") log_debug =","sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 3","repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \"exception\") log_error = mocker.patch.object(scheduler._logger,","\"schedule_day\": 3, \"exclusive\": \"f\", \"enabled\": \"t\" }, { \"id\": \"d1631422-9ec6-11e7-abc4-cec278b6b50a\", \"process_name\": \"backup\", \"schedule_name\":","assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF to PI north'","import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from","= await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \"\"","Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules()","yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN # Confirm","fixture\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","= sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 3 == log_info.call_count args0,","THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN scheduler,","OCS north\", \"schedule_type\": 3, \"schedule_interval\": \"1 day 00:00:40\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\":","mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id]","= sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt)","OMF to PI North # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN","table_name == \"schedules\": return {\"count\": 1} @classmethod async def delete_from_tbl(cls, table_name, condition=None): pass","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() curr_time =","args assert 'North Readings to PI' in args @pytest.mark.asyncio async def test__start_task(self, mocker):","in main Scheduler class.\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self,","= uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # purge schedule # WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN","to OCS\", \"schedule_name\": \"OMF to OCS north\", \"schedule_type\": 3, \"schedule_interval\": \"1 day 00:00:40\",","started: Schedule '%s' process '%s' task %s pid %s, %s running tasks\\n%s\" in","Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now confirm no","scheduler._schedule_executions is None assert scheduler._task_processes is None assert scheduler._schedules is None assert scheduler._process_scripts","task and assert that the North task has been queued await scheduler.queue_task(schedule.id) assert","}, { \"id\": \"d1631422-9ec6-11e7-abc4-cec278b6b50a\", \"process_name\": \"backup\", \"schedule_name\": \"backup hourly\", \"schedule_type\": 3, \"schedule_interval\": \"01:00:00\",","mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules')","mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec',","mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", current_time=current_time - 3600) # TODO: Remove after","mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") # WHEN # THEN with pytest.raises(Exception):","to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has not started yet assert","%s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\"test_interval, is_exception\", [ ('\"Blah\" 0 days', True), ('12:30:11', False),","\"object MagicMock can't be used in 'await' expression\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self,","await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm","side_effect=Exception()) # WHEN # THEN task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo: await","tasks[0].end_time is None assert tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self, mocker): #","\"t\", \"enabled\": \"t\" }, { \"id\": \"2b614d26-760f-11e7-b5a5-be2e44b06b34\", \"process_name\": \"North Readings to PI\", \"schedule_name\":","not None assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 =","WHEN with pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks() # THEN payload =","== resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def","'OMF to PI north' in args assert 'North Readings to PI' in args","THEN assert 1 == len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is None","to PI\", \"state\": 1, \"start_time\": \"2018-02-06 13:28:14.477868\", \"end_time\": \"2018-02-06 13:28:14.856375\", \"exit_code\": \"0\", \"reason\":","return_value=\"North Readings to PI\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task","THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert schedule.name == \"purge\" assert","'debug', side_effect=Exception()) # WHEN # THEN task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo:","0, \"exclusive\": \"t\", \"enabled\": \"f\" }, { \"id\": \"ada12840-68d3-11e7-907b-a6006ad3dba0\", \"process_name\": \"COAP\", \"schedule_name\": \"COAP","is already enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params =","\"schedule_name\": \"purge\", \"schedule_type\": 4, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\":","exception was raised by Scheduler._scheduler_loop %s', \"object MagicMock can't be used in 'await'","enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert","as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as","by Scheduler._scheduler_loop %s', \"object MagicMock can't be used in 'await' expression\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio","datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch","schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0]","self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule = await","# THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker):","@pytest.mark.asyncio @pytest.mark.parametrize(\"test_interval, is_exception\", [ ('\"Blah\" 0 days', True), ('12:30:11', False), ('0 day 12:30:11',","WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self,","= await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params","True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): #","assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return","excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id],","@pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO: Mandatory - Add negative tests for","not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add negative","= mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North # WHEN","time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) #","# THEN assert status is True assert message == \"Schedule is already enabled\"","WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks()","len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN # Now delete schedule await","the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that","WHEN # Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now","\"schedule_name\", \"state\", {\"alias\": \"start_time\", \"column\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, {\"alias\": \"end_time\", \"column\": \"end_time\",","%s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler()","dict() mock_task_process.process = await asyncio.create_subprocess_exec(\"sleep\", \".1\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id","= 'Attempt to delete an enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio","False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 0","\"schedule_name\": \"OMF to PI north\", \"schedule_type\": 3, \"schedule_interval\": \"00:00:30\", \"schedule_time\": \"\", \"schedule_day\": 0,","as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as","# THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls = [call('SCHCH',","@pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","days', True), ('12:30:11', False), ('0 day 12:30:11', False), ('1 day 12:40:11', False), ('2","THEN log_params = \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self,","== 3 and sys.version_info.minor >= 8: _rv = await mock_process() else: _rv =","0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF","\"id\": \"cea17db8-6ccc-11e7-907b-a6006ad3dba0\", \"process_name\": \"purge\", \"schedule_name\": \"purge\", \"schedule_type\": 4, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\":","task.exit_code is '0' @pytest.mark.skip(\"Need a suitable fixture\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): #","schedule_row[3] is 0 # 0 for Interval Schedule assert schedule_row[4] is 0 #","= mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule',","%s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\"Disabled Schedule '%s/%s' process '%s'\\n\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North","'' assert tasks[0].state is not None assert tasks[0].cancel_requested is None assert tasks[0].start_time is","await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self,","temp_schedule assert str(ex).endswith('time must be of type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule","Now confirm there is one schedule less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules)","\"name\": \"North Readings to OCS\", \"script\": [ \"tasks/north\", \"--stream_id\", \"4\", \"--debug_level\", \"1\" ]","THEN task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN payload","'North Readings to PI' in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO:","log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\"test_interval, is_exception\", [ ('\"Blah\" 0 days', True), ('12:30:11', False), ('0 day","@pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler,","= mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN","'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert","tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state is not None assert tasks[0].cancel_requested is","at any given time\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \"value\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \"max_completed_task_age_days\": {","core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") # WHEN #","async def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","@pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler,","scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1 ==","log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task',","+ 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test","scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\"sleep\", \".1\") mock_task_process.schedule = mock_schedule mock_task_id","started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await","@pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","if table_name == 'tasks': return { \"count\": len(MockStorageAsync.tasks), \"rows\": MockStorageAsync.tasks } @classmethod async","with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\"test_interval,","'_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id","cancel request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await","= [ { \"name\": \"purge\", \"script\": [ \"tasks/purge\" ] }, { \"name\": \"stats","False), ('00:25:61', True) ]) async def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler","= mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN task_id = uuid.uuid4() with pytest.raises(Exception)","@pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host,","mocker.patch.object(scheduler._logger, \"info\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to","enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) schedule_id = uuid.uuid4()","\"enabled\": \"f\" }, ] scheduled_processes = [ { \"name\": \"purge\", \"script\": [ \"tasks/purge\"","= scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\"sleep\", \".1\") mock_task_process.schedule = mock_schedule","assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN # Now delete schedule","def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row =","len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN # Confirm that task has started","for execution\", 'OMF to PI north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert","earliest_start_time is not None assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1,","'repeat': 30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls,","mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task')","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now())","mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) #","new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN","len(scheduler._schedules) assert 1 == log_exception.call_count log_params = 'Attempt to delete an enabled Schedule","WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count","= await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # purge schedule # WHEN schedule =","process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler,","enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params = \"Schedule %s","\"Storage\", \"service_port\": 9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } @classmethod async def","= \"${VERSION}\" async def mock_task(): return \"\" async def mock_process(): m = MagicMock()","[ { \"name\": \"purge\", \"script\": [ \"tasks/purge\" ] }, { \"name\": \"stats collector\",","mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler,","= await asyncio.create_subprocess_exec(\"sleep\", \".1\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id","a status of running\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \"value\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } #","async def scheduler_fixture(self, mocker): # Changed in version 3.8: patch() now returns an","log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") return scheduler, schedule, log_info, log_exception,","\"=\", \"value\": str(task_id)}} args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0]","@pytest.mark.skip(\"_terminate_child_processes() not fit for unit test.\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class","pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): #","'schedules', new_schedules) # WHEN # THEN if is_exception is True: with pytest.raises(Exception): await","is None assert task.start_time is not None assert task.end_time is not None assert","False) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio,","can not be None') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time","'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await","await self.scheduler_fixture(mocker) # Assert that there is no task queued for schedule with","already enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params = \"Schedule","scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def test_start(self, mocker): # TODO: Mandatory -","tasks[0].state is not None assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None","\"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN","assert schedule.enabled is True assert schedule.process_name == \"purge\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker):","task has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that","pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\",","mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) #","as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\"_terminate_child_processes() not fit","= time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time","None assert 2 == log_info.call_count # args, kwargs = log_info.call_args_list[0] # assert (\"Queued","class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return","Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)","for unit testing. Will be tested during System tests.\") async def test__scheduler_loop(self, mocker):","an async function. if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv =","def test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo:","\"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"start_time\"}, {\"alias\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"end_time\"}, \"reason\", \"exit_code\"],","delete an enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self,","schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can not be",">= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv)","mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF","is an async function. if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv","has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks() #","first_task.call_count assert 1 == resume_sch.call_count assert 1 == enable_schedule.call_count assert 0 == disable_schedule.call_count","'_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time =","not have a status of running\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \"value\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) },","be empty\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \"\"","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as","assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 1 == enable_schedule.call_count assert","# WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def","list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name","excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo:","else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4())","= {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"column\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"},","3, \"schedule_interval\": \"1 day 00:00:40\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\"","# log_info = mocker.patch.object(scheduler._logger, \"info\") await scheduler._get_schedules() sch_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # backup mocker.patch.object(scheduler,","Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\"Disabled Schedule '%s/%s' process '%s'\\n\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34',","an AsyncMock if the target is an async function. if sys.version_info.major == 3","_core_management_port=9999, _core_management_host=\"0.0.0.0\", current_time=current_time - 3600) # TODO: Remove after implementation of above test","core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules()","ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert","\"purge\", \"script\": [ \"tasks/purge\" ] }, { \"name\": \"stats collector\", \"script\": [ \"tasks/statistics\"","await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger","is None assert scheduler._schedules is None assert scheduler._process_scripts is None assert scheduler._ready is","# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id =","async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","= list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks() # THEN assert schedule.process_name ==","4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2","is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","\"get_category_all_items\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None await","mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None,","scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 ==","scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def test__check_schedules(self, mocker):","None assert tasks[0].end_time is None assert tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self,","process '%s' task %s pid %s\\n%s\" in args assert 'OMF to PI north'","\"default\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \"value\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \"max_completed_task_age_days\": { \"description\": \"The maximum age, in days","= [call('Database command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async","await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN","async def test_queue_task(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","_max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch = scheduler._schedules[sch_id]","del temp_schedule assert str(ex).endswith('day must be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\"To be","assert tasks[0].end_time is not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self,","schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name","assert (scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count calls = [call(\"Enabled Schedule '%s/%s'","True) # WHEN processes = await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes)","3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler,","__init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return { \"id\": uuid.uuid4(),","\"exit_code\": \"0\", \"reason\": \"\" } ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def","retval = await scheduler.stop() # THEN assert retval is True assert scheduler._schedule_executions is","# THEN # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert","\"1\", \"--debug_level\", \"1\" ] }, { \"name\": \"North Readings to OCS\", \"script\": [","# Assert that there is no task queued for mock_schedule with pytest.raises(KeyError) as","log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 ==","test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_schedule_first_task',","return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id)","Now delete schedule await scheduler.delete_schedule(sch_id) # THEN # Now confirm there is one","sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params = \"Schedule %s already enabled\", str(sch_id) log_info.assert_called_with(*log_params)","request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id)","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) ==","def test__check_schedules(self, mocker): # TODO: Mandatory - Add negative tests for full code","scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\"_mark_tasks_interrupted()","1 == first_task.call_count assert 1 == resume_sch.call_count assert 0 == enable_schedule.call_count assert 0","# THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def","'schedules': return { \"count\": len(MockStorageAsync.schedules), \"rows\": MockStorageAsync.schedules } if table_name == 'scheduled_processes': return","schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return","payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"column\": \"start_time\", \"format\": \"YYYY-MM-DD","import datetime import uuid import time import json from unittest.mock import MagicMock, call","coverage # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None,","return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id,","\"enabled\": \"f\" }, { \"id\": \"ada12840-68d3-11e7-907b-a6006ad3dba0\", \"process_name\": \"COAP\", \"schedule_name\": \"COAP listener south\", \"schedule_type\":","%s\\n%s\" in args assert 'OMF to PI north' in args assert 'North Readings","assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None await scheduler._read_config() # THEN assert","scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO: Mandatory -","> time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 =","True), ('12:30:11', False), ('0 day 12:30:11', False), ('1 day 12:40:11', False), ('2 days',","no task queued for mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True","= MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") #","# THEN assert 1 == cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks is","- Add negative tests for full code coverage # GIVEN scheduler = Scheduler()","= uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule',","scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch,","GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug","test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN await scheduler.start() #","# Changed in version 3.8: patch() now returns an AsyncMock if the target","{\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"start_time\"}, {\"alias\":","- 1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule,","\"Queued schedule '%s' for execution\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker):","True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting","\"limit\": 100} args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0] p","uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution()","def test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task')","def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","\"t\" }, { \"id\": \"2b614d26-760f-11e7-b5a5-be2e44b06b34\", \"process_name\": \"North Readings to PI\", \"schedule_name\": \"OMF to","\"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"start_time\"}, {\"alias\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"end_time\"}, \"reason\",","\"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\", \"process_name\": \"North Readings","# Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 ==","task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks() # THEN assert schedule.process_name","= mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule)","== len(scheduler._schedules) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule',","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mocker.patch.object(scheduler, '_schedule_first_task')","used in 'await' expression\"), call('An exception was raised by Scheduler._scheduler_loop %s', \"object MagicMock","\"Schedule %s already enabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN","json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler,","is None assert tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN","3600, _paused=False, _task_processes={}) # WHEN retval = await scheduler.stop() # THEN assert retval","assert \"Process started: Schedule '%s' process '%s' task %s pid %s, %s running","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError) as","async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if","schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day","Schedule '%s/%s' process '%s'\\n\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')]","Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN","self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN with pytest.raises(NotReadyError)","True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","task has not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule)","not None assert 2 == log_info.call_count # args, kwargs = log_info.call_args_list[0] # assert","at first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN await","\"disable_schedule\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0,","0 for Interval Schedule assert schedule_row[4] is 0 # 0 for Interval Schedule","# THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await","type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess()","calls = [call('Starting'), call('Starting Scheduler: Management port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True)","%s', \"object MagicMock can't be used in 'await' expression\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def","mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL,","scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) #","coding: utf-8 -*- # FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import","None assert scheduler._schedules is None assert scheduler._process_scripts is None assert scheduler._ready is False","mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\"sleep\", \".1\") mock_task_process.schedule","== schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN","schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10,","and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\"To be done\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def","= uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there","9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } @classmethod async def insert_into_tbl(cls, table_name, payload): pass","scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio","await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes = await scheduler.get_scheduled_processes() # THEN","# THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1]","Confirm that cancel request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None #","uuid import time import json from unittest.mock import MagicMock, call import sys import","'COAP listener south' in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio","'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async","\"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"2b614d26-760f-11e7-b5a5-be2e44b06b34\", \"process_name\": \"North","\"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" }, ] scheduled_processes = [ { \"name\":","exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule","log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection' in","# WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert","8: _rv = await get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler =","tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert","{ \"id\": \"ada12840-68d3-11e7-907b-a6006ad3dba0\", \"process_name\": \"COAP\", \"schedule_name\": \"COAP listener south\", \"schedule_type\": 1, \"schedule_interval\": \"00:00:00\",","= mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception): await","None assert scheduler._process_scripts is None assert scheduler._ready is False assert scheduler._paused is False","\"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, \"reason\", \"exit_code\"], \"limit\": 100} args, kwargs = log_exception.call_args assert","with pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules)","True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup #","pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\"_terminate_child_processes() not","None assert task.cancel_requested is None assert task.start_time is not None assert task.end_time is","tasks[0].end_time is not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker):","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF","in args assert 'North Readings to PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self,","command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): # TODO: Mandatory","\"purge\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","[call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0,","Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN","1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \"\"","len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes)","table_name == 'schedules': return { \"count\": len(MockStorageAsync.schedules), \"rows\": MockStorageAsync.schedules } if table_name ==","await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await","{ \"id\": \"d1631422-9ec6-11e7-abc4-cec278b6b50a\", \"process_name\": \"backup\", \"schedule_name\": \"backup hourly\", \"schedule_type\": 3, \"schedule_interval\": \"01:00:00\", \"schedule_time\":","to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule","south' in args1 assert 'OMF to PI north' in args2 # As part","scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert schedule.name ==","= await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup await scheduler._get_schedules() # Confirm no.","# WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1","appears twice in this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def","can't be used in 'await' expression\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): #","north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \"Process started: Schedule '%s' process","== log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \"Process started: Schedule '%s' process '%s'","Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler =","async function. if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await","first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") schedule_id","00:00:59', False), ('00:25:61', True) ]) async def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN","None assert scheduler._ready is False assert scheduler._paused is False assert scheduler._start_time is None","number of tasks that can be running at any given time\", \"type\": \"integer\",","'_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task queued for","= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger","WHEN await scheduler.start() # THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts)","sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup await scheduler._get_schedules() # Confirm no. of schedules assert","args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\"_scheduler_loop() not suitable for","'0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1","task.end_time is not None assert task.exit_code is '0' @pytest.mark.skip(\"Need a suitable fixture\") @pytest.mark.asyncio","scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN","log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these exceptions are being raised despite mocking","retval is True assert scheduler._schedule_executions is None assert scheduler._task_processes is None assert scheduler._schedules","- 3600) # TODO: Remove after implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config',","schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1 ==","\"info\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", current_time=current_time","= await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup","kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats","async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule,","\"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, \"reason\", \"exit_code\"], \"limit\": 100} args, kwargs = log_exception.call_args assert 'Query","log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules() # THEN","= datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be between 1 and","= log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection'","with pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks() # THEN payload = {\"return\":","excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo:","mocker.patch.object(scheduler._logger, \"info\") return scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self,","is no task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is","await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await","True) # WHEN # Now delete schedule await scheduler.delete_schedule(sch_id) # THEN # Now","should be left pending assert 0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args,","THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO:","[call('An exception was raised by Scheduler._purge_tasks %s', \"object MagicMock can't be used in","'_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() # THEN","GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\")","tested during System tests.\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self,","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes')","test_start(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage","assert task.exit_code is '0' @pytest.mark.skip(\"Need a suitable fixture\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker):","schedule.process_name == tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state is not None assert","# WHEN await scheduler.start() # THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) ==","log_info.call_args_list[0] assert \"Process started: Schedule '%s' process '%s' task %s pid %s, %s","Confirm that no task has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule)","call(\"Queued schedule '%s' for execution\", 'OMF to PI north') == log_info.call_args_list[0] args, kwargs","GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\")","from unittest.mock import MagicMock, call import sys import copy import pytest from fledge.services.core.scheduler.scheduler","a suitable fixture\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info,","# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN","queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8: patch() now","\"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" }, ] scheduled_processes = [","[call('SCHCH', {'schedule': {'name': 'OMF to PI north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL,","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup","# WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed: %s',","def test_stop(self, mocker): # TODO: Mandatory - Add negative tests for full code","not None assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time","do not have a status of running\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \"value\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS)","mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN with pytest.raises(NotReadyError) as","repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert","\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\", \"process_name\": \"North Readings to OCS\", \"schedule_name\": \"OMF to OCS north\", \"schedule_type\": 3,","@pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","# TODO: Remove after implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert","True assert message == \"Schedule successfully disabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled","return {\"count\": 1} @classmethod async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN","any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): # TODO: Mandatory - Add negative tests","= mocker.patch.object(scheduler._logger, \"exception\") log_error = mocker.patch.object(scheduler._logger, \"error\") log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info =","THEN assert status is True assert message == \"Schedule {} already disabled\".format(str(sch_id)) assert","to PI' in args @pytest.mark.asyncio async def test__start_task(self, mocker): # TODO: Mandatory -","'Attempt to delete an enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async","%s pid %s\\n%s\" in args assert 'OMF to PI north' in args assert","import asyncio import datetime import uuid import time import json from unittest.mock import","assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def","purge schedule # WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule)","pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions","Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)","collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt","log_info = mocker.patch.object(scheduler._logger, \"info\") log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules',","schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self,","return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm","\"default\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \"value\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version 3.8: patch() now","mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) ==","= uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN","\"process_name\": \"North Readings to PI\", \"schedule_name\": \"OMF to PI north\", \"schedule_type\": 3, \"schedule_interval\":","excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\"_terminate_child_processes() not fit for unit test.\") @pytest.mark.asyncio async def test__terminate_child_processes(self,","\"exception\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args","await scheduler._start_task(schedule) # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id","\"service_port\": 9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } class MockStorageAsync(StorageClientAsync): schedules =","time_after_call > time_before_call assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1","return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF to","schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True,","is 0 # 0 for Interval Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive","mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id","mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host,","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task()))","True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id","assert scheduler._schedules is None assert scheduler._process_scripts is None assert scheduler._ready is False assert","log_params = \"Queued schedule '%s' for execution\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def","= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can","def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \"value\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \"max_completed_task_age_days\": { \"description\": \"The maximum age, in days (based","= None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can not be empty\") with","assert 'OMF to PI north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): #","str(ex).endswith('time must be of type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id,","is not None assert task.exit_code is '0' @pytest.mark.skip(\"Need a suitable fixture\") @pytest.mark.asyncio async","assert tasks[0].state is not None assert tasks[0].cancel_requested is None assert tasks[0].start_time is not","(\"Queued schedule '%s' for execution\", 'OMF to PI north') == args args, kwargs","= mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN","North task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True","'%s'\\n\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert 1","task.state is not None assert task.cancel_requested is None assert task.start_time is not None","assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler =","scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not","\"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"2176eb68-7303-11e7-8cf7-a6006ad3dba0\", \"process_name\": \"stats collector\", \"schedule_name\": \"stats","task.start_time is not None assert task.end_time is not None assert task.exit_code is '0'","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler,","test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","collector\", \"script\": [ \"tasks/statistics\" ] }, { \"name\": \"backup\", \"script\": [ \"tasks/backup_postgres\" ]","= MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules()","kwargs = log_info.call_args_list[0] assert 'OMF to PI north' in args assert 'North Readings","PI' in args @pytest.mark.asyncio async def test__start_task(self, mocker): # TODO: Mandatory - Add","'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): #","@pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule)","return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", _start_time=current_time - 3600, _paused=False, _task_processes={}) #","WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self,","# stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time #","'North Readings to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule':","scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug',","that there is no task queued for this schedule at first with pytest.raises(KeyError)","Readings to PI\", \"schedule_name\": \"OMF to PI north\", \"schedule_type\": 3, \"schedule_interval\": \"00:00:30\", \"schedule_time\":","= MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") current_time =","# WHEN await scheduler._start_task(schedule) # THEN # Confirm that task has started assert","pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def","len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\"_mark_tasks_interrupted() not implemented in main","listener south\", \"schedule_type\": 1, \"schedule_interval\": \"00:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\":","[call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these exceptions are","# WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2","30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True)","args assert 'North Readings to PI' in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker):","= [call('SCHCH', {'schedule': {'name': 'OMF to PI north', 'repeat': 30.0, 'enabled': False, 'type':","[ \"tasks/backup_postgres\" ] }, { \"name\": \"COAP\", \"script\": [ \"services/south\" ] }, {","process: Schedule '%s' process '%s' task %s pid %s\\n%s\" in args assert 'OMF","'2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\"Disabled Schedule '%s/%s' process '%s'\\n\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings","'_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\",","be None') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234","{'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive':","schedule.schedule_id == schedule_id assert schedule.name == \"purge\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat","log_exception = mocker.patch.object(scheduler._logger, \"exception\") # WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args","from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \"<NAME>\" __copyright__ =","[ ('\"Blah\" 0 days', True), ('12:30:11', False), ('0 day 12:30:11', False), ('1 day","'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\"test_interval, is_exception\", [ ('\"Blah\" 0 days', True), ('12:30:11', False), ('0","that there is no task queued for mock_schedule with pytest.raises(KeyError) as excinfo: assert","return \"\" # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat","[ \"tasks/north\", \"--stream_id\", \"1\", \"--debug_level\", \"1\" ] }, { \"name\": \"North Readings to","def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \"\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can","scheduler.enable_schedule(sch_id) # THEN assert status is True assert message == \"Schedule successfully enabled\"","in 'await' expression\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler =","None @pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","'2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls = [call('SCHCH',","= mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF","tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None","'stats collection' in args0 assert 'COAP listener south' in args1 assert 'OMF to","= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN #","%s' == args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def","async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add negative tests for full","async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","# Now delete schedule await scheduler.delete_schedule(sch_id) # THEN # Now confirm there is","System tests.\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): #","log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3]","{ \"description\": \"The maximum number of tasks that can be running at any","in args1 assert 'OMF to PI north' in args2 # As part of","copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import *","side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") # WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts()","async def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","def scheduler_fixture(self, mocker): # Changed in version 3.8: patch() now returns an AsyncMock","'await' expression\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler()","audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive':","mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError)","\"id\": \"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\", \"process_name\": \"North Readings to OCS\", \"schedule_name\": \"OMF to OCS north\", \"schedule_type\":","\"tasks/purge\" ] }, { \"name\": \"stats collector\", \"script\": [ \"tasks/statistics\" ] }, {","log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception)","] }, { \"name\": \"North Readings to PI\", \"script\": [ \"tasks/north\", \"--stream_id\", \"1\",","Will be tested during System tests.\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async","# purge schedule # WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule,","disabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count","# log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self,","async def mock_process(): m = MagicMock() m.pid = 9999 m.terminate = lambda: True","time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1]","\"process_name\": \"North Readings to OCS\", \"schedule_name\": \"OMF to OCS north\", \"schedule_type\": 3, \"schedule_interval\":","log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN #","lambda: True return m @pytest.allure.feature(\"unit\") @pytest.allure.story(\"scheduler\") class TestScheduler: async def scheduler_fixture(self, mocker): #","'_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion',","scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None,","message == \"Schedule is already enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is","for unit test.\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self,","MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) ==","scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row","0 # 0 for Interval Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive ==","0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine","= mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task',","= {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"start_time\"},","# Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is","MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \"exception\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] =","sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0","# THEN assert status is True assert message == \"Schedule successfully enabled\" assert","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info =","mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue task","_schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN","\"schedule_interval\": \"00:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\":","\"backup\", \"script\": [ \"tasks/backup_postgres\" ] }, { \"name\": \"COAP\", \"script\": [ \"services/south\" ]","assert 2 == log_info.call_count calls = [call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'),","as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule,","await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio","disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN","mock_task_process.process = await asyncio.create_subprocess_exec(\"sleep\", \".1\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id =","'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow(","are being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception was raised","THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): #","\"schedule_interval\": \"1 day 00:00:40\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" },","# WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() #","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules()","return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async","'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 ==","mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") # WHEN await","days (based on the start time), for a rows \" \"in the tasks","self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger =","Add negative tests for full code coverage # GIVEN scheduler = Scheduler() scheduler._storage","@pytest.mark.skip(\"Need a suitable fixture\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule,","= uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \"No such Schedule","assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count calls","@pytest.mark.skip(reason=\"To be done\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): #","\"schedule_name\": \"backup hourly\", \"schedule_type\": 3, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\",","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN #","audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 1 ==","log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup await scheduler._get_schedules() # Confirm","12:30:11', False), ('1 day 12:40:11', False), ('2 days', True), ('2 days 00:00:59', False),","pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","MagicMock can't be used in 'await' expression\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker):","'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN","@pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info =","(scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count calls = [call(\"Enabled Schedule '%s/%s' process","log_params = \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker):","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready',","# Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0]","> time_before_call assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 =","m.terminate = lambda: True return m @pytest.allure.feature(\"unit\") @pytest.allure.story(\"scheduler\") class TestScheduler: async def scheduler_fixture(self,","# THEN with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None","= uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN payload = {\"return\":","== \"Schedule is already enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True","1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info,","= mocker.patch.object(scheduler._logger, \"exception\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) #","is '' assert task.state is not None assert task.cancel_requested is None assert task.start_time","\"${VERSION}\" async def mock_task(): return \"\" async def mock_process(): m = MagicMock() m.pid","repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule,","\"id\": \"d1631422-9ec6-11e7-abc4-cec278b6b50a\", \"process_name\": \"backup\", \"schedule_name\": \"backup hourly\", \"schedule_type\": 3, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\",","task completion, sleep above, no task processes should be left pending assert 0","scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN schedules =","len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN # Now delete schedule await scheduler.delete_schedule(sch_id) #","Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 0","uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False,","Confirm that task has not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN","\"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"2176eb68-7303-11e7-8cf7-a6006ad3dba0\", \"process_name\": \"stats","async def test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","twice in this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self,","implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False #","datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time","schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0 # 0","temp_schedule assert str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError) as ex: temp_schedule =","assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count log_params = 'Attempt to delete","{ \"name\": \"North Readings to OCS\", \"script\": [ \"tasks/north\", \"--stream_id\", \"4\", \"--debug_level\", \"1\"","\"North Readings to OCS\", \"script\": [ \"tasks/north\", \"--stream_id\", \"4\", \"--debug_level\", \"1\" ] },","get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async","None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN scheduler,","'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 ==","is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count","GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info","@pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO: Mandatory - Add negative tests for","north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process =","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler,","'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow(","None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can not be empty\") with pytest.raises(ValueError)","1 == first_task.call_count assert 1 == resume_sch.call_count assert 1 == enable_schedule.call_count assert 0","if is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count else:","with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule)","assert scheduler._paused is False assert scheduler._start_time is None calls = [call('Processing stop request'),","'_task_processes') log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN status,","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap await","\"t\", \"enabled\": \"f\" }, ] scheduled_processes = [ { \"name\": \"purge\", \"script\": [","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) #","== len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN await scheduler.start()","await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule =","to PI\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion, sleep","PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler,","in args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence #","core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts)","await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not None","sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call","log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError)","full code coverage # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","\"name\": \"purge\", \"script\": [ \"tasks/purge\" ] }, { \"name\": \"stats collector\", \"script\": [","queue task and assert that the task has been queued await scheduler.queue_task(schedule.id) assert","True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True)","== p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","assert 2 == log_info.call_count # args, kwargs = log_info.call_args_list[0] # assert (\"Queued schedule","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN","any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 1 == enable_schedule.call_count","backup # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert status is","WHEN # Now delete schedule await scheduler.delete_schedule(sch_id) # THEN # Now confirm there","\"backup\", \"schedule_name\": \"backup hourly\", \"schedule_type\": 3, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\":","if table_name == 'schedules': return { \"count\": len(MockStorageAsync.schedules), \"rows\": MockStorageAsync.schedules } if table_name","started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert call(\"Queued schedule","status is True assert message == \"Schedule {} already disabled\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id ==","side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks() # THEN","WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes'","disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert","uuid.uuid4(), \"name\": \"Fledge Storage\", \"type\": \"Storage\", \"service_port\": 9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\":","tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time is None assert","\"exclusive\": \"t\", \"enabled\": \"f\" }, ] scheduled_processes = [ { \"name\": \"purge\", \"script\":","stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these exceptions are being","'tasks': return { \"count\": len(MockStorageAsync.tasks), \"rows\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name,","def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","@pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger,","scheduler._get_schedules() # Confirm no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True)","scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() #","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler,","is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count else: await","assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time is not","WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self,","assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name':","len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler()","MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task()))","1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be of type datetime.time') with","mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN status, message = await","tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info,","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN schedules = await","await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await","\"f\" }, { \"id\": \"ada12840-68d3-11e7-907b-a6006ad3dba0\", \"process_name\": \"COAP\", \"schedule_name\": \"COAP listener south\", \"schedule_type\": 1,","PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler()","test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0,","in args assert 'North Readings to PI' in args @pytest.mark.asyncio async def test_purge_tasks(self,","pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError)","== disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","= 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be of type datetime.timedelta')","\"value\": str(task_id)}} args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0] p","repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule)","import * from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \"<NAME>\"","returns an AsyncMock if the target is an async function. if sys.version_info.major ==","to PI north' in args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets","args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO: Mandatory - Add negative tests","== schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0 # 0 for","mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions","= mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions)","= mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN # THEN","async def query_tbl(cls, table_name, query=None): if table_name == 'schedules': return { \"count\": len(MockStorageAsync.schedules),","mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception was raised by Scheduler._purge_tasks %s', \"object","@pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","= mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule,","\"COAP listener south\", \"schedule_type\": 1, \"schedule_interval\": \"00:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\",","pass @pytest.mark.asyncio async def test__read_config(self, mocker): async def get_cat(): return { \"max_running_tasks\": {","is not None assert task.cancel_requested is None assert task.start_time is not None assert","# GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test","== len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task has started assert 1 ==","schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not be","scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL))","schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules)","] }, { \"name\": \"stats collector\", \"script\": [ \"tasks/statistics\" ] }, { \"name\":","datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be between 1 and 7')","with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\"_terminate_child_processes() not fit for unit test.\") @pytest.mark.asyncio","ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert","as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as","MockStorageAsync.schedules } if table_name == 'scheduled_processes': return { \"count\": len(MockStorageAsync.scheduled_processes), \"rows\": MockStorageAsync.scheduled_processes }","\"YYYY-MM-DD HH24:MI:SS.MS\"}, \"reason\", \"exit_code\"], \"limit\": 100} args, kwargs = log_exception.call_args assert 'Query failed:","= MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time)","not be empty\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat =","in args assert 'North Readings to PI' in args args, kwargs = log_info.call_args_list[1]","assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task has started assert","def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","= uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North # WHEN status, message = await","m.pid = 9999 m.terminate = lambda: True return m @pytest.allure.feature(\"unit\") @pytest.allure.story(\"scheduler\") class TestScheduler:","return { \"count\": len(MockStorageAsync.tasks), \"rows\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name, query=None):","assert scheduler._schedule_executions[schedule.id] is True # Now queue task and assert that the task","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # purge schedule","__copyright__ = \"Copyright (c) 2017 OSIsoft, LLC\" __license__ = \"Apache 2.0\" __version__ =","def test__start_task(self, mocker): # TODO: Mandatory - Add negative tests for full code","False), ('0 day 12:30:11', False), ('1 day 12:40:11', False), ('2 days', True), ('2","sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call","'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 ==","13:28:14.477868\", \"end_time\": \"2018-02-06 13:28:14.856375\", \"exit_code\": \"0\", \"reason\": \"\" } ] def __init__(self, core_management_host=None,","uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task()))","must be of type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)","Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count","uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED,","\"The maximum number of tasks that can be running at any given time\",","= log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection'","\"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") # WHEN # THEN with pytest.raises(Exception): await","= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') #","core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger,","pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks() # THEN payload = {\"return\": [\"id\",","test_queue_task(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","\"stats collector\", \"schedule_name\": \"stats collection\", \"schedule_type\": 2, \"schedule_interval\": \"00:00:15\", \"schedule_time\": \"00:00:15\", \"schedule_day\": 3,","asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None,","Now confirm no schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 ==","main Scheduler class.\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker):","repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError) as ex:","= uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30,","mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task queued for this schedule","Changed in version 3.8: patch() now returns an AsyncMock if the target is","to PI\", name=\"OMF to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True)","schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # purge","deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info,","log_info = mocker.patch.object(scheduler._logger, \"info\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings","there is no North task queued for schedule with pytest.raises(KeyError) as excinfo: assert","# WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio","backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN","test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","assert schedule.schedule_id == schedule_id assert schedule.name == \"purge\" assert schedule.schedule_type == Schedule.Type.MANUAL assert","failed: %s' == args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async","\"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)","log_exception.call_count log_params = 'Attempt to delete an enabled Schedule %s. Not deleted.', str(sch_id)","assert message == \"Schedule successfully enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is","is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine","is not None assert tasks[0].end_time is None assert tasks[0].exit_code is None @pytest.mark.asyncio async","schedule '%s' for execution\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): #","async def test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for full","PI north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings","@pytest.allure.story(\"scheduler\") class TestScheduler: async def scheduler_fixture(self, mocker): # Changed in version 3.8: patch()","}, { \"id\": \"2b614d26-760f-11e7-b5a5-be2e44b06b34\", \"process_name\": \"North Readings to PI\", \"schedule_name\": \"OMF to PI","assert 'stats collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO: Mandatory","__author__ = \"<NAME>\" __copyright__ = \"Copyright (c) 2017 OSIsoft, LLC\" __license__ = \"Apache","mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information',","'Query failed: %s' == args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio","# THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"column\": \"start_time\",","assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2,","Readings to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name':","assert status is True assert message == \"Schedule is already enabled\" assert (scheduler._schedules[sch_id]).id","WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def test__check_schedules(self,","assert task.cancel_requested is None assert task.start_time is not None assert task.end_time is not","assert (scheduler._schedules[sch_id]).enabled is False log_params = \"Schedule %s already disabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio","= uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call =","assert 'stats collection' in args0 assert 'COAP listener south' in args1 assert 'OMF","core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes = await scheduler.get_scheduled_processes() #","async def test_stop(self, mocker): # TODO: Mandatory - Add negative tests for full","\"OMF to OCS north\", \"schedule_type\": 3, \"schedule_interval\": \"1 day 00:00:40\", \"schedule_time\": \"\", \"schedule_day\":","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there is no","_ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task","# THEN if is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1 ==","await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)","await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio","== args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_get_tasks(self,","schedules = await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def","Readings to PI\", \"state\": 1, \"start_time\": \"2018-02-06 13:28:14.477868\", \"end_time\": \"2018-02-06 13:28:14.856375\", \"exit_code\": \"0\",","uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False,","'_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") schedule_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North","MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes = await scheduler.get_scheduled_processes()","log_params = 'Attempt to delete an enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params)","assert schedule_row[4] is 0 # 0 for Interval Schedule assert schedule.repeat == schedule_row[5]","== log_exception.call_count log_params = 'Attempt to delete an enabled Schedule %s. Not deleted.',","assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule,","day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is","== enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def","no task queued for this schedule at first with pytest.raises(KeyError) as excinfo: assert","def query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks': return { \"count\": len(MockStorageAsync.tasks), \"rows\":","async def test__start_task(self, mocker): # TODO: Mandatory - Add negative tests for full","to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count","scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name","name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN #","isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \"Queued schedule '%s' for execution\", 'purge' # log_info.assert_called_with(*log_params)","command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self,","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) #","execution\", 'OMF to PI north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \"Process","mocker.patch.object(scheduler._logger, \"info\") log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler,","len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management port received is %d', 9999)] log_info.assert_has_calls(calls,","disabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info,","= mocker.patch.object(scheduler._logger, \"exception\") # WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args =","repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes =","# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id =","= [call('An exception was raised by Scheduler._purge_tasks %s', \"object MagicMock can't be used","mock_task(): return \"\" async def mock_process(): m = MagicMock() m.pid = 9999 m.terminate","'_ready', True) # Confirm there are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) #","await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 == log_info.call_count","pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time()","def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory -","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \"info\") await","repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True)","def test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","= mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler,","THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 == log_info.call_count # args, kwargs","next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time #","__version__ = \"${VERSION}\" async def mock_task(): return \"\" async def mock_process(): m =","# Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks","= await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch","as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as","self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0,","'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 ==","# FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime import uuid","# WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def","'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN","core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger,","str(ex).endswith('day must be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\"To be done\") async def","scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can not","class MockStorageAsync(StorageClientAsync): schedules = [ { \"id\": \"cea17db8-6ccc-11e7-907b-a6006ad3dba0\", \"process_name\": \"purge\", \"schedule_name\": \"purge\", \"schedule_type\":","\"address\": \"0.0.0.0\", \"protocol\": \"http\" } @classmethod async def insert_into_tbl(cls, table_name, payload): pass @classmethod","= scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess')","# WHEN # THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as","log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") # WHEN # THEN","async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory","mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", _start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN retval = await","assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler =","async def get_cat(): return { \"max_running_tasks\": { \"description\": \"The maximum number of tasks","scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls","'%s/%s' process '%s'\\n\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls)","len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management port received is %d',","payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info,","def test_start(self, mocker): # TODO: Mandatory - Add negative tests for full code","tasks[0].reason is '' assert tasks[0].state is not None assert tasks[0].cancel_requested is None assert","(scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count calls =","= None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not be None') with","= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await","\"count\": len(MockStorageAsync.schedules), \"rows\": MockStorageAsync.schedules } if table_name == 'scheduled_processes': return { \"count\": len(MockStorageAsync.scheduled_processes),","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") log_exception =","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time","pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError)","'_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes')","log_info.call_count # assert call(\"Queued schedule '%s' for execution\", 'OMF to PI north') ==","assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2,","assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker):","= 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN","WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap await scheduler._get_schedules()","\"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert","log_info = mocker.patch.object(scheduler._logger, \"info\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North","first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id)","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") current_time","await scheduler._get_schedules() # Confirm no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready',","= log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection' in args0 assert 'COAP","ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync","=[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True,","3.8: patch() now returns an AsyncMock if the target is an async function.","100} args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0] p =","next_dt) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 3 ==","}, { \"name\": \"stats collector\", \"script\": [ \"tasks/statistics\" ] }, { \"name\": \"backup\",","is True assert schedule.enabled is True assert schedule.process_name == \"purge\" @pytest.mark.asyncio async def","= await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) #","== log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self,","_paused=False, _task_processes={}) # WHEN retval = await scheduler.stop() # THEN assert retval is","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mock_schedules =","# backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) #","log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls,","mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \"exception\") random_schedule_id = uuid.uuid4() #","north\", \"schedule_type\": 3, \"schedule_interval\": \"00:00:30\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\"","is True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count else: await scheduler._get_schedules()","time import json from unittest.mock import MagicMock, call import sys import copy import","== \"purge\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","= \"Apache 2.0\" __version__ = \"${VERSION}\" async def mock_task(): return \"\" async def","'_process_scripts', return_value=\"North Readings to PI\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After","# TODO: Find why these exceptions are being raised despite mocking _purge_tasks_task, _scheduler_loop_task","\"start_time\": \"2018-02-06 13:28:14.477868\", \"end_time\": \"2018-02-06 13:28:14.856375\", \"exit_code\": \"0\", \"reason\": \"\" } ] def","'OMF to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\"_scheduler_loop() not suitable for unit testing.","[call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\"Disabled Schedule '%s/%s' process '%s'\\n\", 'OMF","as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \"\" await scheduler.save_schedule(temp_schedule) del temp_schedule","async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row","mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules()","\"service_port\": 9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" } @classmethod async def insert_into_tbl(cls,","assert status is True assert message == \"Schedule {} already disabled\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id","negative tests for full code coverage # GIVEN scheduler = Scheduler() scheduler._storage =","scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN scheduler","await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN with","core_management_port=None) # WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN","return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \"get_category_all_items\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is None assert","= uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio","is '' assert tasks[0].state is not None assert tasks[0].cancel_requested is None assert tasks[0].start_time","\"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) #","'_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task()))","mocker): # GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id,","assert 1 == cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks is not None","def update_tbl(cls, table_name, payload): # Only valid for test_save_schedule_update if table_name == \"schedules\":","log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready',","time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") #","import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import * from","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id","GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False)","collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch)","assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1,","repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that","'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert status","mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution","'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert","test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","= mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\"sleep\", \".1\")","None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO:","# WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert status is True","\"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" }, { \"id\": \"ada12840-68d3-11e7-907b-a6006ad3dba0\", \"process_name\":","'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): # TODO: Mandatory - Add","schedule.process_name == tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested","\"process_name\": \"North Readings to PI\", \"state\": 1, \"start_time\": \"2018-02-06 13:28:14.477868\", \"end_time\": \"2018-02-06 13:28:14.856375\",","day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)","1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id) #","'COAP listener south' in args1 assert 'OMF to PI north' in args2 #","\"--debug_level\", \"1\" ] }, ] tasks = [ { \"id\": \"259b8570-65c1-4b92-8c62-e9642631a600\", \"process_name\": \"North","log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test","== log_info.call_count calls = [call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\"Disabled Schedule","and sys.version_info.minor >= 8: _rv = await get_cat() else: _rv = asyncio.ensure_future(get_cat()) #","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await","is True assert message == \"Schedule {} already disabled\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN assert","the North task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm","None assert tasks[0].start_time is not None assert tasks[0].end_time is None assert tasks[0].exit_code is","log_info.call_count calls = [call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\"Disabled Schedule '%s/%s'","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age',","calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these","len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler() schedule_id =","False log_params = \"Schedule %s already disabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self,","repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert","'_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv)","THEN assert 1 == cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks is not","log_info = mocker.patch.object(scheduler._logger, \"info\") sch_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North #","log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap mocker.patch.object(scheduler, 'queue_task',","{ \"name\": \"purge\", \"script\": [ \"tasks/purge\" ] }, { \"name\": \"stats collector\", \"script\":","\"exception\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1)))","WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self,","\"1\" ] }, ] tasks = [ { \"id\": \"259b8570-65c1-4b92-8c62-e9642631a600\", \"process_name\": \"North Readings","exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process =","\"info\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF","# stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time)","('2 days 00:00:59', False), ('00:25:61', True) ]) async def test__get_schedules(self, test_interval, is_exception, mocker):","log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # purge schedule # WHEN schedule","mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task()))","schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\",","schedule.enabled is True assert schedule.process_name == \"purge\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): #","can not be empty\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name","scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules()","p @pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params = \"Schedule %s already disabled\", str(sch_id) log_info.assert_called_with(*log_params)","enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task","@pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,","await scheduler.get_task(task_id) # THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\",","message == \"Schedule successfully enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True","_get_storage_service(self, host, port): return { \"id\": uuid.uuid4(), \"name\": \"Fledge Storage\", \"type\": \"Storage\", \"service_port\":","14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now delete schedule with","core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings","return { \"max_running_tasks\": { \"description\": \"The maximum number of tasks that can be","str(task_id)}} args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0] p =","excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info,","in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage","processes should be left pending assert 0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes)","disabled\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params = \"Schedule %s","name=\"OMF to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready',","else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =","first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") enable_schedule","mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has not started yet assert 0 ==","of type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive =","Readings to PI\", \"script\": [ \"tasks/north\", \"--stream_id\", \"1\", \"--debug_level\", \"1\" ] }, {","test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add","'_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", current_time=current_time - 3600) # TODO: Remove","@pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule, log_info, log_exception,","to OCS\", \"script\": [ \"tasks/north\", \"--stream_id\", \"4\", \"--debug_level\", \"1\" ] }, ] tasks","\"Process started: Schedule '%s' process '%s' task %s pid %s, %s running tasks\\n%s\"","WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert status is True assert","await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker):","task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task","current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat","= scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30),","= await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN","pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError)","side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN with","scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence # \"stat collector\" appears twice in this","MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \"info\") await scheduler._get_schedules() sch_id =","'_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \"info\") await scheduler._get_schedules() sch_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # backup","schedule_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # purge schedule # WHEN schedule = await scheduler.get_schedule(schedule_id) #","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') #","def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler()","== sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count calls = [call(\"Enabled","mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None","async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as","assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN scheduler =","with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\"_terminate_child_processes()","excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue task and assert that the","log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler,","== datetime.timedelta(0, 3600) assert schedule.exclusive is True assert schedule.enabled is True assert schedule.process_name","test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id)","12:40:11', False), ('2 days', True), ('2 days 00:00:59', False), ('00:25:61', True) ]) async","await scheduler.get_tasks() # THEN payload = {\"return\": [\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\",","request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these exceptions are being raised","queued for mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now","\"Schedule successfully disabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2","await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be of type datetime.timedelta') with pytest.raises(ValueError)","time_before_call assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1]","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True)","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler,","= await self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules)","as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as","mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\")","scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt","%s already disabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN scheduler,","mocker.patch.object(scheduler._logger, \"exception\") # WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query","{'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day': 1, 'time':","_core_management_host=\"0.0.0.0\", _start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN retval = await scheduler.stop() #","assert message == \"Schedule successfully disabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is","json from unittest.mock import MagicMock, call import sys import copy import pytest from","mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has","1 == enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) #","4, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, {","twice in this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self,","part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False # WHEN","start time), for a rows \" \"in the tasks table that do not","test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)","%s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN scheduler = Scheduler()","WHEN tasks = await scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason","assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 == log_info.call_count # args, kwargs =","def test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async","None @pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO: Mandatory - Add negative tests","\"259b8570-65c1-4b92-8c62-e9642631a600\", \"process_name\": \"North Readings to PI\", \"state\": 1, \"start_time\": \"2018-02-06 13:28:14.477868\", \"end_time\": \"2018-02-06","assert 'OMF to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\"_scheduler_loop() not suitable for unit","args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert","random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \"No such","core_management_port) def _get_storage_service(self, host, port): return { \"id\": uuid.uuid4(), \"name\": \"Fledge Storage\", \"type\":","= mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\") enable_schedule =","as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue task and assert that","log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with","= asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None)","audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive':","# WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is","be of type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive","process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules)","await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","= scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time #","== len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName':","await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\"_terminate_child_processes() not fit for unit test.\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker):","= time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\")",">= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler()","# THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert schedule.name == \"purge\"","\"process_name\": \"stats collector\", \"schedule_name\": \"stats collection\", \"schedule_type\": 2, \"schedule_interval\": \"00:00:15\", \"schedule_time\": \"00:00:15\", \"schedule_day\":","mock_process(): m = MagicMock() m.pid = 9999 m.terminate = lambda: True return m","scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\"To","process '%s'\\n\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls","# THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) ==","\"state\", {\"alias\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"start_time\"}, {\"alias\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\",","assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule,","await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls","3, \"exclusive\": \"f\", \"enabled\": \"t\" }, { \"id\": \"d1631422-9ec6-11e7-abc4-cec278b6b50a\", \"process_name\": \"backup\", \"schedule_name\": \"backup","log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","@pytest.mark.asyncio @pytest.mark.skip(\"_mark_tasks_interrupted() not implemented in main Scheduler class.\") async def test__mark_tasks_interrupted(self, mocker): pass","= \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): #","log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN","# Assert that there is no North task queued for schedule with pytest.raises(KeyError)","('1 day 12:40:11', False), ('2 days', True), ('2 days 00:00:59', False), ('00:25:61', True)","# args, kwargs = log_info.call_args_list[0] # assert (\"Queued schedule '%s' for execution\", 'OMF","log_info.call_args_list[1] assert \"Stopping process: Schedule '%s' process '%s' task %s pid %s\\n%s\" in","THEN assert schedule.process_name == task.process_name assert task.reason is '' assert task.state is not","mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") #","temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name","= log_info.call_args_list[2] assert 'stats collection' in args0 assert 'COAP listener south' in args1","scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls =","assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO: Mandatory","pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del","schedule '%s' for execution\", 'OMF to PI north') == args args, kwargs =","be tested during System tests.\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def","mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to","assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \"Queued schedule '%s' for execution\", 'purge' #","= await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4())","mocker.patch.object(ConfigurationManager, \"create_category\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \"get_category_all_items\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is","scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN","PI North # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert status","@pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules() # THEN","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN","\"name\": \"stats collector\", \"script\": [ \"tasks/statistics\" ] }, { \"name\": \"backup\", \"script\": [","part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async","PI north' in args assert 'North Readings to PI' in args args, kwargs","class.\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker): async def","Management port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s',","await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError) as","'_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to","WHEN await scheduler._start_task(schedule) # THEN # Confirm that task has started assert 1","mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def","async def test__read_config(self, mocker): async def get_cat(): return { \"max_running_tasks\": { \"description\": \"The","assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None","await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await","temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not be None')","= MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time)","execution\", 'OMF to PI north') == args args, kwargs = log_info.call_args_list[0] assert \"Process","\"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") return scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio","first_task.call_count assert 1 == resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count","as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule","is '0' @pytest.mark.skip(\"Need a suitable fixture\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN","\"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"column\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, {\"alias\": \"end_time\", \"column\":","mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN #","scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","south' in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\"_scheduler_loop() not","excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo:","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) #","* from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \"<NAME>\" __copyright__","is None assert scheduler._max_completed_task_age is None await scheduler._read_config() # THEN assert 1 ==","== len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management port received is %d', 9999)]","assert scheduler._start_time is None calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) #","See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime import uuid import time import","log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) #","assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8: patch() now returns an AsyncMock","id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule =","with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue task and",">= 8: _rv = await get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler","\"YYYY-MM-DD HH24:MI:SS.MS\"}, {\"alias\": \"end_time\", \"column\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, \"reason\", \"exit_code\"], \"limit\": 100}","\"id\": \"2b614d26-760f-11e7-b5a5-be2e44b06b34\", \"process_name\": \"North Readings to PI\", \"schedule_name\": \"OMF to PI north\", \"schedule_type\":","\"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" }, { \"id\":","has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id) #","import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \"<NAME>\" __copyright__ = \"Copyright (c)","mocker.patch.object(scheduler._logger, \"info\") await scheduler._get_schedules() sch_id = uuid.UUID(\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler,","\"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, {\"alias\": \"end_time\", \"column\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, \"reason\", \"exit_code\"], \"limit\":","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready',","\"schedule_type\": 3, \"schedule_interval\": \"00:00:30\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" },","can be running at any given time\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \"value\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS)","mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", _start_time=current_time","0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task has started assert 1","1 == resume_sch.call_count assert 1 == enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN","args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence # \"stat","on the start time), for a rows \" \"in the tasks table that","sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await","= scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time)","('12:30:11', False), ('0 day 12:30:11', False), ('1 day 12:40:11', False), ('2 days', True),","schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue task","scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4())","] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return {","# THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker):","MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time()","log_exception = mocker.patch.object(scheduler._logger, \"exception\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules)","\"The maximum age, in days (based on the start time), for a rows","= mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler,","MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused',","'OMF to PI north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \"Process started:","= log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection' in args0 assert 'COAP","that can be running at any given time\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \"value\":","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mock_schedules = dict() mock_schedule","'North Readings to PI' in args @pytest.mark.asyncio async def test__start_task(self, mocker): # TODO:","assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks() # THEN assert","not None assert task.end_time is not None assert task.exit_code is '0' @pytest.mark.skip(\"Need a","] }, { \"name\": \"COAP\", \"script\": [ \"services/south\" ] }, { \"name\": \"North","PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info,","test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule, log_info, log_exception,","mocker.patch.object(scheduler, '_ready', True) # WHEN processes = await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes)","assert schedule.process_name == \"purge\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule,","await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio","THEN with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await","cr_cat = mocker.patch.object(ConfigurationManager, \"create_category\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \"get_category_all_items\", return_value=_rv) # WHEN assert","'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule,","8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio,","= log_info.call_args_list[3] assert 'stats collection' in args0 assert 'COAP listener south' in args1","task.process_name assert task.reason is '' assert task.state is not None assert task.cancel_requested is","\"t\" }, { \"id\": \"2176eb68-7303-11e7-8cf7-a6006ad3dba0\", \"process_name\": \"stats collector\", \"schedule_name\": \"stats collection\", \"schedule_type\": 2,","scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4","'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert","= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must","time_after_call > time_before_call assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1","return { \"count\": len(MockStorageAsync.schedules), \"rows\": MockStorageAsync.schedules } if table_name == 'scheduled_processes': return {","__license__ = \"Apache 2.0\" __version__ = \"${VERSION}\" async def mock_task(): return \"\" async","MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info =","# WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call =","= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception","north') == args args, kwargs = log_info.call_args_list[0] assert \"Process started: Schedule '%s' process","part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence # \"stat collector\" appears twice","log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup await scheduler._get_schedules()","schedule less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker):","Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False","'%s' task %s pid %s, %s running tasks\\n%s\" in args assert 'OMF to","Scheduler._scheduler_loop %s', \"object MagicMock can't be used in 'await' expression\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async","\"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"end_time\"}, \"reason\", \"exit_code\"], \"where\": {\"column\": \"id\", \"condition\": \"=\", \"value\": str(task_id)}}","Readings to OCS\", \"schedule_name\": \"OMF to OCS north\", \"schedule_type\": 3, \"schedule_interval\": \"1 day","WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \"Queued schedule","enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN assert","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \"exception\") new_schedules = copy.deepcopy(MockStorageAsync.schedules)","\"1 day 00:00:40\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" }, ]","\"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\", \"process_name\":","log_exception.call_args assert 'Query failed: %s' == args[0] p = json.loads(args[1]) assert payload ==","\"Stopping process: Schedule '%s' process '%s' task %s pid %s\\n%s\" in args assert","args @pytest.mark.asyncio async def test__start_task(self, mocker): # TODO: Mandatory - Add negative tests","'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio","\"purge\", \"schedule_type\": 4, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\"","schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","scheduler._start_time is None calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO:","'exclusive': True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self,","len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF to PI north' in args assert","%s', \"object MagicMock can't be used in 'await' expression\"), call('An exception was raised","log_debug = await self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules() # THEN assert","@pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add negative tests for","'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\"test_interval, is_exception\", [ ('\"Blah\" 0 days', True),","MagicMock can't be used in 'await' expression\"), call('An exception was raised by Scheduler._scheduler_loop","process '%s' task %s pid %s, %s running tasks\\n%s\" in args assert 'OMF","\"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN","# Confirm there are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN #","such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler","Assert that there is no North task queued for schedule with pytest.raises(KeyError) as","@pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","= uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN","log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =","not None assert tasks[0].end_time is None assert tasks[0].exit_code is None @pytest.mark.asyncio async def","Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count","hourly\", \"schedule_type\": 3, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\"","name=\"OMF to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] =","= [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these exceptions","\"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") #","raised by Scheduler._scheduler_loop %s', \"object MagicMock can't be used in 'await' expression\")] log_exception.assert_has_calls(calls)","assert str(ex).endswith('time must be of type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule =","has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks =","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \"create_category\", return_value=asyncio.ensure_future(mock_task()))","async def test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","Schedule '%s' process '%s' task %s pid %s, %s running tasks\\n%s\" in args","assert 'OMF to PI north' in args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task()","Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\"Disabled Schedule '%s/%s' process '%s'\\n\", 'OMF to","be of type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day","# Assert that there is no task queued for this schedule at first","8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage","= log_info.call_args_list[1] assert \"Stopping process: Schedule '%s' process '%s' task %s pid %s\\n%s\"","Only valid for test_save_schedule_update if table_name == \"schedules\": return {\"count\": 1} @classmethod async","scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): #","pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError)","sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there are","scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN","{ \"id\": \"259b8570-65c1-4b92-8c62-e9642631a600\", \"process_name\": \"North Readings to PI\", \"state\": 1, \"start_time\": \"2018-02-06 13:28:14.477868\",","GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await","log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) #","calls = [call('SCHCH', {'schedule': {'name': 'OMF to PI north', 'repeat': 30.0, 'enabled': False,","Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0,","Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule =","\"Schedule %s already disabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN","not None assert task.exit_code is '0' @pytest.mark.skip(\"Need a suitable fixture\") @pytest.mark.asyncio async def","HH24:MI:SS.MS\"}, {\"alias\": \"end_time\", \"column\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, \"reason\", \"exit_code\"], \"limit\": 100} args,","'_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await","Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True","scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule","assert message == \"Schedule is already enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled","has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel","\"t\" }, { \"id\": \"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\", \"process_name\": \"North Readings to OCS\", \"schedule_name\": \"OMF to","None') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await","= dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF to PI","True) ]) async def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler = Scheduler()","status, message = await scheduler.enable_schedule(sch_id) # THEN assert status is True assert message","%s already enabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler,","'OMF to PI north') == args args, kwargs = log_info.call_args_list[0] assert \"Process started:","THEN assert scheduler._check_processes_pending is False # WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task',","is False # WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() #","len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler,","\"Fledge Storage\", \"type\": \"Storage\", \"service_port\": 9999, \"management_port\": 9999, \"address\": \"0.0.0.0\", \"protocol\": \"http\" }","await scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self,","scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): #","= await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self,","sch_id = uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North # WHEN status, message =","m = MagicMock() m.pid = 9999 m.terminate = lambda: True return m @pytest.allure.feature(\"unit\")","= \"\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can not be empty\") with","# Now confirm no schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1","def test__schedule_first_task(self, mocker): # TODO: Mandatory - Add negative tests for full code","\"info\") return scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker):","in args assert 'North Readings to PI' in args @pytest.mark.asyncio async def test__start_task(self,","scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert","core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler,","for mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue","temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time","'0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","\"--stream_id\", \"1\", \"--debug_level\", \"1\" ] }, { \"name\": \"North Readings to OCS\", \"script\":","\"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" }, { \"id\": \"ada12840-68d3-11e7-907b-a6006ad3dba0\", \"process_name\": \"COAP\",","uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \"No such Schedule %s\",","async def mock_task(): return \"\" async def mock_process(): m = MagicMock() m.pid =","Readings to PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN scheduler,","== len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks() # THEN","\"exclusive\": \"f\", \"enabled\": \"t\" }, { \"id\": \"d1631422-9ec6-11e7-abc4-cec278b6b50a\", \"process_name\": \"backup\", \"schedule_name\": \"backup hourly\",","mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN assert","process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert","'_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as","as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN","sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert","async def query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks': return { \"count\": len(MockStorageAsync.tasks),","[\"id\", \"process_name\", \"schedule_name\", \"state\", {\"alias\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\", \"column\": \"start_time\"}, {\"alias\": \"end_time\",","log_exception = mocker.patch.object(scheduler._logger, \"exception\") log_error = mocker.patch.object(scheduler._logger, \"error\") log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info","= uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup await scheduler._get_schedules() # Confirm no. of schedules assert len(scheduler._storage_async.schedules)","assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN # Confirm that","= await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self,","async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","\"enabled\": \"t\" }, { \"id\": \"d1631422-9ec6-11e7-abc4-cec278b6b50a\", \"process_name\": \"backup\", \"schedule_name\": \"backup hourly\", \"schedule_type\": 3,","{\"alias\": \"start_time\", \"column\": \"start_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, {\"alias\": \"end_time\", \"column\": \"end_time\", \"format\": \"YYYY-MM-DD","scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \"exception\") random_schedule_id = uuid.uuid4()","THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \"Queued schedule '%s' for execution\", 'purge'","mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task',","= await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule","_purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\")","# WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \"No such Schedule %s\", str(random_schedule_id)","= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info","True) # Confirm there are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN","'' assert task.state is not None assert task.cancel_requested is None assert task.start_time is","schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN scheduler,","\"--stream_id\", \"4\", \"--debug_level\", \"1\" ] }, ] tasks = [ { \"id\": \"259b8570-65c1-4b92-8c62-e9642631a600\",","Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8]","not None assert tasks[0].end_time is not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async","\"end_time\", \"column\": \"end_time\", \"format\": \"YYYY-MM-DD HH24:MI:SS.MS\"}, \"reason\", \"exit_code\"], \"limit\": 100} args, kwargs =","args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests","'_wait_for_task_completion') # Confirm that task has not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes)","table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks':","log_info = mocker.patch.object(scheduler._logger, \"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id","def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","if the target is an async function. if sys.version_info.major == 3 and sys.version_info.minor","and sys.version_info.minor >= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio,","MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger =","Now queue task and assert that the task has been queued await scheduler.queue_task(schedule.id)","scheduler._ScheduleExecution) # log_params = \"Queued schedule '%s' for execution\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio","args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection' in args0 assert 'COAP listener south'","scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5)))","def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await","= mocker.patch.object(scheduler._logger, \"exception\") random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params","= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts',","to delete an enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def","THEN # Now confirm no schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert","# THEN assert time_after_call > time_before_call assert 3 == log_info.call_count args0, kwargs0 =","scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') #","is True assert schedule.process_name == \"purge\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN","THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1] assert","3, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"f\" }, {","0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF to PI north' in","return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \"info\")","@pytest.mark.skip(\"_scheduler_loop() not suitable for unit testing. Will be tested during System tests.\") async","1, \"start_time\": \"2018-02-06 13:28:14.477868\", \"end_time\": \"2018-02-06 13:28:14.856375\", \"exit_code\": \"0\", \"reason\": \"\" } ]","kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats","schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now delete schedule with pytest.raises(RuntimeWarning):","@pytest.mark.asyncio async def test_start(self, mocker): # TODO: Mandatory - Add negative tests for","calls = [call('An exception was raised by Scheduler._purge_tasks %s', \"object MagicMock can't be","target is an async function. if sys.version_info.major == 3 and sys.version_info.minor >= 8:","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task()))","'debug', side_effect=Exception()) sch_id = uuid.UUID(\"d1631422-9ec6-11e7-abc4-cec278b6b50a\") # backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError)","scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4())","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler,","time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1","not implemented in main Scheduler class.\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async","not be empty\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name =","mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler,","True assert 1 == queue_task.call_count calls = [call(\"Enabled Schedule '%s/%s' process '%s'\\n\", 'backup","== len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id) # THEN","\"schedule_day\": 0, \"exclusive\": \"t\", \"enabled\": \"t\" }, { \"id\": \"2b614d26-760f-11e7-b5a5-be2e44b06b34\", \"process_name\": \"North Readings","uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\") # OMF to PI North # WHEN status, message = await scheduler.disable_schedule(sch_id)","= log_info.call_args_list[0] assert \"Process started: Schedule '%s' process '%s' task %s pid %s,","== len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,","temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive","mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True)","# WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert","are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now delete schedule","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready',","schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3]","that do not have a status of running\", \"type\": \"integer\", \"default\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \"value\":","1 == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule',","WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self,","fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__ =","log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN","uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async","async def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await","GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4()","get_cat = mocker.patch.object(ConfigurationManager, \"get_category_all_items\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age","assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN","_start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules() #","this schedule at first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True #","assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time is None","schedule_row[2] assert schedule_row[3] is 0 # 0 for Interval Schedule assert schedule_row[4] is","is None assert tasks[0].start_time is not None assert tasks[0].end_time is not None assert","north' in args assert 'North Readings to PI' in args args, kwargs =","= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1","assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id)","await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio","@pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for","any_order=True) # TODO: Find why these exceptions are being raised despite mocking _purge_tasks_task,","\"http\" } class MockStorageAsync(StorageClientAsync): schedules = [ { \"id\": \"cea17db8-6ccc-11e7-907b-a6006ad3dba0\", \"process_name\": \"purge\", \"schedule_name\":","scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info =","_core_management_port=9999, _core_management_host=\"0.0.0.0\", _start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN retval = await scheduler.stop()","mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\"North Readings to PI\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that","enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \"enable_schedule\", return_value=mock_coro()) disable_schedule =","scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","calls = [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True,","is True # Now queue task and assert that the North task has","await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await","to PI north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO: Mandatory","sch_id = uuid.UUID(\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] #","# THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args)","async def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =","# THEN assert schedule.process_name == task.process_name assert task.reason is '' assert task.state is","scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mocker.patch.object(scheduler,","await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there are 14 schedules assert len(scheduler._storage_async.schedules)","scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat =","str(ex).endswith('repeat must be of type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id,","that no task has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) #","delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now confirm no schedule","table_name, payload): pass @classmethod async def update_tbl(cls, table_name, payload): # Only valid for","for a rows \" \"in the tasks table that do not have a","scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug =","to PI north\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule","WHEN tasks = await scheduler.get_running_tasks() # THEN assert 1 == len(tasks) assert schedule.process_name","= mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info","assert payload == p @pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN scheduler, schedule,","await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF to PI","any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 0 == enable_schedule.call_count","no North task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is","running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\"Disabled Schedule '%s/%s' process '%s'\\n\", 'OMF to PI","\"info\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) #","for this schedule at first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True","1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName':","= time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\"0.0.0.0\", _start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN retval","assert schedule.name == \"purge\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600)","as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule","\"exit_code\"], \"where\": {\"column\": \"id\", \"condition\": \"=\", \"value\": str(task_id)}} args, kwargs = log_exception.call_args assert","0 for Interval Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7] assert","= MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \"exception\") mocker.patch.object(scheduler,","schedule_row) temp_schedule.name = \"\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\"name can not be","== len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN # Confirm that task has","with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN","log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) #","%s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler,","False # WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN","== len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert call(\"Queued schedule '%s' for execution\",","= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \"create_category\", return_value=asyncio.ensure_future(mock_task())) get_cat","cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is","= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger,","scheduler.get_running_tasks() # THEN assert 1 == len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason","log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError):","has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert call(\"Queued","audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) #","await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be between 1 and 7') @pytest.mark.asyncio","False), ('1 day 12:40:11', False), ('2 days', True), ('2 days 00:00:59', False), ('00:25:61',","# THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN","THEN assert earliest_start_time is not None assert 3 == log_info.call_count args0, kwargs0 =","'_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \"exception\") random_schedule_id","= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert","assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0 # 0 for Interval Schedule","\"t\", \"enabled\": \"t\" }, { \"id\": \"2176eb68-7303-11e7-8cf7-a6006ad3dba0\", \"process_name\": \"stats collector\", \"schedule_name\": \"stats collection\",","disable_schedule = mocker.patch.object(scheduler, \"disable_schedule\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules)","scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,","from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import","\"purge\", \"schedule_name\": \"purge\", \"schedule_type\": 4, \"schedule_interval\": \"01:00:00\", \"schedule_time\": \"\", \"schedule_day\": 0, \"exclusive\": \"t\",","1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert call(\"Queued schedule '%s' for","\"Schedule successfully enabled\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1","log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\"ada12840-68d3-11e7-907b-a6006ad3dba0\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True)","is None assert tasks[0].start_time is not None assert tasks[0].end_time is None assert tasks[0].exit_code","enabled\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info,","schedule '%s' for execution\", 'OMF to PI north') == log_info.call_args_list[0] args, kwargs =","# WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert","as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule,","core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return { \"id\": uuid.uuid4(), \"name\": \"Fledge","hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule':","day 12:40:11', False), ('2 days', True), ('2 days 00:00:59', False), ('00:25:61', True) ])","assert 1 == enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False)","is None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time is","core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \"info\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North","await scheduler.get_running_tasks() # THEN assert 1 == len(tasks) assert schedule.process_name == tasks[0].process_name assert","= dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules')","expression\"), call('An exception was raised by Scheduler._scheduler_loop %s', \"object MagicMock can't be used","def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \"\" # GIVEN scheduler, schedule, log_info,","log_params = \"No such Schedule %s\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker):","@pytest.mark.asyncio @pytest.mark.skip(\"_scheduler_loop() not suitable for unit testing. Will be tested during System tests.\")","@pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug","mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\"2b614d26-760f-11e7-b5a5-be2e44b06b34\"), process_name=\"North Readings to PI\", name=\"OMF to","scheduled_processes = [ { \"name\": \"purge\", \"script\": [ \"tasks/purge\" ] }, { \"name\":","core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \"debug\") log_info = mocker.patch.object(scheduler._logger, \"info\")","process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule) assert","return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert status is","North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False,","await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await","Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check","with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN","def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async"],"string":"[\n \"in args assert 'OMF to PI north' in args assert 'North Readings to\",\n \"scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call >\",\n \"log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup hourly',\",\n \"False # WHEN await scheduler.start() # THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes)\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup queue_task\",\n \"== tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state is not None assert tasks[0].cancel_requested\",\n \"= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler,\",\n \"\\\"schedule_type\\\": 4, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" },\",\n \"self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup await scheduler._get_schedules() # Confirm no. of schedules\",\n \"[call('Database command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN # THEN with\",\n \"mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)\",\n \"= json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN\",\n \"curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks()\",\n \"== log_info.call_count # args, kwargs = log_info.call_args_list[0] # assert (\\\"Queued schedule '%s' for\",\n \"assert scheduler._ready is False assert scheduler._paused is False assert scheduler._start_time is None calls\",\n \"# Now queue task and assert that the North task has been queued\",\n \"uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time\",\n \"log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow(\",\n \"None await scheduler._read_config() # THEN assert 1 == cr_cat.call_count assert 1 == get_cat.call_count\",\n \"is 0 # 0 for Interval Schedule assert schedule_row[4] is 0 # 0\",\n \"await scheduler._start_task(schedule) # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) #\",\n \"WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 4\",\n \"test_save_schedule_update if table_name == \\\"schedules\\\": return {\\\"count\\\": 1} @classmethod async def delete_from_tbl(cls, table_name,\",\n \"schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be of\",\n \"execution\\\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler =\",\n \"Mandatory - Add negative tests for full code coverage # GIVEN scheduler =\",\n \"scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task has started yet assert\",\n \"day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule =\",\n \"None assert task.exit_code is '0' @pytest.mark.skip(\\\"Need a suitable fixture\\\") @pytest.mark.asyncio async def test_get_task_not_found(self,\",\n \"has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task\",\n \"confirm there is one schedule less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio\",\n \"return { \\\"id\\\": uuid.uuid4(), \\\"name\\\": \\\"Fledge Storage\\\", \\\"type\\\": \\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\": 9999,\",\n \"{'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})]\",\n \"'d1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name':\",\n \"# THEN assert time_after_call > time_before_call assert 4 == log_info.call_count args0, kwargs0 =\",\n \"args, kwargs = log_info.call_args_list[1] assert \\\"Stopping process: Schedule '%s' process '%s' task %s\",\n \"MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name, query=None): if table_name == 'schedules': return\",\n \"schedule_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test\",\n \"await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch = scheduler._schedules[sch_id] sch_execution =\",\n \"{'schedule': {'name': 'OMF to PI north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive':\",\n \"sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 4 == log_info.call_count args0, kwargs0\",\n \"GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4()\",\n \"log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN\",\n \"mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler,\",\n \"== len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has not been\",\n \"mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug\",\n \"\\\" \\\"in the tasks table that do not have a status of running\\\",\",\n \"len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management port received\",\n \"no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN #\",\n \"status is True assert message == \\\"Schedule successfully disabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id\",\n \"test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN status, message = await scheduler.disable_schedule(sch_id) #\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there\",\n \"None assert scheduler._task_processes is None assert scheduler._schedules is None assert scheduler._process_scripts is None\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro())\",\n \"test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"= 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be\",\n \"(scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params = \\\"Schedule %s already disabled\\\",\",\n \"0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\", \\\"process_name\\\": \\\"North Readings to\",\n \"# THEN assert status is True assert message == \\\"Schedule {} already disabled\\\".format(str(sch_id))\",\n \"test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage\",\n \"] }, { \\\"name\\\": \\\"North Readings to OCS\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"4\\\",\",\n \"= [ { \\\"id\\\": \\\"259b8570-65c1-4b92-8c62-e9642631a600\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"state\\\": 1, \\\"start_time\\\":\",\n \"be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\\\"To be done\\\") async def test_remove_service_from_task_processes(self): pass\",\n \"as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as\",\n \"ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \\\"\\\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert\",\n \"'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert status\",\n \"repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro())\",\n \"len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"{\\\"alias\\\": \\\"end_time\\\", \\\"column\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"limit\\\": 100} args, kwargs\",\n \"WHEN processes = await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async\",\n \"THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes()\",\n \"'_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\")\",\n \"== disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" #\",\n \"if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await mock_process() else:\",\n \"pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError)\",\n \"True assert schedule.enabled is True assert schedule.process_name == \\\"purge\\\" @pytest.mark.asyncio async def test_get_schedule_exception(self,\",\n \"north' in args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence\",\n \"%s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): # TODO: Mandatory -\",\n \"(scheduler._schedules[sch_id]).enabled is True log_params = \\\"Schedule %s already enabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async\",\n \"def test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError)\",\n \"isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task has started yet assert 0 ==\",\n \"sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 3 == log_info.call_count args0, kwargs0\",\n \"\\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"column\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"column\\\": \\\"end_time\\\", \\\"format\\\":\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger,\",\n \"= uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10,\",\n \"schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9]\",\n \"assert 1 == log_info.call_count # assert call(\\\"Queued schedule '%s' for execution\\\", 'OMF to\",\n \"= mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") schedule_id =\",\n \"is False assert 2 == log_info.call_count calls = [call('No Task running for Schedule\",\n \"await self.scheduler_fixture(mocker) # Assert that there is no North task queued for schedule\",\n \"new_schedules) # WHEN # THEN if is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules()\",\n \"return \\\"\\\" async def mock_process(): m = MagicMock() m.pid = 9999 m.terminate =\",\n \"= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception\",\n \"message == \\\"Schedule {} already disabled\\\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is\",\n \"{ \\\"id\\\": \\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"schedule_name\\\": \\\"OMF to PI north\\\",\",\n \"# WHEN tasks = await scheduler.get_running_tasks() # THEN assert 1 == len(tasks) assert\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mocker.patch.object(scheduler, '_schedule_first_task') await\",\n \"\\\"description\\\": \\\"The maximum number of tasks that can be running at any given\",\n \"# WHEN processes = await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio\",\n \"\\\"schedule_type\\\": 2, \\\"schedule_interval\\\": \\\"00:00:15\\\", \\\"schedule_time\\\": \\\"00:00:15\\\", \\\"schedule_day\\\": 3, \\\"exclusive\\\": \\\"f\\\", \\\"enabled\\\": \\\"t\\\" },\",\n \"mocker.patch.object(scheduler._logger, \\\"exception\\\") log_error = mocker.patch.object(scheduler._logger, \\\"error\\\") log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger,\",\n \"THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): #\",\n \"# Confirm that no task has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await\",\n \"started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks() # THEN\",\n \"suitable for unit testing. Will be tested during System tests.\\\") async def test__scheduler_loop(self,\",\n \"3600) assert schedule.exclusive is True assert schedule.enabled is True assert schedule.process_name == \\\"purge\\\"\",\n \"+= datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN assert time_after_call >\",\n \"= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger,\",\n \"scheduler._schedule_executions[schedule.id] is True # Now queue task and assert that the task has\",\n \"True, 'repeat': 30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})]\",\n \"str(ex).endswith(\\\"name can not be empty\\\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler,\",\n \"MockStorageAsync(StorageClientAsync): schedules = [ { \\\"id\\\": \\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"purge\\\", \\\"schedule_name\\\": \\\"purge\\\", \\\"schedule_type\\\": 4,\",\n \"async def test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"calls = [call(\\\"Enabled Schedule '%s/%s' process '%s'\\\\n\\\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True)\",\n \"len(scheduler._schedules) # WHEN # Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN\",\n \"test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"== len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\\\"_mark_tasks_interrupted() not implemented in main Scheduler\",\n \"'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN status, message =\",\n \"kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection' in args0 assert\",\n \"enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN\",\n \"with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule)\",\n \"Readings to OCS\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"4\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, ]\",\n \"mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings\",\n \"temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \\\"\\\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name\",\n \"repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError) as ex: temp_schedule\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN\",\n \"p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): #\",\n \"mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync,\",\n \"PI north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"00:00:30\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\":\",\n \"is None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): #\",\n \"collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO: Mandatory - Add\",\n \"temp_schedule.name = \\\"\\\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can not be empty\\\")\",\n \"== \\\"Schedule {} already disabled\\\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False\",\n \"Interval Schedule assert schedule_row[4] is 0 # 0 for Interval Schedule assert schedule.repeat\",\n \"= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can\",\n \"THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): #\",\n \"\\\"column\\\": \\\"start_time\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"end_time\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"where\\\": {\\\"column\\\":\",\n \"audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules')\",\n \"task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks\",\n \"mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN if is_exception is True: with pytest.raises(Exception):\",\n \"mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to\",\n \"unit testing. Will be tested during System tests.\\\") async def test__scheduler_loop(self, mocker): pass\",\n \"# FLEDGE_END import asyncio import datetime import uuid import time import json from\",\n \"core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \\\"create_category\\\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \\\"get_category_all_items\\\", return_value=_rv) # WHEN\",\n \"= sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0,\",\n \"in 'await' expression\\\"), call('An exception was raised by Scheduler._scheduler_loop %s', \\\"object MagicMock can't\",\n \"list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is\",\n \"mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert\",\n \"there is one schedule less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async\",\n \"self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message =\",\n \"status is True assert message == \\\"Schedule is already enabled\\\" assert (scheduler._schedules[sch_id]).id ==\",\n \"THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\",\",\n \"await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be of type datetime.time') with pytest.raises(ValueError)\",\n \"tests.\\\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO:\",\n \"args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker):\",\n \"3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2\",\n \"async def test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"be used in 'await' expression\\\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True)\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await\",\n \"assert 'stats collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN scheduler\",\n \"'await' expression\\\"), call('An exception was raised by Scheduler._scheduler_loop %s', \\\"object MagicMock can't be\",\n \"\\\"North Readings to PI\\\", \\\"schedule_name\\\": \\\"OMF to PI north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"00:00:30\\\",\",\n \"TODO: Mandatory - Add negative tests for full code coverage # GIVEN scheduler\",\n \"WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id ==\",\n \"-*- coding: utf-8 -*- # FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mock_schedules\",\n \"0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 ==\",\n \"= await scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name assert task.reason is ''\",\n \"\\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\", \\\"process_name\\\": \\\"North Readings to OCS\\\", \\\"schedule_name\\\":\",\n \"WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async\",\n \"{\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"column\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, {\\\"alias\\\":\",\n \"North # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert status is\",\n \"pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler,\",\n \"as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule,\",\n \"= asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert schedule.name == \\\"purge\\\" assert schedule.schedule_type ==\",\n \"hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True)\",\n \"GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that\",\n \"# WHEN task = await scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name assert\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time)\",\n \"= mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] =\",\n \"core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.object(scheduler,\",\n \"async def test__check_schedules(self, mocker): # TODO: Mandatory - Add negative tests for full\",\n \"collector\\\", \\\"schedule_name\\\": \\\"stats collection\\\", \\\"schedule_type\\\": 2, \\\"schedule_interval\\\": \\\"00:00:15\\\", \\\"schedule_time\\\": \\\"00:00:15\\\", \\\"schedule_day\\\": 3, \\\"exclusive\\\":\",\n \"= [call(\\\"Enabled Schedule '%s/%s' process '%s'\\\\n\\\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert\",\n \"THEN # Now confirm there is one schedule less assert len(scheduler._storage_async.schedules) - 1\",\n \"\\\"schedule_time\\\": \\\"00:00:15\\\", \\\"schedule_day\\\": 3, \\\"exclusive\\\": \\\"f\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\", \\\"process_name\\\":\",\n \"scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') #\",\n \"schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) +\",\n \"\\\"t\\\" }, { \\\"id\\\": \\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\", \\\"process_name\\\": \\\"backup\\\", \\\"schedule_name\\\": \\\"backup hourly\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\":\",\n \"# TODO: Mandatory - Add negative tests for full code coverage # GIVEN\",\n \"\\\"script\\\": [ \\\"tasks/backup_postgres\\\" ] }, { \\\"name\\\": \\\"COAP\\\", \\\"script\\\": [ \\\"services/south\\\" ] },\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id =\",\n \"await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"# WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def\",\n \"assert earliest_start_time is not None assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0]\",\n \"assert status is True assert message == \\\"Schedule successfully enabled\\\" assert (scheduler._schedules[sch_id]).id ==\",\n \"confirm no schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count\",\n \"PI\\\", name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception\",\n \"\\\"stat collector\\\" appears twice in this list. assert 'stats collection' in args3 @pytest.mark.asyncio\",\n \"scheduler.stop() # THEN assert retval is True assert scheduler._schedule_executions is None assert scheduler._task_processes\",\n \"self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async\",\n \"_scheduler_loop_task calls = [call('An exception was raised by Scheduler._purge_tasks %s', \\\"object MagicMock can't\",\n \"in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO: Mandatory - Add negative\",\n \"task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version\",\n \"WHEN retval = await scheduler.stop() # THEN assert retval is True assert scheduler._schedule_executions\",\n \"(c) 2017 OSIsoft, LLC\\\" __license__ = \\\"Apache 2.0\\\" __version__ = \\\"${VERSION}\\\" async def\",\n \"'stats collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN scheduler =\",\n \"= await scheduler.stop() # THEN assert retval is True assert scheduler._schedule_executions is None\",\n \"WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params)\",\n \"started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await\",\n \"assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params = \\\"Schedule %s already\",\n \"mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await\",\n \"args0 assert 'COAP listener south' in args1 assert 'OMF to PI north' in\",\n \"= scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler,\",\n \"FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime import uuid import\",\n \"True log_params = \\\"Schedule %s already enabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self,\",\n \"as excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id) # THEN assert\",\n \"\\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"4\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, ] tasks = [\",\n \"None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError)\",\n \"await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self,\",\n \"async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"[ { \\\"id\\\": \\\"259b8570-65c1-4b92-8c62-e9642631a600\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"state\\\": 1, \\\"start_time\\\": \\\"2018-02-06\",\n \"HH24:MI:SS.MS\\\", \\\"column\\\": \\\"start_time\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"end_time\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"where\\\":\",\n \"\\\"state\\\": 1, \\\"start_time\\\": \\\"2018-02-06 13:28:14.477868\\\", \\\"end_time\\\": \\\"2018-02-06 13:28:14.856375\\\", \\\"exit_code\\\": \\\"0\\\", \\\"reason\\\": \\\"\\\" }\",\n \"assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return\",\n \"@pytest.mark.asyncio async def test__start_task(self, mocker): # TODO: Mandatory - Add negative tests for\",\n \"for execution\\\", 'OMF to PI north') == args args, kwargs = log_info.call_args_list[0] assert\",\n \"0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN # Confirm that task\",\n \"age, in days (based on the start time), for a rows \\\" \\\"in\",\n \"TestScheduler: async def scheduler_fixture(self, mocker): # Changed in version 3.8: patch() now returns\",\n \"is False # WHEN await scheduler.start() # THEN assert scheduler._ready is True assert\",\n \"'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger,\",\n \"call('An exception was raised by Scheduler._scheduler_loop %s', \\\"object MagicMock can't be used in\",\n \"audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"to PI' in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO: Mandatory -\",\n \"started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN #\",\n \"north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls =\",\n \"scheduler._schedule_executions[schedule.id] is True # Now queue task and assert that the North task\",\n \"type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0\",\n \"is False assert scheduler._paused is False assert scheduler._start_time is None calls = [call('Processing\",\n \"await scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name assert task.reason is '' assert\",\n \"await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task has started yet\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError)\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information',\",\n \"the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in\",\n \"m @pytest.allure.feature(\\\"unit\\\") @pytest.allure.story(\\\"scheduler\\\") class TestScheduler: async def scheduler_fixture(self, mocker): # Changed in version\",\n \"to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True)\",\n \"= datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector\",\n \"@classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks': return { \\\"count\\\":\",\n \"PI north' in args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed,\",\n \"\\\"schedule_name\\\": \\\"COAP listener south\\\", \\\"schedule_type\\\": 1, \\\"schedule_interval\\\": \\\"00:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\":\",\n \"exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN\",\n \"collection\\\", \\\"schedule_type\\\": 2, \\\"schedule_interval\\\": \\\"00:00:15\\\", \\\"schedule_time\\\": \\\"00:00:15\\\", \\\"schedule_day\\\": 3, \\\"exclusive\\\": \\\"f\\\", \\\"enabled\\\": \\\"t\\\"\",\n \"uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there are 14 schedules\",\n \"await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker):\",\n \"tasks = await scheduler.get_running_tasks() # THEN assert 1 == len(tasks) assert schedule.process_name ==\",\n \"\\\"error\\\") log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") return scheduler, schedule, log_info,\",\n \"log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker):\",\n \"test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"Remove after implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is\",\n \"pending assert 0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0]\",\n \"test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"\\\"info\\\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\",\",\n \"THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN scheduler,\",\n \"assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING assert\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mock_schedules = dict()\",\n \"scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN\",\n \"assert 'North Readings to PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): #\",\n \"# backup await scheduler._get_schedules() # Confirm no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)\",\n \"time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time =\",\n \"@pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler,\",\n \"\\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN\",\n \"= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule\",\n \"no task has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm\",\n \"# THEN task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN\",\n \"= mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo: tasks = await\",\n \"collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"\\\"exception\\\") random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \\\"No\",\n \"\\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"end_time\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"where\\\": {\\\"column\\\": \\\"id\\\", \\\"condition\\\": \\\"=\\\",\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception =\",\n \"Schedule '%s/%s' process '%s'\\\\n\\\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 ==\",\n \"\\\"name\\\": \\\"COAP\\\", \\\"script\\\": [ \\\"services/south\\\" ] }, { \\\"name\\\": \\\"North Readings to PI\\\",\",\n \"} ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return\",\n \"time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError) as\",\n \"WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion, sleep above, no task\",\n \"assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule':\",\n \"_purge_tasks_task, _scheduler_loop_task calls = [call('An exception was raised by Scheduler._purge_tasks %s', \\\"object MagicMock\",\n \"to PI\\\", \\\"schedule_name\\\": \\\"OMF to PI north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"00:00:30\\\", \\\"schedule_time\\\": \\\"\\\",\",\n \"THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro():\",\n \"any_order=True) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type':\",\n \"== queue_task.call_count calls = [call(\\\"Enabled Schedule '%s/%s' process '%s'\\\\n\\\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')]\",\n \"'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self,\",\n \"mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler,\",\n \"enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): #\",\n \"len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\\\"_mark_tasks_interrupted() not implemented in main Scheduler class.\\\") async def test__mark_tasks_interrupted(self, mocker):\",\n \"async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"'_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has not\",\n \"mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process\",\n \"def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"running tasks\\\\n%s\\\" in args assert 'OMF to PI north' in args assert 'North\",\n \"# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id =\",\n \"call import sys import copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager\",\n \"WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None await scheduler._read_config() # THEN\",\n \"disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"to PI north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"00:00:30\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\",\",\n \"schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN scheduler\",\n \"schedule.process_name == task.process_name assert task.reason is '' assert task.state is not None assert\",\n \"assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\\\"_mark_tasks_interrupted() not implemented in\",\n \"sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time\",\n \"\\\"process_name\\\": \\\"COAP\\\", \\\"schedule_name\\\": \\\"COAP listener south\\\", \\\"schedule_type\\\": 1, \\\"schedule_interval\\\": \\\"00:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\":\",\n \"implemented in main Scheduler class.\\\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def\",\n \"log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"tests for full code coverage # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger,\",\n \"await scheduler.enable_schedule(sch_id) # THEN assert status is True assert message == \\\"Schedule successfully\",\n \"None assert task.end_time is not None assert task.exit_code is '0' @pytest.mark.skip(\\\"Need a suitable\",\n \"assert tasks[0].start_time is not None assert tasks[0].end_time is not None assert tasks[0].exit_code is\",\n \"'North Readings to PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN\",\n \"in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO: Mandatory - Add negative\",\n \"def test__read_storage(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"@pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"= await scheduler.get_tasks() # THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\":\",\n \"mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", _start_time=current_time - 3600, _paused=False,\",\n \"PI\\\", \\\"schedule_name\\\": \\\"OMF to PI north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"00:00:30\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\":\",\n \"1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF to PI north', 'repeat':\",\n \"that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await\",\n \"\\\"column\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"column\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, \\\"reason\\\",\",\n \"OMF to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(),\",\n \"scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =\",\n \"@pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN payload = {\\\"return\\\": [\\\"id\\\",\",\n \"True # Now queue task and assert that the task has been queued\",\n \"len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"raised despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception was raised by Scheduler._purge_tasks\",\n \"\\\"Schedule is already enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params\",\n \"test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence # \\\"stat collector\\\" appears\",\n \"\\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\", \\\"process_name\\\": \\\"North\",\n \"http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime import uuid import time import json\",\n \"assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now delete schedule with pytest.raises(RuntimeWarning): await\",\n \"# After task completion, sleep above, no task processes should be left pending\",\n \"queue task and assert that the North task has been queued await scheduler.queue_task(schedule.id)\",\n \"scheduler_fixture(self, mocker): # Changed in version 3.8: patch() now returns an AsyncMock if\",\n \"'_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\")\",\n \"scheduler._start_task(schedule) # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN\",\n \"task = await scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name assert task.reason is\",\n \"assert tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN scheduler, schedule,\",\n \"assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task has started yet assert 0\",\n \"assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return\",\n \"= mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row\",\n \"'_task_processes') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) #\",\n \"mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\\\"sleep\\\",\",\n \"\\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") #\",\n \"test__start_task(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage\",\n \"WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert\",\n \"mocker.patch.object(scheduler._logger, \\\"exception\\\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN\",\n \"not None @pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO: Mandatory - Add negative\",\n \"any given time\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \\\"max_completed_task_age_days\\\": { \\\"description\\\":\",\n \"'_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", current_time=current_time - 3600) # TODO: Remove after implementation\",\n \"> time_before_call assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 =\",\n \"'_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999,\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage()\",\n \"== sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params = \\\"Schedule %s already enabled\\\", str(sch_id)\",\n \"scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not\",\n \"current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 ==\",\n \"\\\"info\\\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id\",\n \"assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL,\",\n \"len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count log_params = 'Attempt to delete an\",\n \"= datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN\",\n \"for test_save_schedule_update if table_name == \\\"schedules\\\": return {\\\"count\\\": 1} @classmethod async def delete_from_tbl(cls,\",\n \"log_params = \\\"Schedule %s already enabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker):\",\n \"as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as\",\n \"= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must\",\n \"time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", _start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN retval =\",\n \"Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time is\",\n \"\\\"tasks/statistics\\\" ] }, { \\\"name\\\": \\\"backup\\\", \\\"script\\\": [ \\\"tasks/backup_postgres\\\" ] }, { \\\"name\\\":\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \\\"create_category\\\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \\\"get_category_all_items\\\", return_value=_rv)\",\n \"North task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that\",\n \"= uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information',\",\n \"GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN schedules\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await\",\n \"(scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count calls =\",\n \"Assert that there is no task queued for mock_schedule with pytest.raises(KeyError) as excinfo:\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules() #\",\n \"resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro())\",\n \"in days (based on the start time), for a rows \\\" \\\"in the\",\n \"Find why these exceptions are being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls =\",\n \"queued for this schedule at first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is\",\n \"def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add negative tests for full code\",\n \"temp_schedule assert str(ex).endswith('day must be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\\\"To be done\\\")\",\n \"# WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async\",\n \"backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await\",\n \"== len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\\\"_mark_tasks_interrupted() not implemented in main Scheduler class.\\\") async def test__mark_tasks_interrupted(self,\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \\\"create_category\\\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager,\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \\\"create_category\\\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \\\"get_category_all_items\\\", return_value=_rv) #\",\n \"return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0,\",\n \"import MagicMock, call import sys import copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler,\",\n \"\\\"id\\\": \\\"259b8570-65c1-4b92-8c62-e9642631a600\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"state\\\": 1, \\\"start_time\\\": \\\"2018-02-06 13:28:14.477868\\\", \\\"end_time\\\":\",\n \"2017 OSIsoft, LLC\\\" __license__ = \\\"Apache 2.0\\\" __version__ = \\\"${VERSION}\\\" async def mock_task():\",\n \"\\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \\\"max_completed_task_age_days\\\": { \\\"description\\\": \\\"The maximum age,\",\n \"{ \\\"name\\\": \\\"North Readings to PI\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"1\\\", \\\"--debug_level\\\", \\\"1\\\"\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id\",\n \"test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert\",\n \"time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch\",\n \"with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with\",\n \"# THEN log_params = \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def\",\n \"collector\\\" appears twice in this list. assert 'stats collection' in args3 @pytest.mark.asyncio async\",\n \"{'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled':\",\n \"mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add negative\",\n \"patch() now returns an AsyncMock if the target is an async function. if\",\n \"= [call('Starting'), call('Starting Scheduler: Management port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls\",\n \"\\\"--debug_level\\\", \\\"1\\\" ] }, { \\\"name\\\": \\\"North Readings to OCS\\\", \\\"script\\\": [ \\\"tasks/north\\\",\",\n \"\\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"start_time\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD\",\n \"of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN # Now\",\n \"with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule)\",\n \"task queued for mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True #\",\n \"GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\")\",\n \"\\\"reason\\\": \\\"\\\" } ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host,\",\n \"must be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\\\"To be done\\\") async def test_remove_service_from_task_processes(self):\",\n \"ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio\",\n \"is True assert message == \\\"Schedule is already enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id\",\n \"0 days', True), ('12:30:11', False), ('0 day 12:30:11', False), ('1 day 12:40:11', False),\",\n \"None calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"),\",\n \"excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo:\",\n \"\\\"max_completed_task_age_days\\\": { \\\"description\\\": \\\"The maximum age, in days (based on the start time),\",\n \"as excinfo: await scheduler.get_task(task_id) # THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\",\",\n \"and assert that the North task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id],\",\n \"schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL,\",\n \"THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\\\"_mark_tasks_interrupted() not implemented\",\n \"@pytest.mark.asyncio async def test_stop(self, mocker): # TODO: Mandatory - Add negative tests for\",\n \"= scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess')\",\n \"async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time()\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler,\",\n \"testing. Will be tested during System tests.\\\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio\",\n \"delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if table_name ==\",\n \"'_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\")\",\n \"'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls,\",\n \"sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt =\",\n \"= time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector\",\n \"core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10,\",\n \"for Interval Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled\",\n \"def test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"1 == log_exception.call_count log_params = 'Attempt to delete an enabled Schedule %s. Not\",\n \"stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call\",\n \"started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task has\",\n \"True assert message == \\\"Schedule is already enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert\",\n \"THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state is not\",\n \"sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo:\",\n \"== len(scheduler._schedules) assert 1 == log_exception.call_count log_params = 'Attempt to delete an enabled\",\n \"return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert\",\n \"is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =\",\n \"test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is True assert\",\n \"# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug =\",\n \"mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes,\",\n \"def insert_into_tbl(cls, table_name, payload): pass @classmethod async def update_tbl(cls, table_name, payload): # Only\",\n \"None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time is not\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes)\",\n \"== 'tasks': return { \\\"count\\\": len(MockStorageAsync.tasks), \\\"rows\\\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls,\",\n \"== tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is\",\n \"call('Starting Scheduler: Management port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database\",\n \"return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\",\",\n \"mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL,\",\n \"scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") log_error = mocker.patch.object(scheduler._logger, \\\"error\\\") log_debug = mocker.patch.object(scheduler._logger,\",\n \"listener south' in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\\\"_scheduler_loop()\",\n \"_rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts',\",\n \"async def test__read_storage(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat\",\n \"def test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"== schedule_id assert schedule.name == \\\"purge\\\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat ==\",\n \"test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") #\",\n \"assert 'COAP listener south' in args1 assert 'OMF to PI north' in args2\",\n \"is not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add\",\n \"schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0\",\n \"# WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def\",\n \"log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection' in args0 assert 'COAP listener\",\n \"tasks that can be running at any given time\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS),\",\n \"@asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"# WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert\",\n \"= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await\",\n \"len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert call(\\\"Queued schedule '%s' for execution\\\", 'OMF\",\n \"test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage\",\n \"WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params)\",\n \"assert str(ex).endswith('day must be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\\\"To be done\\\") async\",\n \"Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN scheduler =\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo:\",\n \"mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id)\",\n \"super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return { \\\"id\\\": uuid.uuid4(), \\\"name\\\": \\\"Fledge Storage\\\",\",\n \"'_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None assert\",\n \"None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker):\",\n \"{} already disabled\\\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params =\",\n \"# WHEN earliest_start_time = await scheduler._check_schedules() # THEN assert earliest_start_time is not None\",\n \"tasks table that do not have a status of running\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\":\",\n \"1 == log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def\",\n \"args, kwargs = log_info.call_args_list[0] # assert (\\\"Queued schedule '%s' for execution\\\", 'OMF to\",\n \"excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo:\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row =\",\n \"1 == cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks is not None assert\",\n \"PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule =\",\n \"'_resume_check_schedules') # Assert that there is no task queued for mock_schedule with pytest.raises(KeyError)\",\n \"= [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat':\",\n \"scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes = await scheduler.get_scheduled_processes() # THEN assert\",\n \"scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await\",\n \"await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id =\",\n \"\\\"name\\\": \\\"North Readings to PI\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"1\\\", \\\"--debug_level\\\", \\\"1\\\" ]\",\n \"with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with\",\n \"# WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion, sleep above, no\",\n \"self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # purge schedule # WHEN schedule = await scheduler.get_schedule(schedule_id)\",\n \"of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence # \\\"stat collector\\\" appears twice in\",\n \"def test__schedule_next_task(self, mocker): # TODO: Mandatory - Add negative tests for full code\",\n \"assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params = \\\"Schedule %s already\",\n \"schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0 # 0 for Interval\",\n \"exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no\",\n \"True return m @pytest.allure.feature(\\\"unit\\\") @pytest.allure.story(\\\"scheduler\\\") class TestScheduler: async def scheduler_fixture(self, mocker): # Changed\",\n \"args args, kwargs = log_info.call_args_list[1] assert \\\"Stopping process: Schedule '%s' process '%s' task\",\n \"# WHEN # THEN task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id)\",\n \"test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN if is_exception is True: with\",\n \"mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN await scheduler.start() # THEN\",\n \"True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count else: await scheduler._get_schedules() assert\",\n \"\\\"script\\\": [ \\\"tasks/statistics\\\" ] }, { \\\"name\\\": \\\"backup\\\", \\\"script\\\": [ \\\"tasks/backup_postgres\\\" ] },\",\n \"type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id,\",\n \"args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker):\",\n \"@pytest.mark.skip(\\\"_mark_tasks_interrupted() not implemented in main Scheduler class.\\\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio\",\n \"== enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def\",\n \"\\\"tasks/north\\\", \\\"--stream_id\\\", \\\"1\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, { \\\"name\\\": \\\"North Readings to OCS\\\",\",\n \"empty\\\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \\\"\\\" await\",\n \"expression\\\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"== \\\"purge\\\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive\",\n \"# WHEN # THEN with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name\",\n \"core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return { \\\"id\\\": uuid.uuid4(), \\\"name\\\":\",\n \"len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks() # THEN assert\",\n \"await scheduler._check_schedules() # THEN assert earliest_start_time is not None assert 3 == log_info.call_count\",\n \"@pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \\\"\\\" await scheduler.save_schedule(temp_schedule) del\",\n \"test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"enabled=True) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") log_error = mocker.patch.object(scheduler._logger, \\\"error\\\") log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\")\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") log_exception = mocker.patch.object(scheduler._logger,\",\n \"'%s' process '%s' task %s pid %s, %s running tasks\\\\n%s\\\" in args assert\",\n \"1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"already disabled\\\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params = \\\"Schedule\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts()\",\n \"that there is no task queued for schedule with pytest.raises(KeyError) as excinfo: assert\",\n \"mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules() # THEN assert earliest_start_time\",\n \"name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id,\",\n \"Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks =\",\n \"exceptions are being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception was\",\n \"scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules,\",\n \"# Confirm that task has not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) #\",\n \"# \\\"stat collector\\\" appears twice in this list. assert 'stats collection' in args3\",\n \"log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): # TODO: Mandatory - Add negative\",\n \"async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule,\",\n \"\\\"purge\\\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is\",\n \"condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks': return\",\n \"scheduler._ScheduleExecution) # Confirm that no task has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes)\",\n \"_core_management_host=\\\"0.0.0.0\\\", current_time=current_time - 3600) # TODO: Remove after implementation of above test test__read_config()\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await\",\n \"PI\\\", name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id]\",\n \"# WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules)\",\n \"log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await\",\n \"}, { \\\"name\\\": \\\"COAP\\\", \\\"script\\\": [ \\\"services/south\\\" ] }, { \\\"name\\\": \\\"North Readings\",\n \"p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"in args args, kwargs = log_info.call_args_list[1] assert \\\"Stopping process: Schedule '%s' process '%s'\",\n \"type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) #\",\n \"assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state is not None\",\n \"function. if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await get_cat()\",\n \"] tasks = [ { \\\"id\\\": \\\"259b8570-65c1-4b92-8c62-e9642631a600\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"state\\\":\",\n \"await scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\\\"test_interval, is_exception\\\", [\",\n \"# GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None)\",\n \"# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger =\",\n \"assert 'North Readings to PI' in args args, kwargs = log_info.call_args_list[1] assert \\\"Stopping\",\n \"\\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"1 day 00:00:40\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\":\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info =\",\n \"@pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"resume_sch.call_count assert 1 == enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule,\",\n \"HH24:MI:SS.MS\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"limit\\\": 100} args, kwargs = log_exception.call_args assert 'Query failed: %s'\",\n \"= copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN if\",\n \"is None # WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None\",\n \"async def test_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for full\",\n \"tasks\\\\n%s\\\" in args assert 'OMF to PI north' in args assert 'North Readings\",\n \"str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version 3.8: patch() now returns\",\n \"schedule_id assert schedule.name == \\\"purge\\\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0,\",\n \"enabled=True, process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id,\",\n \"is None assert scheduler._ready is False assert scheduler._paused is False assert scheduler._start_time is\",\n \"has not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) #\",\n \"mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN\",\n \"no task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True\",\n \"pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del\",\n \"log_params = \\\"Schedule %s already disabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker):\",\n \"\\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, { \\\"id\\\": \\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"COAP\\\", \\\"schedule_name\\\": \\\"COAP listener\",\n \"disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN\",\n \"False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1\",\n \"to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF\",\n \"pid %s, %s running tasks\\\\n%s\\\" in args assert 'OMF to PI north' in\",\n \"@pytest.mark.asyncio async def test__read_config(self, mocker): async def get_cat(): return { \\\"max_running_tasks\\\": { \\\"description\\\":\",\n \"return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has not started\",\n \"test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None,\",\n \"and sys.version_info.minor >= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler\",\n \"log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"'_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF to\",\n \"uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # purge schedule # WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN assert\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task =\",\n \"pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler,\",\n \"of type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day =\",\n \"log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN\",\n \"'_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", _start_time=current_time -\",\n \"len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id) # THEN assert\",\n \"Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is True assert schedule.enabled is\",\n \"\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"purge\\\", \\\"schedule_name\\\": \\\"purge\\\", \\\"schedule_type\\\": 4, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0,\",\n \"id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule =\",\n \"mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task queued\",\n \"args assert 'OMF to PI north' in args assert 'North Readings to PI'\",\n \"scheduler._paused is False assert scheduler._start_time is None calls = [call('Processing stop request'), call('Stopped')]\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN #\",\n \"scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks()\",\n \"uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is\",\n \"'_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async\",\n \"mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", current_time=current_time - 3600) # TODO:\",\n \"GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule',\",\n \"'_resume_check_schedules') # Assert that there is no task queued for this schedule at\",\n \"mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks()\",\n \"# WHEN schedules = await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio\",\n \"await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" #\",\n \"args1 assert 'OMF to PI north' in args2 # As part of scheduler._get_schedules(),\",\n \"assert 'OMF to PI north' in args assert 'North Readings to PI' in\",\n \"\\\"2018-02-06 13:28:14.856375\\\", \\\"exit_code\\\": \\\"0\\\", \\\"reason\\\": \\\"\\\" } ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host,\",\n \"task and assert that the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id],\",\n \"= log_exception.call_args assert 'Query failed: %s' == args[0] p = json.loads(args[1]) assert payload\",\n \"\\\"backup hourly\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\":\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\",\",\n \"<filename>tests/unit/python/fledge/services/core/scheduler/test_scheduler.py<gh_stars>10-100 # -*- coding: utf-8 -*- # FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END\",\n \"\\\"script\\\": [ \\\"services/south\\\" ] }, { \\\"name\\\": \\\"North Readings to PI\\\", \\\"script\\\": [\",\n \"during System tests.\\\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker):\",\n \"for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\\\"Disabled Schedule '%s/%s' process '%s'\\\\n\\\", 'OMF to PI north',\",\n \"mocker): # TODO: Mandatory - Add negative tests for full code coverage #\",\n \"process_name=\\\"North Readings to PI\\\", name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None,\",\n \"in args2 @pytest.mark.asyncio @pytest.mark.skip(\\\"_scheduler_loop() not suitable for unit testing. Will be tested during\",\n \"= mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message\",\n \"sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger,\",\n \"WHEN earliest_start_time = await scheduler._check_schedules() # THEN assert earliest_start_time is not None assert\",\n \"'_schedule_first_task') # WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules)\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules()\",\n \"kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3\",\n \"mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules()\",\n \"\\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version 3.8:\",\n \"'_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules() # THEN assert earliest_start_time is\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there is no task\",\n \"'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker):\",\n \"await scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is '' assert\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio\",\n \"\\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } class MockStorageAsync(StorageClientAsync): schedules = [ { \\\"id\\\": \\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\",\",\n \"scheduler._get_schedules() sch_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert\",\n \"self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async\",\n \"'_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules',\",\n \"mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\\\"sleep\\\", \\\".1\\\") mock_task_process.schedule =\",\n \"in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id\",\n \"asyncio.create_subprocess_exec(\\\"sleep\\\", \\\".1\\\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] =\",\n \"not fit for unit test.\\\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync):\",\n \"\\\".1\\\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process\",\n \"scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker):\",\n \"be used in 'await' expression\\\"), call('An exception was raised by Scheduler._scheduler_loop %s', \\\"object\",\n \"async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"test_stop(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage\",\n \"log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN task_id = uuid.uuid4() with\",\n \"above, no task processes should be left pending assert 0 == len(scheduler._task_processes) assert\",\n \"north' in args assert 'North Readings to PI' in args @pytest.mark.asyncio async def\",\n \"has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8:\",\n \"these exceptions are being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception\",\n \"FLEDGE_END import asyncio import datetime import uuid import time import json from unittest.mock\",\n \"temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be of type\",\n \"uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) #\",\n \"args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0] p = json.loads(args[1])\",\n \"str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version 3.8: patch() now returns an AsyncMock\",\n \"] }, ] tasks = [ { \\\"id\\\": \\\"259b8570-65c1-4b92-8c62-e9642631a600\\\", \\\"process_name\\\": \\\"North Readings to\",\n \"# THEN assert earliest_start_time is not None assert 3 == log_info.call_count args0, kwargs0\",\n \"Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 1\",\n \"_task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) #\",\n \"True assert message == \\\"Schedule successfully enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled\",\n \"\\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } @classmethod async def insert_into_tbl(cls, table_name, payload):\",\n \"# THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN\",\n \"await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") random_schedule_id =\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") schedule_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North schedule_row\",\n \"despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception was raised by Scheduler._purge_tasks %s',\",\n \"\\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"column\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, \\\"reason\\\", \\\"exit_code\\\"],\",\n \"scheduler._read_config() # THEN assert 1 == cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks\",\n \"queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task has started\",\n \"audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 0 ==\",\n \"Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await\",\n \"processes = await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\")\",\n \"days', True), ('2 days 00:00:59', False), ('00:25:61', True) ]) async def test__get_schedules(self, test_interval,\",\n \"payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\":\",\n \"{ \\\"description\\\": \\\"The maximum age, in days (based on the start time), for\",\n \"fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright\",\n \"THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio\",\n \"args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_get_tasks(self, mocker):\",\n \"9999 m.terminate = lambda: True return m @pytest.allure.feature(\\\"unit\\\") @pytest.allure.story(\\\"scheduler\\\") class TestScheduler: async def\",\n \"get_cat(): return { \\\"max_running_tasks\\\": { \\\"description\\\": \\\"The maximum number of tasks that can\",\n \"assert call(\\\"Queued schedule '%s' for execution\\\", 'OMF to PI north') == log_info.call_args_list[0] args,\",\n \"kwargs = log_info.call_args_list[0] assert \\\"Process started: Schedule '%s' process '%s' task %s pid\",\n \"] scheduled_processes = [ { \\\"name\\\": \\\"purge\\\", \\\"script\\\": [ \\\"tasks/purge\\\" ] }, {\",\n \"raised by Scheduler._purge_tasks %s', \\\"object MagicMock can't be used in 'await' expression\\\"), call('An\",\n \"assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\\\"_mark_tasks_interrupted() not implemented in main Scheduler class.\\\") async\",\n \"{'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})]\",\n \"assert that the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) #\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception =\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused',\",\n \"temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be between 1\",\n \"{ \\\"name\\\": \\\"stats collector\\\", \\\"script\\\": [ \\\"tasks/statistics\\\" ] }, { \\\"name\\\": \\\"backup\\\", \\\"script\\\":\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule =\",\n \"= await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as\",\n \"return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules() # THEN assert earliest_start_time is not\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() curr_time\",\n \"TODO: Remove after implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready\",\n \"is None @pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"assert task.state is not None assert task.cancel_requested is None assert task.start_time is not\",\n \"assert 1 == get_cat.call_count assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is not\",\n \"queue_task.call_count calls = [call(\\\"Enabled Schedule '%s/%s' process '%s'\\\\n\\\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls,\",\n \"mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\")\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception())\",\n \"Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] #\",\n \"Readings to PI\\\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion,\",\n \"time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert time_after_call\",\n \"been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id) # THEN assert\",\n \"True) # WHEN # THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError)\",\n \"\\\"OMF to PI north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"00:00:30\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\":\",\n \"suitable fixture\\\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"to PI\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"1\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, { \\\"name\\\":\",\n \"== first_task.call_count assert 1 == resume_sch.call_count assert 1 == enable_schedule.call_count assert 0 ==\",\n \"day 00:00:40\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, ] scheduled_processes\",\n \"1} @classmethod async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name,\",\n \"def mock_process(): m = MagicMock() m.pid = 9999 m.terminate = lambda: True return\",\n \"scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4())\",\n \"log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF part\",\n \"enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await\",\n \"scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL,\",\n \"\\\"0\\\", \\\"reason\\\": \\\"\\\" } ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self,\",\n \"task processes should be left pending assert 0 == len(scheduler._task_processes) assert 0 ==\",\n \"== \\\"Schedule successfully disabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False assert\",\n \"day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process\",\n \"None assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1]\",\n \"log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF to PI north', 'repeat': 30.0, 'enabled':\",\n \"tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule,\",\n \"schedule = await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id\",\n \"PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has not started yet assert 0\",\n \"\\\"value\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \\\"max_completed_task_age_days\\\": { \\\"description\\\": \\\"The maximum age, in days (based on\",\n \"scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): #\",\n \"assert that the North task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution)\",\n \"@pytest.mark.asyncio @pytest.mark.skip(reason=\\\"To be done\\\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker):\",\n \"= await self.scheduler_fixture(mocker) # Assert that there is no North task queued for\",\n \"tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time is not None\",\n \"the tasks table that do not have a status of running\\\", \\\"type\\\": \\\"integer\\\",\",\n \"pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) ==\",\n \"time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch\",\n \"scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \\\"Queued schedule '%s' for\",\n \"= mocker.patch.object(ConfigurationManager, \\\"create_category\\\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \\\"get_category_all_items\\\", return_value=_rv) # WHEN assert scheduler._max_running_tasks\",\n \"@pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"successfully disabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2 ==\",\n \"# As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence # \\\"stat collector\\\"\",\n \"@pytest.allure.feature(\\\"unit\\\") @pytest.allure.story(\\\"scheduler\\\") class TestScheduler: async def scheduler_fixture(self, mocker): # Changed in version 3.8:\",\n \"PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls\",\n \"enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await\",\n \"await scheduler.start() # THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert\",\n \"schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now confirm no schedule is\",\n \"== Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time\",\n \"== p @pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"assert tasks[0].reason is '' assert tasks[0].state is not None assert tasks[0].cancel_requested is None\",\n \"\\\"count\\\": len(MockStorageAsync.tasks), \\\"rows\\\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name, query=None): if table_name\",\n \"scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\\\"test_interval, is_exception\\\", [ ('\\\"Blah\\\"\",\n \"\\\"protocol\\\": \\\"http\\\" } class MockStorageAsync(StorageClientAsync): schedules = [ { \\\"id\\\": \\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"purge\\\",\",\n \"assert 'North Readings to PI' in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): #\",\n \"\\\"stats collection\\\", \\\"schedule_type\\\": 2, \\\"schedule_interval\\\": \\\"00:00:15\\\", \\\"schedule_time\\\": \\\"00:00:15\\\", \\\"schedule_day\\\": 3, \\\"exclusive\\\": \\\"f\\\", \\\"enabled\\\":\",\n \"return scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): #\",\n \"\\\"services/south\\\" ] }, { \\\"name\\\": \\\"North Readings to PI\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\",\",\n \"mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") schedule_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\")\",\n \"return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", _start_time=current_time - 3600,\",\n \"\\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\",\",\n \"\\\"where\\\": {\\\"column\\\": \\\"id\\\", \\\"condition\\\": \\\"=\\\", \\\"value\\\": str(task_id)}} args, kwargs = log_exception.call_args assert 'Query\",\n \"Schedule '%s' process '%s' task %s pid %s\\\\n%s\\\" in args assert 'OMF to\",\n \"'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"(based on the start time), for a rows \\\" \\\"in the tasks table\",\n \"test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add negative tests\",\n \"is True assert scheduler._schedule_executions is None assert scheduler._task_processes is None assert scheduler._schedules is\",\n \"with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def\",\n \"THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine\",\n \"GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger,\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there is\",\n \"async def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"\\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } class MockStorageAsync(StorageClientAsync): schedules = [ {\",\n \"= await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED,\",\n \"assert scheduler._max_completed_task_age is None await scheduler._read_config() # THEN assert 1 == cr_cat.call_count assert\",\n \"AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import\",\n \"async def test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"assert 1 == resume_sch.call_count assert 1 == enable_schedule.call_count assert 0 == disable_schedule.call_count #\",\n \"schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is True assert schedule.enabled is True assert\",\n \"next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN assert time_after_call\",\n \"== sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count calls = [call('No\",\n \"is True assert message == \\\"Schedule successfully enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert\",\n \"to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30),\",\n \"= sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 4 == log_info.call_count args0,\",\n \"temp_schedule.day = 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must\",\n \"\\\"\\\" } ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port):\",\n \"current_time=current_time - 3600) # TODO: Remove after implementation of above test test__read_config() mocker.patch.object(scheduler,\",\n \"%s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker):\",\n \"audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") #\",\n \"with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN\",\n \"left pending assert 0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs =\",\n \"that the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed\",\n \"'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1\",\n \"def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def\",\n \"PI north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \\\"Process started: Schedule '%s'\",\n \"scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule\",\n \"async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await\",\n \"log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2]\",\n \"version 3.8: patch() now returns an AsyncMock if the target is an async\",\n \"'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName':\",\n \"{ \\\"max_running_tasks\\\": { \\\"description\\\": \\\"The maximum number of tasks that can be running\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() #\",\n \"args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert\",\n \"# Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now confirm\",\n \"test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"\\\"end_time\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"where\\\": {\\\"column\\\": \\\"id\\\", \\\"condition\\\": \\\"=\\\", \\\"value\\\": str(task_id)}} args, kwargs =\",\n \"is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'),\",\n \"type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN with\",\n \"\\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, { \\\"id\\\": \\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"COAP\\\", \\\"schedule_name\\\": \\\"COAP listener south\\\",\",\n \"assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks()\",\n \"not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id) # THEN\",\n \"== audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0,\",\n \"None assert tasks[0].end_time is not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def\",\n \"THEN assert time_after_call > time_before_call assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0]\",\n \"assert (\\\"Queued schedule '%s' for execution\\\", 'OMF to PI north') == args args,\",\n \"schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): #\",\n \"await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count\",\n \"self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler,\",\n \"2.0\\\" __version__ = \\\"${VERSION}\\\" async def mock_task(): return \\\"\\\" async def mock_process(): m\",\n \"mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id]\",\n \"completion, sleep above, no task processes should be left pending assert 0 ==\",\n \"= await scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is ''\",\n \"\\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\", \\\"process_name\\\": \\\"North Readings to OCS\\\", \\\"schedule_name\\\": \\\"OMF\",\n \"= time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector\",\n \"'OMF to PI north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO:\",\n \"copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN if is_exception\",\n \"await scheduler.stop() # THEN assert retval is True assert scheduler._schedule_executions is None assert\",\n \"== cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age\",\n \"async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule,\",\n \"@pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") await scheduler._get_schedules() sch_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\")\",\n \"== log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 =\",\n \"def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError)\",\n \"'%s' for execution\\\", 'OMF to PI north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0]\",\n \"log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \\\"Process started: Schedule '%s' process '%s' task\",\n \"0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\"\",\n \"log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception):\",\n \"excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo:\",\n \"0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\"\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes\",\n \"assert scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution)\",\n \"PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30,\",\n \"already disabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule,\",\n \"def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule, log_info,\",\n \"None @pytest.mark.asyncio async def test_start(self, mocker): # TODO: Mandatory - Add negative tests\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \\\"create_category\\\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \\\"get_category_all_items\\\",\",\n \"core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with\",\n \"scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4())\",\n \"with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with\",\n \"return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN assert\",\n \"THEN log_params = \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self,\",\n \"mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not None\",\n \"= await scheduler._check_schedules() # THEN assert earliest_start_time is not None assert 3 ==\",\n \"scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF to PI north\\\",\",\n \"mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") return scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN status, message\",\n \"str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"that there is no North task queued for schedule with pytest.raises(KeyError) as excinfo:\",\n \"payload): pass @classmethod async def update_tbl(cls, table_name, payload): # Only valid for test_save_schedule_update\",\n \"\\\"create_category\\\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \\\"get_category_all_items\\\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is None\",\n \"mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False # WHEN #\",\n \"core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN\",\n \"PI\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"1\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, { \\\"name\\\": \\\"North\",\n \"[ \\\"tasks/statistics\\\" ] }, { \\\"name\\\": \\\"backup\\\", \\\"script\\\": [ \\\"tasks/backup_postgres\\\" ] }, {\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task',\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger,\",\n \"# THEN assert status is True assert message == \\\"Schedule successfully disabled\\\" assert\",\n \"table_name, query_payload): if table_name == 'tasks': return { \\\"count\\\": len(MockStorageAsync.tasks), \\\"rows\\\": MockStorageAsync.tasks }\",\n \"has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task\",\n \"{\\\"count\\\": 1} @classmethod async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls,\",\n \"in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO: Mandatory - Add negative\",\n \"\\\"Schedule {} already disabled\\\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params\",\n \"mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") enable_schedule = mocker.patch.object(scheduler,\",\n \"@pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"\\\"type\\\": \\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } @classmethod async\",\n \"async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo: await\",\n \"type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule\",\n \"to PI' in args args, kwargs = log_info.call_args_list[1] assert \\\"Stopping process: Schedule '%s'\",\n \"assert str(ex).endswith(\\\"name can not be empty\\\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id,\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) schedule_id\",\n \"between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\\\"To be done\\\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio\",\n \"None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def test_start(self, mocker): # TODO:\",\n \"== len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state ==\",\n \"resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") schedule_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF\",\n \"'_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self,\",\n \"assert schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8] assert\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\",\",\n \"with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \\\"\\\" await scheduler.save_schedule(temp_schedule)\",\n \"fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright (c) 2017 OSIsoft, LLC\\\"\",\n \"is no North task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id]\",\n \"}, } # Changed in version 3.8: patch() now returns an AsyncMock if\",\n \"await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message\",\n \"task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id) # THEN assert schedule.process_name\",\n \"\\\"end_time\\\": \\\"2018-02-06 13:28:14.856375\\\", \\\"exit_code\\\": \\\"0\\\", \\\"reason\\\": \\\"\\\" } ] def __init__(self, core_management_host=None, core_management_port=None):\",\n \"was raised by Scheduler._purge_tasks %s', \\\"object MagicMock can't be used in 'await' expression\\\"),\",\n \"sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await get_cat() else: _rv\",\n \"is not None @pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO: Mandatory - Add\",\n \"with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time =\",\n \"call(\\\"Disabled Schedule '%s/%s' process '%s'\\\\n\\\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to\",\n \"pass @classmethod async def update_tbl(cls, table_name, payload): # Only valid for test_save_schedule_update if\",\n \"has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task =\",\n \"await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN task_id =\",\n \"len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\\\"_mark_tasks_interrupted() not implemented in main Scheduler class.\\\") async def\",\n \"scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\\\"_terminate_child_processes() not fit for unit test.\\\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass\",\n \"'_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN await scheduler.start() # THEN assert\",\n \"mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to\",\n \"pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\\\"_terminate_child_processes() not fit for unit test.\\\") @pytest.mark.asyncio async\",\n \"async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion') #\",\n \"args2 @pytest.mark.asyncio @pytest.mark.skip(\\\"_scheduler_loop() not suitable for unit testing. Will be tested during System\",\n \"mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker): async def get_cat(): return { \\\"max_running_tasks\\\":\",\n \"uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup await scheduler._get_schedules() # Confirm no. of schedules assert len(scheduler._storage_async.schedules) ==\",\n \"in args @pytest.mark.asyncio async def test__start_task(self, mocker): # TODO: Mandatory - Add negative\",\n \"== schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name ==\",\n \"test__read_config(self, mocker): async def get_cat(): return { \\\"max_running_tasks\\\": { \\\"description\\\": \\\"The maximum number\",\n \"MagicMock, call import sys import copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger,\",\n \"PI north' in args assert 'North Readings to PI' in args @pytest.mark.asyncio async\",\n \"Interval Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled ==\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN\",\n \"task.reason is '' assert task.state is not None assert task.cancel_requested is None assert\",\n \"test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"def test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for full code\",\n \"== schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def\",\n \"1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be of type datetime.timedelta') with\",\n \"schedule # WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert\",\n \"\\\"column\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"limit\\\": 100} args, kwargs = log_exception.call_args\",\n \"@pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for\",\n \"# WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def\",\n \"args assert 'North Readings to PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker):\",\n \"random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \\\"No such\",\n \"len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF to PI\",\n \"(scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params = \\\"Schedule %s already enabled\\\",\",\n \"# THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN\",\n \"assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True,\",\n \"scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name assert task.reason is '' assert task.state\",\n \"log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection' in args0 assert 'COAP listener\",\n \"'%s'\\\\n\\\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls =\",\n \"return_value=_rv) # WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None await scheduler._read_config()\",\n \"== enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN\",\n \"= [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day':\",\n \"assert tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None assert\",\n \"scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4())\",\n \"# Confirm that cancel request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None\",\n \"\\\"COAP\\\", \\\"schedule_name\\\": \\\"COAP listener south\\\", \\\"schedule_type\\\": 1, \\\"schedule_interval\\\": \\\"00:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0,\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\",\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\")\",\n \"# WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert status is True\",\n \"assert schedule_row[3] is 0 # 0 for Interval Schedule assert schedule_row[4] is 0\",\n \"assert schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker):\",\n \"scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 4 ==\",\n \"log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1)))\",\n \"= list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id) # THEN assert schedule.process_name ==\",\n \"table_name, query=None): if table_name == 'schedules': return { \\\"count\\\": len(MockStorageAsync.schedules), \\\"rows\\\": MockStorageAsync.schedules }\",\n \"# assert call(\\\"Queued schedule '%s' for execution\\\", 'OMF to PI north') == log_info.call_args_list[0]\",\n \"assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management port received is\",\n \"# WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id\",\n \"= scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess')\",\n \"GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) #\",\n \"assert scheduler._ready is False # WHEN await scheduler.start() # THEN assert scheduler._ready is\",\n \"def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert status is True assert\",\n \"Storage\\\", \\\"type\\\": \\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } @classmethod\",\n \"= await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert\",\n \"'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert\",\n \"THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)\",\n \"assert schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio\",\n \"'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls,\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN\",\n \"dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler,\",\n \"def get_cat(): return { \\\"max_running_tasks\\\": { \\\"description\\\": \\\"The maximum number of tasks that\",\n \"tasks = [ { \\\"id\\\": \\\"259b8570-65c1-4b92-8c62-e9642631a600\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"state\\\": 1,\",\n \"[ \\\"services/south\\\" ] }, { \\\"name\\\": \\\"North Readings to PI\\\", \\\"script\\\": [ \\\"tasks/north\\\",\",\n \"scheduler.enable_schedule(sch_id) # THEN assert status is True assert message == \\\"Schedule is already\",\n \"scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8: patch() now returns an\",\n \"False assert scheduler._start_time is None calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True)\",\n \"async def insert_into_tbl(cls, table_name, payload): pass @classmethod async def update_tbl(cls, table_name, payload): #\",\n \"schedule_row) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name ==\",\n \"\\\"in the tasks table that do not have a status of running\\\", \\\"type\\\":\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") return scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def\",\n \"mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") #\",\n \"temp_schedule assert str(ex).endswith(\\\"name can not be empty\\\") with pytest.raises(ValueError) as ex: temp_schedule =\",\n \"be left pending assert 0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs\",\n \"\\\"Apache 2.0\\\" __version__ = \\\"${VERSION}\\\" async def mock_task(): return \\\"\\\" async def mock_process():\",\n \"WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self,\",\n \"uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch,\",\n \"queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status,\",\n \"test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def test_start(self, mocker): # TODO: Mandatory\",\n \"# THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 == log_info.call_count # args,\",\n \"del temp_schedule assert str(ex).endswith('repeat must be of type datetime.timedelta') with pytest.raises(ValueError) as ex:\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999,\",\n \"}, { \\\"name\\\": \\\"North Readings to OCS\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"4\\\", \\\"--debug_level\\\",\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler,\",\n \"== 3 and sys.version_info.minor >= 8: _rv = await get_cat() else: _rv =\",\n \"scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4())\",\n \"schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True,\",\n \"await asyncio.create_subprocess_exec(\\\"sleep\\\", \\\".1\\\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id]\",\n \"Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule,\",\n \"= 9999 m.terminate = lambda: True return m @pytest.allure.feature(\\\"unit\\\") @pytest.allure.story(\\\"scheduler\\\") class TestScheduler: async\",\n \"scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def test_start(self,\",\n \"[\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"column\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, {\\\"alias\\\": \\\"end_time\\\",\",\n \"await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks = await\",\n \"as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as\",\n \"if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await get_cat() else:\",\n \"assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler =\",\n \"return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\",\",\n \"scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\")\",\n \"else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler,\",\n \"_max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch = scheduler._schedules[sch_id]\",\n \"await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\\\"_terminate_child_processes() not fit for unit\",\n \"\\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\", \\\"process_name\\\": \\\"stats collector\\\",\",\n \"= 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be of type datetime.time')\",\n \"sch_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that\",\n \"str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError) as ex:\",\n \"pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del\",\n \"assert (scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count calls = [call('No Task running\",\n \"import time import json from unittest.mock import MagicMock, call import sys import copy\",\n \"with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN\",\n \"log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task')\",\n \"scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be\",\n \"\\\"rows\\\": MockStorageAsync.schedules } if table_name == 'scheduled_processes': return { \\\"count\\\": len(MockStorageAsync.scheduled_processes), \\\"rows\\\": MockStorageAsync.scheduled_processes\",\n \"Now queue task and assert that the North task has been queued await\",\n \"await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch =\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() #\",\n \"is False assert scheduler._start_time is None calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls,\",\n \"log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): #\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \\\"info\\\")\",\n \"sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt +=\",\n \"== len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF to PI north' in args\",\n \"args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection' in args0\",\n \"new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN if is_exception is\",\n \"after implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False\",\n \"assert scheduler._process_scripts is None assert scheduler._ready is False assert scheduler._paused is False assert\",\n \"= mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) ==\",\n \"= await scheduler.get_running_tasks() # THEN assert 1 == len(tasks) assert schedule.process_name == tasks[0].process_name\",\n \"def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if table_name\",\n \"scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): #\",\n \"\\\"type\\\": \\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } class MockStorageAsync(StorageClientAsync):\",\n \"is True log_params = \\\"Schedule %s already enabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def\",\n \"pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks': return {\",\n \"30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1\",\n \"len(MockStorageAsync.tasks), \\\"rows\\\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name, query=None): if table_name ==\",\n \"import sys import copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from\",\n \"as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\\\"_terminate_child_processes() not fit for unit test.\\\") @pytest.mark.asyncio async def\",\n \"# 0 for Interval Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7]\",\n \"async def test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"for full code coverage # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name':\",\n \"def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return { \\\"id\\\":\",\n \"table_name == 'tasks': return { \\\"count\\\": len(MockStorageAsync.tasks), \\\"rows\\\": MockStorageAsync.tasks } @classmethod async def\",\n \"_max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules()\",\n \"assert 'North Readings to PI' in args @pytest.mark.asyncio async def test__start_task(self, mocker): #\",\n \"= mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") schedule_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to\",\n \"sys.version_info.minor >= 8: _rv = await get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN\",\n \"uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert\",\n \"test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup\",\n \"update_tbl(cls, table_name, payload): # Only valid for test_save_schedule_update if table_name == \\\"schedules\\\": return\",\n \"1 == log_info.call_count # assert call(\\\"Queued schedule '%s' for execution\\\", 'OMF to PI\",\n \"return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN await scheduler.start() # THEN assert scheduler._ready\",\n \"that the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm\",\n \"from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright (c) 2017 OSIsoft,\",\n \"mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time\",\n \"WHEN # THEN if is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1\",\n \"async def test__schedule_next_task(self, mocker): # TODO: Mandatory - Add negative tests for full\",\n \"log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo: tasks =\",\n \"}, ] tasks = [ { \\\"id\\\": \\\"259b8570-65c1-4b92-8c62-e9642631a600\\\", \\\"process_name\\\": \\\"North Readings to PI\\\",\",\n \"repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) #\",\n \"pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue task and assert\",\n \"time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict()\",\n \"\\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"schedule_name\\\": \\\"OMF\",\n \"mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval']\",\n \"== args args, kwargs = log_info.call_args_list[0] assert \\\"Process started: Schedule '%s' process '%s'\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes = await\",\n \"scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id]\",\n \"9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')]\",\n \"mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN\",\n \"is not None assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert\",\n \"name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id,\",\n \"WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert\",\n \"('2 days', True), ('2 days 00:00:59', False), ('00:25:61', True) ]) async def test__get_schedules(self,\",\n \"done\\\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN scheduler\",\n \"'%s/%s' process '%s'\\\\n\\\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count\",\n \"schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0 # 0 for Interval Schedule assert\",\n \"== audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF to PI north', 'repeat': 30.0,\",\n \"pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now confirm no schedule is deleted assert\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task()))\",\n \"len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test\",\n \"scheduler.delete_schedule(sch_id) # THEN # Now confirm no schedule is deleted assert len(scheduler._storage_async.schedules) ==\",\n \"= await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task()))\",\n \"test__read_storage(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"False assert 2 == log_info.call_count calls = [call('No Task running for Schedule %s',\",\n \"@pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN task_id = uuid.uuid4() with pytest.raises(Exception) as\",\n \"}, { \\\"id\\\": \\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"COAP\\\", \\\"schedule_name\\\": \\\"COAP listener south\\\", \\\"schedule_type\\\": 1, \\\"schedule_interval\\\":\",\n \"\\\"North Readings to PI\\\", \\\"state\\\": 1, \\\"start_time\\\": \\\"2018-02-06 13:28:14.477868\\\", \\\"end_time\\\": \\\"2018-02-06 13:28:14.856375\\\", \\\"exit_code\\\":\",\n \"assert 0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1\",\n \"== log_info.call_count # assert call(\\\"Queued schedule '%s' for execution\\\", 'OMF to PI north')\",\n \"\\\"1\\\" ] }, { \\\"name\\\": \\\"North Readings to OCS\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\",\",\n \"pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port):\",\n \"GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler,\",\n \"time_before_call assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1]\",\n \"== len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN # Now delete schedule await scheduler.delete_schedule(sch_id)\",\n \"= uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \\\"No such Schedule\",\n \"assert 1 == queue_task.call_count calls = [call(\\\"Enabled Schedule '%s/%s' process '%s'\\\\n\\\", 'backup hourly',\",\n \"test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"in this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker):\",\n \"_rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage =\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes)\",\n \"1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL,\",\n \"mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\",\",\n \"THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self,\",\n \"= \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): #\",\n \"\\\"exception\\\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN #\",\n \"enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro():\",\n \"assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def test__check_purge_tasks(self,\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") new_schedules =\",\n \"# THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def\",\n \"True assert message == \\\"Schedule {} already disabled\\\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert\",\n \"used in 'await' expression\\\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler\",\n \"schedule_row) enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN\",\n \"THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"column\\\": \\\"start_time\\\", \\\"format\\\":\",\n \"# Now queue task and assert that the task has been queued await\",\n \"mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task\",\n \"is not None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def test_start(self, mocker):\",\n \"self.scheduler_fixture(mocker) # Assert that there is no task queued for schedule with pytest.raises(KeyError)\",\n \"# log_params = \\\"Queued schedule '%s' for execution\\\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async\",\n \"\\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } class MockStorageAsync(StorageClientAsync): schedules = [ { \\\"id\\\": \\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\":\",\n \"log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\\\"test_interval, is_exception\\\", [ ('\\\"Blah\\\" 0\",\n \"@pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio\",\n \"fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import *\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup queue_task = mocker.patch.object(scheduler,\",\n \"assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert call(\\\"Queued schedule '%s'\",\n \"\\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } @classmethod async def insert_into_tbl(cls, table_name, payload): pass @classmethod async\",\n \"WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time\",\n \"True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") random_schedule_id = uuid.uuid4() # WHEN await\",\n \"= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager,\",\n \"time_before_call = sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution,\",\n \"schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30),\",\n \"mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\")\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") schedule_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North schedule_row = scheduler._ScheduleRow(\",\n \"\\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task()))\",\n \"await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has\",\n \"scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker):\",\n \"} class MockStorageAsync(StorageClientAsync): schedules = [ { \\\"id\\\": \\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"purge\\\", \\\"schedule_name\\\": \\\"purge\\\",\",\n \"]) async def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler\",\n \"@classmethod async def update_tbl(cls, table_name, payload): # Only valid for test_save_schedule_update if table_name\",\n \"_rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None,\",\n \"len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING\",\n \"scheduler.get_task(task_id) # THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"format\\\":\",\n \"assert time_after_call > time_before_call assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1,\",\n \"# THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args)\",\n \"== Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is True assert schedule.enabled\",\n \"THEN assert status is True assert message == \\\"Schedule successfully enabled\\\" assert (scheduler._schedules[sch_id]).id\",\n \"repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\",\",\n \"assert scheduler._schedule_executions[schedule.id] is True # Now queue task and assert that the North\",\n \"None assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time is\",\n \"\\\"id\\\": uuid.uuid4(), \\\"name\\\": \\\"Fledge Storage\\\", \\\"type\\\": \\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\",\",\n \"\\\"info\\\") await scheduler._get_schedules() sch_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules')\",\n \"# THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \\\"Queued schedule '%s' for execution\\\",\",\n \"with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with\",\n \"calls = [call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\\\"Disabled Schedule '%s/%s' process\",\n \"# WHEN # Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN #\",\n \"task %s pid %s\\\\n%s\\\" in args assert 'OMF to PI north' in args\",\n \"PI\\\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion, sleep above,\",\n \"def test_queue_task(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"already enabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule,\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") schedule_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North schedule_row =\",\n \"@pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\\\"sleep\\\", \\\".1\\\") mock_task_process.schedule = mock_schedule mock_task_id =\",\n \"'_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") random_schedule_id = uuid.uuid4() # WHEN\",\n \"def query_tbl(cls, table_name, query=None): if table_name == 'schedules': return { \\\"count\\\": len(MockStorageAsync.schedules), \\\"rows\\\":\",\n \"of tasks that can be running at any given time\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\":\",\n \"async def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"= list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested\",\n \"[call(\\\"Enabled Schedule '%s/%s' process '%s'\\\\n\\\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1\",\n \"== len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF to\",\n \"async def update_tbl(cls, table_name, payload): # Only valid for test_save_schedule_update if table_name ==\",\n \"core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval\",\n \"== get_cat.call_count assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio\",\n \"# THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state is\",\n \"the target is an async function. if sys.version_info.major == 3 and sys.version_info.minor >=\",\n \"log_info.call_args_list[3] assert 'stats collection' in args0 assert 'COAP listener south' in args1 assert\",\n \"== len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id,\",\n \"assert status is True assert message == \\\"Schedule successfully disabled\\\" assert (scheduler._schedules[sch_id]).id ==\",\n \"assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type':\",\n \"WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 ==\",\n \"\\\"script\\\": [ \\\"tasks/purge\\\" ] }, { \\\"name\\\": \\\"stats collector\\\", \\\"script\\\": [ \\\"tasks/statistics\\\" ]\",\n \"to PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule,\",\n \"north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\\\"_scheduler_loop() not suitable for unit testing. Will be tested\",\n \"mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger,\",\n \"rows \\\" \\\"in the tasks table that do not have a status of\",\n \"= uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id)\",\n \"datetime.time') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time\",\n \"scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO: Mandatory -\",\n \"Readings to PI' in args args, kwargs = log_info.call_args_list[1] assert \\\"Stopping process: Schedule\",\n \"test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"= mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North\",\n \"assert scheduler._schedule_executions is None assert scheduler._task_processes is None assert scheduler._schedules is None assert\",\n \"== \\\"schedules\\\": return {\\\"count\\\": 1} @classmethod async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod\",\n \"scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info =\",\n \"scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count\",\n \"= \\\"<NAME>\\\" __copyright__ = \\\"Copyright (c) 2017 OSIsoft, LLC\\\" __license__ = \\\"Apache 2.0\\\"\",\n \"query_payload): if table_name == 'tasks': return { \\\"count\\\": len(MockStorageAsync.tasks), \\\"rows\\\": MockStorageAsync.tasks } @classmethod\",\n \"south' in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio async def\",\n \"for Interval Schedule assert schedule_row[4] is 0 # 0 for Interval Schedule assert\",\n \"resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self,\",\n \"00:00:40\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, ] scheduled_processes =\",\n \"# WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id\",\n \"table_name, payload): # Only valid for test_save_schedule_update if table_name == \\\"schedules\\\": return {\\\"count\\\":\",\n \"pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id) # THEN\",\n \"THEN # After task completion, sleep above, no task processes should be left\",\n \"THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule':\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception\",\n \"core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception())\",\n \"_rv = await get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler()\",\n \"0 # 0 for Interval Schedule assert schedule_row[4] is 0 # 0 for\",\n \"\\\"start_time\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"end_time\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"where\\\": {\\\"column\\\": \\\"id\\\",\",\n \"payload): # Only valid for test_save_schedule_update if table_name == \\\"schedules\\\": return {\\\"count\\\": 1}\",\n \"3600) # TODO: Remove after implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task()))\",\n \"'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN scheduler\",\n \"list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN\",\n \"('\\\"Blah\\\" 0 days', True), ('12:30:11', False), ('0 day 12:30:11', False), ('1 day 12:40:11',\",\n \"args, kwargs = log_info.call_args_list[0] assert \\\"Process started: Schedule '%s' process '%s' task %s\",\n \"@pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"\\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } class MockStorageAsync(StorageClientAsync): schedules\",\n \"[ \\\"tasks/purge\\\" ] }, { \\\"name\\\": \\\"stats collector\\\", \\\"script\\\": [ \\\"tasks/statistics\\\" ] },\",\n \"async def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"= uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30,\",\n \"any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8: patch() now returns\",\n \"isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type ==\",\n \"time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", current_time=current_time - 3600) #\",\n \"await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # purge schedule # WHEN schedule = await\",\n \"len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess',\",\n \"THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0]\",\n \"mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", current_time=current_time - 3600) # TODO: Remove after implementation of above\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules()\",\n \"== 'schedules': return { \\\"count\\\": len(MockStorageAsync.schedules), \\\"rows\\\": MockStorageAsync.schedules } if table_name == 'scheduled_processes':\",\n \"@classmethod async def insert_into_tbl(cls, table_name, payload): pass @classmethod async def update_tbl(cls, table_name, payload):\",\n \"asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False # WHEN # Check ELSE\",\n \"await scheduler._read_config() # THEN assert 1 == cr_cat.call_count assert 1 == get_cat.call_count assert\",\n \"pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN scheduler,\",\n \"to PI north' in args assert 'North Readings to PI' in args args,\",\n \"sys.version_info.minor >= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec',\",\n \"datetime import uuid import time import json from unittest.mock import MagicMock, call import\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings\",\n \"# -*- coding: utf-8 -*- # FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import\",\n \"scheduler._process_scripts is None assert scheduler._ready is False assert scheduler._paused is False assert scheduler._start_time\",\n \"async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count calls = [call(\\\"Enabled Schedule\",\n \"\\\"exception\\\") # WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed:\",\n \"query_tbl(cls, table_name, query=None): if table_name == 'schedules': return { \\\"count\\\": len(MockStorageAsync.schedules), \\\"rows\\\": MockStorageAsync.schedules\",\n \"'_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_scheduler_loop',\",\n \"== \\\"Schedule successfully enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True assert\",\n \"\\\"http\\\" } @classmethod async def insert_into_tbl(cls, table_name, payload): pass @classmethod async def update_tbl(cls,\",\n \"'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type':\",\n \"to PI North # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert\",\n \"_start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN retval = await scheduler.stop() # THEN\",\n \"scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be of type datetime.timedelta') with pytest.raises(ValueError) as\",\n \"9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } @classmethod async def insert_into_tbl(cls, table_name,\",\n \"assert time_after_call > time_before_call assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1,\",\n \"WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending\",\n \"True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task queued for this\",\n \"1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has not\",\n \"return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", current_time=current_time - 3600) # TODO: Remove after implementation of\",\n \"status, message = await scheduler.disable_schedule(sch_id) # THEN assert status is True assert message\",\n \"exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError) as ex: temp_schedule =\",\n \"PI north') == args args, kwargs = log_info.call_args_list[0] assert \\\"Process started: Schedule '%s'\",\n \"self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \\\"No\",\n \"assert schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0 #\",\n \"1 == queue_task.call_count calls = [call(\\\"Enabled Schedule '%s/%s' process '%s'\\\\n\\\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a',\",\n \"\\\"4\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, ] tasks = [ { \\\"id\\\": \\\"259b8570-65c1-4b92-8c62-e9642631a600\\\", \\\"process_name\\\":\",\n \"mocker): # Changed in version 3.8: patch() now returns an AsyncMock if the\",\n \"async def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"to PI north' in args assert 'North Readings to PI' in args @pytest.mark.asyncio\",\n \"task %s pid %s, %s running tasks\\\\n%s\\\" in args assert 'OMF to PI\",\n \"scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30,\",\n \"test__schedule_next_task(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage\",\n \"is None assert scheduler._task_processes is None assert scheduler._schedules is None assert scheduler._process_scripts is\",\n \"# THEN assert 1 == len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is\",\n \"test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task()))\",\n \"tasks = await scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is\",\n \"}, { \\\"id\\\": \\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\", \\\"process_name\\\": \\\"stats collector\\\", \\\"schedule_name\\\": \\\"stats collection\\\", \\\"schedule_type\\\": 2, \\\"schedule_interval\\\":\",\n \"# OMF to PI North # WHEN status, message = await scheduler.disable_schedule(sch_id) #\",\n \"log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN scheduler =\",\n \"== disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count\",\n \"PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\")\",\n \"\\\"schedules\\\": return {\\\"count\\\": 1} @classmethod async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async\",\n \"\\\"schedule_type\\\": 1, \\\"schedule_interval\\\": \\\"00:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" },\",\n \"enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro():\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN # THEN\",\n \"# Assert that there is no task queued for schedule with pytest.raises(KeyError) as\",\n \"OCS\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"4\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, ] tasks =\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task\",\n \"side_effect=Exception()) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as\",\n \"no task processes should be left pending assert 0 == len(scheduler._task_processes) assert 0\",\n \"# 0 for Interval Schedule assert schedule_row[4] is 0 # 0 for Interval\",\n \"assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count calls\",\n \"day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError)\",\n \"@pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm\",\n \"not None @pytest.mark.asyncio async def test_start(self, mocker): # TODO: Mandatory - Add negative\",\n \"del temp_schedule assert str(ex).endswith(\\\"name can not be empty\\\") with pytest.raises(ValueError) as ex: temp_schedule\",\n \"# THEN # After task completion, sleep above, no task processes should be\",\n \"'%s' for execution\\\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN\",\n \"there are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now delete\",\n \"\\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN\",\n \"scheduler._schedules is None assert scheduler._process_scripts is None assert scheduler._ready is False assert scheduler._paused\",\n \"\\\"tasks/backup_postgres\\\" ] }, { \\\"name\\\": \\\"COAP\\\", \\\"script\\\": [ \\\"services/south\\\" ] }, { \\\"name\\\":\",\n \"}, { \\\"name\\\": \\\"North Readings to PI\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"1\\\", \\\"--debug_level\\\",\",\n \"to PI north') == args args, kwargs = log_info.call_args_list[0] assert \\\"Process started: Schedule\",\n \"pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN scheduler,\",\n \"process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)\",\n \"# backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio\",\n \"Readings to PI\\\", name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True,\",\n \"\\\"start_time\\\", \\\"column\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"column\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"},\",\n \"\\\"00:00:15\\\", \\\"schedule_day\\\": 3, \\\"exclusive\\\": \\\"f\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\", \\\"process_name\\\": \\\"backup\\\",\",\n \"await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler,\",\n \"p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_get_tasks(self, mocker): #\",\n \"{'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0',\",\n \"mocker.patch.object(scheduler._logger, \\\"exception\\\") random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params =\",\n \"False) mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN with pytest.raises(NotReadyError) as excinfo: await\",\n \"True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1\",\n \"mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion')\",\n \"async def test__schedule_first_task(self, mocker): # TODO: Mandatory - Add negative tests for full\",\n \"(scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count calls = [call('No Task running for\",\n \"True assert schedule.process_name == \\\"purge\\\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN scheduler,\",\n \"await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params =\",\n \"assert task.reason is '' assert task.state is not None assert task.cancel_requested is None\",\n \"scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True,\",\n \"ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule)\",\n \"backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task\",\n \"mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message =\",\n \"{'name': 'OMF to PI north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True,\",\n \"] }, { \\\"name\\\": \\\"backup\\\", \\\"script\\\": [ \\\"tasks/backup_postgres\\\" ] }, { \\\"name\\\": \\\"COAP\\\",\",\n \"sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call\",\n \"time), for a rows \\\" \\\"in the tasks table that do not have\",\n \"north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO: Mandatory - Add\",\n \"'_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\")\",\n \"[call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day': 1,\",\n \"'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls = [call('SCHCH',\",\n \"log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN #\",\n \"7') @pytest.mark.asyncio @pytest.mark.skip(reason=\\\"To be done\\\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self,\",\n \"schedule await scheduler.delete_schedule(sch_id) # THEN # Now confirm there is one schedule less\",\n \"# WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) ==\",\n \"= scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess')\",\n \"schedule.name == \\\"purge\\\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert\",\n \"= MagicMock() m.pid = 9999 m.terminate = lambda: True return m @pytest.allure.feature(\\\"unit\\\") @pytest.allure.story(\\\"scheduler\\\")\",\n \"be running at any given time\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) },\",\n \"'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def\",\n \"1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat':\",\n \"# WHEN tasks = await scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name assert\",\n \"str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"@pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler,\",\n \"maximum age, in days (based on the start time), for a rows \\\"\",\n \"}, \\\"max_completed_task_age_days\\\": { \\\"description\\\": \\\"The maximum age, in days (based on the start\",\n \"unittest.mock import MagicMock, call import sys import copy import pytest from fledge.services.core.scheduler.scheduler import\",\n \"is None assert scheduler._process_scripts is None assert scheduler._ready is False assert scheduler._paused is\",\n \"been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8: patch()\",\n \"in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self,\",\n \"== len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management port\",\n \"= mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule\",\n \"disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow(\",\n \"await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await\",\n \"uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False,\",\n \"from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__\",\n \"def test__read_config(self, mocker): async def get_cat(): return { \\\"max_running_tasks\\\": { \\\"description\\\": \\\"The maximum\",\n \"THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def\",\n \"mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row =\",\n \"scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion, sleep above, no task processes should\",\n \"utf-8 -*- # FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime\",\n \"schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True,\",\n \"there is no task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id]\",\n \"pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError)\",\n \"Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async\",\n \"THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio\",\n \"repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN\",\n \"# THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD\",\n \"%s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"table that do not have a status of running\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS),\",\n \"scheduler._max_completed_task_age is None await scheduler._read_config() # THEN assert 1 == cr_cat.call_count assert 1\",\n \"self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo: tasks\",\n \"assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler:\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError)\",\n \"as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule\",\n \"Readings to PI' in args @pytest.mark.asyncio async def test__start_task(self, mocker): # TODO: Mandatory\",\n \"await scheduler.delete_schedule(sch_id) # THEN # Now confirm no schedule is deleted assert len(scheduler._storage_async.schedules)\",\n \"made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested\",\n \"return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN\",\n \"del temp_schedule assert str(ex).endswith('time must be of type datetime.time') with pytest.raises(ValueError) as ex:\",\n \"StorageClientAsync __author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright (c) 2017 OSIsoft, LLC\\\" __license__ =\",\n \"* from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright (c) 2017\",\n \"} @classmethod async def insert_into_tbl(cls, table_name, payload): pass @classmethod async def update_tbl(cls, table_name,\",\n \"await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio\",\n \"await scheduler.disable_schedule(sch_id) # THEN assert status is True assert message == \\\"Schedule successfully\",\n \"= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro())\",\n \"with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async\",\n \"self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules)\",\n \"core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert\",\n \"is not None assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1\",\n \"== schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has not been made assert\",\n \"assert 0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert\",\n \"assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert schedule.name == \\\"purge\\\" assert schedule.schedule_type\",\n \"Scheduler: Management port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command:\",\n \"= scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds)\",\n \"OCS\\\", \\\"schedule_name\\\": \\\"OMF to OCS north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"1 day 00:00:40\\\", \\\"schedule_time\\\":\",\n \"to PI north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \\\"Process started: Schedule\",\n \"1, \\\"schedule_interval\\\": \\\"00:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, {\",\n \"assert 'Query failed: %s' == args[0] p = json.loads(args[1]) assert payload == p\",\n \"schedule.process_name == \\\"purge\\\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"days 00:00:59', False), ('00:25:61', True) ]) async def test__get_schedules(self, test_interval, is_exception, mocker): #\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # purge schedule # WHEN\",\n \"\\\"description\\\": \\\"The maximum age, in days (based on the start time), for a\",\n \"self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN\",\n \"args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup await scheduler._get_schedules() #\",\n \"'%s' for execution\\\", 'OMF to PI north') == args args, kwargs = log_info.call_args_list[0]\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() # THEN assert\",\n \"= \\\"Schedule %s already enabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): #\",\n \"# THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker):\",\n \"test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN payload =\",\n \"\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\", \\\"process_name\\\": \\\"backup\\\", \\\"schedule_name\\\": \\\"backup hourly\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\":\",\n \"that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN\",\n \"exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule,\",\n \"@pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"await scheduler.disable_schedule(sch_id) # THEN assert status is True assert message == \\\"Schedule {}\",\n \"is no task queued for this schedule at first with pytest.raises(KeyError) as excinfo:\",\n \"PI\\\", name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler,\",\n \"return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler,\",\n \"code coverage # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"= mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") # WHEN # THEN with\",\n \"PI north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO: Mandatory -\",\n \"Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2]\",\n \"\\\"id\\\": \\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\", \\\"process_name\\\": \\\"stats collector\\\", \\\"schedule_name\\\": \\\"stats collection\\\", \\\"schedule_type\\\": 2, \\\"schedule_interval\\\": \\\"00:00:15\\\", \\\"schedule_time\\\":\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mock_schedules = dict() mock_schedule =\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") new_schedules\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") #\",\n \"scheduler._check_schedules() # THEN assert earliest_start_time is not None assert 3 == log_info.call_count args0,\",\n \"Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess',\",\n \"scheduler._ScheduleExecution) # Changed in version 3.8: patch() now returns an AsyncMock if the\",\n \"'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio\",\n \"kwargs2 = log_info.call_args_list[2] assert 'stats collection' in args0 assert 'COAP listener south' in\",\n \"json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN scheduler,\",\n \"is_exception\\\", [ ('\\\"Blah\\\" 0 days', True), ('12:30:11', False), ('0 day 12:30:11', False), ('1\",\n \"now returns an AsyncMock if the target is an async function. if sys.version_info.major\",\n \"== schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is\",\n \"not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN\",\n \"0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\", \\\"process_name\\\": \\\"North Readings to\",\n \"OSIsoft, LLC\\\" __license__ = \\\"Apache 2.0\\\" __version__ = \\\"${VERSION}\\\" async def mock_task(): return\",\n \"{\\\"alias\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"end_time\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"where\\\": {\\\"column\\\": \\\"id\\\", \\\"condition\\\":\",\n \"why these exceptions are being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An\",\n \"THEN if is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count\",\n \"'_ready', True) # WHEN # Now delete schedule await scheduler.delete_schedule(sch_id) # THEN #\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time =\",\n \"schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True,\",\n \"be done\\\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN\",\n \"'OMF to PI north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName':\",\n \"mocker.patch.object(scheduler, '_ready', True) # Confirm there are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)\",\n \"mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler,\",\n \"scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert\",\n \"@pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO: Mandatory - Add negative tests for\",\n \"log_info.call_args_list[0] assert 'OMF to PI north' in args assert 'North Readings to PI'\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True)\",\n \"to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger,\",\n \"0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be between\",\n \"%s running tasks\\\\n%s\\\" in args assert 'OMF to PI north' in args assert\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN\",\n \"def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"maximum number of tasks that can be running at any given time\\\", \\\"type\\\":\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\")\",\n \"uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4())\",\n \"THEN assert time_after_call > time_before_call assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0]\",\n \"as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time() await\",\n \"assert schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert\",\n \"assert \\\"Stopping process: Schedule '%s' process '%s' task %s pid %s\\\\n%s\\\" in args\",\n \"args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO: Mandatory - Add negative tests\",\n \"len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"return m @pytest.allure.feature(\\\"unit\\\") @pytest.allure.story(\\\"scheduler\\\") class TestScheduler: async def scheduler_fixture(self, mocker): # Changed in\",\n \"time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 4 == log_info.call_count\",\n \"THEN assert status is True assert message == \\\"Schedule successfully disabled\\\" assert (scheduler._schedules[sch_id]).id\",\n \"None # WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert\",\n \"given time\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \\\"max_completed_task_age_days\\\": { \\\"description\\\": \\\"The\",\n \"an enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker):\",\n \"#Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there are 14 schedules assert\",\n \"'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\")\",\n \"\\\"<NAME>\\\" __copyright__ = \\\"Copyright (c) 2017 OSIsoft, LLC\\\" __license__ = \\\"Apache 2.0\\\" __version__\",\n \"assert message == \\\"Schedule {} already disabled\\\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled\",\n \"# WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \\\"Queued\",\n \"THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler\",\n \"assert task.start_time is not None assert task.end_time is not None assert task.exit_code is\",\n \"scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 == log_info.call_count # args, kwargs = log_info.call_args_list[0]\",\n \"with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with\",\n \"\\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\":\",\n \"def test_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for full code\",\n \"mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"}, ] scheduled_processes = [ { \\\"name\\\": \\\"purge\\\", \\\"script\\\": [ \\\"tasks/purge\\\" ] },\",\n \"3 and sys.version_info.minor >= 8: _rv = await get_cat() else: _rv = asyncio.ensure_future(get_cat())\",\n \"mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict()\",\n \"3 and sys.version_info.minor >= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process())\",\n \"args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection' in args0 assert 'COAP listener south'\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError) as\",\n \"# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready',\",\n \"'_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler,\",\n \"log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection' in\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler,\",\n \"Assert that there is no task queued for schedule with pytest.raises(KeyError) as excinfo:\",\n \"scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 == log_info.call_count #\",\n \"str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)\",\n \"== disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" #\",\n \"time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count\",\n \"return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time()\",\n \"[ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"4\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, ] tasks = [ {\",\n \"= sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert time_after_call >\",\n \"sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time #\",\n \"\\\"00:00:15\\\", \\\"schedule_time\\\": \\\"00:00:15\\\", \\\"schedule_day\\\": 3, \\\"exclusive\\\": \\\"f\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\",\",\n \"is not None assert tasks[0].end_time is not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio\",\n \"= await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"await scheduler._get_schedules() assert 1 == log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)\",\n \"not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN\",\n \"datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call\",\n \"current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", current_time=current_time -\",\n \"await get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"Confirm there are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now\",\n \"of running\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in\",\n \"assert 1 == log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async\",\n \"payload == p @pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"== len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks() # THEN assert 1\",\n \"@pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"not None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def test_start(self, mocker): #\",\n \"is no task queued for mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is\",\n \"for execution\\\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler\",\n \"kwargs = log_info.call_args_list[0] # assert (\\\"Queued schedule '%s' for execution\\\", 'OMF to PI\",\n \"else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): #\",\n \"PI\\\", \\\"state\\\": 1, \\\"start_time\\\": \\\"2018-02-06 13:28:14.477868\\\", \\\"end_time\\\": \\\"2018-02-06 13:28:14.856375\\\", \\\"exit_code\\\": \\\"0\\\", \\\"reason\\\": \\\"\\\"\",\n \"such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN scheduler\",\n \"list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name\",\n \"str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \\\"max_completed_task_age_days\\\": { \\\"description\\\": \\\"The maximum age, in days (based on the\",\n \"async def test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"# Only valid for test_save_schedule_update if table_name == \\\"schedules\\\": return {\\\"count\\\": 1} @classmethod\",\n \"'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True)\",\n \"\\\"name\\\": \\\"Fledge Storage\\\", \\\"type\\\": \\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\"\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # purge schedule #\",\n \"# WHEN with pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks() # THEN payload\",\n \"await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert schedule.name\",\n \"scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there are 14 schedules assert len(scheduler._storage_async.schedules) ==\",\n \"message == \\\"Schedule successfully disabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False\",\n \"False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio\",\n \"= scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call =\",\n \"# THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\\\"_mark_tasks_interrupted() not\",\n \"'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert\",\n \"{ \\\"name\\\": \\\"backup\\\", \\\"script\\\": [ \\\"tasks/backup_postgres\\\" ] }, { \\\"name\\\": \\\"COAP\\\", \\\"script\\\": [\",\n \"log_debug = await self.scheduler_fixture(mocker) # Assert that there is no task queued for\",\n \"in args0 assert 'COAP listener south' in args1 assert 'OMF to PI north'\",\n \"\\\"id\\\": \\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"COAP\\\", \\\"schedule_name\\\": \\\"COAP listener south\\\", \\\"schedule_type\\\": 1, \\\"schedule_interval\\\": \\\"00:00:00\\\", \\\"schedule_time\\\":\",\n \"= await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call\",\n \"== first_task.call_count assert 1 == resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 ==\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to\",\n \"collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call =\",\n \"def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no task has\",\n \"is not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): #\",\n \"in version 3.8: patch() now returns an AsyncMock if the target is an\",\n \"1 == get_cat.call_count assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is not None\",\n \"THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): #\",\n \"tasks[0].start_time is not None assert tasks[0].end_time is None assert tasks[0].exit_code is None @pytest.mark.asyncio\",\n \"}, { \\\"name\\\": \\\"backup\\\", \\\"script\\\": [ \\\"tasks/backup_postgres\\\" ] }, { \\\"name\\\": \\\"COAP\\\", \\\"script\\\":\",\n \"this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): #\",\n \"len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\\\"_mark_tasks_interrupted() not implemented in main Scheduler class.\\\")\",\n \"test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow(\",\n \"is True # WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with\",\n \"disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN\",\n \"} # Changed in version 3.8: patch() now returns an AsyncMock if the\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo:\",\n \"async def test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"tasks[0].start_time is not None assert tasks[0].end_time is not None assert tasks[0].exit_code is '0'\",\n \"message = await scheduler.disable_schedule(sch_id) # THEN assert status is True assert message ==\",\n \"0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine\",\n \"enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count\",\n \"async def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"\\\"object MagicMock can't be used in 'await' expression\\\"), call('An exception was raised by\",\n \"scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert\",\n \"datetime.timedelta(0, 3600) assert schedule.exclusive is True assert schedule.enabled is True assert schedule.process_name ==\",\n \"async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"'_schedule_first_task', side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query\",\n \"# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North # WHEN status,\",\n \"'North Readings to PI' in args args, kwargs = log_info.call_args_list[1] assert \\\"Stopping process:\",\n \"args args, kwargs = log_info.call_args_list[0] assert \\\"Process started: Schedule '%s' process '%s' task\",\n \"\\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\", \\\"process_name\\\": \\\"North Readings to PI\\\",\",\n \"log_info.call_count # args, kwargs = log_info.call_args_list[0] # assert (\\\"Queued schedule '%s' for execution\\\",\",\n \"# WHEN # THEN if is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules() assert\",\n \"AsyncMock if the target is an async function. if sys.version_info.major == 3 and\",\n \"len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks() # THEN assert 1 == len(tasks)\",\n \"id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN\",\n \"#Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN\",\n \"to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\\\"_scheduler_loop() not suitable for unit testing. Will\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN\",\n \"is not None assert task.end_time is not None assert task.exit_code is '0' @pytest.mark.skip(\\\"Need\",\n \"WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)\",\n \"\\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \\\"max_completed_task_age_days\\\": { \\\"description\\\": \\\"The maximum age, in\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there is no North\",\n \"with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with\",\n \"is True assert 1 == queue_task.call_count calls = [call(\\\"Enabled Schedule '%s/%s' process '%s'\\\\n\\\",\",\n \"9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } class MockStorageAsync(StorageClientAsync): schedules = [\",\n \"is True assert message == \\\"Schedule successfully disabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert\",\n \"collection' in args0 assert 'COAP listener south' in args1 assert 'OMF to PI\",\n \"True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker):\",\n \"in this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker):\",\n \"\\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version 3.8: patch()\",\n \"assert 1 == log_exception.call_count log_params = 'Attempt to delete an enabled Schedule %s.\",\n \"any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() #\",\n \"'_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", _start_time=current_time - 3600, _paused=False, _task_processes={})\",\n \"\\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, { \\\"id\\\": \\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"COAP\\\", \\\"schedule_name\\\":\",\n \"by Scheduler._purge_tasks %s', \\\"object MagicMock can't be used in 'await' expression\\\"), call('An exception\",\n \"'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI\",\n \"scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) #\",\n \"None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests\",\n \"Scheduler class.\\\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker): async\",\n \"scheduler.delete_schedule(sch_id) # THEN # Now confirm there is one schedule less assert len(scheduler._storage_async.schedules)\",\n \"pid %s\\\\n%s\\\" in args assert 'OMF to PI north' in args assert 'North\",\n \"== args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self,\",\n \"# Now confirm there is one schedule less assert len(scheduler._storage_async.schedules) - 1 ==\",\n \"to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler =\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") await scheduler._get_schedules() sch_id\",\n \"'0' @pytest.mark.skip(\\\"Need a suitable fixture\\\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN scheduler,\",\n \"excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo:\",\n \"assert payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule,\",\n \"one schedule less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self,\",\n \"Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client\",\n \"\\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\", \\\"process_name\\\":\",\n \"- 3600, _paused=False, _task_processes={}) # WHEN retval = await scheduler.stop() # THEN assert\",\n \"scheduler._check_processes_pending is False # WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules()\",\n \"excinfo: tasks = await scheduler.get_tasks() # THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\",\",\n \"async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker): async def get_cat():\",\n \"def test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"THEN # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1\",\n \"task queued for this schedule at first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id]\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() #\",\n \"host, port): return { \\\"id\\\": uuid.uuid4(), \\\"name\\\": \\\"Fledge Storage\\\", \\\"type\\\": \\\"Storage\\\", \\\"service_port\\\": 9999,\",\n \"log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4())\",\n \"\\\"schedule_name\\\": \\\"stats collection\\\", \\\"schedule_type\\\": 2, \\\"schedule_interval\\\": \\\"00:00:15\\\", \\\"schedule_time\\\": \\\"00:00:15\\\", \\\"schedule_day\\\": 3, \\\"exclusive\\\": \\\"f\\\",\",\n \"enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule)\",\n \"def mock_task(): return \\\"\\\" async def mock_process(): m = MagicMock() m.pid = 9999\",\n \"args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection' in args0\",\n \"yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task has started\",\n \"exception was raised by Scheduler._purge_tasks %s', \\\"object MagicMock can't be used in 'await'\",\n \"as excinfo: tasks = await scheduler.get_tasks() # THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\",\",\n \"time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") log_error = mocker.patch.object(scheduler._logger, \\\"error\\\") log_debug\",\n \"mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts',\",\n \"async def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"await scheduler._start_task(schedule) # THEN # Confirm that task has started assert 1 ==\",\n \"async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN scheduler =\",\n \"\\\"f\\\" }, ] scheduled_processes = [ { \\\"name\\\": \\\"purge\\\", \\\"script\\\": [ \\\"tasks/purge\\\" ]\",\n \"schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be of\",\n \"def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule, log_info,\",\n \"WHEN # THEN with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name =\",\n \"mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo:\",\n \"no schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count log_params\",\n \"that the North task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) #\",\n \"assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type\",\n \"valid for test_save_schedule_update if table_name == \\\"schedules\\\": return {\\\"count\\\": 1} @classmethod async def\",\n \"After task completion, sleep above, no task processes should be left pending assert\",\n \"log_info.call_args_list[2] assert 'stats collection' in args0 assert 'COAP listener south' in args1 assert\",\n \"mocker.patch.object(ConfigurationManager, \\\"get_category_all_items\\\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None\",\n \"\\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\", \\\"process_name\\\": \\\"North Readings to OCS\\\",\",\n \"@pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"mocker.patch.object(scheduler._logger, \\\"error\\\") log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") return scheduler, schedule,\",\n \"test_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage\",\n \"await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can not be empty\\\") with pytest.raises(ValueError) as\",\n \"await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker):\",\n \"running\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version\",\n \"can not be empty\\\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat\",\n \"temp_schedule assert str(ex).endswith('repeat must be of type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule\",\n \"scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker):\",\n \"ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert\",\n \"log_debug = await self.scheduler_fixture(mocker) # Assert that there is no North task queued\",\n \"{\\\"alias\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"start_time\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\":\",\n \"with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with\",\n \"process '%s'\\\\n\\\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert\",\n \"day 12:30:11', False), ('1 day 12:40:11', False), ('2 days', True), ('2 days 00:00:59',\",\n \"True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task queued for mock_schedule\",\n \"\\\"info\\\") enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) schedule_id =\",\n \"('0 day 12:30:11', False), ('1 day 12:40:11', False), ('2 days', True), ('2 days\",\n \"is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler,\",\n \"\\\"schedule_interval\\\": \\\"00:00:15\\\", \\\"schedule_time\\\": \\\"00:00:15\\\", \\\"schedule_day\\\": 3, \\\"exclusive\\\": \\\"f\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\":\",\n \"mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") await scheduler._get_schedules() sch_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") #\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\")\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10,\",\n \"= 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\\\"test_interval, is_exception\\\", [ ('\\\"Blah\\\" 0 days',\",\n \"= test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN if is_exception is True:\",\n \"excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo:\",\n \"time\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \\\"max_completed_task_age_days\\\": { \\\"description\\\": \\\"The maximum\",\n \"task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that no\",\n \"Storage\\\", \\\"type\\\": \\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } class\",\n \"{ \\\"count\\\": len(MockStorageAsync.tasks), \\\"rows\\\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name, query=None): if\",\n \"%s, %s running tasks\\\\n%s\\\" in args assert 'OMF to PI north' in args\",\n \"\\\"max_running_tasks\\\": { \\\"description\\\": \\\"The maximum number of tasks that can be running at\",\n \"schedule_id = uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id)\",\n \"\\\"\\\" # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) audit_logger\",\n \"# WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple())\",\n \"assert (scheduler._schedules[sch_id]).enabled is True log_params = \\\"Schedule %s already enabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio\",\n \"calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled':\",\n \"1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks() #\",\n \"= scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call\",\n \"def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO: Mandatory\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) #\",\n \"temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be of type\",\n \"status of running\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed\",\n \"scheduler._start_task(schedule) # THEN # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes)\",\n \"9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } class MockStorageAsync(StorageClientAsync): schedules = [ { \\\"id\\\":\",\n \"log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") #\",\n \"def _get_storage_service(self, host, port): return { \\\"id\\\": uuid.uuid4(), \\\"name\\\": \\\"Fledge Storage\\\", \\\"type\\\": \\\"Storage\\\",\",\n \"mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN # THEN with\",\n \"with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with\",\n \"= \\\"Copyright (c) 2017 OSIsoft, LLC\\\" __license__ = \\\"Apache 2.0\\\" __version__ = \\\"${VERSION}\\\"\",\n \"= uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution =\",\n \"calls = [call('Database command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio\",\n \"THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler\",\n \"scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker):\",\n \"PI' in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO: Mandatory - Add\",\n \"\\\"00:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\",\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF part mocker.patch.object(scheduler,\",\n \"north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") log_error\",\n \"pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del\",\n \"args, kwargs = log_info.call_args_list[0] assert 'OMF to PI north' in args assert 'North\",\n \"= \\\"Schedule %s already disabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): #\",\n \"== task.process_name assert task.reason is '' assert task.state is not None assert task.cancel_requested\",\n \"disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test\",\n \"function. if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await mock_process()\",\n \"dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF to PI north\\\",\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() #\",\n \"empty\\\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap mocker.patch.object(scheduler,\",\n \"= await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks =\",\n \"type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') #\",\n \"'_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False # WHEN # Check\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") log_exception\",\n \"LLC\\\" __license__ = \\\"Apache 2.0\\\" __version__ = \\\"${VERSION}\\\" async def mock_task(): return \\\"\\\"\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \\\"create_category\\\", return_value=asyncio.ensure_future(mock_task())) get_cat =\",\n \"asyncio import datetime import uuid import time import json from unittest.mock import MagicMock,\",\n \"sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count calls = [call('No Task\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler,\",\n \"scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be of type datetime.time') with pytest.raises(ValueError) as\",\n \"= await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN task_id\",\n \"'stats collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO: Mandatory -\",\n \"await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await\",\n \"return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1\",\n \"WHEN # THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo:\",\n \"await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo:\",\n \"\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\", \\\"process_name\\\": \\\"stats collector\\\", \\\"schedule_name\\\": \\\"stats collection\\\", \\\"schedule_type\\\": 2, \\\"schedule_interval\\\": \\\"00:00:15\\\", \\\"schedule_time\\\": \\\"00:00:15\\\",\",\n \"# Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is\",\n \"\\\"COAP\\\", \\\"script\\\": [ \\\"services/south\\\" ] }, { \\\"name\\\": \\\"North Readings to PI\\\", \\\"script\\\":\",\n \"core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async\",\n \"2 == log_info.call_count calls = [call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\\\"Disabled\",\n \"and assert that the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution)\",\n \"THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler\",\n \"list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO:\",\n \"# THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN\",\n \"\\\"Copyright (c) 2017 OSIsoft, LLC\\\" __license__ = \\\"Apache 2.0\\\" __version__ = \\\"${VERSION}\\\" async\",\n \"name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception =\",\n \"WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1\",\n \"ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert\",\n \"== sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params = \\\"Schedule %s already disabled\\\", str(sch_id)\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup queue_task =\",\n \"schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30),\",\n \"= await self.scheduler_fixture(mocker) # Assert that there is no task queued for schedule\",\n \"{\\\"column\\\": \\\"id\\\", \\\"condition\\\": \\\"=\\\", \\\"value\\\": str(task_id)}} args, kwargs = log_exception.call_args assert 'Query failed:\",\n \"{ \\\"id\\\": uuid.uuid4(), \\\"name\\\": \\\"Fledge Storage\\\", \\\"type\\\": \\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\":\",\n \"'_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"),\",\n \"len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"\\\"condition\\\": \\\"=\\\", \\\"value\\\": str(task_id)}} args, kwargs = log_exception.call_args assert 'Query failed: %s' ==\",\n \"test.\\\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None):\",\n \"earliest_start_time = await scheduler._check_schedules() # THEN assert earliest_start_time is not None assert 3\",\n \"'OMF to PI north' in args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task() also\",\n \"assert tasks[0].end_time is None assert tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self, mocker):\",\n \"assert 1 == len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is None assert\",\n \"scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time\",\n \"# THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker):\",\n \"def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule, log_info,\",\n \"}, { \\\"id\\\": \\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\", \\\"process_name\\\": \\\"North Readings to OCS\\\", \\\"schedule_name\\\": \\\"OMF to OCS\",\n \"await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion, sleep above, no task processes\",\n \"deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count log_params = 'Attempt to\",\n \"successfully enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1 ==\",\n \"\\\"value\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version 3.8: patch() now returns an\",\n \"13:28:14.856375\\\", \\\"exit_code\\\": \\\"0\\\", \\\"reason\\\": \\\"\\\" } ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port)\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") return scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async\",\n \"# backup # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert status\",\n \"test__schedule_first_task(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage\",\n \"scheduler._start_task(schedule) # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id =\",\n \"\\\"\\\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can not be empty\\\") with pytest.raises(ValueError)\",\n \"args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"= asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North\",\n \"# THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN\",\n \"# THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def test__check_schedules(self, mocker): #\",\n \"\\\"info\\\") schedule_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id,\",\n \"'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to PI'}})]\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts)\",\n \"status is True assert message == \\\"Schedule successfully enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id\",\n \"\\\"schedule_name\\\": \\\"OMF to OCS north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"1 day 00:00:40\\\", \\\"schedule_time\\\": \\\"\\\",\",\n \"MagicMock() m.pid = 9999 m.terminate = lambda: True return m @pytest.allure.feature(\\\"unit\\\") @pytest.allure.story(\\\"scheduler\\\") class\",\n \"must be of type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)\",\n \"\\\"protocol\\\": \\\"http\\\" } @classmethod async def insert_into_tbl(cls, table_name, payload): pass @classmethod async def\",\n \"\\\"stats collector\\\", \\\"script\\\": [ \\\"tasks/statistics\\\" ] }, { \\\"name\\\": \\\"backup\\\", \\\"script\\\": [ \\\"tasks/backup_postgres\\\"\",\n \"import StorageClientAsync __author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright (c) 2017 OSIsoft, LLC\\\" __license__\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False)\",\n \"%d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s', 'scheduled_processes'), call('Database command: %s',\",\n \"schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules)\",\n \"None assert tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN scheduler,\",\n \"\\\"reason\\\", \\\"exit_code\\\"], \\\"limit\\\": 100} args, kwargs = log_exception.call_args assert 'Query failed: %s' ==\",\n \"@pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4()\",\n \"north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"1 day 00:00:40\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\",\",\n \"False assert scheduler._paused is False assert scheduler._start_time is None calls = [call('Processing stop\",\n \"Assert that there is no task queued for this schedule at first with\",\n \"assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is\",\n \"MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return {\",\n \"== len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks() # THEN assert 1 ==\",\n \"test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"COAP\\\", \\\"schedule_name\\\": \\\"COAP listener south\\\", \\\"schedule_type\\\": 1, \\\"schedule_interval\\\": \\\"00:00:00\\\", \\\"schedule_time\\\": \\\"\\\",\",\n \"current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN\",\n \"north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to\",\n \"assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls\",\n \"def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"# backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no\",\n \"\\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\", \\\"process_name\\\": \\\"stats collector\\\", \\\"schedule_name\\\": \\\"stats collection\\\", \\\"schedule_type\\\":\",\n \"current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id =\",\n \"async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule,\",\n \"is None calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find\",\n \"excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN scheduler,\",\n \"{ \\\"name\\\": \\\"COAP\\\", \\\"script\\\": [ \\\"services/south\\\" ] }, { \\\"name\\\": \\\"North Readings to\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks',\",\n \"listener south' in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio async\",\n \"= scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN\",\n \"type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") log_error =\",\n \"kwargs3 = log_info.call_args_list[3] assert 'stats collection' in args0 assert 'COAP listener south' in\",\n \"also gets executed, hence # \\\"stat collector\\\" appears twice in this list. assert\",\n \"'_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") # WHEN\",\n \"scheduler._ready is False # WHEN await scheduler.start() # THEN assert scheduler._ready is True\",\n \"\\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow(\",\n \"'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): #\",\n \"uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \\\"No such Schedule %s\\\",\",\n \"2 == log_info.call_count # args, kwargs = log_info.call_args_list[0] # assert (\\\"Queued schedule '%s'\",\n \"with pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker):\",\n \"{ \\\"count\\\": len(MockStorageAsync.schedules), \\\"rows\\\": MockStorageAsync.schedules } if table_name == 'scheduled_processes': return { \\\"count\\\":\",\n \"self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN task_id = uuid.uuid4()\",\n \"\\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"1\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, { \\\"name\\\": \\\"North Readings\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info\",\n \"\\\"process_name\\\": \\\"purge\\\", \\\"schedule_name\\\": \\\"purge\\\", \\\"schedule_type\\\": 4, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\":\",\n \"port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s', 'scheduled_processes'),\",\n \"return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await\",\n \"self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there\",\n \"== len(scheduler._schedules) # WHEN # Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) #\",\n \"mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start()\",\n \"(scheduler._schedules[sch_id]).enabled is False log_params = \\\"Schedule %s already disabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async\",\n \"del temp_schedule assert str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError) as ex: temp_schedule\",\n \"await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1\",\n \"less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): #\",\n \"= await scheduler.enable_schedule(sch_id) # THEN assert status is True assert message == \\\"Schedule\",\n \"stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN\",\n \"resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self,\",\n \"assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is True assert schedule.enabled is True\",\n \"that task has not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await\",\n \"'%s' task %s pid %s\\\\n%s\\\" in args assert 'OMF to PI north' in\",\n \"is_exception, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler,\",\n \"= uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await\",\n \"for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue\",\n \"assert str(ex).endswith('repeat must be of type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule =\",\n \"== audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat':\",\n \"\\\"info\\\") log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task',\",\n \"mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task queued for mock_schedule with\",\n \"mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args =\",\n \"sys import copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities\",\n \"failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN scheduler =\",\n \"mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert\",\n \"test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"Scheduler._purge_tasks %s', \\\"object MagicMock can't be used in 'await' expression\\\"), call('An exception was\",\n \"== audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup',\",\n \"@pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"assert task.end_time is not None assert task.exit_code is '0' @pytest.mark.skip(\\\"Need a suitable fixture\\\")\",\n \"scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be\",\n \"1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\\\"To be done\\\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async\",\n \"scheduler.enable_schedule(random_schedule_id) # THEN log_params = \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async\",\n \"in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\\\"_scheduler_loop() not suitable\",\n \"query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks': return { \\\"count\\\": len(MockStorageAsync.tasks), \\\"rows\\\": MockStorageAsync.tasks\",\n \"sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await mock_process() else: _rv\",\n \"await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \\\"Queued schedule '%s'\",\n \"WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id ==\",\n \"\\\"exception\\\") log_error = mocker.patch.object(scheduler._logger, \\\"error\\\") log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\")\",\n \"= mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") return scheduler, schedule, log_info, log_exception, log_error,\",\n \"@pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"WHEN task = await scheduler.get_task(task_id) # THEN assert schedule.process_name == task.process_name assert task.reason\",\n \"as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule\",\n \"log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks\",\n \"scheduler.disable_schedule(random_schedule_id) # THEN log_params = \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async\",\n \"is not None @pytest.mark.asyncio async def test_start(self, mocker): # TODO: Mandatory - Add\",\n \"not None assert task.cancel_requested is None assert task.start_time is not None assert task.end_time\",\n \"get_cat.call_count assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async\",\n \"with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id) #\",\n \"str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"_last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not\",\n \"@classmethod async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload):\",\n \"'%s' process '%s' task %s pid %s\\\\n%s\\\" in args assert 'OMF to PI\",\n \"'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks() #\",\n \"scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False # WHEN # Check ELSE part\",\n \"0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, ] scheduled_processes = [ { \\\"name\\\": \\\"purge\\\",\",\n \"\\\"tasks/north\\\", \\\"--stream_id\\\", \\\"4\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, ] tasks = [ { \\\"id\\\":\",\n \"await self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) ==\",\n \"not be None') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time =\",\n \"_schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") # WHEN await scheduler._wait_for_task_completion(mock_task_process)\",\n \"assert 1 == resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio\",\n \"scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None await scheduler._read_config() # THEN assert 1\",\n \"# THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async\",\n \"'_paused', True) # WHEN # THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with\",\n \"\\\"name\\\": \\\"backup\\\", \\\"script\\\": [ \\\"tasks/backup_postgres\\\" ] }, { \\\"name\\\": \\\"COAP\\\", \\\"script\\\": [ \\\"services/south\\\"\",\n \"PI' in args args, kwargs = log_info.call_args_list[1] assert \\\"Stopping process: Schedule '%s' process\",\n \"def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker): async def get_cat(): return\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") await scheduler._get_schedules()\",\n \"time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there\",\n \"scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker):\",\n \"north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules')\",\n \"schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"\\\"North Readings to OCS\\\", \\\"schedule_name\\\": \\\"OMF to OCS north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"1\",\n \"scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state\",\n \"\\\"2018-02-06 13:28:14.477868\\\", \\\"end_time\\\": \\\"2018-02-06 13:28:14.856375\\\", \\\"exit_code\\\": \\\"0\\\", \\\"reason\\\": \\\"\\\" } ] def __init__(self,\",\n \"is not None assert 2 == log_info.call_count # args, kwargs = log_info.call_args_list[0] #\",\n \"# THEN assert retval is True assert scheduler._schedule_executions is None assert scheduler._task_processes is\",\n \"\\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, ] scheduled_processes = [ {\",\n \"assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF to PI north',\",\n \"GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN #\",\n \"that cancel request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN\",\n \"assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN scheduler, schedule,\",\n \"\\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"end_time\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"where\\\": {\\\"column\\\": \\\"id\\\", \\\"condition\\\": \\\"=\\\", \\\"value\\\":\",\n \"if table_name == \\\"schedules\\\": return {\\\"count\\\": 1} @classmethod async def delete_from_tbl(cls, table_name, condition=None):\",\n \"{ \\\"id\\\": \\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"purge\\\", \\\"schedule_name\\\": \\\"purge\\\", \\\"schedule_type\\\": 4, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\",\",\n \"== resume_sch.call_count assert 1 == enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN await\",\n \"PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\\\"_scheduler_loop() not suitable for unit testing. Will be\",\n \"schedule at first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN\",\n \"datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN assert\",\n \"args assert 'North Readings to PI' in args args, kwargs = log_info.call_args_list[1] assert\",\n \"scheduler._schedule_first_task() also gets executed, hence # \\\"stat collector\\\" appears twice in this list.\",\n \"test_interval, is_exception, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler,\",\n \"\\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"start_time\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"end_time\\\"},\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler,\",\n \"Schedule) assert schedule.schedule_id == schedule_id assert schedule.name == \\\"purge\\\" assert schedule.schedule_type == Schedule.Type.MANUAL\",\n \"# WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed: %s',\",\n \"len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"assert scheduler._check_processes_pending is False # WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None)\",\n \"Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has not started yet\",\n \"started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") await scheduler._get_schedules() sch_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # backup mocker.patch.object(scheduler, '_ready', True)\",\n \"assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600) assert schedule.exclusive is True\",\n \"[ { \\\"id\\\": \\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"purge\\\", \\\"schedule_name\\\": \\\"purge\\\", \\\"schedule_type\\\": 4, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\":\",\n \"insert_into_tbl(cls, table_name, payload): pass @classmethod async def update_tbl(cls, table_name, payload): # Only valid\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") # WHEN\",\n \"hence # \\\"stat collector\\\" appears twice in this list. assert 'stats collection' in\",\n \"@classmethod async def query_tbl(cls, table_name, query=None): if table_name == 'schedules': return { \\\"count\\\":\",\n \"test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker): async def get_cat(): return {\",\n \"@pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\\\"test_interval, is_exception\\\", [ ('\\\"Blah\\\" 0 days', True), ('12:30:11',\",\n \"current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", _start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN\",\n \"('00:25:61', True) ]) async def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler =\",\n \"@pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with\",\n \"\\\"exit_code\\\"], \\\"limit\\\": 100} args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0]\",\n \"of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN\",\n \"= json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN\",\n \"def test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"== schedule_row[2] assert schedule_row[3] is 0 # 0 for Interval Schedule assert schedule_row[4]\",\n \"there is no task queued for this schedule at first with pytest.raises(KeyError) as\",\n \"\\\"info\\\") sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN status, message = await scheduler.disable_schedule(sch_id)\",\n \"Confirm no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN\",\n \"= await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4())\",\n \"# THEN # Now confirm there is one schedule less assert len(scheduler._storage_async.schedules) -\",\n \"True # Now queue task and assert that the North task has been\",\n \"sleep above, no task processes should be left pending assert 0 == len(scheduler._task_processes)\",\n \"any_order=True) calls = [call('Database command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True)\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger,\",\n \"gets executed, hence # \\\"stat collector\\\" appears twice in this list. assert 'stats\",\n \"scheduler._get_schedules() assert 1 == log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio\",\n \"= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler,\",\n \"type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None\",\n \"= log_info.call_args_list[0] # assert (\\\"Queued schedule '%s' for execution\\\", 'OMF to PI north')\",\n \"True), ('2 days 00:00:59', False), ('00:25:61', True) ]) async def test__get_schedules(self, test_interval, is_exception,\",\n \"task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that\",\n \"assert scheduler._task_processes is None assert scheduler._schedules is None assert scheduler._process_scripts is None assert\",\n \"# WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 ==\",\n \"# THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0 =\",\n \"await scheduler._get_schedules() sch_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') #\",\n \"mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN #\",\n \"# WHEN # Now delete schedule await scheduler.delete_schedule(sch_id) # THEN # Now confirm\",\n \"= await scheduler.disable_schedule(sch_id) # THEN assert status is True assert message == \\\"Schedule\",\n \"= await get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"listener south' in args1 assert 'OMF to PI north' in args2 # As\",\n \"_paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is\",\n \"not suitable for unit testing. Will be tested during System tests.\\\") async def\",\n \"len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"delete schedule await scheduler.delete_schedule(sch_id) # THEN # Now confirm there is one schedule\",\n \"def test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap\",\n \"is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): #\",\n \"assert schedule.exclusive is True assert schedule.enabled is True assert schedule.process_name == \\\"purge\\\" @pytest.mark.asyncio\",\n \"message = await scheduler.enable_schedule(sch_id) # THEN assert status is True assert message ==\",\n \"query=None): if table_name == 'schedules': return { \\\"count\\\": len(MockStorageAsync.schedules), \\\"rows\\\": MockStorageAsync.schedules } if\",\n \"is False log_params = \\\"Schedule %s already disabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def\",\n \"30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls,\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") await scheduler._get_schedules() sch_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # backup mocker.patch.object(scheduler, '_ready',\",\n \"await scheduler.delete_schedule(sch_id) # THEN # Now confirm there is one schedule less assert\",\n \"= mocker.patch.object(scheduler._logger, \\\"error\\\") log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") return scheduler,\",\n \"mocker): async def get_cat(): return { \\\"max_running_tasks\\\": { \\\"description\\\": \\\"The maximum number of\",\n \"excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"_rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future',\",\n \"= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) +\",\n \"== len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler() schedule_id\",\n \"asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\")\",\n \"HH24:MI:SS.MS\\\", \\\"column\\\": \\\"end_time\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"where\\\": {\\\"column\\\": \\\"id\\\", \\\"condition\\\": \\\"=\\\", \\\"value\\\": str(task_id)}} args,\",\n \"test__check_schedules(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600)\",\n \"have a status of running\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, }\",\n \"\\\"column\\\": \\\"end_time\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"where\\\": {\\\"column\\\": \\\"id\\\", \\\"condition\\\": \\\"=\\\", \\\"value\\\": str(task_id)}} args, kwargs\",\n \"# WHEN retval = await scheduler.stop() # THEN assert retval is True assert\",\n \"None assert tasks[0].start_time is not None assert tasks[0].end_time is not None assert tasks[0].exit_code\",\n \"mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler,\",\n \"time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 3 == log_info.call_count\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes =\",\n \"kwargs = log_exception.call_args assert 'Query failed: %s' == args[0] p = json.loads(args[1]) assert\",\n \"3, \\\"schedule_interval\\\": \\\"00:00:30\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, {\",\n \"-*- # FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime import\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id =\",\n \"= mocker.patch.object(ConfigurationManager, \\\"get_category_all_items\\\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is\",\n \"async def test_start(self, mocker): # TODO: Mandatory - Add negative tests for full\",\n \"task.cancel_requested is None assert task.start_time is not None assert task.end_time is not None\",\n \"pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError)\",\n \"Readings to PI' in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO: Mandatory\",\n \"= mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules)\",\n \"this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): #\",\n \"pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\\\"test_interval, is_exception\\\",\",\n \"be empty\\\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234\",\n \"await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info\",\n \"len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id)\",\n \"WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not\",\n \"temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del\",\n \"THEN assert retval is True assert scheduler._schedule_executions is None assert scheduler._task_processes is None\",\n \"can't be used in 'await' expression\\\"), call('An exception was raised by Scheduler._scheduler_loop %s',\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North\",\n \"False), ('2 days', True), ('2 days 00:00:59', False), ('00:25:61', True) ]) async def\",\n \"received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s', 'scheduled_processes'), call('Database\",\n \"mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") schedule_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI\",\n \"core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger,\",\n \"import copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import\",\n \"\\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, { \\\"id\\\": \\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\",\",\n \"'_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") schedule_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") #\",\n \"\\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"start_time\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"format\\\":\",\n \"scheduler.disable_schedule(sch_id) # THEN assert status is True assert message == \\\"Schedule successfully disabled\\\"\",\n \"# Confirm no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) #\",\n \"\\\"process_name\\\": \\\"backup\\\", \\\"schedule_name\\\": \\\"backup hourly\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0,\",\n \"} @classmethod async def query_tbl(cls, table_name, query=None): if table_name == 'schedules': return {\",\n \"isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8: patch() now returns an AsyncMock if\",\n \"%s pid %s, %s running tasks\\\\n%s\\\" in args assert 'OMF to PI north'\",\n \"log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF to PI\",\n \"a rows \\\" \\\"in the tasks table that do not have a status\",\n \"task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True #\",\n \"= log_info.call_args_list[0] assert 'OMF to PI north' in args assert 'North Readings to\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception =\",\n \"mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to\",\n \"day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN\",\n \"temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat\",\n \"test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"tasks = await scheduler.get_tasks() # THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\",\",\n \"@pytest.mark.parametrize(\\\"test_interval, is_exception\\\", [ ('\\\"Blah\\\" 0 days', True), ('12:30:11', False), ('0 day 12:30:11', False),\",\n \"call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): # TODO:\",\n \"test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"\\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\", \\\"process_name\\\":\",\n \"task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert\",\n \"kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection' in args0 assert\",\n \"1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count\",\n \"side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed:\",\n \"kwargs = log_info.call_args_list[1] assert \\\"Stopping process: Schedule '%s' process '%s' task %s pid\",\n \"\\\"North Readings to PI\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"1\\\", \\\"--debug_level\\\", \\\"1\\\" ] },\",\n \"sys.version_info.minor >= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler =\",\n \"scheduler._task_processes is None assert scheduler._schedules is None assert scheduler._process_scripts is None assert scheduler._ready\",\n \"assert str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id,\",\n \"\\\"reason\\\", \\\"exit_code\\\"], \\\"where\\\": {\\\"column\\\": \\\"id\\\", \\\"condition\\\": \\\"=\\\", \\\"value\\\": str(task_id)}} args, kwargs = log_exception.call_args\",\n \"\\\"\\\" async def mock_process(): m = MagicMock() m.pid = 9999 m.terminate = lambda:\",\n \"running at any given time\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \\\"max_completed_task_age_days\\\":\",\n \"mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch =\",\n \"as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule,\",\n \"'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert 1 ==\",\n \"None assert task.start_time is not None assert task.end_time is not None assert task.exit_code\",\n \"repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes\",\n \"# assert (\\\"Queued schedule '%s' for execution\\\", 'OMF to PI north') == args\",\n \"= mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions =\",\n \"0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\", \\\"process_name\\\": \\\"stats collector\\\", \\\"schedule_name\\\":\",\n \"len(MockStorageAsync.schedules), \\\"rows\\\": MockStorageAsync.schedules } if table_name == 'scheduled_processes': return { \\\"count\\\": len(MockStorageAsync.scheduled_processes), \\\"rows\\\":\",\n \"the start time), for a rows \\\" \\\"in the tasks table that do\",\n \"PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'OMF to\",\n \"repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") log_error = mocker.patch.object(scheduler._logger, \\\"error\\\")\",\n \"log_debug = await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task')\",\n \"schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN # Now delete\",\n \"\\\"id\\\", \\\"condition\\\": \\\"=\\\", \\\"value\\\": str(task_id)}} args, kwargs = log_exception.call_args assert 'Query failed: %s'\",\n \"= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False)\",\n \"queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now\",\n \"WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules'\",\n \"= Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0,\",\n \"PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process\",\n \"mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch =\",\n \"excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo:\",\n \"_start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch = scheduler._schedules[sch_id] sch_execution\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN #\",\n \"core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules()\",\n \"is None await scheduler._read_config() # THEN assert 1 == cr_cat.call_count assert 1 ==\",\n \"mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id\",\n \"to PI north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North\",\n \"is one schedule less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async def\",\n \"scheduler.get_tasks() # THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"column\\\":\",\n \"south\\\", \\\"schedule_type\\\": 1, \\\"schedule_interval\\\": \\\"00:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\"\",\n \"# THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count calls\",\n \"\\\"schedule_interval\\\": \\\"00:00:30\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\":\",\n \"scheduler._ready is False assert scheduler._paused is False assert scheduler._start_time is None calls =\",\n \"def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\\\"_terminate_child_processes() not fit for\",\n \"WHEN schedules = await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async\",\n \"= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None)\",\n \"= uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there are 14\",\n \"above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN await\",\n \"assert tasks[0].start_time is not None assert tasks[0].end_time is None assert tasks[0].exit_code is None\",\n \"excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"True # WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params =\",\n \"await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"# THEN # Now confirm no schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)\",\n \"@pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0,\",\n \"\\\"00:00:30\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\",\",\n \"WHEN # THEN task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) #\",\n \"[call('Starting'), call('Starting Scheduler: Management port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls =\",\n \"len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there is no North task\",\n \"to OCS north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"1 day 00:00:40\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0,\",\n \"with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now confirm no schedule is deleted\",\n \"self.scheduler_fixture(mocker) # Assert that there is no North task queued for schedule with\",\n \"await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup #\",\n \"import uuid import time import json from unittest.mock import MagicMock, call import sys\",\n \"assert schedule.process_name == task.process_name assert task.reason is '' assert task.state is not None\",\n \"assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 0 == enable_schedule.call_count assert\",\n \"mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings\",\n \"None assert scheduler._max_completed_task_age is None await scheduler._read_config() # THEN assert 1 == cr_cat.call_count\",\n \"= mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] =\",\n \"len(scheduler._schedules) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled':\",\n \"= log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 =\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler,\",\n \"True assert scheduler._schedule_executions is None assert scheduler._task_processes is None assert scheduler._schedules is None\",\n \"task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks()\",\n \"'_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN with pytest.raises(NotReadyError) as excinfo:\",\n \"tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time\",\n \"Schedule assert schedule_row[4] is 0 # 0 for Interval Schedule assert schedule.repeat ==\",\n \"TODO: Find why these exceptions are being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls\",\n \"1 == len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state\",\n \"excinfo: await scheduler.get_task(task_id) # THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\":\",\n \"mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop',\",\n \"= time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", current_time=current_time - 3600)\",\n \"= \\\"Queued schedule '%s' for execution\\\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self,\",\n \"THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD',\",\n \"_start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch = scheduler._schedules[sch_id] sch_execution\",\n \"scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules() # THEN assert\",\n \"# OMF to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1,\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id =\",\n \"= dict() mock_task_process.process = await asyncio.create_subprocess_exec(\\\"sleep\\\", \\\".1\\\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4()\",\n \"\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"schedule_name\\\": \\\"OMF to PI north\\\", \\\"schedule_type\\\": 3,\",\n \"return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North\",\n \"exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) #\",\n \"mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule =\",\n \"\\\"info\\\") sch_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North # WHEN status, message\",\n \"unit test.\\\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None,\",\n \"call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these exceptions are being raised despite\",\n \"was raised by Scheduler._scheduler_loop %s', \\\"object MagicMock can't be used in 'await' expression\\\")]\",\n \"class TestScheduler: async def scheduler_fixture(self, mocker): # Changed in version 3.8: patch() now\",\n \"assert retval is True assert scheduler._schedule_executions is None assert scheduler._task_processes is None assert\",\n \"# WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \\\"No such Schedule %s\\\", str(random_schedule_id)\",\n \"schedules = [ { \\\"id\\\": \\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"purge\\\", \\\"schedule_name\\\": \\\"purge\\\", \\\"schedule_type\\\": 4, \\\"schedule_interval\\\":\",\n \"name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule\",\n \"fit for unit test.\\\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def\",\n \"THEN assert status is True assert message == \\\"Schedule is already enabled\\\" assert\",\n \"mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id =\",\n \"= lambda: True return m @pytest.allure.feature(\\\"unit\\\") @pytest.allure.story(\\\"scheduler\\\") class TestScheduler: async def scheduler_fixture(self, mocker):\",\n \"is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count log_params = 'Attempt\",\n \"'_ready', True) # WHEN processes = await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) ==\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\")\",\n \"scheduler.disable_schedule(sch_id) # THEN assert status is True assert message == \\\"Schedule {} already\",\n \"tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s', 'scheduled_processes'), call('Database command:\",\n \"async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port)\",\n \"there is no task queued for mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id]\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN\",\n \"await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup await scheduler._get_schedules() # Confirm no. of\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \\\"create_category\\\",\",\n \"executed, hence # \\\"stat collector\\\" appears twice in this list. assert 'stats collection'\",\n \"args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3,\",\n \"log_error = mocker.patch.object(scheduler._logger, \\\"error\\\") log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") return\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules')\",\n \"scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\\\"_terminate_child_processes() not fit for unit test.\\\")\",\n \"_rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"\\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" },\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception())\",\n \"# THEN assert scheduler._check_processes_pending is False # WHEN # Check ELSE part mocker.patch.object(scheduler,\",\n \"log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule',\",\n \"== disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" #\",\n \"_task_processes={}) # WHEN retval = await scheduler.stop() # THEN assert retval is True\",\n \"backup await scheduler._get_schedules() # Confirm no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler,\",\n \"True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task()))\",\n \"with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\",\",\n \"being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception was raised by\",\n \"2, \\\"schedule_interval\\\": \\\"00:00:15\\\", \\\"schedule_time\\\": \\\"00:00:15\\\", \\\"schedule_day\\\": 3, \\\"exclusive\\\": \\\"f\\\", \\\"enabled\\\": \\\"t\\\" }, {\",\n \"IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False #\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there is no task queued\",\n \"\\\"rows\\\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name, query=None): if table_name == 'schedules':\",\n \"assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN scheduler, schedule,\",\n \"False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 1\",\n \"{ \\\"id\\\": \\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\", \\\"process_name\\\": \\\"North Readings to OCS\\\", \\\"schedule_name\\\": \\\"OMF to OCS north\\\",\",\n \"that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count #\",\n \"log_info.call_args_list[0] # assert (\\\"Queued schedule '%s' for execution\\\", 'OMF to PI north') ==\",\n \"scheduler.start() # THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules)\",\n \"schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count log_params =\",\n \"= [call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\\\"Disabled Schedule '%s/%s' process '%s'\\\\n\\\",\",\n \"await scheduler.enable_schedule(sch_id) # THEN assert status is True assert message == \\\"Schedule is\",\n \"id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN\",\n \"1 == resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async\",\n \"core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"),\",\n \"\\\"f\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\", \\\"process_name\\\": \\\"backup\\\", \\\"schedule_name\\\": \\\"backup hourly\\\", \\\"schedule_type\\\":\",\n \"GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler,\",\n \"Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True)\",\n \"scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can not be empty\\\") with pytest.raises(ValueError) as ex:\",\n \"schedule.exclusive is True assert schedule.enabled is True assert schedule.process_name == \\\"purge\\\" @pytest.mark.asyncio async\",\n \"= await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status,\",\n \"is True # Now queue task and assert that the task has been\",\n \"calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False,\",\n \"# THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker):\",\n \"await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 ==\",\n \"= [ { \\\"id\\\": \\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"purge\\\", \\\"schedule_name\\\": \\\"purge\\\", \\\"schedule_type\\\": 4, \\\"schedule_interval\\\": \\\"01:00:00\\\",\",\n \"pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro():\",\n \"= await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task()))\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup await\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN\",\n \"schedule_row[4] is 0 # 0 for Interval Schedule assert schedule.repeat == schedule_row[5] assert\",\n \"port): return { \\\"id\\\": uuid.uuid4(), \\\"name\\\": \\\"Fledge Storage\\\", \\\"type\\\": \\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\":\",\n \"temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can not be empty\\\")\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) #\",\n \"import json from unittest.mock import MagicMock, call import sys import copy import pytest\",\n \"{ \\\"id\\\": \\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\", \\\"process_name\\\": \\\"stats collector\\\", \\\"schedule_name\\\": \\\"stats collection\\\", \\\"schedule_type\\\": 2, \\\"schedule_interval\\\": \\\"00:00:15\\\",\",\n \"scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts()\",\n \"mocker.patch.object(scheduler, '_ready', True) # WHEN # Now delete schedule await scheduler.delete_schedule(sch_id) # THEN\",\n \"# See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime import uuid import time\",\n \"scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \\\"\\\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can not\",\n \"len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel request has not been made\",\n \"# WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None await scheduler._read_config() #\",\n \"day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") log_error = mocker.patch.object(scheduler._logger, \\\"error\\\") log_debug =\",\n \"sch_execution, next_dt) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 3\",\n \"repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") log_error = mocker.patch.object(scheduler._logger,\",\n \"\\\"schedule_day\\\": 3, \\\"exclusive\\\": \\\"f\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\", \\\"process_name\\\": \\\"backup\\\", \\\"schedule_name\\\":\",\n \"assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF to PI north'\",\n \"import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from\",\n \"= await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\"\",\n \"Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules()\",\n \"yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN # Confirm\",\n \"fixture\\\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"= sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 3 == log_info.call_count args0,\",\n \"THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN scheduler,\",\n \"OCS north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"1 day 00:00:40\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\":\",\n \"mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id]\",\n \"= sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt)\",\n \"OMF to PI North # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN\",\n \"table_name == \\\"schedules\\\": return {\\\"count\\\": 1} @classmethod async def delete_from_tbl(cls, table_name, condition=None): pass\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() curr_time =\",\n \"args assert 'North Readings to PI' in args @pytest.mark.asyncio async def test__start_task(self, mocker):\",\n \"in main Scheduler class.\\\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self,\",\n \"= uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # purge schedule # WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN\",\n \"to OCS\\\", \\\"schedule_name\\\": \\\"OMF to OCS north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"1 day 00:00:40\\\",\",\n \"started: Schedule '%s' process '%s' task %s pid %s, %s running tasks\\\\n%s\\\" in\",\n \"Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now confirm no\",\n \"scheduler._schedule_executions is None assert scheduler._task_processes is None assert scheduler._schedules is None assert scheduler._process_scripts\",\n \"task and assert that the North task has been queued await scheduler.queue_task(schedule.id) assert\",\n \"}, { \\\"id\\\": \\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\", \\\"process_name\\\": \\\"backup\\\", \\\"schedule_name\\\": \\\"backup hourly\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"01:00:00\\\",\",\n \"mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio, 'ensure_future', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules')\",\n \"mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec',\",\n \"mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", current_time=current_time - 3600) # TODO: Remove after\",\n \"mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") # WHEN # THEN with pytest.raises(Exception):\",\n \"to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has not started yet assert\",\n \"%s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\\\"test_interval, is_exception\\\", [ ('\\\"Blah\\\" 0 days', True), ('12:30:11', False),\",\n \"\\\"object MagicMock can't be used in 'await' expression\\\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self,\",\n \"await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm\",\n \"side_effect=Exception()) # WHEN # THEN task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo: await\",\n \"tasks[0].end_time is None assert tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self, mocker): #\",\n \"\\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"schedule_name\\\":\",\n \"not None assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 =\",\n \"WHEN with pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks() # THEN payload =\",\n \"== resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def\",\n \"'OMF to PI north' in args assert 'North Readings to PI' in args\",\n \"THEN assert 1 == len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason is None\",\n \"to PI\\\", \\\"state\\\": 1, \\\"start_time\\\": \\\"2018-02-06 13:28:14.477868\\\", \\\"end_time\\\": \\\"2018-02-06 13:28:14.856375\\\", \\\"exit_code\\\": \\\"0\\\", \\\"reason\\\":\",\n \"return_value=\\\"North Readings to PI\\\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task\",\n \"THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert schedule.name == \\\"purge\\\" assert\",\n \"'debug', side_effect=Exception()) # WHEN # THEN task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo:\",\n \"0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, { \\\"id\\\": \\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"COAP\\\", \\\"schedule_name\\\": \\\"COAP\",\n \"is already enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params =\",\n \"\\\"schedule_name\\\": \\\"purge\\\", \\\"schedule_type\\\": 4, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\":\",\n \"exception was raised by Scheduler._scheduler_loop %s', \\\"object MagicMock can't be used in 'await'\",\n \"enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert\",\n \"as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as\",\n \"by Scheduler._scheduler_loop %s', \\\"object MagicMock can't be used in 'await' expression\\\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio\",\n \"datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch\",\n \"schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0]\",\n \"self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule = await\",\n \"# THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker):\",\n \"@pytest.mark.asyncio @pytest.mark.parametrize(\\\"test_interval, is_exception\\\", [ ('\\\"Blah\\\" 0 days', True), ('12:30:11', False), ('0 day 12:30:11',\",\n \"WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self,\",\n \"= await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN log_params\",\n \"True, 'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): #\",\n \"assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return\",\n \"excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id],\",\n \"@pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO: Mandatory - Add negative tests for\",\n \"not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add negative\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North # WHEN\",\n \"time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) #\",\n \"# THEN assert status is True assert message == \\\"Schedule is already enabled\\\"\",\n \"WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks()\",\n \"len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN # Now delete schedule await\",\n \"the task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm that\",\n \"WHEN # Now delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now\",\n \"\\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"column\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"column\\\": \\\"end_time\\\",\",\n \"%s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"dict() mock_task_process.process = await asyncio.create_subprocess_exec(\\\"sleep\\\", \\\".1\\\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id\",\n \"= 'Attempt to delete an enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio\",\n \"False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 0\",\n \"\\\"schedule_name\\\": \\\"OMF to PI north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"00:00:30\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0,\",\n \"as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as\",\n \"# THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls = [call('SCHCH',\",\n \"@pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"days', True), ('12:30:11', False), ('0 day 12:30:11', False), ('1 day 12:40:11', False), ('2\",\n \"THEN log_params = \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self,\",\n \"== 3 and sys.version_info.minor >= 8: _rv = await mock_process() else: _rv =\",\n \"0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF\",\n \"\\\"id\\\": \\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"purge\\\", \\\"schedule_name\\\": \\\"purge\\\", \\\"schedule_type\\\": 4, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\":\",\n \"task.exit_code is '0' @pytest.mark.skip(\\\"Need a suitable fixture\\\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): #\",\n \"schedule_row[3] is 0 # 0 for Interval Schedule assert schedule_row[4] is 0 #\",\n \"= mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule',\",\n \"%s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\\\"Disabled Schedule '%s/%s' process '%s'\\\\n\\\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North\",\n \"'' assert tasks[0].state is not None assert tasks[0].cancel_requested is None assert tasks[0].start_time is\",\n \"await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self,\",\n \"temp_schedule assert str(ex).endswith('time must be of type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule\",\n \"Now confirm there is one schedule less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules)\",\n \"\\\"name\\\": \\\"North Readings to OCS\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"4\\\", \\\"--debug_level\\\", \\\"1\\\" ]\",\n \"THEN task_id = uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN payload\",\n \"'North Readings to PI' in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO:\",\n \"log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\\\"test_interval, is_exception\\\", [ ('\\\"Blah\\\" 0 days', True), ('12:30:11', False), ('0 day\",\n \"@pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler,\",\n \"= mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN\",\n \"'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert\",\n \"tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state is not None assert tasks[0].cancel_requested is\",\n \"at any given time\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \\\"max_completed_task_age_days\\\": {\",\n \"core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") # WHEN #\",\n \"async def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"@pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler,\",\n \"scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1 ==\",\n \"log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task',\",\n \"+ 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test\",\n \"scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\\\"sleep\\\", \\\".1\\\") mock_task_process.schedule = mock_schedule mock_task_id\",\n \"started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await\",\n \"@pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"if table_name == 'tasks': return { \\\"count\\\": len(MockStorageAsync.tasks), \\\"rows\\\": MockStorageAsync.tasks } @classmethod async\",\n \"with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\\\"test_interval,\",\n \"'_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id\",\n \"cancel request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await\",\n \"= [ { \\\"name\\\": \\\"purge\\\", \\\"script\\\": [ \\\"tasks/purge\\\" ] }, { \\\"name\\\": \\\"stats\",\n \"False), ('00:25:61', True) ]) async def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler\",\n \"= mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN # THEN task_id = uuid.uuid4() with pytest.raises(Exception)\",\n \"@pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host,\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to\",\n \"enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) schedule_id = uuid.uuid4()\",\n \"\\\"enabled\\\": \\\"f\\\" }, ] scheduled_processes = [ { \\\"name\\\": \\\"purge\\\", \\\"script\\\": [ \\\"tasks/purge\\\"\",\n \"= scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\\\"sleep\\\", \\\".1\\\") mock_task_process.schedule = mock_schedule\",\n \"assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN # Now delete schedule\",\n \"def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row =\",\n \"len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN # Confirm that task has started\",\n \"for execution\\\", 'OMF to PI north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert\",\n \"earliest_start_time is not None assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1,\",\n \"'repeat': 30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls,\",\n \"mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task')\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now())\",\n \"mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) #\",\n \"new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) # WHEN # THEN\",\n \"len(scheduler._schedules) assert 1 == log_exception.call_count log_params = 'Attempt to delete an enabled Schedule\",\n \"WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count\",\n \"= await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # purge schedule # WHEN schedule =\",\n \"process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler,\",\n \"enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params = \\\"Schedule %s\",\n \"\\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } @classmethod async def\",\n \"= \\\"${VERSION}\\\" async def mock_task(): return \\\"\\\" async def mock_process(): m = MagicMock()\",\n \"[ { \\\"name\\\": \\\"purge\\\", \\\"script\\\": [ \\\"tasks/purge\\\" ] }, { \\\"name\\\": \\\"stats collector\\\",\",\n \"mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler,\",\n \"= await asyncio.create_subprocess_exec(\\\"sleep\\\", \\\".1\\\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id\",\n \"a status of running\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } #\",\n \"async def scheduler_fixture(self, mocker): # Changed in version 3.8: patch() now returns an\",\n \"log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") return scheduler, schedule, log_info, log_exception,\",\n \"\\\"=\\\", \\\"value\\\": str(task_id)}} args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0]\",\n \"@pytest.mark.skip(\\\"_terminate_child_processes() not fit for unit test.\\\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class\",\n \"pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): #\",\n \"'schedules', new_schedules) # WHEN # THEN if is_exception is True: with pytest.raises(Exception): await\",\n \"is None assert task.start_time is not None assert task.end_time is not None assert\",\n \"False) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio,\",\n \"can not be None') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time\",\n \"'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await\",\n \"await self.scheduler_fixture(mocker) # Assert that there is no task queued for schedule with\",\n \"already enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params = \\\"Schedule\",\n \"scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def test_start(self, mocker): # TODO: Mandatory -\",\n \"tasks[0].state is not None assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None\",\n \"\\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN\",\n \"assert schedule.enabled is True assert schedule.process_name == \\\"purge\\\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker):\",\n \"task has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that\",\n \"pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\",\",\n \"mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) #\",\n \"as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\\\"_terminate_child_processes() not fit\",\n \"= time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time\",\n \"None assert 2 == log_info.call_count # args, kwargs = log_info.call_args_list[0] # assert (\\\"Queued\",\n \"class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return\",\n \"Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)\",\n \"for unit testing. Will be tested during System tests.\\\") async def test__scheduler_loop(self, mocker):\",\n \"an async function. if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv =\",\n \"def test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo:\",\n \"\\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"start_time\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"end_time\\\"}, \\\"reason\\\", \\\"exit_code\\\"],\",\n \"delete an enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self,\",\n \"schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can not be\",\n \">= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv)\",\n \"mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF\",\n \"is an async function. if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv\",\n \"has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks() #\",\n \"first_task.call_count assert 1 == resume_sch.call_count assert 1 == enable_schedule.call_count assert 0 == disable_schedule.call_count\",\n \"'_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time =\",\n \"not have a status of running\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) },\",\n \"be empty\\\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \\\"\\\"\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as\",\n \"assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 1 == enable_schedule.call_count assert\",\n \"# WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def\",\n \"list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name\",\n \"excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo:\",\n \"else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4())\",\n \"= {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"column\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"},\",\n \"3, \\\"schedule_interval\\\": \\\"1 day 00:00:40\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\"\",\n \"# log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") await scheduler._get_schedules() sch_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # backup mocker.patch.object(scheduler,\",\n \"Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\\\"Disabled Schedule '%s/%s' process '%s'\\\\n\\\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34',\",\n \"an AsyncMock if the target is an async function. if sys.version_info.major == 3\",\n \"_core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", current_time=current_time - 3600) # TODO: Remove after implementation of above test\",\n \"core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules()\",\n \"ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert\",\n \"\\\"purge\\\", \\\"script\\\": [ \\\"tasks/purge\\\" ] }, { \\\"name\\\": \\\"stats collector\\\", \\\"script\\\": [ \\\"tasks/statistics\\\"\",\n \"await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger\",\n \"is None assert scheduler._schedules is None assert scheduler._process_scripts is None assert scheduler._ready is\",\n \"# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id =\",\n \"async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"= list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks() # THEN assert schedule.process_name ==\",\n \"4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2\",\n \"is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"\\\"get_category_all_items\\\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None await\",\n \"mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None,\",\n \"scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 ==\",\n \"scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def test__check_schedules(self, mocker):\",\n \"None assert tasks[0].end_time is None assert tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self,\",\n \"process '%s' task %s pid %s\\\\n%s\\\" in args assert 'OMF to PI north'\",\n \"\\\"default\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \\\"max_completed_task_age_days\\\": { \\\"description\\\": \\\"The maximum age, in days\",\n \"= [call('Database command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async\",\n \"await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN\",\n \"async def test_queue_task(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"_max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch = scheduler._schedules[sch_id]\",\n \"del temp_schedule assert str(ex).endswith('day must be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\\\"To be\",\n \"assert tasks[0].end_time is not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self,\",\n \"schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name\",\n \"assert (scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count calls = [call(\\\"Enabled Schedule '%s/%s'\",\n \"True) # WHEN processes = await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes)\",\n \"3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler,\",\n \"__init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return { \\\"id\\\": uuid.uuid4(),\",\n \"\\\"exit_code\\\": \\\"0\\\", \\\"reason\\\": \\\"\\\" } ] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def\",\n \"retval = await scheduler.stop() # THEN assert retval is True assert scheduler._schedule_executions is\",\n \"# THEN # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert\",\n \"\\\"1\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, { \\\"name\\\": \\\"North Readings to OCS\\\", \\\"script\\\": [\",\n \"# Assert that there is no task queued for mock_schedule with pytest.raises(KeyError) as\",\n \"log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 ==\",\n \"test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_schedule_first_task',\",\n \"return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id)\",\n \"Now delete schedule await scheduler.delete_schedule(sch_id) # THEN # Now confirm there is one\",\n \"sch_id assert (scheduler._schedules[sch_id]).enabled is True log_params = \\\"Schedule %s already enabled\\\", str(sch_id) log_info.assert_called_with(*log_params)\",\n \"request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id)\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) ==\",\n \"def test__check_schedules(self, mocker): # TODO: Mandatory - Add negative tests for full code\",\n \"scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\\\"_mark_tasks_interrupted()\",\n \"1 == first_task.call_count assert 1 == resume_sch.call_count assert 0 == enable_schedule.call_count assert 0\",\n \"# THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def\",\n \"'schedules': return { \\\"count\\\": len(MockStorageAsync.schedules), \\\"rows\\\": MockStorageAsync.schedules } if table_name == 'scheduled_processes': return\",\n \"schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return\",\n \"payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"column\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD\",\n \"import datetime import uuid import time import json from unittest.mock import MagicMock, call\",\n \"coverage # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None,\",\n \"return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id,\",\n \"\\\"enabled\\\": \\\"f\\\" }, { \\\"id\\\": \\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"COAP\\\", \\\"schedule_name\\\": \\\"COAP listener south\\\", \\\"schedule_type\\\":\",\n \"%s\\\\n%s\\\" in args assert 'OMF to PI north' in args assert 'North Readings\",\n \"assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age is None await scheduler._read_config() # THEN assert\",\n \"scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO: Mandatory -\",\n \"> time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 =\",\n \"True), ('12:30:11', False), ('0 day 12:30:11', False), ('1 day 12:40:11', False), ('2 days',\",\n \"no task queued for mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") #\",\n \"# THEN assert 1 == cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks is\",\n \"- Add negative tests for full code coverage # GIVEN scheduler = Scheduler()\",\n \"= uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule',\",\n \"scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch,\",\n \"GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug\",\n \"test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN await scheduler.start() #\",\n \"# Changed in version 3.8: patch() now returns an AsyncMock if the target\",\n \"{\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"start_time\\\"}, {\\\"alias\\\":\",\n \"- 1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule,\",\n \"\\\"Queued schedule '%s' for execution\\\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker):\",\n \"True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting\",\n \"\\\"limit\\\": 100} args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0] p\",\n \"uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution()\",\n \"def test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task')\",\n \"def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"\\\"t\\\" }, { \\\"id\\\": \\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"schedule_name\\\": \\\"OMF to\",\n \"\\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"start_time\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"end_time\\\"}, \\\"reason\\\",\",\n \"\\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\", \\\"process_name\\\": \\\"North Readings\",\n \"# Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 ==\",\n \"task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks() # THEN assert schedule.process_name\",\n \"= mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule)\",\n \"== len(scheduler._schedules) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule',\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mocker.patch.object(scheduler, '_schedule_first_task')\",\n \"used in 'await' expression\\\"), call('An exception was raised by Scheduler._scheduler_loop %s', \\\"object MagicMock\",\n \"\\\"Schedule %s already enabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN\",\n \"json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler,\",\n \"is None assert tasks[0].exit_code is None @pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN\",\n \"3600, _paused=False, _task_processes={}) # WHEN retval = await scheduler.stop() # THEN assert retval\",\n \"assert \\\"Process started: Schedule '%s' process '%s' task %s pid %s, %s running\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotFoundError) as\",\n \"async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if\",\n \"schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day\",\n \"Schedule '%s/%s' process '%s'\\\\n\\\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')]\",\n \"Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN\",\n \"self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN with pytest.raises(NotReadyError)\",\n \"True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"task has not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule)\",\n \"not None assert 2 == log_info.call_count # args, kwargs = log_info.call_args_list[0] # assert\",\n \"at first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN await\",\n \"\\\"disable_schedule\\\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0,\",\n \"0 for Interval Schedule assert schedule_row[4] is 0 # 0 for Interval Schedule\",\n \"# THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await\",\n \"type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess()\",\n \"calls = [call('Starting'), call('Starting Scheduler: Management port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True)\",\n \"%s', \\\"object MagicMock can't be used in 'await' expression\\\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def\",\n \"mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL,\",\n \"scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) #\",\n \"coding: utf-8 -*- # FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import\",\n \"None assert scheduler._schedules is None assert scheduler._process_scripts is None assert scheduler._ready is False\",\n \"mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\\\"sleep\\\", \\\".1\\\") mock_task_process.schedule\",\n \"== schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN\",\n \"schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10,\",\n \"and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\\\"To be done\\\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def\",\n \"= uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there\",\n \"9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } @classmethod async def insert_into_tbl(cls, table_name, payload): pass\",\n \"scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio\",\n \"await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes = await scheduler.get_scheduled_processes() # THEN\",\n \"# THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1]\",\n \"Confirm that cancel request has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None #\",\n \"uuid import time import json from unittest.mock import MagicMock, call import sys import\",\n \"'COAP listener south' in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio\",\n \"'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async\",\n \"\\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\", \\\"process_name\\\": \\\"North\",\n \"\\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, ] scheduled_processes = [ { \\\"name\\\":\",\n \"exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule\",\n \"log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection' in\",\n \"# WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert\",\n \"8: _rv = await get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler =\",\n \"tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert\",\n \"{ \\\"id\\\": \\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"COAP\\\", \\\"schedule_name\\\": \\\"COAP listener south\\\", \\\"schedule_type\\\": 1, \\\"schedule_interval\\\": \\\"00:00:00\\\",\",\n \"= mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception): await\",\n \"None assert scheduler._process_scripts is None assert scheduler._ready is False assert scheduler._paused is False\",\n \"\\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"limit\\\": 100} args, kwargs = log_exception.call_args assert\",\n \"with pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules)\",\n \"True) mocker.patch.object(scheduler, '_task_processes') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup #\",\n \"pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\\\"_terminate_child_processes() not\",\n \"None assert task.cancel_requested is None assert task.start_time is not None assert task.end_time is\",\n \"tasks[0].end_time is not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker):\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF\",\n \"in args assert 'North Readings to PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self,\",\n \"command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): # TODO: Mandatory\",\n \"\\\"purge\\\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"[call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True, 'repeat': 3600.0,\",\n \"Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN\",\n \"1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\"\",\n \"len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes)\",\n \"table_name == 'schedules': return { \\\"count\\\": len(MockStorageAsync.schedules), \\\"rows\\\": MockStorageAsync.schedules } if table_name ==\",\n \"await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await\",\n \"{ \\\"id\\\": \\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\", \\\"process_name\\\": \\\"backup\\\", \\\"schedule_name\\\": \\\"backup hourly\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\":\",\n \"to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule\",\n \"south' in args1 assert 'OMF to PI north' in args2 # As part\",\n \"scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert schedule.name ==\",\n \"= await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup await scheduler._get_schedules() # Confirm no.\",\n \"# WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1\",\n \"appears twice in this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def\",\n \"can't be used in 'await' expression\\\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): #\",\n \"north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \\\"Process started: Schedule '%s' process\",\n \"== log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \\\"Process started: Schedule '%s' process '%s'\",\n \"Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler =\",\n \"async function. if sys.version_info.major == 3 and sys.version_info.minor >= 8: _rv = await\",\n \"first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") schedule_id\",\n \"00:00:59', False), ('00:25:61', True) ]) async def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN\",\n \"None assert scheduler._ready is False assert scheduler._paused is False assert scheduler._start_time is None\",\n \"number of tasks that can be running at any given time\\\", \\\"type\\\": \\\"integer\\\",\",\n \"'_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task queued for\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger\",\n \"WHEN await scheduler.start() # THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts)\",\n \"sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup await scheduler._get_schedules() # Confirm no. of schedules assert\",\n \"args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\\\"_scheduler_loop() not suitable for\",\n \"'0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1\",\n \"task.end_time is not None assert task.exit_code is '0' @pytest.mark.skip(\\\"Need a suitable fixture\\\") @pytest.mark.asyncio\",\n \"scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN\",\n \"log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these exceptions are being raised despite mocking\",\n \"retval is True assert scheduler._schedule_executions is None assert scheduler._task_processes is None assert scheduler._schedules\",\n \"- 3600) # TODO: Remove after implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config',\",\n \"schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1 ==\",\n \"\\\"info\\\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", current_time=current_time\",\n \"= await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup\",\n \"kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats\",\n \"async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule,\",\n \"\\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"limit\\\": 100} args, kwargs = log_exception.call_args assert 'Query\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules() # THEN\",\n \"= datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be between 1 and\",\n \"= log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection'\",\n \"with pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks() # THEN payload = {\\\"return\\\":\",\n \"excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo:\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") return scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self,\",\n \"is no task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is\",\n \"await scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await\",\n \"True) # WHEN # Now delete schedule await scheduler.delete_schedule(sch_id) # THEN # Now\",\n \"should be left pending assert 0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args,\",\n \"THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO:\",\n \"[call('An exception was raised by Scheduler._purge_tasks %s', \\\"object MagicMock can't be used in\",\n \"'_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() # THEN\",\n \"GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\")\",\n \"tested during System tests.\\\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self,\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes')\",\n \"test_start(self, mocker): # TODO: Mandatory - Add negative tests for full code coverage\",\n \"assert task.exit_code is '0' @pytest.mark.skip(\\\"Need a suitable fixture\\\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker):\",\n \"schedule.process_name == tasks[0].process_name assert tasks[0].reason is '' assert tasks[0].state is not None assert\",\n \"# WHEN await scheduler.start() # THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) ==\",\n \"log_info.call_args_list[0] assert \\\"Process started: Schedule '%s' process '%s' task %s pid %s, %s\",\n \"Confirm that no task has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule)\",\n \"call(\\\"Queued schedule '%s' for execution\\\", 'OMF to PI north') == log_info.call_args_list[0] args, kwargs\",\n \"GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\")\",\n \"from unittest.mock import MagicMock, call import sys import copy import pytest from fledge.services.core.scheduler.scheduler\",\n \"a suitable fixture\\\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN\",\n \"queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8: patch() now\",\n \"\\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, ] scheduled_processes = [\",\n \"[call('SCHCH', {'schedule': {'name': 'OMF to PI north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL,\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup\",\n \"# WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed: %s',\",\n \"def test_stop(self, mocker): # TODO: Mandatory - Add negative tests for full code\",\n \"not None assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time\",\n \"do not have a status of running\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS)\",\n \"mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN with pytest.raises(NotReadyError) as\",\n \"repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert\",\n \"\\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\", \\\"process_name\\\": \\\"North Readings to OCS\\\", \\\"schedule_name\\\": \\\"OMF to OCS north\\\", \\\"schedule_type\\\": 3,\",\n \"@pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"# TODO: Remove after implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert\",\n \"True assert message == \\\"Schedule successfully disabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled\",\n \"return {\\\"count\\\": 1} @classmethod async def delete_from_tbl(cls, table_name, condition=None): pass @classmethod async def\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN\",\n \"any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): # TODO: Mandatory - Add negative tests\",\n \"= mocker.patch.object(scheduler._logger, \\\"exception\\\") log_error = mocker.patch.object(scheduler._logger, \\\"error\\\") log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info =\",\n \"THEN assert status is True assert message == \\\"Schedule {} already disabled\\\".format(str(sch_id)) assert\",\n \"to PI' in args @pytest.mark.asyncio async def test__start_task(self, mocker): # TODO: Mandatory -\",\n \"'Attempt to delete an enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async\",\n \"%s pid %s\\\\n%s\\\" in args assert 'OMF to PI north' in args assert\",\n \"import asyncio import datetime import uuid import time import json from unittest.mock import\",\n \"assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is not None @pytest.mark.asyncio async def\",\n \"purge schedule # WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule, Schedule)\",\n \"pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions\",\n \"Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)\",\n \"collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules',\",\n \"schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self,\",\n \"return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm\",\n \"\\\"default\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS) }, } # Changed in version 3.8: patch() now\",\n \"mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) ==\",\n \"= uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN\",\n \"\\\"process_name\\\": \\\"North Readings to PI\\\", \\\"schedule_name\\\": \\\"OMF to PI north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\":\",\n \"excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\\\"_terminate_child_processes() not fit for unit test.\\\") @pytest.mark.asyncio async def test__terminate_child_processes(self,\",\n \"\\\"exception\\\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN with pytest.raises(Exception): await scheduler._get_schedules() log_args\",\n \"await scheduler._start_task(schedule) # Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id\",\n \"\\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } class MockStorageAsync(StorageClientAsync): schedules =\",\n \"time_after_call > time_before_call assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1\",\n \"return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF to\",\n \"schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True,\",\n \"is 0 # 0 for Interval Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive\",\n \"mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id\",\n \"mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host,\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task()))\",\n \"True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id\",\n \"assert scheduler._schedules is None assert scheduler._process_scripts is None assert scheduler._ready is False assert\",\n \"log_params = \\\"Queued schedule '%s' for execution\\\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def\",\n \"= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can\",\n \"def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS) }, \\\"max_completed_task_age_days\\\": { \\\"description\\\": \\\"The maximum age, in days (based\",\n \"= None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can not be empty\\\") with\",\n \"assert 'OMF to PI north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): #\",\n \"str(ex).endswith('time must be of type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id,\",\n \"is not None assert task.exit_code is '0' @pytest.mark.skip(\\\"Need a suitable fixture\\\") @pytest.mark.asyncio async\",\n \"assert tasks[0].state is not None assert tasks[0].cancel_requested is None assert tasks[0].start_time is not\",\n \"(\\\"Queued schedule '%s' for execution\\\", 'OMF to PI north') == args args, kwargs\",\n \"= mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN\",\n \"North task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True\",\n \"'%s'\\\\n\\\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert 1\",\n \"task.state is not None assert task.cancel_requested is None assert task.start_time is not None\",\n \"assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler =\",\n \"scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not\",\n \"\\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\", \\\"process_name\\\": \\\"stats collector\\\", \\\"schedule_name\\\": \\\"stats\",\n \"task.start_time is not None assert task.end_time is not None assert task.exit_code is '0'\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler,\",\n \"test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"collector\\\", \\\"script\\\": [ \\\"tasks/statistics\\\" ] }, { \\\"name\\\": \\\"backup\\\", \\\"script\\\": [ \\\"tasks/backup_postgres\\\" ]\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules()\",\n \"kwargs = log_info.call_args_list[0] assert 'OMF to PI north' in args assert 'North Readings\",\n \"PI' in args @pytest.mark.asyncio async def test__start_task(self, mocker): # TODO: Mandatory - Add\",\n \"'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): #\",\n \"@pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule)\",\n \"return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", _start_time=current_time - 3600, _paused=False, _task_processes={}) #\",\n \"WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self,\",\n \"# stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time #\",\n \"'North Readings to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule':\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug',\",\n \"that there is no task queued for this schedule at first with pytest.raises(KeyError)\",\n \"Readings to PI\\\", \\\"schedule_name\\\": \\\"OMF to PI north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"00:00:30\\\", \\\"schedule_time\\\":\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time =\",\n \"# WHEN await scheduler._start_task(schedule) # THEN # Confirm that task has started assert\",\n \"pytest.raises(Exception): await scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def\",\n \"len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio @pytest.mark.skip(\\\"_mark_tasks_interrupted() not implemented in main\",\n \"listener south\\\", \\\"schedule_type\\\": 1, \\\"schedule_interval\\\": \\\"00:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\":\",\n \"[call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these exceptions are\",\n \"# WHEN await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2\",\n \"30.0, 'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True)\",\n \"args assert 'North Readings to PI' in args @pytest.mark.asyncio async def test_purge_tasks(self, mocker):\",\n \"= [call('SCHCH', {'schedule': {'name': 'OMF to PI north', 'repeat': 30.0, 'enabled': False, 'type':\",\n \"[ \\\"tasks/backup_postgres\\\" ] }, { \\\"name\\\": \\\"COAP\\\", \\\"script\\\": [ \\\"services/south\\\" ] }, {\",\n \"process: Schedule '%s' process '%s' task %s pid %s\\\\n%s\\\" in args assert 'OMF\",\n \"'2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\\\"Disabled Schedule '%s/%s' process '%s'\\\\n\\\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings\",\n \"'_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\",\",\n \"be None') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234\",\n \"{'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive':\",\n \"schedule.schedule_id == schedule_id assert schedule.name == \\\"purge\\\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat\",\n \"log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") # WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args\",\n \"from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \\\"<NAME>\\\" __copyright__ =\",\n \"[ ('\\\"Blah\\\" 0 days', True), ('12:30:11', False), ('0 day 12:30:11', False), ('1 day\",\n \"'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\\\"test_interval, is_exception\\\", [ ('\\\"Blah\\\" 0 days', True), ('12:30:11', False), ('0\",\n \"that there is no task queued for mock_schedule with pytest.raises(KeyError) as excinfo: assert\",\n \"return \\\"\\\" # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat\",\n \"[ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"1\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, { \\\"name\\\": \\\"North Readings to\",\n \"def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \\\"\\\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can\",\n \"scheduler.enable_schedule(sch_id) # THEN assert status is True assert message == \\\"Schedule successfully enabled\\\"\",\n \"in 'await' expression\\\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler =\",\n \"None @pytest.mark.asyncio async def test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"'2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls = [call('SCHCH',\",\n \"= mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF\",\n \"tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None\",\n \"'stats collection' in args0 assert 'COAP listener south' in args1 assert 'OMF to\",\n \"= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN #\",\n \"%s' == args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def\",\n \"async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add negative tests for full\",\n \"async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"# Now delete schedule await scheduler.delete_schedule(sch_id) # THEN # Now confirm there is\",\n \"System tests.\\\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): #\",\n \"log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3]\",\n \"{ \\\"description\\\": \\\"The maximum number of tasks that can be running at any\",\n \"in args1 assert 'OMF to PI north' in args2 # As part of\",\n \"copy import pytest from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import *\",\n \"side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") # WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts()\",\n \"async def test_delete_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"def scheduler_fixture(self, mocker): # Changed in version 3.8: patch() now returns an AsyncMock\",\n \"'await' expression\\\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive':\",\n \"mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError)\",\n \"\\\"id\\\": \\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\", \\\"process_name\\\": \\\"North Readings to OCS\\\", \\\"schedule_name\\\": \\\"OMF to OCS north\\\", \\\"schedule_type\\\":\",\n \"\\\"tasks/purge\\\" ] }, { \\\"name\\\": \\\"stats collector\\\", \\\"script\\\": [ \\\"tasks/statistics\\\" ] }, {\",\n \"log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with pytest.raises(Exception)\",\n \"] }, { \\\"name\\\": \\\"North Readings to PI\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"1\\\",\",\n \"Will be tested during System tests.\\\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async\",\n \"# purge schedule # WHEN schedule = await scheduler.get_schedule(schedule_id) # THEN assert isinstance(schedule,\",\n \"disabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2 == log_info.call_count\",\n \"# log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self,\",\n \"async def mock_process(): m = MagicMock() m.pid = 9999 m.terminate = lambda: True\",\n \"time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1]\",\n \"\\\"process_name\\\": \\\"North Readings to OCS\\\", \\\"schedule_name\\\": \\\"OMF to OCS north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\":\",\n \"log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN #\",\n \"lambda: True return m @pytest.allure.feature(\\\"unit\\\") @pytest.allure.story(\\\"scheduler\\\") class TestScheduler: async def scheduler_fixture(self, mocker): #\",\n \"'_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion',\",\n \"scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None,\",\n \"message == \\\"Schedule is already enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is\",\n \"for unit test.\\\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker): pass class MockStorage(StorageClientAsync): def __init__(self,\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) ==\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row\",\n \"0 # 0 for Interval Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive ==\",\n \"0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine\",\n \"= mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task',\",\n \"= {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"start_time\\\"},\",\n \"# Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] =\",\n \"sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0\",\n \"# THEN assert status is True assert message == \\\"Schedule successfully enabled\\\" assert\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info =\",\n \"mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue task\",\n \"_schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN\",\n \"\\\"schedule_interval\\\": \\\"00:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\":\",\n \"\\\"backup\\\", \\\"script\\\": [ \\\"tasks/backup_postgres\\\" ] }, { \\\"name\\\": \\\"COAP\\\", \\\"script\\\": [ \\\"services/south\\\" ]\",\n \"assert 2 == log_info.call_count calls = [call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'),\",\n \"as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule,\",\n \"await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio\",\n \"disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN\",\n \"mock_task_process.process = await asyncio.create_subprocess_exec(\\\"sleep\\\", \\\".1\\\") mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id =\",\n \"'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow(\",\n \"are being raised despite mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception was raised\",\n \"THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): #\",\n \"\\\"schedule_interval\\\": \\\"1 day 00:00:40\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" },\",\n \"# WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() #\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules()\",\n \"return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async\",\n \"'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 ==\",\n \"mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") # WHEN await\",\n \"days (based on the start time), for a rows \\\" \\\"in the tasks\",\n \"self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger =\",\n \"Add negative tests for full code coverage # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"@pytest.mark.skip(\\\"Need a suitable fixture\\\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN scheduler, schedule,\",\n \"= uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \\\"No such Schedule\",\n \"assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count calls\",\n \"@pytest.mark.skip(reason=\\\"To be done\\\") async def test_remove_service_from_task_processes(self): pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): #\",\n \"\\\"schedule_name\\\": \\\"backup hourly\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\",\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN #\",\n \"audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 1 ==\",\n \"log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup await scheduler._get_schedules() # Confirm\",\n \"12:30:11', False), ('1 day 12:40:11', False), ('2 days', True), ('2 days 00:00:59', False),\",\n \"pass @pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"MagicMock can't be used in 'await' expression\\\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async def test_get_scheduled_processes(self, mocker):\",\n \"'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN\",\n \"@pytest.mark.asyncio async def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info =\",\n \"(scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count calls = [call(\\\"Enabled Schedule '%s/%s' process\",\n \"log_params = \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker):\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready',\",\n \"# Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0]\",\n \"> time_before_call assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 =\",\n \"m.terminate = lambda: True return m @pytest.allure.feature(\\\"unit\\\") @pytest.allure.story(\\\"scheduler\\\") class TestScheduler: async def scheduler_fixture(self,\",\n \"# THEN with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None\",\n \"= uuid.uuid4() with pytest.raises(Exception) as excinfo: await scheduler.get_task(task_id) # THEN payload = {\\\"return\\\":\",\n \"== \\\"Schedule is already enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True\",\n \"1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"= mocker.patch.object(scheduler._logger, \\\"exception\\\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules) #\",\n \"is '' assert task.state is not None assert task.cancel_requested is None assert task.start_time\",\n \"\\\"${VERSION}\\\" async def mock_task(): return \\\"\\\" async def mock_process(): m = MagicMock() m.pid\",\n \"repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule,\",\n \"\\\"id\\\": \\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\", \\\"process_name\\\": \\\"backup\\\", \\\"schedule_name\\\": \\\"backup hourly\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\",\",\n \"task completion, sleep above, no task processes should be left pending assert 0\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN schedules =\",\n \"len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True) # WHEN # Now delete schedule await scheduler.delete_schedule(sch_id) #\",\n \"Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 0\",\n \"uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False,\",\n \"Confirm that task has not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN\",\n \"\\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\", \\\"process_name\\\": \\\"stats\",\n \"async def test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"twice in this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__get_process_scripts(self,\",\n \"implementation of above test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False #\",\n \"datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time\",\n \"schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0 # 0\",\n \"temp_schedule assert str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError) as ex: temp_schedule =\",\n \"assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == log_exception.call_count log_params = 'Attempt to delete\",\n \"{ \\\"name\\\": \\\"North Readings to OCS\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"4\\\", \\\"--debug_level\\\", \\\"1\\\"\",\n \"\\\"North Readings to OCS\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"4\\\", \\\"--debug_level\\\", \\\"1\\\" ] },\",\n \"get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async\",\n \"None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN scheduler,\",\n \"'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 ==\",\n \"is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) + 1 == len(scheduler._schedules) assert 1 == audit_logger.call_count\",\n \"GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info\",\n \"@pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO: Mandatory - Add negative tests for\",\n \"north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process =\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler,\",\n \"'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow(\",\n \"None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can not be empty\\\") with pytest.raises(ValueError)\",\n \"1 == first_task.call_count assert 1 == resume_sch.call_count assert 1 == enable_schedule.call_count assert 0\",\n \"if is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count else:\",\n \"with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule)\",\n \"assert scheduler._paused is False assert scheduler._start_time is None calls = [call('Processing stop request'),\",\n \"'_task_processes') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN status,\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap await\",\n \"\\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, ] scheduled_processes = [ { \\\"name\\\": \\\"purge\\\", \\\"script\\\": [\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) #\",\n \"== len(schedules) @pytest.mark.asyncio async def test_get_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"test test__read_config() mocker.patch.object(scheduler, '_read_config', return_value=asyncio.ensure_future(mock_task())) assert scheduler._ready is False # WHEN await scheduler.start()\",\n \"await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule =\",\n \"to PI\\\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After task completion, sleep\",\n \"PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler,\",\n \"in args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence #\",\n \"core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await scheduler._read_storage() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts)\",\n \"await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is not None\",\n \"sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call\",\n \"log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) with pytest.raises(NotReadyError)\",\n \"full code coverage # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"\\\"name\\\": \\\"purge\\\", \\\"script\\\": [ \\\"tasks/purge\\\" ] }, { \\\"name\\\": \\\"stats collector\\\", \\\"script\\\": [\",\n \"queue task and assert that the task has been queued await scheduler.queue_task(schedule.id) assert\",\n \"True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True)\",\n \"== p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"assert 2 == log_info.call_count # args, kwargs = log_info.call_args_list[0] # assert (\\\"Queued schedule\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN\",\n \"any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 1 == enable_schedule.call_count\",\n \"backup # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert status is\",\n \"WHEN # Now delete schedule await scheduler.delete_schedule(sch_id) # THEN # Now confirm there\",\n \"\\\"backup\\\", \\\"schedule_name\\\": \\\"backup hourly\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\":\",\n \"if table_name == 'schedules': return { \\\"count\\\": len(MockStorageAsync.schedules), \\\"rows\\\": MockStorageAsync.schedules } if table_name\",\n \"started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert call(\\\"Queued schedule\",\n \"status is True assert message == \\\"Schedule {} already disabled\\\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id ==\",\n \"side_effect=Exception()) # WHEN with pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks() # THEN\",\n \"WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes'\",\n \"disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert\",\n \"uuid.uuid4(), \\\"name\\\": \\\"Fledge Storage\\\", \\\"type\\\": \\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\":\",\n \"tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time is None assert\",\n \"\\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, ] scheduled_processes = [ { \\\"name\\\": \\\"purge\\\", \\\"script\\\":\",\n \"stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these exceptions are being\",\n \"'tasks': return { \\\"count\\\": len(MockStorageAsync.tasks), \\\"rows\\\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name,\",\n \"def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"@pytest.mark.asyncio async def test_disable_schedule(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger,\",\n \"scheduler._get_schedules() # Confirm no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready', True)\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() #\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler,\",\n \"is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count else: await\",\n \"assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time is not\",\n \"WHEN await scheduler._get_process_scripts() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) @pytest.mark.asyncio async def test__get_process_scripts_exception(self,\",\n \"assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name':\",\n \"len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task()))\",\n \"1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must be of type datetime.time') with\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN status, message = await\",\n \"tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # WHEN schedules = await\",\n \"await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await\",\n \"\\\"f\\\" }, { \\\"id\\\": \\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"COAP\\\", \\\"schedule_name\\\": \\\"COAP listener south\\\", \\\"schedule_type\\\": 1,\",\n \"PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0,\",\n \"in args assert 'North Readings to PI' in args @pytest.mark.asyncio async def test_purge_tasks(self,\",\n \"pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError)\",\n \"== disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"= 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be of type datetime.timedelta')\",\n \"\\\"value\\\": str(task_id)}} args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0] p\",\n \"repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule)\",\n \"import * from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \\\"<NAME>\\\"\",\n \"returns an AsyncMock if the target is an async function. if sys.version_info.major ==\",\n \"to PI north' in args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets\",\n \"args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO: Mandatory - Add negative tests\",\n \"== schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0 # 0 for\",\n \"mock_task_process.schedule = mock_schedule mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions\",\n \"= mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions)\",\n \"= mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN # THEN\",\n \"async def query_tbl(cls, table_name, query=None): if table_name == 'schedules': return { \\\"count\\\": len(MockStorageAsync.schedules),\",\n \"mocking _purge_tasks_task, _scheduler_loop_task calls = [call('An exception was raised by Scheduler._purge_tasks %s', \\\"object\",\n \"@pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"= mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule,\",\n \"\\\"COAP listener south\\\", \\\"schedule_type\\\": 1, \\\"schedule_interval\\\": \\\"00:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\",\",\n \"pass @pytest.mark.asyncio async def test__read_config(self, mocker): async def get_cat(): return { \\\"max_running_tasks\\\": {\",\n \"is not None assert task.cancel_requested is None assert task.start_time is not None assert\",\n \"# GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test\",\n \"== len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task has started assert 1 ==\",\n \"schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not be\",\n \"scheduler.get_schedules() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL))\",\n \"schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules)\",\n \"] }, { \\\"name\\\": \\\"stats collector\\\", \\\"script\\\": [ \\\"tasks/statistics\\\" ] }, { \\\"name\\\":\",\n \"datetime.time() await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be between 1 and 7')\",\n \"with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\\\"_terminate_child_processes() not fit for unit test.\\\") @pytest.mark.asyncio\",\n \"ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert\",\n \"as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as\",\n \"MockStorageAsync.schedules } if table_name == 'scheduled_processes': return { \\\"count\\\": len(MockStorageAsync.scheduled_processes), \\\"rows\\\": MockStorageAsync.scheduled_processes }\",\n \"\\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"limit\\\": 100} args, kwargs = log_exception.call_args assert 'Query failed:\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time)\",\n \"not be empty\\\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat =\",\n \"in args assert 'North Readings to PI' in args args, kwargs = log_info.call_args_list[1]\",\n \"assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task has started assert\",\n \"def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"= uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North # WHEN status, message = await\",\n \"m.pid = 9999 m.terminate = lambda: True return m @pytest.allure.feature(\\\"unit\\\") @pytest.allure.story(\\\"scheduler\\\") class TestScheduler:\",\n \"return { \\\"count\\\": len(MockStorageAsync.tasks), \\\"rows\\\": MockStorageAsync.tasks } @classmethod async def query_tbl(cls, table_name, query=None):\",\n \"assert scheduler._schedule_executions[schedule.id] is True # Now queue task and assert that the task\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # purge schedule\",\n \"__copyright__ = \\\"Copyright (c) 2017 OSIsoft, LLC\\\" __license__ = \\\"Apache 2.0\\\" __version__ =\",\n \"def test__start_task(self, mocker): # TODO: Mandatory - Add negative tests for full code\",\n \"False), ('0 day 12:30:11', False), ('1 day 12:40:11', False), ('2 days', True), ('2\",\n \"sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call\",\n \"'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert 1 ==\",\n \"13:28:14.477868\\\", \\\"end_time\\\": \\\"2018-02-06 13:28:14.856375\\\", \\\"exit_code\\\": \\\"0\\\", \\\"reason\\\": \\\"\\\" } ] def __init__(self, core_management_host=None,\",\n \"uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task()))\",\n \"must be of type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)\",\n \"Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count\",\n \"uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED,\",\n \"\\\"The maximum number of tasks that can be running at any given time\\\",\",\n \"= log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection'\",\n \"\\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") # WHEN # THEN with pytest.raises(Exception): await\",\n \"= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') #\",\n \"core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger,\",\n \"pytest.raises(Exception) as excinfo: tasks = await scheduler.get_tasks() # THEN payload = {\\\"return\\\": [\\\"id\\\",\",\n \"test_queue_task(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"\\\"stats collector\\\", \\\"schedule_name\\\": \\\"stats collection\\\", \\\"schedule_type\\\": 2, \\\"schedule_interval\\\": \\\"00:00:15\\\", \\\"schedule_time\\\": \\\"00:00:15\\\", \\\"schedule_day\\\": 3,\",\n \"asyncio.ensure_future(get_cat()) # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None,\",\n \"Now confirm no schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 ==\",\n \"main Scheduler class.\\\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker):\",\n \"repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN # THEN with pytest.raises(ValueError) as ex:\",\n \"= uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30,\",\n \"mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task queued for this schedule\",\n \"Changed in version 3.8: patch() now returns an AsyncMock if the target is\",\n \"to PI\\\", name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True)\",\n \"schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # purge\",\n \"deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings\",\n \"there is no North task queued for schedule with pytest.raises(KeyError) as excinfo: assert\",\n \"# WHEN # THEN with pytest.raises(TaskNotFoundError) as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio\",\n \"backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN\",\n \"test__get_schedules_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"assert schedule.schedule_id == schedule_id assert schedule.name == \\\"purge\\\" assert schedule.schedule_type == Schedule.Type.MANUAL assert\",\n \"failed: %s' == args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async\",\n \"\\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules)\",\n \"log_exception.call_count log_params = 'Attempt to delete an enabled Schedule %s. Not deleted.', str(sch_id)\",\n \"assert message == \\\"Schedule successfully enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is\",\n \"is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update(self, mocker): @asyncio.coroutine\",\n \"is not None assert tasks[0].end_time is None assert tasks[0].exit_code is None @pytest.mark.asyncio async\",\n \"schedule '%s' for execution\\\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): #\",\n \"async def test__check_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for full\",\n \"PI north', 'repeat': 30.0, 'enabled': False, 'type': Schedule.Type.INTERVAL, 'exclusive': True, 'processName': 'North Readings\",\n \"@pytest.allure.story(\\\"scheduler\\\") class TestScheduler: async def scheduler_fixture(self, mocker): # Changed in version 3.8: patch()\",\n \"}, { \\\"id\\\": \\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"schedule_name\\\": \\\"OMF to PI\",\n \"assert 'stats collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self, mocker): # TODO: Mandatory\",\n \"__author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright (c) 2017 OSIsoft, LLC\\\" __license__ = \\\"Apache\",\n \"mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information',\",\n \"'Query failed: %s' == args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio\",\n \"# THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"column\\\": \\\"start_time\\\",\",\n \"assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2,\",\n \"Readings to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name':\",\n \"assert status is True assert message == \\\"Schedule is already enabled\\\" assert (scheduler._schedules[sch_id]).id\",\n \"WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def test__check_schedules(self,\",\n \"assert task.cancel_requested is None assert task.start_time is not None assert task.end_time is not\",\n \"assert (scheduler._schedules[sch_id]).enabled is False log_params = \\\"Schedule %s already disabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio\",\n \"= uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call =\",\n \"assert 'stats collection' in args0 assert 'COAP listener south' in args1 assert 'OMF\",\n \"core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes = await scheduler.get_scheduled_processes() #\",\n \"async def test_stop(self, mocker): # TODO: Mandatory - Add negative tests for full\",\n \"\\\"OMF to OCS north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"1 day 00:00:40\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\":\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) # Assert that there is no\",\n \"_ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task\",\n \"# THEN if is_exception is True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1 ==\",\n \"await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None)\",\n \"await scheduler.enable_schedule(random_schedule_id) # THEN log_params = \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio\",\n \"== args[0] p = json.loads(args[1]) assert payload == p @pytest.mark.asyncio async def test_get_tasks(self,\",\n \"schedules = await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def\",\n \"Readings to PI\\\", \\\"state\\\": 1, \\\"start_time\\\": \\\"2018-02-06 13:28:14.477868\\\", \\\"end_time\\\": \\\"2018-02-06 13:28:14.856375\\\", \\\"exit_code\\\": \\\"0\\\",\",\n \"uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False,\",\n \"'_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") schedule_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) await scheduler._get_process_scripts() mocker.patch.object(scheduler, '_ready', True) # WHEN processes = await scheduler.get_scheduled_processes()\",\n \"log_params = 'Attempt to delete an enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params)\",\n \"assert schedule_row[4] is 0 # 0 for Interval Schedule assert schedule.repeat == schedule_row[5]\",\n \"== log_exception.call_count log_params = 'Attempt to delete an enabled Schedule %s. Not deleted.',\",\n \"assert tasks[0].exit_code is '0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule,\",\n \"day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is\",\n \"== enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_update_with_enable_modified(self, mocker): @asyncio.coroutine def\",\n \"no task queued for this schedule at first with pytest.raises(KeyError) as excinfo: assert\",\n \"def query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks': return { \\\"count\\\": len(MockStorageAsync.tasks), \\\"rows\\\":\",\n \"async def test__start_task(self, mocker): # TODO: Mandatory - Add negative tests for full\",\n \"to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls) assert 1 == audit_logger.call_count\",\n \"scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name\",\n \"name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') # WHEN #\",\n \"isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \\\"Queued schedule '%s' for execution\\\", 'purge' # log_info.assert_called_with(*log_params)\",\n \"command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self,\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) #\",\n \"execution\\\", 'OMF to PI north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \\\"Process\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler,\",\n \"len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management port received is %d', 9999)] log_info.assert_has_calls(calls,\",\n \"disabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"= mocker.patch.object(scheduler._logger, \\\"exception\\\") # WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args =\",\n \"repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes =\",\n \"# GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id =\",\n \"= [call('An exception was raised by Scheduler._purge_tasks %s', \\\"object MagicMock can't be used\",\n \"mock_task(): return \\\"\\\" async def mock_process(): m = MagicMock() m.pid = 9999 m.terminate\",\n \"'_ready', True) # Confirm there are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) #\",\n \"await scheduler.cancel_task(task_id) # THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 == log_info.call_count\",\n \"pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day = 0 temp_schedule.time = datetime.time()\",\n \"def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory -\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") await\",\n \"repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True)\",\n \"def test_get_task(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"= mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler,\",\n \"THEN assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 == log_info.call_count # args, kwargs\",\n \"next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call = sch_execution.next_start_time #\",\n \"__version__ = \\\"${VERSION}\\\" async def mock_task(): return \\\"\\\" async def mock_process(): m =\",\n \"# Confirm that task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks\",\n \"= await self.scheduler_fixture(mocker) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch\",\n \"as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules() with pytest.raises(NotReadyError) as\",\n \"self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0,\",\n \"'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 ==\",\n \"# FLEDGE_BEGIN # See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime import uuid\",\n \"# WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def\",\n \"'repeat': 3600.0, 'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN\",\n \"core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger,\",\n \"str(ex).endswith('day must be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\\\"To be done\\\") async def\",\n \"scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can not\",\n \"class MockStorageAsync(StorageClientAsync): schedules = [ { \\\"id\\\": \\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"purge\\\", \\\"schedule_name\\\": \\\"purge\\\", \\\"schedule_type\\\":\",\n \"\\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } @classmethod async def insert_into_tbl(cls, table_name, payload): pass @classmethod\",\n \"= scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess')\",\n \"# WHEN # THEN with pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as\",\n \"log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") # WHEN # THEN\",\n \"async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory\",\n \"mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", _start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN retval = await\",\n \"assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler =\",\n \"async def get_cat(): return { \\\"max_running_tasks\\\": { \\\"description\\\": \\\"The maximum number of tasks\",\n \"scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls\",\n \"'%s/%s' process '%s'\\\\n\\\", 'OMF to PI north', '2b614d26-760f-11e7-b5a5-be2e44b06b34', 'North Readings to PI')] log_info.assert_has_calls(calls)\",\n \"len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management port received is %d',\",\n \"payload == p @pytest.mark.asyncio async def test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"def test_start(self, mocker): # TODO: Mandatory - Add negative tests for full code\",\n \"tasks[0].reason is '' assert tasks[0].state is not None assert tasks[0].cancel_requested is None assert\",\n \"(scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count calls =\",\n \"= None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not be None') with\",\n \"= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await\",\n \"\\\"count\\\": len(MockStorageAsync.schedules), \\\"rows\\\": MockStorageAsync.schedules } if table_name == 'scheduled_processes': return { \\\"count\\\": len(MockStorageAsync.scheduled_processes),\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") log_exception =\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time\",\n \"pytest.raises(NotReadyError) as excinfo: await scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError)\",\n \"'_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes')\",\n \"log_info.call_count # assert call(\\\"Queued schedule '%s' for execution\\\", 'OMF to PI north') ==\",\n \"assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1] args2,\",\n \"assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_new_with_enable_modified(self, mocker):\",\n \"= 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN\",\n \"WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) # THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap await scheduler._get_schedules()\",\n \"\\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North\",\n \"first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True # WHEN await scheduler.queue_task(sch_id)\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time\",\n \"await scheduler._get_schedules() # Confirm no. of schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) mocker.patch.object(scheduler, '_ready',\",\n \"= log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection' in args0 assert 'COAP\",\n \"ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync\",\n \"=[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName': 'TestProcess', 'type': Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True,\",\n \"3.8: patch() now returns an AsyncMock if the target is an async function.\",\n \"100} args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0] p =\",\n \"next_dt) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert 3 ==\",\n \"}, { \\\"name\\\": \\\"stats collector\\\", \\\"script\\\": [ \\\"tasks/statistics\\\" ] }, { \\\"name\\\": \\\"backup\\\",\",\n \"is True assert schedule.enabled is True assert schedule.process_name == \\\"purge\\\" @pytest.mark.asyncio async def\",\n \"= await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) #\",\n \"== log_exception.call_count else: await scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self,\",\n \"_paused=False, _task_processes={}) # WHEN retval = await scheduler.stop() # THEN assert retval is\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mock_schedules =\",\n \"# backup queue_task = mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) #\",\n \"log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s', 'scheduled_processes'), call('Database command: %s', 'schedules')] log_debug.assert_has_calls(calls,\",\n \"mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") random_schedule_id = uuid.uuid4() #\",\n \"north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"00:00:30\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\"\",\n \"is True: with pytest.raises(Exception): await scheduler._get_schedules() assert 1 == log_exception.call_count else: await scheduler._get_schedules()\",\n \"time import json from unittest.mock import MagicMock, call import sys import copy import\",\n \"== \\\"purge\\\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"= \\\"Apache 2.0\\\" __version__ = \\\"${VERSION}\\\" async def mock_task(): return \\\"\\\" async def\",\n \"'_process_scripts', return_value=\\\"North Readings to PI\\\") # WHEN await scheduler._wait_for_task_completion(mock_task_process) # THEN # After\",\n \"# TODO: Find why these exceptions are being raised despite mocking _purge_tasks_task, _scheduler_loop_task\",\n \"\\\"start_time\\\": \\\"2018-02-06 13:28:14.477868\\\", \\\"end_time\\\": \\\"2018-02-06 13:28:14.856375\\\", \\\"exit_code\\\": \\\"0\\\", \\\"reason\\\": \\\"\\\" } ] def\",\n \"'OMF to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\\\"_scheduler_loop() not suitable for unit testing.\",\n \"[call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\\\"Disabled Schedule '%s/%s' process '%s'\\\\n\\\", 'OMF\",\n \"as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = \\\"\\\" await scheduler.save_schedule(temp_schedule) del temp_schedule\",\n \"async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules()\",\n \"\\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" } @classmethod async def insert_into_tbl(cls,\",\n \"assert status is True assert message == \\\"Schedule {} already disabled\\\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id\",\n \"negative tests for full code coverage # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"scheduler._get_schedules() assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN scheduler\",\n \"await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN with\",\n \"core_management_port=None) # WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN\",\n \"return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \\\"get_category_all_items\\\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is None assert\",\n \"= uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio\",\n \"is '' assert tasks[0].state is not None assert tasks[0].cancel_requested is None assert tasks[0].start_time\",\n \"\\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) #\",\n \"'_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task()))\",\n \"mocker): # GIVEN scheduler = Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id,\",\n \"assert 1 == cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks is not None\",\n \"def update_tbl(cls, table_name, payload): # Only valid for test_save_schedule_update if table_name == \\\"schedules\\\":\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready',\",\n \"time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") #\",\n \"import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import * from\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) sch_id\",\n \"GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False)\",\n \"collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch)\",\n \"assert time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1,\",\n \"repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that\",\n \"'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert status\",\n \"mock_task_id = uuid.uuid4() mock_task_process.task_id = mock_task_id mock_task_processes[mock_task_process.task_id] = mock_task_process mock_schedule_executions = dict() mock_schedule_execution\",\n \"'exclusive': False, 'day': 1, 'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert\",\n \"test__wait_for_task_completion(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"= mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process = await asyncio.create_subprocess_exec(\\\"sleep\\\", \\\".1\\\")\",\n \"None assert scheduler._last_task_purge_time is not None @pytest.mark.asyncio async def test__check_purge_tasks(self, mocker): # TODO:\",\n \"# WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert status is True\",\n \"\\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, { \\\"id\\\": \\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\":\",\n \"'schedules')] log_debug.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_stop(self, mocker): # TODO: Mandatory - Add\",\n \"schedule.process_name == tasks[0].process_name assert tasks[0].reason is None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested\",\n \"\\\"process_name\\\": \\\"North Readings to PI\\\", \\\"state\\\": 1, \\\"start_time\\\": \\\"2018-02-06 13:28:14.477868\\\", \\\"end_time\\\": \\\"2018-02-06 13:28:14.856375\\\",\",\n \"day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row)\",\n \"1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id) #\",\n \"'COAP listener south' in args1 assert 'OMF to PI north' in args2 #\",\n \"\\\"--debug_level\\\", \\\"1\\\" ] }, ] tasks = [ { \\\"id\\\": \\\"259b8570-65c1-4b92-8c62-e9642631a600\\\", \\\"process_name\\\": \\\"North\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test\",\n \"== log_info.call_count calls = [call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\\\"Disabled Schedule\",\n \"and sys.version_info.minor >= 8: _rv = await get_cat() else: _rv = asyncio.ensure_future(get_cat()) #\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # WHEN await\",\n \"is True assert message == \\\"Schedule {} already disabled\\\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN await scheduler._get_process_scripts() # THEN assert\",\n \"the North task has been queued await scheduler.queue_task(schedule.id) assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Confirm\",\n \"None assert tasks[0].start_time is not None assert tasks[0].end_time is None assert tasks[0].exit_code is\",\n \"log_info.call_count calls = [call('No Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\\\"Disabled Schedule '%s/%s'\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age',\",\n \"calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these\",\n \"len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler() schedule_id =\",\n \"False log_params = \\\"Schedule %s already disabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self,\",\n \"repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert\",\n \"'_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv)\",\n \"THEN assert 1 == cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks is not\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") sch_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North #\",\n \"log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap mocker.patch.object(scheduler, 'queue_task',\",\n \"{ \\\"name\\\": \\\"purge\\\", \\\"script\\\": [ \\\"tasks/purge\\\" ] }, { \\\"name\\\": \\\"stats collector\\\", \\\"script\\\":\",\n \"\\\"exception\\\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1)))\",\n \"WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self,\",\n \"\\\"1\\\" ] }, ] tasks = [ { \\\"id\\\": \\\"259b8570-65c1-4b92-8c62-e9642631a600\\\", \\\"process_name\\\": \\\"North Readings\",\n \"exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule mock_task_process = scheduler._TaskProcess() mock_task_processes = dict() mock_task_process.process =\",\n \"\\\"info\\\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF\",\n \"# stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time)\",\n \"('2 days 00:00:59', False), ('00:25:61', True) ]) async def test__get_schedules(self, test_interval, is_exception, mocker):\",\n \"log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # purge schedule # WHEN schedule\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task()))\",\n \"schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\",\",\n \"schedule.enabled is True assert schedule.process_name == \\\"purge\\\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): #\",\n \"can not be empty\\\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name\",\n \"scheduler.start() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_scheduled_processes() with pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedules()\",\n \"p @pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params = \\\"Schedule %s already disabled\\\", str(sch_id) log_info.assert_called_with(*log_params)\",\n \"enabled=True) mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # Assert that there is no task\",\n \"@pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None,\",\n \"await scheduler.get_task(task_id) # THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\",\",\n \"message == \\\"Schedule successfully enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True\",\n \"_get_storage_service(self, host, port): return { \\\"id\\\": uuid.uuid4(), \\\"name\\\": \\\"Fledge Storage\\\", \\\"type\\\": \\\"Storage\\\", \\\"service_port\\\":\",\n \"14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now delete schedule with\",\n \"core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings\",\n \"return { \\\"max_running_tasks\\\": { \\\"description\\\": \\\"The maximum number of tasks that can be\",\n \"str(task_id)}} args, kwargs = log_exception.call_args assert 'Query failed: %s' == args[0] p =\",\n \"excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"in args3 @pytest.mark.asyncio async def test__get_process_scripts(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage\",\n \"processes should be left pending assert 0 == len(scheduler._task_processes) assert 0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes)\",\n \"disabled\\\".format(str(sch_id)) assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False log_params = \\\"Schedule %s\",\n \"name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mocker.patch.object(scheduler, '_ready',\",\n \"else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async =\",\n \"first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") enable_schedule\",\n \"mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has not started yet assert 0 ==\",\n \"of type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive =\",\n \"Readings to PI\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"1\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, {\",\n \"test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add\",\n \"'_schedule_first_task') mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", current_time=current_time - 3600) # TODO: Remove\",\n \"@pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"to OCS\\\", \\\"script\\\": [ \\\"tasks/north\\\", \\\"--stream_id\\\", \\\"4\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, ] tasks\",\n \"\\\"Process started: Schedule '%s' process '%s' task %s pid %s, %s running tasks\\\\n%s\\\"\",\n \"WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert status is True assert\",\n \"await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker):\",\n \"task has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task\",\n \"current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat\",\n \"= scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30),\",\n \"= await self.scheduler_fixture(mocker) mocker.patch.object(scheduler, '_ready', False) mocker.patch.object(scheduler, '_paused', True) # WHEN # THEN\",\n \"pytest.raises(NotReadyError) as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError)\",\n \"side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN # THEN with\",\n \"scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence # \\\"stat collector\\\" appears twice in this\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") await scheduler._get_schedules() sch_id =\",\n \"'_schedule_first_task') # log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") await scheduler._get_schedules() sch_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # backup\",\n \"schedule_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # purge schedule # WHEN schedule = await scheduler.get_schedule(schedule_id) #\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') #\",\n \"def test_enable_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"== sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1 == queue_task.call_count calls = [call(\\\"Enabled\",\n \"mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None\",\n \"async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"as excinfo: await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as\",\n \"assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) @pytest.mark.asyncio async def test__get_schedules_exception(self, mocker): # GIVEN scheduler =\",\n \"with pytest.raises(NotReadyError) as excinfo: await scheduler.get_running_tasks() with pytest.raises(NotReadyError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\\\"_terminate_child_processes()\",\n \"excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue task and assert that the\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler,\",\n \"== datetime.timedelta(0, 3600) assert schedule.exclusive is True assert schedule.enabled is True assert schedule.process_name\",\n \"test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id)\",\n \"12:40:11', False), ('2 days', True), ('2 days 00:00:59', False), ('00:25:61', True) ]) async\",\n \"await scheduler.get_tasks() # THEN payload = {\\\"return\\\": [\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\",\",\n \"request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these exceptions are being raised\",\n \"queued for mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now\",\n \"\\\"Schedule successfully disabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is False assert 2\",\n \"await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('repeat must be of type datetime.timedelta') with pytest.raises(ValueError)\",\n \"time_before_call assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1 = log_info.call_args_list[1]\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True)\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler,\",\n \"= await self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules)\",\n \"as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time-3600) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\")\",\n \"scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt\",\n \"%s already disabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN scheduler,\",\n \"mocker.patch.object(scheduler._logger, \\\"exception\\\") # WHEN # THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query\",\n \"{'schedule': {'name': 'Test Schedule', 'enabled': True, 'repeat': 30.0, 'exclusive': False, 'day': 1, 'time':\",\n \"_core_management_host=\\\"0.0.0.0\\\", _start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN retval = await scheduler.stop() #\",\n \"assert message == \\\"Schedule successfully disabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is\",\n \"json from unittest.mock import MagicMock, call import sys import copy import pytest from\",\n \"mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that task has\",\n \"1 == enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False) #\",\n \"4, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, {\",\n \"twice in this list. assert 'stats collection' in args3 @pytest.mark.asyncio async def test__schedule_first_task(self,\",\n \"part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False # WHEN\",\n \"start time), for a rows \\\" \\\"in the tasks table that do not\",\n \"test_cancel_task_all_ok(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker)\",\n \"%s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self, mocker): # GIVEN scheduler = Scheduler()\",\n \"WHEN tasks = await scheduler.get_tasks() # THEN assert schedule.process_name == tasks[0].process_name assert tasks[0].reason\",\n \"assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is not None assert 2 == log_info.call_count # args, kwargs =\",\n \"def test__resume_check_schedules(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\",\n \"None @pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO: Mandatory - Add negative tests\",\n \"\\\"259b8570-65c1-4b92-8c62-e9642631a600\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"state\\\": 1, \\\"start_time\\\": \\\"2018-02-06 13:28:14.477868\\\", \\\"end_time\\\": \\\"2018-02-06\",\n \"assert 'OMF to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\\\"_scheduler_loop() not suitable for unit\",\n \"args1, kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert\",\n \"random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \\\"No such\",\n \"core_management_port) def _get_storage_service(self, host, port): return { \\\"id\\\": uuid.uuid4(), \\\"name\\\": \\\"Fledge Storage\\\", \\\"type\\\":\",\n \"= mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") enable_schedule =\",\n \"as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue task and assert that\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) log_debug = mocker.patch.object(scheduler._logger, 'debug', side_effect=Exception()) # WHEN with\",\n \"= asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None)\",\n \"audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive':\",\n \"# WHEN await scheduler.purge_tasks() # THEN assert scheduler._purge_tasks_task is None assert scheduler._last_task_purge_time is\",\n \"be of type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive\",\n \"process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules)\",\n \"await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"= scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time #\",\n \"== len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule', 'processName':\",\n \"await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.skip(\\\"_terminate_child_processes() not fit for unit test.\\\") @pytest.mark.asyncio async def test__terminate_child_processes(self, mocker):\",\n \"= time.time() curr_time = datetime.datetime.fromtimestamp(current_time) mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\")\",\n \">= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler()\",\n \"# THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_id assert schedule.name == \\\"purge\\\"\",\n \"\\\"process_name\\\": \\\"stats collector\\\", \\\"schedule_name\\\": \\\"stats collection\\\", \\\"schedule_type\\\": 2, \\\"schedule_interval\\\": \\\"00:00:15\\\", \\\"schedule_time\\\": \\\"00:00:15\\\", \\\"schedule_day\\\":\",\n \"mock_process(): m = MagicMock() m.pid = 9999 m.terminate = lambda: True return m\",\n \"scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be between 1 and 7') @pytest.mark.asyncio @pytest.mark.skip(reason=\\\"To\",\n \"process '%s'\\\\n\\\", 'backup hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls\",\n \"# THEN assert scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) ==\",\n \"\\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"start_time\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\",\",\n \"assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule,\",\n \"await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1 == audit_logger.call_count calls\",\n \"3, \\\"exclusive\\\": \\\"f\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\", \\\"process_name\\\": \\\"backup\\\", \\\"schedule_name\\\": \\\"backup\",\n \"log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"@pytest.mark.asyncio @pytest.mark.skip(\\\"_mark_tasks_interrupted() not implemented in main Scheduler class.\\\") async def test__mark_tasks_interrupted(self, mocker): pass\",\n \"= \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): #\",\n \"log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN\",\n \"# Assert that there is no North task queued for schedule with pytest.raises(KeyError)\",\n \"('1 day 12:40:11', False), ('2 days', True), ('2 days 00:00:59', False), ('00:25:61', True)\",\n \"# args, kwargs = log_info.call_args_list[0] # assert (\\\"Queued schedule '%s' for execution\\\", 'OMF\",\n \"log_info.call_args_list[1] assert \\\"Stopping process: Schedule '%s' process '%s' task %s pid %s\\\\n%s\\\" in\",\n \"THEN assert schedule.process_name == task.process_name assert task.reason is '' assert task.state is not\",\n \"mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") #\",\n \"temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name\",\n \"= log_info.call_args_list[2] assert 'stats collection' in args0 assert 'COAP listener south' in args1\",\n \"scheduler._ready is True assert len(scheduler._storage_async.scheduled_processes) == len(scheduler._process_scripts) assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) calls =\",\n \"assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio async def test__check_schedules(self, mocker): # TODO: Mandatory\",\n \"pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del\",\n \"schedule '%s' for execution\\\", 'OMF to PI north') == args args, kwargs =\",\n \"be tested during System tests.\\\") async def test__scheduler_loop(self, mocker): pass @pytest.mark.asyncio async def\",\n \"mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_schedule_next_task') mocker.patch.multiple(scheduler, _schedules=mock_schedules, _task_processes=mock_task_processes, _schedule_executions=mock_schedule_executions) mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to\",\n \"assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \\\"Queued schedule '%s' for execution\\\", 'purge' #\",\n \"= await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4())\",\n \"mocker.patch.object(ConfigurationManager, \\\"create_category\\\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \\\"get_category_all_items\\\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is\",\n \"scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN\",\n \"PI North # WHEN status, message = await scheduler.disable_schedule(sch_id) # THEN assert status\",\n \"@pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules() # THEN\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN\",\n \"\\\"name\\\": \\\"stats collector\\\", \\\"script\\\": [ \\\"tasks/statistics\\\" ] }, { \\\"name\\\": \\\"backup\\\", \\\"script\\\": [\",\n \"part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async\",\n \"PI north' in args assert 'North Readings to PI' in args args, kwargs\",\n \"class.\\\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async def test__read_config(self, mocker): async def\",\n \"Management port received is %d', 9999)] log_info.assert_has_calls(calls, any_order=True) calls = [call('Database command: %s',\",\n \"await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not be None') with pytest.raises(ValueError) as\",\n \"'_terminate_child_processes') mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to\",\n \"WHEN await scheduler._start_task(schedule) # THEN # Confirm that task has started assert 1\",\n \"mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def\",\n \"async def test__read_config(self, mocker): async def get_cat(): return { \\\"max_running_tasks\\\": { \\\"description\\\": \\\"The\",\n \"assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None\",\n \"await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await\",\n \"temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive can not be None')\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() curr_time = datetime.datetime.fromtimestamp(current_time)\",\n \"execution\\\", 'OMF to PI north') == args args, kwargs = log_info.call_args_list[0] assert \\\"Process\",\n \"\\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") return scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio\",\n \"first_task.call_count assert 1 == resume_sch.call_count assert 0 == enable_schedule.call_count assert 0 == disable_schedule.call_count\",\n \"as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule\",\n \"is '0' @pytest.mark.skip(\\\"Need a suitable fixture\\\") @pytest.mark.asyncio async def test_get_task_not_found(self, mocker): # GIVEN\",\n \"\\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"column\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"column\\\":\",\n \"mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) # WHEN #\",\n \"scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio async def test_not_ready_and_paused(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"south' in args1 assert 'OMF to PI north' in args2 @pytest.mark.asyncio @pytest.mark.skip(\\\"_scheduler_loop() not\",\n \"excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo:\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) #\",\n \"* from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \\\"<NAME>\\\" __copyright__\",\n \"is None assert scheduler._max_completed_task_age is None await scheduler._read_config() # THEN assert 1 ==\",\n \"== len(scheduler._schedules) calls = [call('Starting'), call('Starting Scheduler: Management port received is %d', 9999)]\",\n \"assert scheduler._start_time is None calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) #\",\n \"See: http://fledge-iot.readthedocs.io/ # FLEDGE_END import asyncio import datetime import uuid import time import\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) #\",\n \"assert isinstance(scheduler._schedule_executions[schedule.id], scheduler._ScheduleExecution) # Changed in version 3.8: patch() now returns an AsyncMock\",\n \"id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule =\",\n \"with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue task and\",\n \">= 8: _rv = await get_cat() else: _rv = asyncio.ensure_future(get_cat()) # GIVEN scheduler\",\n \"\\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"column\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"limit\\\": 100}\",\n \"\\\"id\\\": \\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"schedule_name\\\": \\\"OMF to PI north\\\", \\\"schedule_type\\\":\",\n \"\\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, { \\\"id\\\":\",\n \"has not been made assert scheduler._schedule_executions[schedule.id].task_processes[task_id].cancel_requested is None # WHEN await scheduler.cancel_task(task_id) #\",\n \"import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__ = \\\"<NAME>\\\" __copyright__ = \\\"Copyright (c)\",\n \"mocker.patch.object(scheduler._logger, \\\"info\\\") await scheduler._get_schedules() sch_id = uuid.UUID(\\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\") # backup mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler,\",\n \"\\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"column\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"limit\\\":\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready',\",\n \"\\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"00:00:30\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" },\",\n \"can be running at any given time\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \\\"value\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS)\",\n \"mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) current_time = time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", _start_time=current_time\",\n \"0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) # Confirm that task has started assert 1\",\n \"1 == resume_sch.call_count assert 1 == enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN\",\n \"args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence # \\\"stat\",\n \"on the start time), for a rows \\\" \\\"in the tasks table that\",\n \"sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap mocker.patch.object(scheduler, 'queue_task', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await\",\n \"= scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time)\",\n \"('12:30:11', False), ('0 day 12:30:11', False), ('1 day 12:40:11', False), ('2 days', True),\",\n \"schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue task\",\n \"scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.enable_schedule(uuid.uuid4())\",\n \"] def __init__(self, core_management_host=None, core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return {\",\n \"# THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker):\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time()\",\n \"log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") new_schedules = copy.deepcopy(MockStorageAsync.schedules) new_schedules[5]['schedule_interval'] = test_interval mocker.patch.object(MockStorageAsync, 'schedules', new_schedules)\",\n \"\\\"The maximum age, in days (based on the start time), for a rows\",\n \"= mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler,\",\n \"MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused',\",\n \"'OMF to PI north') == log_info.call_args_list[0] args, kwargs = log_info.call_args_list[0] assert \\\"Process started:\",\n \"= log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] assert 'stats collection' in args0 assert 'COAP\",\n \"that can be running at any given time\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_RUNNING_TASKS), \\\"value\\\":\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mock_schedules = dict() mock_schedule\",\n \"'North Readings to PI' in args @pytest.mark.asyncio async def test__start_task(self, mocker): # TODO:\",\n \"assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN tasks = await scheduler.get_running_tasks() # THEN assert\",\n \"not None assert task.end_time is not None assert task.exit_code is '0' @pytest.mark.skip(\\\"Need a\",\n \"] }, { \\\"name\\\": \\\"COAP\\\", \\\"script\\\": [ \\\"services/south\\\" ] }, { \\\"name\\\": \\\"North\",\n \"PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"test_save_schedule_new_with_enable_modified(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"mocker.patch.object(scheduler, '_ready', True) # WHEN processes = await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes)\",\n \"assert schedule.process_name == \\\"purge\\\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule,\",\n \"await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio\",\n \"THEN with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name = None await\",\n \"cr_cat = mocker.patch.object(ConfigurationManager, \\\"create_category\\\", return_value=asyncio.ensure_future(mock_task())) get_cat = mocker.patch.object(ConfigurationManager, \\\"get_category_all_items\\\", return_value=_rv) # WHEN assert\",\n \"'enabled': True}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_enable_schedule_already_enabled(self, mocker): # GIVEN scheduler, schedule,\",\n \"8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio, 'create_subprocess_exec', return_value=_rv) mocker.patch.object(asyncio,\",\n \"= log_info.call_args_list[3] assert 'stats collection' in args0 assert 'COAP listener south' in args1\",\n \"task.process_name assert task.reason is '' assert task.state is not None assert task.cancel_requested is\",\n \"\\\"t\\\" }, { \\\"id\\\": \\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\", \\\"process_name\\\": \\\"stats collector\\\", \\\"schedule_name\\\": \\\"stats collection\\\", \\\"schedule_type\\\": 2,\",\n \"scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time.mktime(curr_time.timetuple()) assert 4\",\n \"'time': '0:0:0', 'processName': 'TestProcess', 'type': Schedule.Type.TIMED}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count assert\",\n \"= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time must\",\n \"time_after_call > time_before_call assert 3 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1\",\n \"return { \\\"count\\\": len(MockStorageAsync.schedules), \\\"rows\\\": MockStorageAsync.schedules } if table_name == 'scheduled_processes': return {\",\n \"__license__ = \\\"Apache 2.0\\\" __version__ = \\\"${VERSION}\\\" async def mock_task(): return \\\"\\\" async\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info =\",\n \"# WHEN next_dt = datetime.datetime.fromtimestamp(sch_execution.next_start_time) next_dt += datetime.timedelta(seconds=sch.repeat_seconds) scheduler._schedule_next_timed_task(sch, sch_execution, next_dt) time_after_call =\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception\",\n \"north') == args args, kwargs = log_info.call_args_list[0] assert \\\"Process started: Schedule '%s' process\",\n \"part of scheduler._get_schedules(), scheduler._schedule_first_task() also gets executed, hence # \\\"stat collector\\\" appears twice\",\n \"log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup await scheduler._get_schedules()\",\n \"schedule less assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker):\",\n \"Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5))) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is False\",\n \"'%s' task %s pid %s, %s running tasks\\\\n%s\\\" in args assert 'OMF to\",\n \"Scheduler._scheduler_loop %s', \\\"object MagicMock can't be used in 'await' expression\\\")] log_exception.assert_has_calls(calls) @pytest.mark.asyncio async\",\n \"\\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"end_time\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"where\\\": {\\\"column\\\": \\\"id\\\", \\\"condition\\\": \\\"=\\\", \\\"value\\\": str(task_id)}}\",\n \"Readings to OCS\\\", \\\"schedule_name\\\": \\\"OMF to OCS north\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"1 day\",\n \"WHEN await scheduler.queue_task(sch_id) # THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \\\"Queued schedule\",\n \"enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN assert\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") new_schedules = copy.deepcopy(MockStorageAsync.schedules)\",\n \"\\\"1 day 00:00:40\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, ]\",\n \"\\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\", \\\"process_name\\\":\",\n \"log_exception.call_args assert 'Query failed: %s' == args[0] p = json.loads(args[1]) assert payload ==\",\n \"\\\"Stopping process: Schedule '%s' process '%s' task %s pid %s\\\\n%s\\\" in args assert\",\n \"args @pytest.mark.asyncio async def test__start_task(self, mocker): # TODO: Mandatory - Add negative tests\",\n \"'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is not None @pytest.mark.asyncio\",\n \"\\\"purge\\\", \\\"schedule_type\\\": 4, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\"\",\n \"schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"scheduler._start_time is None calls = [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO:\",\n \"'exclusive': True, 'processName': 'North Readings to PI'}})] audit_logger.assert_has_calls(calls, any_order=True) @pytest.mark.asyncio async def test_disable_schedule_wrong_schedule_id(self,\",\n \"len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF to PI north' in args assert\",\n \"%s', \\\"object MagicMock can't be used in 'await' expression\\\"), call('An exception was raised\",\n \"log_debug = await self.scheduler_fixture(mocker) # WHEN schedules = await scheduler.get_schedules() # THEN assert\",\n \"@pytest.mark.asyncio async def test__schedule_next_timed_task(self, mocker): # TODO: Mandatory - Add negative tests for\",\n \"'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio @pytest.mark.parametrize(\\\"test_interval, is_exception\\\", [ ('\\\"Blah\\\" 0 days', True),\",\n \"MagicMock can't be used in 'await' expression\\\"), call('An exception was raised by Scheduler._scheduler_loop\",\n \"process '%s' task %s pid %s, %s running tasks\\\\n%s\\\" in args assert 'OMF\",\n \"\\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task(self, mocker): # GIVEN\",\n \"# Confirm there are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN #\",\n \"such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker): # GIVEN scheduler\",\n \"Assert that there is no North task queued for schedule with pytest.raises(KeyError) as\",\n \"@pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"= uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] # WHEN\",\n \"log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_queue_task_schedule_not_found(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage =\",\n \"not None assert tasks[0].end_time is None assert tasks[0].exit_code is None @pytest.mark.asyncio async def\",\n \"Schedule.Type.INTERVAL, 'repeat': 30.0, 'enabled': True, 'exclusive': False}})] audit_logger.assert_has_calls(calls, any_order=True) assert 1 == first_task.call_count\",\n \"hourly\\\", \\\"schedule_type\\\": 3, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\"\",\n \"name=\\\"OMF to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] =\",\n \"= [call('Processing stop request'), call('Stopped')] log_info.assert_has_calls(calls, any_order=True) # TODO: Find why these exceptions\",\n \"\\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") #\",\n \"raised by Scheduler._scheduler_loop %s', \\\"object MagicMock can't be used in 'await' expression\\\")] log_exception.assert_has_calls(calls)\",\n \"assert str(ex).endswith('time must be of type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule =\",\n \"has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks =\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \\\"create_category\\\", return_value=asyncio.ensure_future(mock_task()))\",\n \"async def test_get_schedules(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"Schedule '%s' process '%s' task %s pid %s, %s running tasks\\\\n%s\\\" in args\",\n \"assert 'OMF to PI north' in args2 # As part of scheduler._get_schedules(), scheduler._schedule_first_task()\",\n \"Task running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\\\"Disabled Schedule '%s/%s' process '%s'\\\\n\\\", 'OMF to\",\n \"be of type datetime.time') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.day\",\n \"# Assert that there is no task queued for this schedule at first\",\n \"8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) scheduler = Scheduler() scheduler._storage\",\n \"= log_info.call_args_list[1] assert \\\"Stopping process: Schedule '%s' process '%s' task %s pid %s\\\\n%s\\\"\",\n \"Only valid for test_save_schedule_update if table_name == \\\"schedules\\\": return {\\\"count\\\": 1} @classmethod async\",\n \"scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True @pytest.mark.asyncio async def test__wait_for_task_completion(self, mocker): #\",\n \"pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await scheduler.disable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError)\",\n \"sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there are\",\n \"scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker): # GIVEN\",\n \"{ \\\"id\\\": \\\"259b8570-65c1-4b92-8c62-e9642631a600\\\", \\\"process_name\\\": \\\"North Readings to PI\\\", \\\"state\\\": 1, \\\"start_time\\\": \\\"2018-02-06 13:28:14.477868\\\",\",\n \"GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) await\",\n \"log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_schedule_first_task', side_effect=Exception()) #\",\n \"calls = [call('SCHCH', {'schedule': {'name': 'OMF to PI north', 'repeat': 30.0, 'enabled': False,\",\n \"Scheduler() schedule_id = uuid.uuid4() schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.INTERVAL, day=0, time=0,\",\n \"Schedule', type=Schedule.Type.INTERVAL, day=0, time=0, repeat=10, repeat_seconds=10, exclusive=False, enabled=True, process_name='TestProcess') # WHEN schedule =\",\n \"\\\"Schedule %s already disabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule(self, mocker): # GIVEN\",\n \"not None assert task.exit_code is '0' @pytest.mark.skip(\\\"Need a suitable fixture\\\") @pytest.mark.asyncio async def\",\n \"HH24:MI:SS.MS\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"column\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"limit\\\": 100} args,\",\n \"'_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await\",\n \"Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert scheduler._check_processes_pending is True\",\n \"scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') schedule\",\n \"assert message == \\\"Schedule is already enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled\",\n \"has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # Confirm that cancel\",\n \"\\\"t\\\" }, { \\\"id\\\": \\\"5d7fed92-fb9a-11e7-8c3f-9a214cf093ae\\\", \\\"process_name\\\": \\\"North Readings to OCS\\\", \\\"schedule_name\\\": \\\"OMF to\",\n \"None') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await\",\n \"= dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF to PI\",\n \"True) ]) async def test__get_schedules(self, test_interval, is_exception, mocker): # GIVEN scheduler = Scheduler()\",\n \"status, message = await scheduler.enable_schedule(sch_id) # THEN assert status is True assert message\",\n \"%s already enabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler,\",\n \"'OMF to PI north') == args args, kwargs = log_info.call_args_list[0] assert \\\"Process started:\",\n \"THEN assert scheduler._check_processes_pending is False # WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task',\",\n \"is False # WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() #\",\n \"len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler,\",\n \"\\\"Fledge Storage\\\", \\\"type\\\": \\\"Storage\\\", \\\"service_port\\\": 9999, \\\"management_port\\\": 9999, \\\"address\\\": \\\"0.0.0.0\\\", \\\"protocol\\\": \\\"http\\\" }\",\n \"await scheduler._get_schedules() log_args = 'Query failed: %s', 'schedules' log_exception.assert_called_once_with(*log_args) @pytest.mark.asyncio async def test__read_storage(self,\",\n \"scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self, mocker): #\",\n \"= await scheduler.get_schedules() # THEN assert len(scheduler._storage_async.schedules) == len(schedules) @pytest.mark.asyncio async def test_get_schedule(self,\",\n \"sch_id = uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North # WHEN status, message =\",\n \"m = MagicMock() m.pid = 9999 m.terminate = lambda: True return m @pytest.allure.feature(\\\"unit\\\")\",\n \"= \\\"\\\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can not be empty\\\") with\",\n \"# Now confirm no schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert 1\",\n \"def test__schedule_first_task(self, mocker): # TODO: Mandatory - Add negative tests for full code\",\n \"\\\"info\\\") return scheduler, schedule, log_info, log_exception, log_error, log_debug @pytest.mark.asyncio async def test__resume_check_schedules(self, mocker):\",\n \"in args assert 'North Readings to PI' in args @pytest.mark.asyncio async def test__start_task(self,\",\n \"scheduler._schedule_executions[sch_id] time_before_call = sch_execution.next_start_time # WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert\",\n \"core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler,\",\n \"for mock_schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is True # Now queue\",\n \"temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.time = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('time\",\n \"'0' @pytest.mark.asyncio async def test_get_tasks_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"\\\"--stream_id\\\", \\\"1\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, { \\\"name\\\": \\\"North Readings to OCS\\\", \\\"script\\\":\",\n \"\\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, { \\\"id\\\": \\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"COAP\\\",\",\n \"uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \\\"No such Schedule %s\\\",\",\n \"async def mock_task(): return \\\"\\\" async def mock_process(): m = MagicMock() m.pid =\",\n \"Readings to PI' in args @pytest.mark.asyncio async def test_cancel_task_exception(self, mocker): # GIVEN scheduler,\",\n \"== len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN tasks = await scheduler.get_tasks() # THEN\",\n \"\\\"exclusive\\\": \\\"f\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\", \\\"process_name\\\": \\\"backup\\\", \\\"schedule_name\\\": \\\"backup hourly\\\",\",\n \"mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler, '_max_completed_task_age', datetime.datetime.now()) # WHEN await scheduler.purge_tasks() # THEN assert\",\n \"process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True) # THEN assert\",\n \"'_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_resume_check_schedules') # WHEN # THEN with pytest.raises(ScheduleNotFoundError) as\",\n \"as excinfo: tasks = await scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN\",\n \"sch_execution = scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert\",\n \"async def query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks': return { \\\"count\\\": len(MockStorageAsync.tasks),\",\n \"[\\\"id\\\", \\\"process_name\\\", \\\"schedule_name\\\", \\\"state\\\", {\\\"alias\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\", \\\"column\\\": \\\"start_time\\\"}, {\\\"alias\\\": \\\"end_time\\\",\",\n \"log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") log_error = mocker.patch.object(scheduler._logger, \\\"error\\\") log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info\",\n \"= uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup await scheduler._get_schedules() # Confirm no. of schedules assert len(scheduler._storage_async.schedules)\",\n \"assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN # Confirm that\",\n \"= await scheduler.get_scheduled_processes() # THEN assert len(scheduler._storage_async.scheduled_processes) == len(processes) @pytest.mark.asyncio async def test_schedule_row_to_schedule(self,\",\n \"async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"\\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\", \\\"process_name\\\": \\\"backup\\\", \\\"schedule_name\\\": \\\"backup hourly\\\", \\\"schedule_type\\\": 3,\",\n \"{\\\"alias\\\": \\\"start_time\\\", \\\"column\\\": \\\"start_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, {\\\"alias\\\": \\\"end_time\\\", \\\"column\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD\",\n \"scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") random_schedule_id = uuid.uuid4()\",\n \"THEN assert isinstance(scheduler._schedule_executions[sch_id], scheduler._ScheduleExecution) # log_params = \\\"Queued schedule '%s' for execution\\\", 'purge'\",\n \"mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler, '_scheduler_loop', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_resume_check_schedules', return_value=asyncio.ensure_future(mock_task())) mocker.patch.object(scheduler, '_purge_tasks_task', return_value=asyncio.ensure_future(asyncio.sleep(.1))) mocker.patch.object(scheduler, '_scheduler_loop_task',\",\n \"= await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule\",\n \"_purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task())) # WHEN scheduler._check_purge_tasks() # THEN assert scheduler._purge_tasks_task is\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\")\",\n \"# WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params = \\\"No such Schedule %s\\\", str(random_schedule_id)\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_info\",\n \"True) # Confirm there are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN\",\n \"'' assert task.state is not None assert task.cancel_requested is None assert task.start_time is\",\n \"schedule_row[8] assert schedule.process_name == schedule_row[9] @pytest.mark.asyncio async def test_get_schedules(self, mocker): # GIVEN scheduler,\",\n \"\\\"--stream_id\\\", \\\"4\\\", \\\"--debug_level\\\", \\\"1\\\" ] }, ] tasks = [ { \\\"id\\\": \\\"259b8570-65c1-4b92-8c62-e9642631a600\\\",\",\n \"Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7] assert schedule.enabled == schedule_row[8]\",\n \"not None assert tasks[0].end_time is not None assert tasks[0].exit_code is '0' @pytest.mark.asyncio async\",\n \"\\\"end_time\\\", \\\"column\\\": \\\"end_time\\\", \\\"format\\\": \\\"YYYY-MM-DD HH24:MI:SS.MS\\\"}, \\\"reason\\\", \\\"exit_code\\\"], \\\"limit\\\": 100} args, kwargs =\",\n \"args @pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests\",\n \"'_wait_for_task_completion') # Confirm that task has not started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes)\",\n \"table_name, condition=None): pass @classmethod async def query_tbl_with_payload(cls, table_name, query_payload): if table_name == 'tasks':\",\n \"log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() sch_id\",\n \"def test_cancel_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"if the target is an async function. if sys.version_info.major == 3 and sys.version_info.minor\",\n \"and sys.version_info.minor >= 8: _rv = await mock_process() else: _rv = asyncio.ensure_future(mock_process()) mocker.patch.object(asyncio,\",\n \"MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') audit_logger =\",\n \"Now queue task and assert that the task has been queued await scheduler.queue_task(schedule.id)\",\n \"scheduler._ScheduleExecution) # log_params = \\\"Queued schedule '%s' for execution\\\", 'purge' # log_info.assert_called_with(*log_params) @pytest.mark.asyncio\",\n \"args3, kwargs3 = log_info.call_args_list[3] assert 'stats collection' in args0 assert 'COAP listener south'\",\n \"scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check IF part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', asyncio.Task(asyncio.sleep(5)))\",\n \"def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await\",\n \"= mocker.patch.object(scheduler._logger, \\\"exception\\\") random_schedule_id = uuid.uuid4() # WHEN await scheduler.disable_schedule(random_schedule_id) # THEN log_params\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_paused', False) mocker.patch.object(scheduler, '_process_scripts',\",\n \"to delete an enabled Schedule %s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def\",\n \"THEN # Now confirm no schedule is deleted assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) assert\",\n \"# THEN assert time_after_call > time_before_call assert 3 == log_info.call_count args0, kwargs0 =\",\n \"scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=0, time=0, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False, enabled=True, process_name='TestProcess') #\",\n \"is True assert schedule.process_name == \\\"purge\\\" @pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN\",\n \"THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1] assert\",\n \"3, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"f\\\" }, {\",\n \"0 == len(scheduler._schedule_executions[mock_schedule.id].task_processes) args, kwargs = log_info.call_args_list[0] assert 'OMF to PI north' in\",\n \"return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info = mocker.patch.object(scheduler._logger, \\\"info\\\")\",\n \"@pytest.mark.skip(\\\"_scheduler_loop() not suitable for unit testing. Will be tested during System tests.\\\") async\",\n \"1, \\\"start_time\\\": \\\"2018-02-06 13:28:14.477868\\\", \\\"end_time\\\": \\\"2018-02-06 13:28:14.856375\\\", \\\"exit_code\\\": \\\"0\\\", \\\"reason\\\": \\\"\\\" } ]\",\n \"kwargs1 = log_info.call_args_list[1] args2, kwargs2 = log_info.call_args_list[2] args3, kwargs3 = log_info.call_args_list[3] assert 'stats\",\n \"schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now delete schedule with pytest.raises(RuntimeWarning):\",\n \"@pytest.mark.asyncio async def test_start(self, mocker): # TODO: Mandatory - Add negative tests for\",\n \"calls = [call('An exception was raised by Scheduler._purge_tasks %s', \\\"object MagicMock can't be\",\n \"target is an async function. if sys.version_info.major == 3 and sys.version_info.minor >= 8:\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _purge_tasks_task=None, _last_task_purge_time=None) mocker.patch.object(scheduler, 'purge_tasks', return_value=asyncio.ensure_future(mock_task()))\",\n \"'debug', side_effect=Exception()) sch_id = uuid.UUID(\\\"d1631422-9ec6-11e7-abc4-cec278b6b50a\\\") # backup # WHEN # THEN with pytest.raises(ScheduleNotFoundError)\",\n \"scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.delete_schedule(uuid.uuid4())\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.multiple(scheduler, _ready=True, _paused=False) mocker.patch.object(scheduler,\",\n \"time_after_call > time.mktime(curr_time.timetuple()) assert 4 == log_info.call_count args0, kwargs0 = log_info.call_args_list[0] args1, kwargs1\",\n \"not implemented in main Scheduler class.\\\") async def test__mark_tasks_interrupted(self, mocker): pass @pytest.mark.asyncio async\",\n \"not be empty\\\") with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.name =\",\n \"mock_schedule_executions = dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler,\",\n \"True assert 1 == queue_task.call_count calls = [call(\\\"Enabled Schedule '%s/%s' process '%s'\\\\n\\\", 'backup\",\n \"== len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id) # THEN\",\n \"\\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\", \\\"process_name\\\": \\\"North Readings\",\n \"uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\") # OMF to PI North # WHEN status, message = await scheduler.disable_schedule(sch_id)\",\n \"= log_info.call_args_list[0] assert \\\"Process started: Schedule '%s' process '%s' task %s pid %s,\",\n \"== len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception,\",\n \"temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('exclusive\",\n \"mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=True)\",\n \"# WHEN scheduler._schedule_next_task(sch) time_after_call = sch_execution.next_start_time # THEN assert time_after_call > time_before_call assert\",\n \"are 14 schedules assert len(scheduler._storage_async.schedules) == len(scheduler._schedules) # WHEN # Now delete schedule\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) mocker.patch.object(scheduler, '_schedule_first_task') mocker.patch.object(scheduler, '_ready',\",\n \"schedule.schedule_id == schedule_row[0] assert schedule.name == schedule_row[1] assert schedule.schedule_type == schedule_row[2] assert schedule_row[3]\",\n \"that do not have a status of running\\\", \\\"type\\\": \\\"integer\\\", \\\"default\\\": str(Scheduler._DEFAULT_MAX_COMPLETED_TASK_AGE_DAYS), \\\"value\\\":\",\n \"1 == len(scheduler._schedules) assert 1 == audit_logger.call_count calls =[call('SCHAD', {'schedule': {'name': 'Test Schedule',\",\n \"WHEN # THEN with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self,\",\n \"fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import * from fledge.common.storage_client.storage_client import StorageClientAsync __author__ =\",\n \"log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) # THEN\",\n \"uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError): schedule = await scheduler.get_schedule(schedule_id) @pytest.mark.asyncio async\",\n \"async def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.exclusive = None await\",\n \"GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4()\",\n \"get_cat = mocker.patch.object(ConfigurationManager, \\\"get_category_all_items\\\", return_value=_rv) # WHEN assert scheduler._max_running_tasks is None assert scheduler._max_completed_task_age\",\n \"assert len(scheduler._storage_async.schedules) - 1 == len(scheduler._schedules) @pytest.mark.asyncio async def test_delete_schedule_enabled_schedule(self, mocker): # GIVEN\",\n \"_start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) # WHEN earliest_start_time = await scheduler._check_schedules() #\",\n \"this schedule at first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True #\",\n \"assert tasks[0].cancel_requested is None assert tasks[0].start_time is not None assert tasks[0].end_time is None\",\n \"schedule_row[2] assert schedule_row[3] is 0 # 0 for Interval Schedule assert schedule_row[4] is\",\n \"is None assert tasks[0].start_time is not None assert tasks[0].end_time is not None assert\",\n \"north' in args assert 'North Readings to PI' in args args, kwargs =\",\n \"= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules) + 1\",\n \"assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) task_id = list(scheduler._schedule_executions[schedule.id].task_processes.keys())[0] # WHEN task = await scheduler.get_task(task_id)\",\n \"await self.scheduler_fixture(mocker) # WHEN # THEN with pytest.raises(TaskNotRunningError) as excinfo: await scheduler.cancel_task(uuid.uuid4()) @pytest.mark.asyncio\",\n \"@pytest.mark.asyncio async def test_purge_tasks(self, mocker): # TODO: Mandatory - Add negative tests for\",\n \"any_order=True) # TODO: Find why these exceptions are being raised despite mocking _purge_tasks_task,\",\n \"\\\"http\\\" } class MockStorageAsync(StorageClientAsync): schedules = [ { \\\"id\\\": \\\"cea17db8-6ccc-11e7-907b-a6006ad3dba0\\\", \\\"process_name\\\": \\\"purge\\\", \\\"schedule_name\\\":\",\n \"scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info =\",\n \"_core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", _start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN retval = await scheduler.stop()\",\n \"mocker.patch.object(scheduler, '_resume_check_schedules') mocker.patch.object(scheduler, '_process_scripts', return_value=\\\"North Readings to PI\\\") mocker.patch.object(scheduler, '_wait_for_task_completion') # Confirm that\",\n \"enabled=True, process_name='TestProcess') schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) enable_schedule = mocker.patch.object(scheduler, \\\"enable_schedule\\\", return_value=mock_coro()) disable_schedule =\",\n \"scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"calls = [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName': 'backup', 'exclusive': True,\",\n \"is True # Now queue task and assert that the North task has\",\n \"await scheduler.enable_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.queue_task(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await\",\n \"to PI north' in args2 @pytest.mark.asyncio async def test__schedule_next_task(self, mocker): # TODO: Mandatory\",\n \"sch_id = uuid.UUID(\\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\") # stat collector sch = scheduler._schedules[sch_id] sch_execution = scheduler._schedule_executions[sch_id] #\",\n \"# THEN with pytest.raises(Exception): await scheduler._get_process_scripts() log_args = 'Query failed: %s', 'scheduled_processes' log_exception.assert_called_once_with(*log_args)\",\n \"async def test_save_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug =\",\n \"# THEN assert schedule.process_name == task.process_name assert task.reason is '' assert task.state is\",\n \"scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mocker.patch.object(scheduler,\",\n \"await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) # Confirm there are 14 schedules assert len(scheduler._storage_async.schedules)\",\n \"scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat =\",\n \"str(ex).endswith('repeat must be of type datetime.timedelta') with pytest.raises(ValueError) as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id,\",\n \"that no task has started yet assert 0 == len(scheduler._schedule_executions[schedule.id].task_processes) await scheduler._start_task(schedule) #\",\n \"delete schedule with pytest.raises(RuntimeWarning): await scheduler.delete_schedule(sch_id) # THEN # Now confirm no schedule\",\n \"table_name, payload): pass @classmethod async def update_tbl(cls, table_name, payload): # Only valid for\",\n \"for a rows \\\" \\\"in the tasks table that do not have a\",\n \"scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug =\",\n \"to PI north\\\", type=Schedule.Type.INTERVAL, repeat=datetime.timedelta(seconds=30), repeat_seconds=30, time=None, day=None, exclusive=True, enabled=True) mock_schedules[mock_schedule.id] = mock_schedule\",\n \"WHEN tasks = await scheduler.get_running_tasks() # THEN assert 1 == len(tasks) assert schedule.process_name\",\n \"= mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) first_task = mocker.patch.object(scheduler, '_schedule_first_task') resume_sch = mocker.patch.object(scheduler, '_resume_check_schedules') log_info\",\n \"assert payload == p @pytest.mark.asyncio async def test_get_tasks(self, mocker): # GIVEN scheduler, schedule,\",\n \"await scheduler._get_schedules() schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF to PI\",\n \"any_order=True) assert 1 == first_task.call_count assert 1 == resume_sch.call_count assert 0 == enable_schedule.call_count\",\n \"no North task queued for schedule with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[schedule.id] is\",\n \"running for Schedule %s', '2b614d26-760f-11e7-b5a5-be2e44b06b34'), call(\\\"Disabled Schedule '%s/%s' process '%s'\\\\n\\\", 'OMF to PI\",\n \"\\\"info\\\") current_time = time.time() mocker.patch.multiple(scheduler, _max_running_tasks=10, _start_time=current_time) await scheduler._get_schedules() mocker.patch.object(scheduler, '_start_task', return_value=asyncio.ensure_future(mock_task())) #\",\n \"for this schedule at first with pytest.raises(KeyError) as excinfo: assert scheduler._schedule_executions[sch_id] is True\",\n \"1 == audit_logger.call_count calls = [call('SCHCH', {'schedule': {'name': 'backup hourly', 'type': Schedule.Type.INTERVAL, 'processName':\",\n \"= time.time() mocker.patch.multiple(scheduler, _core_management_port=9999, _core_management_host=\\\"0.0.0.0\\\", _start_time=current_time - 3600, _paused=False, _task_processes={}) # WHEN retval\",\n \"assert schedule.name == \\\"purge\\\" assert schedule.schedule_type == Schedule.Type.MANUAL assert schedule.repeat == datetime.timedelta(0, 3600)\",\n \"as ex: temp_schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) temp_schedule.repeat = 1234 await scheduler.save_schedule(temp_schedule) del temp_schedule\",\n \"\\\"exit_code\\\"], \\\"where\\\": {\\\"column\\\": \\\"id\\\", \\\"condition\\\": \\\"=\\\", \\\"value\\\": str(task_id)}} args, kwargs = log_exception.call_args assert\",\n \"0 for Interval Schedule assert schedule.repeat == schedule_row[5] assert schedule.exclusive == schedule_row[7] assert\",\n \"= MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\", side_effect=Exception()) log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") mocker.patch.object(scheduler,\",\n \"schedule_row) temp_schedule.name = \\\"\\\" await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith(\\\"name can not be\",\n \"== len(scheduler._schedule_executions[schedule.id].task_processes) # WHEN await scheduler._start_task(schedule) # THEN # Confirm that task has\",\n \"with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_get_running_tasks(self, mocker): # GIVEN\",\n \"log_error, log_debug = await self.scheduler_fixture(mocker) random_schedule_id = uuid.uuid4() # WHEN await scheduler.enable_schedule(random_schedule_id) #\",\n \"%s. Not deleted.', str(sch_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_delete_schedule_exception(self, mocker): # GIVEN scheduler,\",\n \"False # WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN\",\n \"== len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert call(\\\"Queued schedule '%s' for execution\\\",\",\n \"= MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) cr_cat = mocker.patch.object(ConfigurationManager, \\\"create_category\\\", return_value=asyncio.ensure_future(mock_task())) get_cat\",\n \"cr_cat.call_count assert 1 == get_cat.call_count assert scheduler._max_running_tasks is not None assert scheduler._max_completed_task_age is\",\n \"= Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger,\",\n \"scheduler.get_running_tasks() # THEN assert 1 == len(tasks) assert schedule.process_name == tasks[0].process_name assert tasks[0].reason\",\n \"log_debug = await self.scheduler_fixture(mocker) schedule_id = uuid.uuid4() # WHEN # THEN with pytest.raises(ScheduleNotFoundError):\",\n \"has started assert 1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert call(\\\"Queued\",\n \"audit_logger = mocker.patch.object(AuditLogger, 'information', return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) #\",\n \"await scheduler.save_schedule(temp_schedule) del temp_schedule assert str(ex).endswith('day must be between 1 and 7') @pytest.mark.asyncio\",\n \"False), ('1 day 12:40:11', False), ('2 days', True), ('2 days 00:00:59', False), ('00:25:61',\",\n \"# THEN assert 1 == disable_schedule.call_count @pytest.mark.asyncio async def test_save_schedule_exception(self, mocker): # GIVEN\",\n \"THEN assert earliest_start_time is not None assert 3 == log_info.call_count args0, kwargs0 =\",\n \"'_schedule_first_task') await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True) mocker.patch.object(scheduler, '_task_processes') log_exception = mocker.patch.object(scheduler._logger, \\\"exception\\\") random_schedule_id\",\n \"= scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule) assert schedule.schedule_id == schedule_row[0] assert\",\n \"assert schedule.schedule_type == schedule_row[2] assert schedule_row[3] is 0 # 0 for Interval Schedule\",\n \"\\\"t\\\", \\\"enabled\\\": \\\"t\\\" }, { \\\"id\\\": \\\"2176eb68-7303-11e7-8cf7-a6006ad3dba0\\\", \\\"process_name\\\": \\\"stats collector\\\", \\\"schedule_name\\\": \\\"stats collection\\\",\",\n \"disable_schedule = mocker.patch.object(scheduler, \\\"disable_schedule\\\", return_value=mock_coro()) # WHEN await scheduler.save_schedule(schedule) # THEN assert len(scheduler._storage_async.schedules)\",\n \"scheduler.get_task(uuid.uuid4()) @pytest.mark.asyncio async def test_get_task_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error,\",\n \"from fledge.services.core.scheduler.scheduler import Scheduler, AuditLogger, ConfigurationManager from fledge.services.core.scheduler.entities import * from fledge.services.core.scheduler.exceptions import\",\n \"\\\"purge\\\", \\\"schedule_name\\\": \\\"purge\\\", \\\"schedule_type\\\": 4, \\\"schedule_interval\\\": \\\"01:00:00\\\", \\\"schedule_time\\\": \\\"\\\", \\\"schedule_day\\\": 0, \\\"exclusive\\\": \\\"t\\\",\",\n \"1 == len(scheduler._schedule_executions[schedule.id].task_processes) assert 1 == log_info.call_count # assert call(\\\"Queued schedule '%s' for\",\n \"\\\"Schedule successfully enabled\\\" assert (scheduler._schedules[sch_id]).id == sch_id assert (scheduler._schedules[sch_id]).enabled is True assert 1\",\n \"log_debug = await self.scheduler_fixture(mocker) sch_id = uuid.UUID(\\\"ada12840-68d3-11e7-907b-a6006ad3dba0\\\") #Coap await scheduler._get_schedules() mocker.patch.object(scheduler, '_ready', True)\",\n \"is None assert tasks[0].start_time is not None assert tasks[0].end_time is None assert tasks[0].exit_code\",\n \"enabled\\\", str(sch_id) log_info.assert_called_with(*log_params) @pytest.mark.asyncio async def test_enable_schedule_wrong_schedule_id(self, mocker): # GIVEN scheduler, schedule, log_info,\",\n \"schedule '%s' for execution\\\", 'OMF to PI north') == log_info.call_args_list[0] args, kwargs =\",\n \"# WHEN # Check ELSE part mocker.patch.object(scheduler, '_scheduler_loop_sleep_task', None) scheduler._resume_check_schedules() # THEN assert\",\n \"as excinfo: await scheduler.delete_schedule(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule_not_found(self, mocker): # GIVEN scheduler, schedule,\",\n \"core_management_port=None): super().__init__(core_management_host, core_management_port) def _get_storage_service(self, host, port): return { \\\"id\\\": uuid.uuid4(), \\\"name\\\": \\\"Fledge\",\n \"hourly', 'd1631422-9ec6-11e7-abc4-cec278b6b50a', 'backup')] log_info.assert_has_calls(calls, any_order=True) assert 1 == audit_logger.call_count calls = [call('SCHCH', {'schedule':\",\n \"day 12:40:11', False), ('2 days', True), ('2 days 00:00:59', False), ('00:25:61', True) ])\",\n \"assert 1 == enable_schedule.call_count assert 0 == disable_schedule.call_count # WHEN await scheduler.save_schedule(schedule, is_enabled_modified=False)\",\n \"is None assert tasks[0].state == Task.State.RUNNING assert tasks[0].cancel_requested is None assert tasks[0].start_time is\",\n \"core_management_port=None) log_info = mocker.patch.object(scheduler._logger, \\\"info\\\") mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North\",\n \"await scheduler.get_running_tasks() # THEN assert 1 == len(tasks) assert schedule.process_name == tasks[0].process_name assert\",\n \"= dict() mock_schedule_execution = scheduler._ScheduleExecution() mock_schedule_executions[mock_schedule.id] = mock_schedule_execution mock_schedule_executions[mock_schedule.id].task_processes[mock_task_id] = mock_task_process mocker.patch.object(scheduler, '_resume_check_schedules')\",\n \"expression\\\"), call('An exception was raised by Scheduler._scheduler_loop %s', \\\"object MagicMock can't be used\",\n \"def test_save_schedule_new(self, mocker): @asyncio.coroutine def mock_coro(): return \\\"\\\" # GIVEN scheduler, schedule, log_info,\",\n \"log_params = \\\"No such Schedule %s\\\", str(random_schedule_id) log_exception.assert_called_with(*log_params) @pytest.mark.asyncio async def test_disable_schedule_already_disabled(self, mocker):\",\n \"@pytest.mark.asyncio @pytest.mark.skip(\\\"_scheduler_loop() not suitable for unit testing. Will be tested during System tests.\\\")\",\n \"@pytest.mark.asyncio async def test_get_schedule_exception(self, mocker): # GIVEN scheduler, schedule, log_info, log_exception, log_error, log_debug\",\n \"mock_schedules = dict() mock_schedule = scheduler._ScheduleRow( id=uuid.UUID(\\\"2b614d26-760f-11e7-b5a5-be2e44b06b34\\\"), process_name=\\\"North Readings to PI\\\", name=\\\"OMF to\",\n \"scheduled_processes = [ { \\\"name\\\": \\\"purge\\\", \\\"script\\\": [ \\\"tasks/purge\\\" ] }, { \\\"name\\\":\",\n \"core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) log_debug = mocker.patch.object(scheduler._logger, \\\"debug\\\") log_info = mocker.patch.object(scheduler._logger, \\\"info\\\")\",\n \"process_name='TestProcess') # WHEN schedule = scheduler._schedule_row_to_schedule(schedule_id, schedule_row) # THEN assert isinstance(schedule, Schedule) assert\",\n \"return_value=asyncio.ensure_future(mock_task())) # WHEN status, message = await scheduler.enable_schedule(sch_id) # THEN assert status is\",\n \"North schedule_row = scheduler._ScheduleRow( id=schedule_id, name='Test Schedule', type=Schedule.Type.TIMED, day=1, time=datetime.time(), repeat=datetime.timedelta(seconds=30), repeat_seconds=30, exclusive=False,\",\n \"await scheduler.get_schedule(uuid.uuid4()) with pytest.raises(NotReadyError) as excinfo: await scheduler.save_schedule(Schedule(Schedule.Type.INTERVAL)) with pytest.raises(NotReadyError) as excinfo: await\",\n \"Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async = MockStorageAsync(core_management_host=None, core_management_port=None) # WHEN # Check\",\n \"with pytest.raises(ScheduleNotFoundError) as excinfo: await scheduler.queue_task(uuid.uuid4()) @pytest.mark.asyncio async def test_delete_schedule(self, mocker): # GIVEN\",\n \"def test__get_process_scripts_exception(self, mocker): # GIVEN scheduler = Scheduler() scheduler._storage = MockStorage(core_management_host=None, core_management_port=None) scheduler._storage_async\"\n]","isConversational":false}}},{"rowIdx":1474,"cells":{"ngram":{"kind":"list like","value":["you solve based on the highest calorie to lowest calorie cupcake Args: calorie","\"__main__\": assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3, 2]) == 11","highest calorie to lowest calorie cupcake Args: calorie (list): List of integers denoting","the highest calorie to lowest calorie cupcake Args: calorie (list): List of integers","calories. If Marc has eaten j cupcakes so far, after eating a cupcake","List of integers denoting the calories for each cupcake Returns: int: The minimum","a calorie count, and Marc can walk a distance to expend those calories.","calorie count, and Marc can walk a distance to expend those calories. If","of integers denoting the calories for each cupcake Returns: int: The minimum number","miles to maintain his weight. Solve: To calculate the minimum miles, you solve","expend those calories. If Marc has eaten j cupcakes so far, after eating","== 44 assert marcs_cakewalk([1, 3, 2]) == 11 assert marcs_cakewalk([7, 4, 9, 6])","calorie cupcake Args: calorie (list): List of integers denoting the calories for each","walk to maintain his weight \"\"\" calories = 0 for i, c in","Marc loves cupcakes, but he also likes to stay fit. Each cupcake has","to maintain his weight \"\"\" calories = 0 for i, c in enumerate(sorted(calorie,","x c miles to maintain his weight. Solve: To calculate the minimum miles,","calories if __name__ == \"__main__\": assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1,","in enumerate(sorted(calorie, reverse=True)): calories += (2 ** i * c) return calories if","must walk at least 2**j x c miles to maintain his weight. Solve:","walk at least 2**j x c miles to maintain his weight. Solve: To","denoting the calories for each cupcake Returns: int: The minimum number of miels","each cupcake Returns: int: The minimum number of miels Marc must walk to","he also likes to stay fit. Each cupcake has a calorie count, and","Marc must walk to maintain his weight \"\"\" calories = 0 for i,","maintain his weight \"\"\" calories = 0 for i, c in enumerate(sorted(calorie, reverse=True)):","can walk a distance to expend those calories. If Marc has eaten j","cupcake Args: calorie (list): List of integers denoting the calories for each cupcake","c in enumerate(sorted(calorie, reverse=True)): calories += (2 ** i * c) return calories","distance to expend those calories. If Marc has eaten j cupcakes so far,","calorie to lowest calorie cupcake Args: calorie (list): List of integers denoting the","reverse=True)): calories += (2 ** i * c) return calories if __name__ ==","0 for i, c in enumerate(sorted(calorie, reverse=True)): calories += (2 ** i *","i * c) return calories if __name__ == \"__main__\": assert marcs_cakewalk([5, 10, 7])","** i * c) return calories if __name__ == \"__main__\": assert marcs_cakewalk([5, 10,","with c calories he must walk at least 2**j x c miles to","likes to stay fit. Each cupcake has a calorie count, and Marc can","cupcake with c calories he must walk at least 2**j x c miles","and Marc can walk a distance to expend those calories. If Marc has","his weight \"\"\" calories = 0 for i, c in enumerate(sorted(calorie, reverse=True)): calories","count, and Marc can walk a distance to expend those calories. If Marc","Marc has eaten j cupcakes so far, after eating a cupcake with c","cupcakes so far, after eating a cupcake with c calories he must walk","based on the highest calorie to lowest calorie cupcake Args: calorie (list): List","to expend those calories. If Marc has eaten j cupcakes so far, after","(2 ** i * c) return calories if __name__ == \"__main__\": assert marcs_cakewalk([5,","enumerate(sorted(calorie, reverse=True)): calories += (2 ** i * c) return calories if __name__","eaten j cupcakes so far, after eating a cupcake with c calories he","Marc can walk a distance to expend those calories. If Marc has eaten","minimum miles, you solve based on the highest calorie to lowest calorie cupcake","https://www.hackerrank.com/challenges/marcs-cakewalk/problem Marc loves cupcakes, but he also likes to stay fit. Each cupcake","(list): List of integers denoting the calories for each cupcake Returns: int: The","but he also likes to stay fit. Each cupcake has a calorie count,","must walk to maintain his weight \"\"\" calories = 0 for i, c","calculate the minimum miles, you solve based on the highest calorie to lowest","number of miels Marc must walk to maintain his weight \"\"\" calories =","marcs_cakewalk(calorie): \"\"\"Hackerrank Problem: https://www.hackerrank.com/challenges/marcs-cakewalk/problem Marc loves cupcakes, but he also likes to stay","cupcakes, but he also likes to stay fit. Each cupcake has a calorie","a distance to expend those calories. If Marc has eaten j cupcakes so","The minimum number of miels Marc must walk to maintain his weight \"\"\"","of miels Marc must walk to maintain his weight \"\"\" calories = 0","int: The minimum number of miels Marc must walk to maintain his weight","least 2**j x c miles to maintain his weight. Solve: To calculate the","minimum number of miels Marc must walk to maintain his weight \"\"\" calories","Solve: To calculate the minimum miles, you solve based on the highest calorie","has a calorie count, and Marc can walk a distance to expend those","i, c in enumerate(sorted(calorie, reverse=True)): calories += (2 ** i * c) return","also likes to stay fit. Each cupcake has a calorie count, and Marc","calories he must walk at least 2**j x c miles to maintain his","his weight. Solve: To calculate the minimum miles, you solve based on the","walk a distance to expend those calories. If Marc has eaten j cupcakes","* c) return calories if __name__ == \"__main__\": assert marcs_cakewalk([5, 10, 7]) ==","c calories he must walk at least 2**j x c miles to maintain","to maintain his weight. Solve: To calculate the minimum miles, you solve based","far, after eating a cupcake with c calories he must walk at least","at least 2**j x c miles to maintain his weight. Solve: To calculate","miles, you solve based on the highest calorie to lowest calorie cupcake Args:","To calculate the minimum miles, you solve based on the highest calorie to","Returns: int: The minimum number of miels Marc must walk to maintain his","so far, after eating a cupcake with c calories he must walk at","lowest calorie cupcake Args: calorie (list): List of integers denoting the calories for","for each cupcake Returns: int: The minimum number of miels Marc must walk","\"\"\" calories = 0 for i, c in enumerate(sorted(calorie, reverse=True)): calories += (2","calories += (2 ** i * c) return calories if __name__ == \"__main__\":","assert marcs_cakewalk([1, 3, 2]) == 11 assert marcs_cakewalk([7, 4, 9, 6]) == 79","44 assert marcs_cakewalk([1, 3, 2]) == 11 assert marcs_cakewalk([7, 4, 9, 6]) ==","Args: calorie (list): List of integers denoting the calories for each cupcake Returns:","to stay fit. Each cupcake has a calorie count, and Marc can walk","def marcs_cakewalk(calorie): \"\"\"Hackerrank Problem: https://www.hackerrank.com/challenges/marcs-cakewalk/problem Marc loves cupcakes, but he also likes to","eating a cupcake with c calories he must walk at least 2**j x","== \"__main__\": assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3, 2]) ==","to lowest calorie cupcake Args: calorie (list): List of integers denoting the calories","loves cupcakes, but he also likes to stay fit. Each cupcake has a","calories for each cupcake Returns: int: The minimum number of miels Marc must","weight \"\"\" calories = 0 for i, c in enumerate(sorted(calorie, reverse=True)): calories +=","after eating a cupcake with c calories he must walk at least 2**j","cupcake Returns: int: The minimum number of miels Marc must walk to maintain","he must walk at least 2**j x c miles to maintain his weight.","miels Marc must walk to maintain his weight \"\"\" calories = 0 for","c miles to maintain his weight. Solve: To calculate the minimum miles, you","the calories for each cupcake Returns: int: The minimum number of miels Marc","Each cupcake has a calorie count, and Marc can walk a distance to","marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3, 2]) == 11 assert marcs_cakewalk([7,","integers denoting the calories for each cupcake Returns: int: The minimum number of","maintain his weight. Solve: To calculate the minimum miles, you solve based on","weight. Solve: To calculate the minimum miles, you solve based on the highest","fit. Each cupcake has a calorie count, and Marc can walk a distance","cupcake has a calorie count, and Marc can walk a distance to expend","those calories. If Marc has eaten j cupcakes so far, after eating a","stay fit. Each cupcake has a calorie count, and Marc can walk a","= 0 for i, c in enumerate(sorted(calorie, reverse=True)): calories += (2 ** i","7]) == 44 assert marcs_cakewalk([1, 3, 2]) == 11 assert marcs_cakewalk([7, 4, 9,","assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3, 2]) == 11 assert","for i, c in enumerate(sorted(calorie, reverse=True)): calories += (2 ** i * c)","has eaten j cupcakes so far, after eating a cupcake with c calories","solve based on the highest calorie to lowest calorie cupcake Args: calorie (list):","Problem: https://www.hackerrank.com/challenges/marcs-cakewalk/problem Marc loves cupcakes, but he also likes to stay fit. Each","c) return calories if __name__ == \"__main__\": assert marcs_cakewalk([5, 10, 7]) == 44","on the highest calorie to lowest calorie cupcake Args: calorie (list): List of","calories = 0 for i, c in enumerate(sorted(calorie, reverse=True)): calories += (2 **","If Marc has eaten j cupcakes so far, after eating a cupcake with","if __name__ == \"__main__\": assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3,","return calories if __name__ == \"__main__\": assert marcs_cakewalk([5, 10, 7]) == 44 assert","10, 7]) == 44 assert marcs_cakewalk([1, 3, 2]) == 11 assert marcs_cakewalk([7, 4,","calorie (list): List of integers denoting the calories for each cupcake Returns: int:","\"\"\"Hackerrank Problem: https://www.hackerrank.com/challenges/marcs-cakewalk/problem Marc loves cupcakes, but he also likes to stay fit.","the minimum miles, you solve based on the highest calorie to lowest calorie","a cupcake with c calories he must walk at least 2**j x c","+= (2 ** i * c) return calories if __name__ == \"__main__\": assert","__name__ == \"__main__\": assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3, 2])","j cupcakes so far, after eating a cupcake with c calories he must","2**j x c miles to maintain his weight. Solve: To calculate the minimum"],"string":"[\n \"you solve based on the highest calorie to lowest calorie cupcake Args: calorie\",\n \"\\\"__main__\\\": assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3, 2]) == 11\",\n \"highest calorie to lowest calorie cupcake Args: calorie (list): List of integers denoting\",\n \"the highest calorie to lowest calorie cupcake Args: calorie (list): List of integers\",\n \"calories. If Marc has eaten j cupcakes so far, after eating a cupcake\",\n \"List of integers denoting the calories for each cupcake Returns: int: The minimum\",\n \"a calorie count, and Marc can walk a distance to expend those calories.\",\n \"calorie count, and Marc can walk a distance to expend those calories. If\",\n \"of integers denoting the calories for each cupcake Returns: int: The minimum number\",\n \"miles to maintain his weight. Solve: To calculate the minimum miles, you solve\",\n \"expend those calories. If Marc has eaten j cupcakes so far, after eating\",\n \"== 44 assert marcs_cakewalk([1, 3, 2]) == 11 assert marcs_cakewalk([7, 4, 9, 6])\",\n \"calorie cupcake Args: calorie (list): List of integers denoting the calories for each\",\n \"walk to maintain his weight \\\"\\\"\\\" calories = 0 for i, c in\",\n \"Marc loves cupcakes, but he also likes to stay fit. Each cupcake has\",\n \"to maintain his weight \\\"\\\"\\\" calories = 0 for i, c in enumerate(sorted(calorie,\",\n \"x c miles to maintain his weight. Solve: To calculate the minimum miles,\",\n \"calories if __name__ == \\\"__main__\\\": assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1,\",\n \"in enumerate(sorted(calorie, reverse=True)): calories += (2 ** i * c) return calories if\",\n \"must walk at least 2**j x c miles to maintain his weight. Solve:\",\n \"walk at least 2**j x c miles to maintain his weight. Solve: To\",\n \"denoting the calories for each cupcake Returns: int: The minimum number of miels\",\n \"each cupcake Returns: int: The minimum number of miels Marc must walk to\",\n \"he also likes to stay fit. Each cupcake has a calorie count, and\",\n \"Marc must walk to maintain his weight \\\"\\\"\\\" calories = 0 for i,\",\n \"maintain his weight \\\"\\\"\\\" calories = 0 for i, c in enumerate(sorted(calorie, reverse=True)):\",\n \"can walk a distance to expend those calories. If Marc has eaten j\",\n \"cupcake Args: calorie (list): List of integers denoting the calories for each cupcake\",\n \"c in enumerate(sorted(calorie, reverse=True)): calories += (2 ** i * c) return calories\",\n \"distance to expend those calories. If Marc has eaten j cupcakes so far,\",\n \"calorie to lowest calorie cupcake Args: calorie (list): List of integers denoting the\",\n \"reverse=True)): calories += (2 ** i * c) return calories if __name__ ==\",\n \"0 for i, c in enumerate(sorted(calorie, reverse=True)): calories += (2 ** i *\",\n \"i * c) return calories if __name__ == \\\"__main__\\\": assert marcs_cakewalk([5, 10, 7])\",\n \"** i * c) return calories if __name__ == \\\"__main__\\\": assert marcs_cakewalk([5, 10,\",\n \"with c calories he must walk at least 2**j x c miles to\",\n \"likes to stay fit. Each cupcake has a calorie count, and Marc can\",\n \"cupcake with c calories he must walk at least 2**j x c miles\",\n \"and Marc can walk a distance to expend those calories. If Marc has\",\n \"his weight \\\"\\\"\\\" calories = 0 for i, c in enumerate(sorted(calorie, reverse=True)): calories\",\n \"count, and Marc can walk a distance to expend those calories. If Marc\",\n \"Marc has eaten j cupcakes so far, after eating a cupcake with c\",\n \"cupcakes so far, after eating a cupcake with c calories he must walk\",\n \"based on the highest calorie to lowest calorie cupcake Args: calorie (list): List\",\n \"to expend those calories. If Marc has eaten j cupcakes so far, after\",\n \"(2 ** i * c) return calories if __name__ == \\\"__main__\\\": assert marcs_cakewalk([5,\",\n \"enumerate(sorted(calorie, reverse=True)): calories += (2 ** i * c) return calories if __name__\",\n \"eaten j cupcakes so far, after eating a cupcake with c calories he\",\n \"Marc can walk a distance to expend those calories. If Marc has eaten\",\n \"minimum miles, you solve based on the highest calorie to lowest calorie cupcake\",\n \"https://www.hackerrank.com/challenges/marcs-cakewalk/problem Marc loves cupcakes, but he also likes to stay fit. Each cupcake\",\n \"(list): List of integers denoting the calories for each cupcake Returns: int: The\",\n \"but he also likes to stay fit. Each cupcake has a calorie count,\",\n \"must walk to maintain his weight \\\"\\\"\\\" calories = 0 for i, c\",\n \"calculate the minimum miles, you solve based on the highest calorie to lowest\",\n \"number of miels Marc must walk to maintain his weight \\\"\\\"\\\" calories =\",\n \"marcs_cakewalk(calorie): \\\"\\\"\\\"Hackerrank Problem: https://www.hackerrank.com/challenges/marcs-cakewalk/problem Marc loves cupcakes, but he also likes to stay\",\n \"cupcakes, but he also likes to stay fit. Each cupcake has a calorie\",\n \"a distance to expend those calories. If Marc has eaten j cupcakes so\",\n \"The minimum number of miels Marc must walk to maintain his weight \\\"\\\"\\\"\",\n \"of miels Marc must walk to maintain his weight \\\"\\\"\\\" calories = 0\",\n \"int: The minimum number of miels Marc must walk to maintain his weight\",\n \"least 2**j x c miles to maintain his weight. Solve: To calculate the\",\n \"minimum number of miels Marc must walk to maintain his weight \\\"\\\"\\\" calories\",\n \"Solve: To calculate the minimum miles, you solve based on the highest calorie\",\n \"has a calorie count, and Marc can walk a distance to expend those\",\n \"i, c in enumerate(sorted(calorie, reverse=True)): calories += (2 ** i * c) return\",\n \"also likes to stay fit. Each cupcake has a calorie count, and Marc\",\n \"calories he must walk at least 2**j x c miles to maintain his\",\n \"his weight. Solve: To calculate the minimum miles, you solve based on the\",\n \"walk a distance to expend those calories. If Marc has eaten j cupcakes\",\n \"* c) return calories if __name__ == \\\"__main__\\\": assert marcs_cakewalk([5, 10, 7]) ==\",\n \"c calories he must walk at least 2**j x c miles to maintain\",\n \"to maintain his weight. Solve: To calculate the minimum miles, you solve based\",\n \"far, after eating a cupcake with c calories he must walk at least\",\n \"at least 2**j x c miles to maintain his weight. Solve: To calculate\",\n \"miles, you solve based on the highest calorie to lowest calorie cupcake Args:\",\n \"To calculate the minimum miles, you solve based on the highest calorie to\",\n \"Returns: int: The minimum number of miels Marc must walk to maintain his\",\n \"so far, after eating a cupcake with c calories he must walk at\",\n \"lowest calorie cupcake Args: calorie (list): List of integers denoting the calories for\",\n \"for each cupcake Returns: int: The minimum number of miels Marc must walk\",\n \"\\\"\\\"\\\" calories = 0 for i, c in enumerate(sorted(calorie, reverse=True)): calories += (2\",\n \"calories += (2 ** i * c) return calories if __name__ == \\\"__main__\\\":\",\n \"assert marcs_cakewalk([1, 3, 2]) == 11 assert marcs_cakewalk([7, 4, 9, 6]) == 79\",\n \"44 assert marcs_cakewalk([1, 3, 2]) == 11 assert marcs_cakewalk([7, 4, 9, 6]) ==\",\n \"Args: calorie (list): List of integers denoting the calories for each cupcake Returns:\",\n \"to stay fit. Each cupcake has a calorie count, and Marc can walk\",\n \"def marcs_cakewalk(calorie): \\\"\\\"\\\"Hackerrank Problem: https://www.hackerrank.com/challenges/marcs-cakewalk/problem Marc loves cupcakes, but he also likes to\",\n \"eating a cupcake with c calories he must walk at least 2**j x\",\n \"== \\\"__main__\\\": assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3, 2]) ==\",\n \"to lowest calorie cupcake Args: calorie (list): List of integers denoting the calories\",\n \"loves cupcakes, but he also likes to stay fit. Each cupcake has a\",\n \"calories for each cupcake Returns: int: The minimum number of miels Marc must\",\n \"weight \\\"\\\"\\\" calories = 0 for i, c in enumerate(sorted(calorie, reverse=True)): calories +=\",\n \"after eating a cupcake with c calories he must walk at least 2**j\",\n \"cupcake Returns: int: The minimum number of miels Marc must walk to maintain\",\n \"he must walk at least 2**j x c miles to maintain his weight.\",\n \"miels Marc must walk to maintain his weight \\\"\\\"\\\" calories = 0 for\",\n \"c miles to maintain his weight. Solve: To calculate the minimum miles, you\",\n \"the calories for each cupcake Returns: int: The minimum number of miels Marc\",\n \"Each cupcake has a calorie count, and Marc can walk a distance to\",\n \"marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3, 2]) == 11 assert marcs_cakewalk([7,\",\n \"integers denoting the calories for each cupcake Returns: int: The minimum number of\",\n \"maintain his weight. Solve: To calculate the minimum miles, you solve based on\",\n \"weight. Solve: To calculate the minimum miles, you solve based on the highest\",\n \"fit. Each cupcake has a calorie count, and Marc can walk a distance\",\n \"cupcake has a calorie count, and Marc can walk a distance to expend\",\n \"those calories. If Marc has eaten j cupcakes so far, after eating a\",\n \"stay fit. Each cupcake has a calorie count, and Marc can walk a\",\n \"= 0 for i, c in enumerate(sorted(calorie, reverse=True)): calories += (2 ** i\",\n \"7]) == 44 assert marcs_cakewalk([1, 3, 2]) == 11 assert marcs_cakewalk([7, 4, 9,\",\n \"assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3, 2]) == 11 assert\",\n \"for i, c in enumerate(sorted(calorie, reverse=True)): calories += (2 ** i * c)\",\n \"has eaten j cupcakes so far, after eating a cupcake with c calories\",\n \"solve based on the highest calorie to lowest calorie cupcake Args: calorie (list):\",\n \"Problem: https://www.hackerrank.com/challenges/marcs-cakewalk/problem Marc loves cupcakes, but he also likes to stay fit. Each\",\n \"c) return calories if __name__ == \\\"__main__\\\": assert marcs_cakewalk([5, 10, 7]) == 44\",\n \"on the highest calorie to lowest calorie cupcake Args: calorie (list): List of\",\n \"calories = 0 for i, c in enumerate(sorted(calorie, reverse=True)): calories += (2 **\",\n \"If Marc has eaten j cupcakes so far, after eating a cupcake with\",\n \"if __name__ == \\\"__main__\\\": assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3,\",\n \"return calories if __name__ == \\\"__main__\\\": assert marcs_cakewalk([5, 10, 7]) == 44 assert\",\n \"10, 7]) == 44 assert marcs_cakewalk([1, 3, 2]) == 11 assert marcs_cakewalk([7, 4,\",\n \"calorie (list): List of integers denoting the calories for each cupcake Returns: int:\",\n \"\\\"\\\"\\\"Hackerrank Problem: https://www.hackerrank.com/challenges/marcs-cakewalk/problem Marc loves cupcakes, but he also likes to stay fit.\",\n \"the minimum miles, you solve based on the highest calorie to lowest calorie\",\n \"a cupcake with c calories he must walk at least 2**j x c\",\n \"+= (2 ** i * c) return calories if __name__ == \\\"__main__\\\": assert\",\n \"__name__ == \\\"__main__\\\": assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3, 2])\",\n \"j cupcakes so far, after eating a cupcake with c calories he must\",\n \"2**j x c miles to maintain his weight. Solve: To calculate the minimum\"\n]","isConversational":false}}},{"rowIdx":1475,"cells":{"ngram":{"kind":"list like","value":["context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True) }","state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context = { 'corona_info': info,","info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span',","\"Testaaaa\" corona_html = requests.get(\"https://www.mygov.in/covid-19\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information","information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [ { \"state_name\":","'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [ { \"state_name\": state.find_all('span', class_='st_name')[0].string, \"confirm_case\":","= { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string,","render import requests from bs4 import BeautifulSoup def corona_data(request): \"Testaaaa\" corona_html = requests.get(\"https://www.mygov.in/covid-19\")","'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True) } return render(request, 'coronainfo/index.html',","= soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string,","] context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True)","'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info = { 'update_data':","class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info =","class_='death_case').find('span', class_='icount').string } corona_info = [ { \"state_name\": state.find_all('span', class_='st_name')[0].string, \"confirm_case\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string,","from bs4 import BeautifulSoup def corona_data(request): \"Testaaaa\" corona_html = requests.get(\"https://www.mygov.in/covid-19\") soup = BeautifulSoup(corona_html.content,","class_='icount').string } corona_info = [ { \"state_name\": state.find_all('span', class_='st_name')[0].string, \"confirm_case\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \"active_case\":","= requests.get(\"https://www.mygov.in/covid-19\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div',","'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div',","= [ { \"state_name\": state.find_all('span', class_='st_name')[0].string, \"confirm_case\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \"active_case\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \"discharge\":","in state_wise_data ] context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',',","state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \"active_case\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \"discharge\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \"death\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for","state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \"death\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context =","class_='views-row') information = soup.find('div', class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div',","class_='tick-confirmed')[0].find_all('small')[0].string, \"active_case\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \"discharge\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \"death\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state","[ { \"state_name\": state.find_all('span', class_='st_name')[0].string, \"confirm_case\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \"active_case\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \"discharge\": state.find_all('div',","requests.get(\"https://www.mygov.in/covid-19\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row')","from django.shortcuts import render import requests from bs4 import BeautifulSoup def corona_data(request): \"Testaaaa\"","= soup.find('div', class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string,","'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string }","django.shortcuts import render import requests from bs4 import BeautifulSoup def corona_data(request): \"Testaaaa\" corona_html","class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [","information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info","} for state in state_wise_data ] context = { 'corona_info': info, 'data': sorted(corona_info,","BeautifulSoup def corona_data(request): \"Testaaaa\" corona_html = requests.get(\"https://www.mygov.in/covid-19\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data =","'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [ {","class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context = { 'corona_info': info, 'data':","class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [ { \"state_name\": state.find_all('span',","class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string","state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \"discharge\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \"death\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data","\"state_name\": state.find_all('span', class_='st_name')[0].string, \"confirm_case\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \"active_case\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \"discharge\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \"death\":","state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info = { 'update_data': information.find('div',","class_='st_name')[0].string, \"confirm_case\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \"active_case\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \"discharge\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \"death\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string","import BeautifulSoup def corona_data(request): \"Testaaaa\" corona_html = requests.get(\"https://www.mygov.in/covid-19\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data","information = soup.find('div', class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span',","soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info","\"discharge\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \"death\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context","corona_data(request): \"Testaaaa\" corona_html = requests.get(\"https://www.mygov.in/covid-19\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row')","class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div',","for state in state_wise_data ] context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda","class_='tick-active')[0].find_all('small')[0].string, \"discharge\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \"death\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ]","class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [ { \"state_name\": state.find_all('span', class_='st_name')[0].string,","} corona_info = [ { \"state_name\": state.find_all('span', class_='st_name')[0].string, \"confirm_case\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \"active_case\": state.find_all('div',","class_='tick-discharged')[0].find_all('small')[0].string, \"death\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context = {","BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info = {","corona_info = [ { \"state_name\": state.find_all('span', class_='st_name')[0].string, \"confirm_case\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \"active_case\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string,","{ 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death':","soup.find('div', class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge':","soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case':","bs4 import BeautifulSoup def corona_data(request): \"Testaaaa\" corona_html = requests.get(\"https://www.mygov.in/covid-19\") soup = BeautifulSoup(corona_html.content, 'html.parser')","state in state_wise_data ] context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda i:","information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span',","state_wise_data ] context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))),","information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [ { \"state_name\": state.find_all('span', class_='st_name')[0].string, \"confirm_case\": state.find_all('div',","{ 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True) } return render(request,","corona_html = requests.get(\"https://www.mygov.in/covid-19\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information =","def corona_data(request): \"Testaaaa\" corona_html = requests.get(\"https://www.mygov.in/covid-19\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div',","\"death\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context = { 'corona_info':","= BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info =","requests from bs4 import BeautifulSoup def corona_data(request): \"Testaaaa\" corona_html = requests.get(\"https://www.mygov.in/covid-19\") soup =","= { 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True) } return","state.find_all('span', class_='st_name')[0].string, \"confirm_case\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \"active_case\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \"discharge\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \"death\": state.find_all('div',","\"confirm_case\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \"active_case\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \"discharge\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \"death\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string }","\"active_case\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \"discharge\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \"death\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in","import requests from bs4 import BeautifulSoup def corona_data(request): \"Testaaaa\" corona_html = requests.get(\"https://www.mygov.in/covid-19\") soup","info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True) } return render(request, 'coronainfo/index.html', context)","import render import requests from bs4 import BeautifulSoup def corona_data(request): \"Testaaaa\" corona_html =","{ \"state_name\": state.find_all('span', class_='st_name')[0].string, \"confirm_case\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \"active_case\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \"discharge\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string,"],"string":"[\n \"context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True) }\",\n \"state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context = { 'corona_info': info,\",\n \"info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span',\",\n \"\\\"Testaaaa\\\" corona_html = requests.get(\\\"https://www.mygov.in/covid-19\\\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information\",\n \"information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [ { \\\"state_name\\\":\",\n \"'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [ { \\\"state_name\\\": state.find_all('span', class_='st_name')[0].string, \\\"confirm_case\\\":\",\n \"= { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string,\",\n \"render import requests from bs4 import BeautifulSoup def corona_data(request): \\\"Testaaaa\\\" corona_html = requests.get(\\\"https://www.mygov.in/covid-19\\\")\",\n \"'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True) } return render(request, 'coronainfo/index.html',\",\n \"= soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string,\",\n \"] context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True)\",\n \"'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info = { 'update_data':\",\n \"class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info =\",\n \"class_='death_case').find('span', class_='icount').string } corona_info = [ { \\\"state_name\\\": state.find_all('span', class_='st_name')[0].string, \\\"confirm_case\\\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string,\",\n \"from bs4 import BeautifulSoup def corona_data(request): \\\"Testaaaa\\\" corona_html = requests.get(\\\"https://www.mygov.in/covid-19\\\") soup = BeautifulSoup(corona_html.content,\",\n \"class_='icount').string } corona_info = [ { \\\"state_name\\\": state.find_all('span', class_='st_name')[0].string, \\\"confirm_case\\\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \\\"active_case\\\":\",\n \"= requests.get(\\\"https://www.mygov.in/covid-19\\\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div',\",\n \"'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div',\",\n \"= [ { \\\"state_name\\\": state.find_all('span', class_='st_name')[0].string, \\\"confirm_case\\\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \\\"active_case\\\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \\\"discharge\\\":\",\n \"in state_wise_data ] context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',',\",\n \"state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \\\"active_case\\\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \\\"discharge\\\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \\\"death\\\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for\",\n \"state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \\\"death\\\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context =\",\n \"class_='views-row') information = soup.find('div', class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div',\",\n \"class_='tick-confirmed')[0].find_all('small')[0].string, \\\"active_case\\\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \\\"discharge\\\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \\\"death\\\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state\",\n \"[ { \\\"state_name\\\": state.find_all('span', class_='st_name')[0].string, \\\"confirm_case\\\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \\\"active_case\\\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \\\"discharge\\\": state.find_all('div',\",\n \"requests.get(\\\"https://www.mygov.in/covid-19\\\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row')\",\n \"from django.shortcuts import render import requests from bs4 import BeautifulSoup def corona_data(request): \\\"Testaaaa\\\"\",\n \"= soup.find('div', class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string,\",\n \"'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string }\",\n \"django.shortcuts import render import requests from bs4 import BeautifulSoup def corona_data(request): \\\"Testaaaa\\\" corona_html\",\n \"class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [\",\n \"information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info\",\n \"} for state in state_wise_data ] context = { 'corona_info': info, 'data': sorted(corona_info,\",\n \"BeautifulSoup def corona_data(request): \\\"Testaaaa\\\" corona_html = requests.get(\\\"https://www.mygov.in/covid-19\\\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data =\",\n \"'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [ {\",\n \"class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context = { 'corona_info': info, 'data':\",\n \"class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [ { \\\"state_name\\\": state.find_all('span',\",\n \"class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string\",\n \"state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \\\"discharge\\\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \\\"death\\\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data\",\n \"\\\"state_name\\\": state.find_all('span', class_='st_name')[0].string, \\\"confirm_case\\\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \\\"active_case\\\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \\\"discharge\\\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \\\"death\\\":\",\n \"state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info = { 'update_data': information.find('div',\",\n \"class_='st_name')[0].string, \\\"confirm_case\\\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \\\"active_case\\\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \\\"discharge\\\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \\\"death\\\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string\",\n \"import BeautifulSoup def corona_data(request): \\\"Testaaaa\\\" corona_html = requests.get(\\\"https://www.mygov.in/covid-19\\\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data\",\n \"information = soup.find('div', class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span',\",\n \"soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info\",\n \"\\\"discharge\\\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \\\"death\\\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context\",\n \"corona_data(request): \\\"Testaaaa\\\" corona_html = requests.get(\\\"https://www.mygov.in/covid-19\\\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row')\",\n \"class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div',\",\n \"for state in state_wise_data ] context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda\",\n \"class_='tick-active')[0].find_all('small')[0].string, \\\"discharge\\\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \\\"death\\\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ]\",\n \"class_='icount').string, 'death': information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [ { \\\"state_name\\\": state.find_all('span', class_='st_name')[0].string,\",\n \"} corona_info = [ { \\\"state_name\\\": state.find_all('span', class_='st_name')[0].string, \\\"confirm_case\\\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \\\"active_case\\\": state.find_all('div',\",\n \"class_='tick-discharged')[0].find_all('small')[0].string, \\\"death\\\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context = {\",\n \"BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info = {\",\n \"corona_info = [ { \\\"state_name\\\": state.find_all('span', class_='st_name')[0].string, \\\"confirm_case\\\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \\\"active_case\\\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string,\",\n \"{ 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death':\",\n \"soup.find('div', class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge':\",\n \"soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info = { 'update_data': information.find('div', class_='info_title').find('span').string, 'active_case':\",\n \"bs4 import BeautifulSoup def corona_data(request): \\\"Testaaaa\\\" corona_html = requests.get(\\\"https://www.mygov.in/covid-19\\\") soup = BeautifulSoup(corona_html.content, 'html.parser')\",\n \"state in state_wise_data ] context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda i:\",\n \"information.find('div', class_='info_title').find('span').string, 'active_case': information.find('div', class_='active-case').find('span', class_='icount').string, 'discharge': information.find('div', class_='discharge').find('span', class_='icount').string, 'death': information.find('div', class_='death_case').find('span',\",\n \"state_wise_data ] context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))),\",\n \"information.find('div', class_='death_case').find('span', class_='icount').string } corona_info = [ { \\\"state_name\\\": state.find_all('span', class_='st_name')[0].string, \\\"confirm_case\\\": state.find_all('div',\",\n \"{ 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True) } return render(request,\",\n \"corona_html = requests.get(\\\"https://www.mygov.in/covid-19\\\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information =\",\n \"def corona_data(request): \\\"Testaaaa\\\" corona_html = requests.get(\\\"https://www.mygov.in/covid-19\\\") soup = BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div',\",\n \"\\\"death\\\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context = { 'corona_info':\",\n \"= BeautifulSoup(corona_html.content, 'html.parser') state_wise_data = soup.find_all('div', class_='views-row') information = soup.find('div', class_='information_row') info =\",\n \"requests from bs4 import BeautifulSoup def corona_data(request): \\\"Testaaaa\\\" corona_html = requests.get(\\\"https://www.mygov.in/covid-19\\\") soup =\",\n \"= { 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True) } return\",\n \"state.find_all('span', class_='st_name')[0].string, \\\"confirm_case\\\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \\\"active_case\\\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \\\"discharge\\\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \\\"death\\\": state.find_all('div',\",\n \"\\\"confirm_case\\\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \\\"active_case\\\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \\\"discharge\\\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \\\"death\\\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string }\",\n \"\\\"active_case\\\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \\\"discharge\\\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string, \\\"death\\\": state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in\",\n \"import requests from bs4 import BeautifulSoup def corona_data(request): \\\"Testaaaa\\\" corona_html = requests.get(\\\"https://www.mygov.in/covid-19\\\") soup\",\n \"info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True) } return render(request, 'coronainfo/index.html', context)\",\n \"import render import requests from bs4 import BeautifulSoup def corona_data(request): \\\"Testaaaa\\\" corona_html =\",\n \"{ \\\"state_name\\\": state.find_all('span', class_='st_name')[0].string, \\\"confirm_case\\\": state.find_all('div', class_='tick-confirmed')[0].find_all('small')[0].string, \\\"active_case\\\": state.find_all('div', class_='tick-active')[0].find_all('small')[0].string, \\\"discharge\\\": state.find_all('div', class_='tick-discharged')[0].find_all('small')[0].string,\"\n]","isConversational":false}}},{"rowIdx":1476,"cells":{"ngram":{"kind":"list like","value":["[] model_out = [] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival =","= open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in the arrival times to","= 'P' times = key_lookup(event, phase, model_dict) if len(times) == 0: phase =","model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return model_dict # lookup time in","with open(filename) as f: for line in f: tmp = line.split() key =","row[2].strip()]) formatted_time = datetime.strptime(row[3], \"%Y-%m-%dT%H:%M:%S.%f\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list","+ 23 if sec_int > 59: sec_int = sec_int - 60 sec_int =","datetime.strptime(row[3], \"%Y-%m-%dT%H:%M:%S.%f\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks","if key in model_dict.keys(): times = model_dict[key] times = time_lookup(event[3], times) return times","times # search for arrivals within the padding time window def time_lookup(t, time_arr):","time_arr: if time > t_lower and time < t_upper: offset = t -","key not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return model_dict #","return times # search for arrivals within the padding time window def time_lookup(t,","picks = {} for arr in arrivals: key = datetime.strftime(arr[3], \"%Y-%m-%dT%H:%M:%S.%f\") key =","f: for ln in f: entry = ln.split() entry = entry[0].strip() entry =","time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf, comp_out): #","and time < t_upper: offset = t - time # or format time","import timedelta # params padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10)","model_dict.keys(): times = model_dict[key] times = time_lookup(event[3], times) return times # search for","f: tmp = line.split() key = tmp[0] + \"-\" + tmp[1] + \"-\"","+ phase) for offset in times: outp_file.write(\" \" + str(offset)) outp_file.write('\\n') outp_file.close() for","truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary (key=truncated timestamp) model_in =","model_dict[key] times = time_lookup(event[3], times) return times # search for arrivals within the","t_lower = t - timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets = []","= datetime.strptime(time, \"%Y-%m-%dT%H:%M:%S\") + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") # ----------------------------------------------------- timestamps.append(time) return","+ etype + \".out\") # ------------------ # read in UW arrival times as","time = time + timedelta(seconds=23) + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") else: sec_int",".in file as a list truth_arr = filter_times(truth_dict, model_in) # filter arrivals to","offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf, comp_out): # write outputs to file","= timedelta(seconds=10) # file dirs parsed_arrivals = [] model_in = [] model_out =","= entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \"-\" + entry[4:6] + \"-\" + entry[6:8]","time.second <=51: time = time + timedelta(seconds=23) + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\")","+ \"-\" + event[1] + \"-\" + phase times = [] if key","SNS, SNP, PXS, PXP] # - phase [P, S, N] Note: N -","+ timedelta(seconds=padding_time) offsets = [] for time in time_arr: if time > t_lower","time + timedelta(seconds=23) + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") else: sec_int = time.second","if key not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return model_dict","event[1] + \"-\" + phase times = [] if key in model_dict.keys(): times","using UW truth data # Test outputs: # - type of event tested","\"\"\" # case 2: run if .mseed files have buggy minutes in the","(.in file) model_dict = read_output_to_dict(outf) # read output file for event in truth_arr:","+ entry[12:14] # ------------- TIME STAMP ISSUES -------------------- # case 1: run if","filtered # read in Caltech model output and create a dictionary def read_output_to_dict(filename):","arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) #","datetime import timedelta # params padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff =","\".out\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\"comparison_out/comp.\" + etype + \".out\") # ------------------ # read","'P' times = key_lookup(event, phase, model_dict) if len(times) == 0: phase = 'N'","list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary (key=truncated timestamp) model_in","+ \"-\" + entry[4:6] + \"-\" + entry[6:8] + \"T\" + entry[8:10] +","time < t_upper: offset = t - time # or format time to","times = time_lookup(event[3], times) return times # search for arrivals within the padding","sec_int - 60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") time = time[:-2]","time > t_lower and time < t_upper: offset = t - time #","key_lookup(event, phase, model_dict): key = event[0] + \"-\" + event[1] + \"-\" +","offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf, comp_out): # write","def read_arrivals_to_arr(filename): model_list = [] with open(filename) as f: for ln in f:","key[0:-7] picks[key] = arr return picks def model_in_to_array(file): timestamps = [] with open(file)","phase, model_dict) if len(times) == 0: if phase == 'P': phase = 'S'","tested [EQS, EQP, SUS, SUP, THS, THP, SNS, SNP, PXS, PXP] # -","in the dictionary def key_lookup(event, phase, model_dict): key = event[0] + \"-\" +","= key_lookup(event, phase, model_dict) if len(times) == 0: phase = 'N' times =","tmp[0] + \"-\" + tmp[1] + \"-\" + tmp[2] try: # fails if","time[:-2] + sec_int time = datetime.strptime(time, \"%Y-%m-%dT%H:%M:%S\") + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\")","\"%Y-%m-%dT%H:%M:%S\") if time.second >=37 and time.second <=51: time = time + timedelta(seconds=23) +","# lookup time in the dictionary def key_lookup(event, phase, model_dict): key = event[0]","+ event[1] + \"-\" + phase times = [] if key in model_dict.keys():","timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets = [] for time in time_arr:","+ timedelta(seconds=23) + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") else: sec_int = time.second +","model_in_to_array(file): timestamps = [] with open(file) as f: for ln in f: entry","open(file) as f: for ln in f: entry = ln.split() entry = entry[0].strip()","output and create a dictionary def read_output_to_dict(filename): model_dict = {} with open(filename) as","== 0: phase = 'N' times = ['nan'] outp_file.write(str(event[5]) + \" \" +","timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs parsed_arrivals = [] model_in = []","= [] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \"parsed_arrivals/\" +","timedelta # params padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) #","array def read_arrivals_to_arr(filename): model_list = [] with open(filename) as f: for ln in","+ \":\" + entry[10:12] + \":\" + entry[12:14] # ------------- TIME STAMP ISSUES","a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) # read in model .in file","entry[8:10] + \":\" + entry[10:12] + \":\" + entry[12:14] # ------------- TIME STAMP","time.second + 23 if sec_int > 59: sec_int = sec_int - 60 sec_int","key in model_in: if key in arrivals: filtered.append(arrivals[key]) return filtered # read in","= [] if key in model_dict.keys(): times = model_dict[key] times = time_lookup(event[3], times)","return picks def model_in_to_array(file): timestamps = [] with open(file) as f: for ln","were passed to the model (.in file) model_dict = read_output_to_dict(outf) # read output","= datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") else: sec_int = time.second + 23 if sec_int > 59:","EQP, SUS, SUP, THS, THP, SNS, SNP, PXS, PXP] # - phase [P,","[] model_dict[key].append(formatted_time) except: pass return model_dict # lookup time in the dictionary def","N - not detected # - model time offset (t_truth - t_model_pick) import","key = key[0:-7] picks[key] = arr return picks def model_in_to_array(file): timestamps = []","in Caltech model output and create a dictionary def read_output_to_dict(filename): model_dict = {}","phase times = [] if key in model_dict.keys(): times = model_dict[key] times =","# search for arrivals within the padding time window def time_lookup(t, time_arr): t_lower","= {} for arr in arrivals: key = datetime.strftime(arr[3], \"%Y-%m-%dT%H:%M:%S.%f\") key = key[0:-7]","= {} with open(filename) as f: for line in f: tmp = line.split()","len(times) == 0: if phase == 'P': phase = 'S' else: phase =","time # or format time to absolute value: abs(t - time) offset =","offsets = [] for time in time_arr: if time > t_lower and time","arr return picks def model_in_to_array(file): timestamps = [] with open(file) as f: for","key_lookup(event, phase, model_dict) if len(times) == 0: phase = 'N' times = ['nan']","dictionary def key_lookup(event, phase, model_dict): key = event[0] + \"-\" + event[1] +","read in model .in file as a list truth_arr = filter_times(truth_dict, model_in) #","- timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets = [] for time in","<=51: time = time + timedelta(seconds=23) + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") else:","for line in f: tmp = line.split() key = tmp[0] + \"-\" +","= key_lookup(event, phase, model_dict) if len(times) == 0: if phase == 'P': phase","\" + str(offset)) outp_file.write('\\n') outp_file.close() for i in range(len(model_out)): execute_script(parsed_arrivals[i], model_in[i], model_out[i], comp_out[i])","datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") \"\"\" # case 2: run if .mseed files have buggy minutes","offset in times: outp_file.write(\" \" + str(offset)) outp_file.write('\\n') outp_file.close() for i in range(len(model_out)):","model_dict): key = event[0] + \"-\" + event[1] + \"-\" + phase times","the model (.in file) model_dict = read_output_to_dict(outf) # read output file for event","picks that were passed to the model (.in file) model_dict = read_output_to_dict(outf) #","+ entry[4:6] + \"-\" + entry[6:8] + \"T\" + entry[8:10] + \":\" +","return timestamps def filter_times(arrivals, model_in): filtered = [] for key in model_in: if","\"-\" + entry[6:8] + \"T\" + entry[8:10] + \":\" + entry[10:12] + \":\"","in UW arrival times as an array def read_arrivals_to_arr(filename): model_list = [] with","create a dictionary def read_output_to_dict(filename): model_dict = {} with open(filename) as f: for","picks[key] = arr return picks def model_in_to_array(file): timestamps = [] with open(file) as","= datetime.strptime(row[3], \"%Y-%m-%dT%H:%M:%S.%f\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals):","time.second >=37 and time.second <=51: time = time + timedelta(seconds=23) + time_diff time","f: row = ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3],","\"%Y-%m-%dT%H:%M:%S\") time = time[:-2] + sec_int time = datetime.strptime(time, \"%Y-%m-%dT%H:%M:%S\") + time_diff time","[] with open(filename) as f: for ln in f: row = ln.split() line","row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \"%Y-%m-%dT%H:%M:%S.%f\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return","[] for key in model_in: if key in arrivals: filtered.append(arrivals[key]) return filtered #","TIME STAMP ISSUES -------------------- # case 1: run if .mseed files have correct","open(filename) as f: for ln in f: row = ln.split() line = []","ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \"%Y-%m-%dT%H:%M:%S.%f\") - fudge_factor","else: phase = 'P' times = key_lookup(event, phase, model_dict) if len(times) == 0:","- not detected # - model time offset (t_truth - t_model_pick) import numpy","the arrival times to a list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to","in model .in file as a list truth_arr = filter_times(truth_dict, model_in) # filter","pass return model_dict # lookup time in the dictionary def key_lookup(event, phase, model_dict):","for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \"parsed_arrivals/\" + etype + \".arrivals.txt\" infile =","= datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") time = time[:-2] + sec_int time = datetime.strptime(time, \"%Y-%m-%dT%H:%M:%S\") +","+ entry[6:8] + \"T\" + entry[8:10] + \":\" + entry[10:12] + \":\" +","numbers formatted_time = datetime.strptime(tmp[3], \"%Y-%m-%dT%H:%M:%S.%f\") if key not in model_dict: model_dict[key] = []","the timestamps time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") if time.second >=37 and time.second <=51: time","+ tmp[1] + \"-\" + tmp[2] try: # fails if date is missing","t + timedelta(seconds=padding_time) offsets = [] for time in time_arr: if time >","times as an array def read_arrivals_to_arr(filename): model_list = [] with open(filename) as f:","from datetime import datetime from datetime import timedelta # params padding_time = 10","1: run if .mseed files have correct timestamps \"\"\" time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\")","model (.in file) model_dict = read_output_to_dict(outf) # read output file for event in","phase [P, S, N] Note: N - not detected # - model time","comp_out): # write outputs to file outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival)","= [] with open(file) as f: for ln in f: entry = ln.split()",">=37 and time.second <=51: time = time + timedelta(seconds=23) + time_diff time =","times = model_dict[key] times = time_lookup(event[3], times) return times # search for arrivals","string import datetime import sys import os import csv from datetime import datetime","# Test outputs: # - type of event tested [EQS, EQP, SUS, SUP,","THP, SNS, SNP, PXS, PXP] # - phase [P, S, N] Note: N","= datetime.strptime(tmp[3], \"%Y-%m-%dT%H:%M:%S.%f\") if key not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except:","SUP, THS, THP, SNS, SNP, PXS, PXP] # - phase [P, S, N]","file for event in truth_arr: phase = event[2] times = key_lookup(event, phase, model_dict)","----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered = [] for key in","= time_lookup(event[3], times) return times # search for arrivals within the padding time","for arr in arrivals: key = datetime.strftime(arr[3], \"%Y-%m-%dT%H:%M:%S.%f\") key = key[0:-7] picks[key] =","model_out = [] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \"parsed_arrivals/\"","- model time offset (t_truth - t_model_pick) import numpy import math import string","\"%Y-%m-%dT%H:%M:%S\") + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") # ----------------------------------------------------- timestamps.append(time) return timestamps def","line in f: tmp = line.split() key = tmp[0] + \"-\" + tmp[1]","\".out\") # ------------------ # read in UW arrival times as an array def","'P': phase = 'S' else: phase = 'P' times = key_lookup(event, phase, model_dict)","# read in model .in file as a list truth_arr = filter_times(truth_dict, model_in)","return offsets def execute_script(arrival, inf, outf, comp_out): # write outputs to file outp_file","SUS, SUP, THS, THP, SNS, SNP, PXS, PXP] # - phase [P, S,","return filtered # read in Caltech model output and create a dictionary def","f: for ln in f: row = ln.split() line = [] line.extend([row[0].strip(), row[1].strip(),","f: for line in f: tmp = line.split() key = tmp[0] + \"-\"","entry = entry[0:4] + \"-\" + entry[4:6] + \"-\" + entry[6:8] + \"T\"","value: abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf,","event[2] times = key_lookup(event, phase, model_dict) if len(times) == 0: if phase ==","= [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \"parsed_arrivals/\" + etype + \".arrivals.txt\"","f: entry = ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4]","truth data # Test outputs: # - type of event tested [EQS, EQP,","of event tested [EQS, EQP, SUS, SUP, THS, THP, SNS, SNP, PXS, PXP]","row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks = {} for arr in arrivals:","+ tmp[2] try: # fails if date is missing floating point numbers formatted_time","+ \"-\" + phase times = [] if key in model_dict.keys(): times =","truth_arr = filter_times(truth_dict, model_in) # filter arrivals to picks that were passed to","file outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in the arrival","{} for arr in arrivals: key = datetime.strftime(arr[3], \"%Y-%m-%dT%H:%M:%S.%f\") key = key[0:-7] picks[key]","timestamps = [] with open(file) as f: for ln in f: entry =","params padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs","read_output_to_dict(filename): model_dict = {} with open(filename) as f: for line in f: tmp","import numpy import math import string import datetime import sys import os import","times = key_lookup(event, phase, model_dict) if len(times) == 0: if phase == 'P':","# convert arrivals to a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) # read","\"%Y-%m-%dT%H:%M:%S.%f\") key = key[0:-7] picks[key] = arr return picks def model_in_to_array(file): timestamps =","[EQS, EQP, SUS, SUP, THS, THP, SNS, SNP, PXS, PXP] # - phase","for ln in f: entry = ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6]","\"%Y-%m-%dT%H:%M:%S\") - fudge_factor # + time_diff (might need to add this) time =","entry[0:4] + \"-\" + entry[4:6] + \"-\" + entry[6:8] + \"T\" + entry[8:10]","floating point numbers formatted_time = datetime.strptime(tmp[3], \"%Y-%m-%dT%H:%M:%S.%f\") if key not in model_dict: model_dict[key]","line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \"%Y-%m-%dT%H:%M:%S.%f\") - fudge_factor line.extend([formatted_time,","else: sec_int = time.second + 23 if sec_int > 59: sec_int = sec_int","return model_dict # lookup time in the dictionary def key_lookup(event, phase, model_dict): key","abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf,","'N' times = ['nan'] outp_file.write(str(event[5]) + \" \" + phase) for offset in","time = time[:-2] + sec_int time = datetime.strptime(time, \"%Y-%m-%dT%H:%M:%S\") + time_diff time =","key in model_dict.keys(): times = model_dict[key] times = time_lookup(event[3], times) return times #","SNP, PXS, PXP] # - phase [P, S, N] Note: N - not","list truth_arr = filter_times(truth_dict, model_in) # filter arrivals to picks that were passed","within the padding time window def time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time)","= entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \"-\" + entry[4:6] +","+ \" \" + phase) for offset in times: outp_file.write(\" \" + str(offset))","= ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \"-\"","missing floating point numbers formatted_time = datetime.strptime(tmp[3], \"%Y-%m-%dT%H:%M:%S.%f\") if key not in model_dict:","in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return model_dict # lookup time","this) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") \"\"\" # case 2: run if .mseed files","padding time window def time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper =","line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \"%Y-%m-%dT%H:%M:%S.%f\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line)","execute_script(arrival, inf, outf, comp_out): # write outputs to file outp_file = open(comp_out, 'w')","read_arrivals_to_arr(arrival) # read in the arrival times to a list truth_dict = arrivals_to_dictionary(truth_arr)","tmp[2] try: # fails if date is missing floating point numbers formatted_time =","+ \":\" + entry[12:14] # ------------- TIME STAMP ISSUES -------------------- # case 1:","model_in): filtered = [] for key in model_in: if key in arrivals: filtered.append(arrivals[key])","time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") time = time[:-2] + sec_int time = datetime.strptime(time, \"%Y-%m-%dT%H:%M:%S\")","that were passed to the model (.in file) model_dict = read_output_to_dict(outf) # read","+ \".arrivals.txt\" infile = \"input_files/GPD.\" + etype + \".in\" outfile = \"output_files/GPD.\" +","= [] with open(filename) as f: for ln in f: row = ln.split()","output file for event in truth_arr: phase = event[2] times = key_lookup(event, phase,","[] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \"parsed_arrivals/\" + etype","ln in f: entry = ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry","datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") - fudge_factor # + time_diff (might need to add this) time","as f: for ln in f: entry = ln.split() entry = entry[0].strip() entry","case 2: run if .mseed files have buggy minutes in the timestamps time","def execute_script(arrival, inf, outf, comp_out): # write outputs to file outp_file = open(comp_out,","to add this) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") \"\"\" # case 2: run if","+ sec_int time = datetime.strptime(time, \"%Y-%m-%dT%H:%M:%S\") + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") #","write outputs to file outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read","'w') truth_arr = read_arrivals_to_arr(arrival) # read in the arrival times to a list","= 'N' times = ['nan'] outp_file.write(str(event[5]) + \" \" + phase) for offset","len(times) == 0: phase = 'N' times = ['nan'] outp_file.write(str(event[5]) + \" \"","entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \"-\" + entry[4:6] + \"-\"","# Script tests GPD model using UW truth data # Test outputs: #","model_list = [] with open(filename) as f: for ln in f: row =","+ time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") else: sec_int = time.second + 23 if","event[0] + \"-\" + event[1] + \"-\" + phase times = [] if","correct timestamps \"\"\" time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") - fudge_factor # + time_diff (might","run if .mseed files have correct timestamps \"\"\" time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") -","sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") time = time[:-2] + sec_int time","timedelta(seconds=padding_time) offsets = [] for time in time_arr: if time > t_lower and","entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \"-\" + entry[4:6] + \"-\" +","open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in the arrival times to a","THS, THP, SNS, SNP, PXS, PXP] # - phase [P, S, N] Note:","\"input_files/GPD.\" + etype + \".in\" outfile = \"output_files/GPD.\" + etype + \".out\" parsed_arrivals.append(arrival)","\":\" + entry[10:12] + \":\" + entry[12:14] # ------------- TIME STAMP ISSUES --------------------","model_in = [] model_out = [] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']:","model_list def arrivals_to_dictionary(arrivals): picks = {} for arr in arrivals: key = datetime.strftime(arr[3],","key = tmp[0] + \"-\" + tmp[1] + \"-\" + tmp[2] try: #","10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs parsed_arrivals = []","\" \" + phase) for offset in times: outp_file.write(\" \" + str(offset)) outp_file.write('\\n')","if phase == 'P': phase = 'S' else: phase = 'P' times =","= datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") \"\"\" # case 2: run if .mseed files have buggy","times) return times # search for arrivals within the padding time window def","model_dict # lookup time in the dictionary def key_lookup(event, phase, model_dict): key =","format time to absolute value: abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return","+ etype + \".out\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\"comparison_out/comp.\" + etype + \".out\") #","import math import string import datetime import sys import os import csv from","from datetime import timedelta # params padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff","model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks = {} for arr in arrivals: key","time = datetime.strptime(time, \"%Y-%m-%dT%H:%M:%S\") + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") # ----------------------------------------------------- timestamps.append(time)","filter_times(arrivals, model_in): filtered = [] for key in model_in: if key in arrivals:","for time in time_arr: if time > t_lower and time < t_upper: offset","import datetime import sys import os import csv from datetime import datetime from","model_out.append(outfile) comp_out.append(\"comparison_out/comp.\" + etype + \".out\") # ------------------ # read in UW arrival","padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs parsed_arrivals","time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") else: sec_int = time.second + 23 if sec_int >","tmp = line.split() key = tmp[0] + \"-\" + tmp[1] + \"-\" +","dictionary def read_output_to_dict(filename): model_dict = {} with open(filename) as f: for line in","\"-\" + tmp[2] try: # fails if date is missing floating point numbers","sys import os import csv from datetime import datetime from datetime import timedelta","model_dict[key].append(formatted_time) except: pass return model_dict # lookup time in the dictionary def key_lookup(event,","truth_arr: phase = event[2] times = key_lookup(event, phase, model_dict) if len(times) == 0:","time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") if time.second >=37 and time.second <=51: time = time","entry = ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] +","file) model_dict = read_output_to_dict(outf) # read output file for event in truth_arr: phase","model output and create a dictionary def read_output_to_dict(filename): model_dict = {} with open(filename)","with open(filename) as f: for ln in f: row = ln.split() line =","\"\"\" time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") - fudge_factor # + time_diff (might need to","arrivals: filtered.append(arrivals[key]) return filtered # read in Caltech model output and create a","time to absolute value: abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets","2: run if .mseed files have buggy minutes in the timestamps time =","== 'P': phase = 'S' else: phase = 'P' times = key_lookup(event, phase,","= read_output_to_dict(outf) # read output file for event in truth_arr: phase = event[2]","\"T\" + entry[8:10] + \":\" + entry[10:12] + \":\" + entry[12:14] # -------------","timestamps \"\"\" time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") - fudge_factor # + time_diff (might need","row = ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \"%Y-%m-%dT%H:%M:%S.%f\")","etype + \".in\" outfile = \"output_files/GPD.\" + etype + \".out\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile)","case 1: run if .mseed files have correct timestamps \"\"\" time = datetime.strptime(entry,","offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf, comp_out): # write outputs to","- 60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") time = time[:-2] +","in times: outp_file.write(\" \" + str(offset)) outp_file.write('\\n') outp_file.close() for i in range(len(model_out)): execute_script(parsed_arrivals[i],","t_upper = t + timedelta(seconds=padding_time) offsets = [] for time in time_arr: if","= model_in_to_array(inf) # read in model .in file as a list truth_arr =","# or format time to absolute value: abs(t - time) offset = offset.total_seconds()","minutes in the timestamps time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") if time.second >=37 and time.second","return model_list def arrivals_to_dictionary(arrivals): picks = {} for arr in arrivals: key =","= ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \"%Y-%m-%dT%H:%M:%S.%f\") -","[] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \"%Y-%m-%dT%H:%M:%S.%f\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()])","# case 2: run if .mseed files have buggy minutes in the timestamps","tmp[1] + \"-\" + tmp[2] try: # fails if date is missing floating","times to a list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary","if len(times) == 0: if phase == 'P': phase = 'S' else: phase","STAMP ISSUES -------------------- # case 1: run if .mseed files have correct timestamps","= [] model_in = [] model_out = [] comp_out = [] for etype","add this) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") \"\"\" # case 2: run if .mseed","= offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf, comp_out): # write outputs","or format time to absolute value: abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset))","if len(times) == 0: phase = 'N' times = ['nan'] outp_file.write(str(event[5]) + \"","time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") - fudge_factor # + time_diff (might need to add","line.split() key = tmp[0] + \"-\" + tmp[1] + \"-\" + tmp[2] try:","UW truth data # Test outputs: # - type of event tested [EQS,","\"-\" + phase times = [] if key in model_dict.keys(): times = model_dict[key]","= t - timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets = [] for","time offset (t_truth - t_model_pick) import numpy import math import string import datetime","= [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \"%Y-%m-%dT%H:%M:%S.%f\") - fudge_factor line.extend([formatted_time, row[4].strip(),","time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets =","offsets def execute_script(arrival, inf, outf, comp_out): # write outputs to file outp_file =","if time.second >=37 and time.second <=51: time = time + timedelta(seconds=23) + time_diff","arrivals to a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) # read in model","datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") time = time[:-2] + sec_int time = datetime.strptime(time, \"%Y-%m-%dT%H:%M:%S\") + time_diff","phase, model_dict) if len(times) == 0: phase = 'N' times = ['nan'] outp_file.write(str(event[5])","as an array def read_arrivals_to_arr(filename): model_list = [] with open(filename) as f: for","\"-\" + entry[4:6] + \"-\" + entry[6:8] + \"T\" + entry[8:10] + \":\"","model_dict) if len(times) == 0: phase = 'N' times = ['nan'] outp_file.write(str(event[5]) +","ISSUES -------------------- # case 1: run if .mseed files have correct timestamps \"\"\"","# read in Caltech model output and create a dictionary def read_output_to_dict(filename): model_dict","type of event tested [EQS, EQP, SUS, SUP, THS, THP, SNS, SNP, PXS,","\"%Y-%m-%dT%H:%M:%S\") else: sec_int = time.second + 23 if sec_int > 59: sec_int =","to absolute value: abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def","in model_dict.keys(): times = model_dict[key] times = time_lookup(event[3], times) return times # search","datetime.strptime(tmp[3], \"%Y-%m-%dT%H:%M:%S.%f\") if key not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass","the dictionary def key_lookup(event, phase, model_dict): key = event[0] + \"-\" + event[1]","timedelta(seconds=10) # file dirs parsed_arrivals = [] model_in = [] model_out = []","phase = event[2] times = key_lookup(event, phase, model_dict) if len(times) == 0: if","# read in UW arrival times as an array def read_arrivals_to_arr(filename): model_list =","line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks = {} for arr","timestamps time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") if time.second >=37 and time.second <=51: time =","file as a list truth_arr = filter_times(truth_dict, model_in) # filter arrivals to picks","datetime import sys import os import csv from datetime import datetime from datetime","key_lookup(event, phase, model_dict) if len(times) == 0: if phase == 'P': phase =","+ time_diff (might need to add this) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") \"\"\" #","if .mseed files have buggy minutes in the timestamps time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\")",".mseed files have buggy minutes in the timestamps time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") if","absolute value: abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival,","a list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary (key=truncated timestamp)","- fudge_factor # + time_diff (might need to add this) time = datetime.strftime(time,","= datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") if time.second >=37 and time.second <=51: time = time +","[] with open(file) as f: for ln in f: entry = ln.split() entry","time_diff (might need to add this) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") \"\"\" # case","formatted_time = datetime.strptime(tmp[3], \"%Y-%m-%dT%H:%M:%S.%f\") if key not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time)","as f: for ln in f: row = ln.split() line = [] line.extend([row[0].strip(),","t_upper: offset = t - time # or format time to absolute value:","= arr return picks def model_in_to_array(file): timestamps = [] with open(file) as f:","times: outp_file.write(\" \" + str(offset)) outp_file.write('\\n') outp_file.close() for i in range(len(model_out)): execute_script(parsed_arrivals[i], model_in[i],","etype + \".out\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\"comparison_out/comp.\" + etype + \".out\") # ------------------","= entry[0:4] + \"-\" + entry[4:6] + \"-\" + entry[6:8] + \"T\" +","is missing floating point numbers formatted_time = datetime.strptime(tmp[3], \"%Y-%m-%dT%H:%M:%S.%f\") if key not in","offset (t_truth - t_model_pick) import numpy import math import string import datetime import","in f: row = ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time =","t - timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets = [] for time","to file outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in the","= t + timedelta(seconds=padding_time) offsets = [] for time in time_arr: if time","entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \"-\" + entry[4:6] + \"-\" + entry[6:8] +","and time.second <=51: time = time + timedelta(seconds=23) + time_diff time = datetime.strftime(time,","parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\"comparison_out/comp.\" + etype + \".out\") # ------------------ # read in","files have buggy minutes in the timestamps time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") if time.second","- t_model_pick) import numpy import math import string import datetime import sys import","# case 1: run if .mseed files have correct timestamps \"\"\" time =","= [] for key in model_in: if key in arrivals: filtered.append(arrivals[key]) return filtered","GPD model using UW truth data # Test outputs: # - type of","S, N] Note: N - not detected # - model time offset (t_truth","to picks that were passed to the model (.in file) model_dict = read_output_to_dict(outf)","model using UW truth data # Test outputs: # - type of event","23 if sec_int > 59: sec_int = sec_int - 60 sec_int = str(sec_int).zfill(2)","time window def time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper = t","row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks = {} for arr in","date is missing floating point numbers formatted_time = datetime.strptime(tmp[3], \"%Y-%m-%dT%H:%M:%S.%f\") if key not","read_output_to_dict(outf) # read output file for event in truth_arr: phase = event[2] times","event in truth_arr: phase = event[2] times = key_lookup(event, phase, model_dict) if len(times)","phase == 'P': phase = 'S' else: phase = 'P' times = key_lookup(event,","fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks = {} for","# read output file for event in truth_arr: phase = event[2] times =","(might need to add this) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") \"\"\" # case 2:","ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \"-\" +","sec_int = time.second + 23 if sec_int > 59: sec_int = sec_int -","= datetime.strftime(arr[3], \"%Y-%m-%dT%H:%M:%S.%f\") key = key[0:-7] picks[key] = arr return picks def model_in_to_array(file):","= read_arrivals_to_arr(arrival) # read in the arrival times to a list truth_dict =","def key_lookup(event, phase, model_dict): key = event[0] + \"-\" + event[1] + \"-\"","= event[0] + \"-\" + event[1] + \"-\" + phase times = []","# filter arrivals to picks that were passed to the model (.in file)","math import string import datetime import sys import os import csv from datetime","\"%Y-%m-%dT%H:%M:%S.%f\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks =","time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") # ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in):","in arrivals: filtered.append(arrivals[key]) return filtered # read in Caltech model output and create","outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in the arrival times","timestamp) model_in = model_in_to_array(inf) # read in model .in file as a list","for ln in f: row = ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()])","# - phase [P, S, N] Note: N - not detected # -","= arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf)","with open(file) as f: for ln in f: entry = ln.split() entry =","numpy import math import string import datetime import sys import os import csv","an array def read_arrivals_to_arr(filename): model_list = [] with open(filename) as f: for ln","in f: tmp = line.split() key = tmp[0] + \"-\" + tmp[1] +","model_in = model_in_to_array(inf) # read in model .in file as a list truth_arr","= 'S' else: phase = 'P' times = key_lookup(event, phase, model_dict) if len(times)","filtered.append(arrivals[key]) return filtered # read in Caltech model output and create a dictionary","Script tests GPD model using UW truth data # Test outputs: # -","run if .mseed files have buggy minutes in the timestamps time = datetime.strptime(entry,",".mseed files have correct timestamps \"\"\" time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") - fudge_factor #","parsed_arrivals = [] model_in = [] model_out = [] comp_out = [] for","read in Caltech model output and create a dictionary def read_output_to_dict(filename): model_dict =","time_diff = timedelta(seconds=10) # file dirs parsed_arrivals = [] model_in = [] model_out","in f: entry = ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry =","csv from datetime import datetime from datetime import timedelta # params padding_time =","= model_dict[key] times = time_lookup(event[3], times) return times # search for arrivals within","+ \".in\" outfile = \"output_files/GPD.\" + etype + \".out\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\"comparison_out/comp.\"","+ \"-\" + entry[6:8] + \"T\" + entry[8:10] + \":\" + entry[10:12] +","filtered = [] for key in model_in: if key in arrivals: filtered.append(arrivals[key]) return","convert arrivals to a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) # read in","as a list truth_arr = filter_times(truth_dict, model_in) # filter arrivals to picks that","\" + phase) for offset in times: outp_file.write(\" \" + str(offset)) outp_file.write('\\n') outp_file.close()","+ \"T\" + entry[8:10] + \":\" + entry[10:12] + \":\" + entry[12:14] #","buggy minutes in the timestamps time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") if time.second >=37 and","etype + \".out\") # ------------------ # read in UW arrival times as an","arrivals_to_dictionary(arrivals): picks = {} for arr in arrivals: key = datetime.strftime(arr[3], \"%Y-%m-%dT%H:%M:%S.%f\") key","in the arrival times to a list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals","arr in arrivals: key = datetime.strftime(arr[3], \"%Y-%m-%dT%H:%M:%S.%f\") key = key[0:-7] picks[key] = arr","model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return model_dict # lookup time in the","filter arrivals to picks that were passed to the model (.in file) model_dict","read_arrivals_to_arr(filename): model_list = [] with open(filename) as f: for ln in f: row","sec_int time = datetime.strptime(time, \"%Y-%m-%dT%H:%M:%S\") + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") # -----------------------------------------------------","timestamps def filter_times(arrivals, model_in): filtered = [] for key in model_in: if key","+ time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") # ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals,","timedelta(seconds=23) + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") else: sec_int = time.second + 23","# ------------- TIME STAMP ISSUES -------------------- # case 1: run if .mseed files","= tmp[0] + \"-\" + tmp[1] + \"-\" + tmp[2] try: # fails","arrivals within the padding time window def time_lookup(t, time_arr): t_lower = t -","Test outputs: # - type of event tested [EQS, EQP, SUS, SUP, THS,","def read_output_to_dict(filename): model_dict = {} with open(filename) as f: for line in f:","etype + \".arrivals.txt\" infile = \"input_files/GPD.\" + etype + \".in\" outfile = \"output_files/GPD.\"","to the model (.in file) model_dict = read_output_to_dict(outf) # read output file for","phase = 'S' else: phase = 'P' times = key_lookup(event, phase, model_dict) if","import string import datetime import sys import os import csv from datetime import","UW arrival times as an array def read_arrivals_to_arr(filename): model_list = [] with open(filename)","- fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks = {}","= 10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs parsed_arrivals =","timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered = [] for key in model_in:","+ etype + \".in\" outfile = \"output_files/GPD.\" + etype + \".out\" parsed_arrivals.append(arrival) model_in.append(infile)","0: phase = 'N' times = ['nan'] outp_file.write(str(event[5]) + \" \" + phase)","= [] model_out = [] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival","= \"parsed_arrivals/\" + etype + \".arrivals.txt\" infile = \"input_files/GPD.\" + etype + \".in\"","for key in model_in: if key in arrivals: filtered.append(arrivals[key]) return filtered # read","= t - time # or format time to absolute value: abs(t -","entry[10:12] + \":\" + entry[12:14] # ------------- TIME STAMP ISSUES -------------------- # case","event tested [EQS, EQP, SUS, SUP, THS, THP, SNS, SNP, PXS, PXP] #","# - model time offset (t_truth - t_model_pick) import numpy import math import","\".arrivals.txt\" infile = \"input_files/GPD.\" + etype + \".in\" outfile = \"output_files/GPD.\" + etype","def time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time)","os import csv from datetime import datetime from datetime import timedelta # params","= str(sec_int).zfill(2) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") time = time[:-2] + sec_int time =","in arrivals: key = datetime.strftime(arr[3], \"%Y-%m-%dT%H:%M:%S.%f\") key = key[0:-7] picks[key] = arr return","= \"output_files/GPD.\" + etype + \".out\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\"comparison_out/comp.\" + etype +","open(filename) as f: for line in f: tmp = line.split() key = tmp[0]","+ etype + \".arrivals.txt\" infile = \"input_files/GPD.\" + etype + \".in\" outfile =","for event in truth_arr: phase = event[2] times = key_lookup(event, phase, model_dict) if","except: pass return model_dict # lookup time in the dictionary def key_lookup(event, phase,","lookup time in the dictionary def key_lookup(event, phase, model_dict): key = event[0] +","have correct timestamps \"\"\" time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") - fudge_factor # + time_diff","key = datetime.strftime(arr[3], \"%Y-%m-%dT%H:%M:%S.%f\") key = key[0:-7] picks[key] = arr return picks def","+ \".out\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\"comparison_out/comp.\" + etype + \".out\") # ------------------ #","\".in\" outfile = \"output_files/GPD.\" + etype + \".out\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\"comparison_out/comp.\" +","sec_int > 59: sec_int = sec_int - 60 sec_int = str(sec_int).zfill(2) time =","datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") # ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered = []","datetime from datetime import timedelta # params padding_time = 10 fudge_factor = timedelta(seconds=27)","picks def model_in_to_array(file): timestamps = [] with open(file) as f: for ln in","fails if date is missing floating point numbers formatted_time = datetime.strptime(tmp[3], \"%Y-%m-%dT%H:%M:%S.%f\") if","t - time # or format time to absolute value: abs(t - time)","PXP] # - phase [P, S, N] Note: N - not detected #","filter_times(truth_dict, model_in) # filter arrivals to picks that were passed to the model","------------------ # read in UW arrival times as an array def read_arrivals_to_arr(filename): model_list","-------------------- # case 1: run if .mseed files have correct timestamps \"\"\" time","# fails if date is missing floating point numbers formatted_time = datetime.strptime(tmp[3], \"%Y-%m-%dT%H:%M:%S.%f\")","(t_truth - t_model_pick) import numpy import math import string import datetime import sys","comp_out.append(\"comparison_out/comp.\" + etype + \".out\") # ------------------ # read in UW arrival times","ln in f: row = ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time","if .mseed files have correct timestamps \"\"\" time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") - fudge_factor","[] model_in = [] model_out = [] comp_out = [] for etype in","= ['nan'] outp_file.write(str(event[5]) + \" \" + phase) for offset in times: outp_file.write(\"","= key[0:-7] picks[key] = arr return picks def model_in_to_array(file): timestamps = [] with","if date is missing floating point numbers formatted_time = datetime.strptime(tmp[3], \"%Y-%m-%dT%H:%M:%S.%f\") if key","\":\" + entry[12:14] # ------------- TIME STAMP ISSUES -------------------- # case 1: run","[] if key in model_dict.keys(): times = model_dict[key] times = time_lookup(event[3], times) return","times = [] if key in model_dict.keys(): times = model_dict[key] times = time_lookup(event[3],","comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \"parsed_arrivals/\" + etype +","try: # fails if date is missing floating point numbers formatted_time = datetime.strptime(tmp[3],","# ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered = [] for key","\"%Y-%m-%dT%H:%M:%S\") # ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered = [] for","< t_upper: offset = t - time # or format time to absolute","PXS, PXP] # - phase [P, S, N] Note: N - not detected","+ entry[10:12] + \":\" + entry[12:14] # ------------- TIME STAMP ISSUES -------------------- #","datetime import datetime from datetime import timedelta # params padding_time = 10 fudge_factor","in the timestamps time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") if time.second >=37 and time.second <=51:","model .in file as a list truth_arr = filter_times(truth_dict, model_in) # filter arrivals","phase = 'N' times = ['nan'] outp_file.write(str(event[5]) + \" \" + phase) for","- phase [P, S, N] Note: N - not detected # - model","59: sec_int = sec_int - 60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\")","def filter_times(arrivals, model_in): filtered = [] for key in model_in: if key in","= \"input_files/GPD.\" + etype + \".in\" outfile = \"output_files/GPD.\" + etype + \".out\"","[] for time in time_arr: if time > t_lower and time < t_upper:","['nan'] outp_file.write(str(event[5]) + \" \" + phase) for offset in times: outp_file.write(\" \"","= [] for time in time_arr: if time > t_lower and time <","have buggy minutes in the timestamps time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") if time.second >=37","not detected # - model time offset (t_truth - t_model_pick) import numpy import","model_in_to_array(inf) # read in model .in file as a list truth_arr = filter_times(truth_dict,","in truth_arr: phase = event[2] times = key_lookup(event, phase, model_dict) if len(times) ==","- type of event tested [EQS, EQP, SUS, SUP, THS, THP, SNS, SNP,","times = ['nan'] outp_file.write(str(event[5]) + \" \" + phase) for offset in times:","dirs parsed_arrivals = [] model_in = [] model_out = [] comp_out = []","N] Note: N - not detected # - model time offset (t_truth -","(key=truncated timestamp) model_in = model_in_to_array(inf) # read in model .in file as a","read output file for event in truth_arr: phase = event[2] times = key_lookup(event,","\"output_files/GPD.\" + etype + \".out\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\"comparison_out/comp.\" + etype + \".out\")","model_dict = read_output_to_dict(outf) # read output file for event in truth_arr: phase =","= time.second + 23 if sec_int > 59: sec_int = sec_int - 60","and create a dictionary def read_output_to_dict(filename): model_dict = {} with open(filename) as f:","# params padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) # file","import datetime from datetime import timedelta # params padding_time = 10 fudge_factor =","datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") else: sec_int = time.second + 23 if sec_int > 59: sec_int","offset = t - time # or format time to absolute value: abs(t","a list truth_arr = filter_times(truth_dict, model_in) # filter arrivals to picks that were","read in the arrival times to a list truth_dict = arrivals_to_dictionary(truth_arr) # convert","# ------------------ # read in UW arrival times as an array def read_arrivals_to_arr(filename):","\"-\" + tmp[1] + \"-\" + tmp[2] try: # fails if date is","= line.split() key = tmp[0] + \"-\" + tmp[1] + \"-\" + tmp[2]","arrival = \"parsed_arrivals/\" + etype + \".arrivals.txt\" infile = \"input_files/GPD.\" + etype +","as f: for line in f: tmp = line.split() key = tmp[0] +","= timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs parsed_arrivals = [] model_in =","str(sec_int).zfill(2) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") time = time[:-2] + sec_int time = datetime.strptime(time,","def model_in_to_array(file): timestamps = [] with open(file) as f: for ln in f:","key in arrivals: filtered.append(arrivals[key]) return filtered # read in Caltech model output and","outp_file.write(\" \" + str(offset)) outp_file.write('\\n') outp_file.close() for i in range(len(model_out)): execute_script(parsed_arrivals[i], model_in[i], model_out[i],","> 59: sec_int = sec_int - 60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time,","phase, model_dict): key = event[0] + \"-\" + event[1] + \"-\" + phase","arrival times to a list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to a","\"%Y-%m-%dT%H:%M:%S.%f\") if key not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return","time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets","time_lookup(event[3], times) return times # search for arrivals within the padding time window","files have correct timestamps \"\"\" time = datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") - fudge_factor # +","file dirs parsed_arrivals = [] model_in = [] model_out = [] comp_out =","= time[:-2] + sec_int time = datetime.strptime(time, \"%Y-%m-%dT%H:%M:%S\") + time_diff time = datetime.strftime(time,","\"-\" + event[1] + \"-\" + phase times = [] if key in","need to add this) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") \"\"\" # case 2: run","time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") \"\"\" # case 2: run if .mseed files have","datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") if time.second >=37 and time.second <=51: time = time + timedelta(seconds=23)","to a list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary (key=truncated","to a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) # read in model .in","time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") else: sec_int = time.second + 23 if sec_int","def arrivals_to_dictionary(arrivals): picks = {} for arr in arrivals: key = datetime.strftime(arr[3], \"%Y-%m-%dT%H:%M:%S.%f\")","read in UW arrival times as an array def read_arrivals_to_arr(filename): model_list = []","entry[6:8] + \"T\" + entry[8:10] + \":\" + entry[10:12] + \":\" + entry[12:14]","if sec_int > 59: sec_int = sec_int - 60 sec_int = str(sec_int).zfill(2) time","key = event[0] + \"-\" + event[1] + \"-\" + phase times =","+ \"-\" + tmp[1] + \"-\" + tmp[2] try: # fails if date","'S' else: phase = 'P' times = key_lookup(event, phase, model_dict) if len(times) ==","import os import csv from datetime import datetime from datetime import timedelta #","arrival times as an array def read_arrivals_to_arr(filename): model_list = [] with open(filename) as","for offset in times: outp_file.write(\" \" + str(offset)) outp_file.write('\\n') outp_file.close() for i in","Note: N - not detected # - model time offset (t_truth - t_model_pick)","entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \"-\" + entry[4:6]","= [] model_dict[key].append(formatted_time) except: pass return model_dict # lookup time in the dictionary","+ phase times = [] if key in model_dict.keys(): times = model_dict[key] times","0: if phase == 'P': phase = 'S' else: phase = 'P' times","outputs to file outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in","search for arrivals within the padding time window def time_lookup(t, time_arr): t_lower =","datetime.strptime(time, \"%Y-%m-%dT%H:%M:%S\") + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") # ----------------------------------------------------- timestamps.append(time) return timestamps","[P, S, N] Note: N - not detected # - model time offset","# file dirs parsed_arrivals = [] model_in = [] model_out = [] comp_out","model_in: if key in arrivals: filtered.append(arrivals[key]) return filtered # read in Caltech model","# + time_diff (might need to add this) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") \"\"\"","in time_arr: if time > t_lower and time < t_upper: offset = t","sec_int = sec_int - 60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") time","model_in) # filter arrivals to picks that were passed to the model (.in","------------- TIME STAMP ISSUES -------------------- # case 1: run if .mseed files have","model time offset (t_truth - t_model_pick) import numpy import math import string import","the padding time window def time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper","import csv from datetime import datetime from datetime import timedelta # params padding_time","if time > t_lower and time < t_upper: offset = t - time","outf, comp_out): # write outputs to file outp_file = open(comp_out, 'w') truth_arr =","entry[12:14] # ------------- TIME STAMP ISSUES -------------------- # case 1: run if .mseed","[] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \"parsed_arrivals/\" + etype + \".arrivals.txt\" infile","import sys import os import csv from datetime import datetime from datetime import","arrivals to picks that were passed to the model (.in file) model_dict =","{} with open(filename) as f: for line in f: tmp = line.split() key","+ \".out\") # ------------------ # read in UW arrival times as an array","detected # - model time offset (t_truth - t_model_pick) import numpy import math","+ entry[8:10] + \":\" + entry[10:12] + \":\" + entry[12:14] # ------------- TIME","> t_lower and time < t_upper: offset = t - time # or","# read in the arrival times to a list truth_dict = arrivals_to_dictionary(truth_arr) #","60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") time = time[:-2] + sec_int","outputs: # - type of event tested [EQS, EQP, SUS, SUP, THS, THP,","outfile = \"output_files/GPD.\" + etype + \".out\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\"comparison_out/comp.\" + etype","t_model_pick) import numpy import math import string import datetime import sys import os","model_dict = {} with open(filename) as f: for line in f: tmp =","model_dict) if len(times) == 0: if phase == 'P': phase = 'S' else:","= datetime.strptime(entry, \"%Y-%m-%dT%H:%M:%S\") - fudge_factor # + time_diff (might need to add this)","+ \"-\" + tmp[2] try: # fails if date is missing floating point","outp_file.write(str(event[5]) + \" \" + phase) for offset in times: outp_file.write(\" \" +","# - type of event tested [EQS, EQP, SUS, SUP, THS, THP, SNS,","in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \"parsed_arrivals/\" + etype + \".arrivals.txt\" infile = \"input_files/GPD.\" +","# write outputs to file outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) #","fudge_factor # + time_diff (might need to add this) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\")","= time + timedelta(seconds=23) + time_diff time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") else: sec_int =","['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \"parsed_arrivals/\" + etype + \".arrivals.txt\" infile = \"input_files/GPD.\" + etype","fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs parsed_arrivals = [] model_in","== 0: if phase == 'P': phase = 'S' else: phase = 'P'","time in the dictionary def key_lookup(event, phase, model_dict): key = event[0] + \"-\"","= datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") # ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered =","- time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf, comp_out):","etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \"parsed_arrivals/\" + etype + \".arrivals.txt\" infile = \"input_files/GPD.\"","window def time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper = t +","tests GPD model using UW truth data # Test outputs: # - type","for arrivals within the padding time window def time_lookup(t, time_arr): t_lower = t","truth_arr = read_arrivals_to_arr(arrival) # read in the arrival times to a list truth_dict","= sec_int - 60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") time =","in model_in: if key in arrivals: filtered.append(arrivals[key]) return filtered # read in Caltech","- time # or format time to absolute value: abs(t - time) offset","\"parsed_arrivals/\" + etype + \".arrivals.txt\" infile = \"input_files/GPD.\" + etype + \".in\" outfile","inf, outf, comp_out): # write outputs to file outp_file = open(comp_out, 'w') truth_arr","= event[2] times = key_lookup(event, phase, model_dict) if len(times) == 0: if phase","\"%Y-%m-%dT%H:%M:%S\") \"\"\" # case 2: run if .mseed files have buggy minutes in","arrivals: key = datetime.strftime(arr[3], \"%Y-%m-%dT%H:%M:%S.%f\") key = key[0:-7] picks[key] = arr return picks","data # Test outputs: # - type of event tested [EQS, EQP, SUS,","if key in arrivals: filtered.append(arrivals[key]) return filtered # read in Caltech model output","datetime.strftime(arr[3], \"%Y-%m-%dT%H:%M:%S.%f\") key = key[0:-7] picks[key] = arr return picks def model_in_to_array(file): timestamps","point numbers formatted_time = datetime.strptime(tmp[3], \"%Y-%m-%dT%H:%M:%S.%f\") if key not in model_dict: model_dict[key] =","t_lower and time < t_upper: offset = t - time # or format","time in time_arr: if time > t_lower and time < t_upper: offset =","phase) for offset in times: outp_file.write(\" \" + str(offset)) outp_file.write('\\n') outp_file.close() for i","a dictionary def read_output_to_dict(filename): model_dict = {} with open(filename) as f: for line","time = datetime.strftime(time, \"%Y-%m-%dT%H:%M:%S\") # ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered","Caltech model output and create a dictionary def read_output_to_dict(filename): model_dict = {} with","entry[4:6] + \"-\" + entry[6:8] + \"T\" + entry[8:10] + \":\" + entry[10:12]","= filter_times(truth_dict, model_in) # filter arrivals to picks that were passed to the","times = key_lookup(event, phase, model_dict) if len(times) == 0: phase = 'N' times","model_in.append(infile) model_out.append(outfile) comp_out.append(\"comparison_out/comp.\" + etype + \".out\") # ------------------ # read in UW","dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) # read in model .in file as","infile = \"input_files/GPD.\" + etype + \".in\" outfile = \"output_files/GPD.\" + etype +","passed to the model (.in file) model_dict = read_output_to_dict(outf) # read output file","phase = 'P' times = key_lookup(event, phase, model_dict) if len(times) == 0: phase","formatted_time = datetime.strptime(row[3], \"%Y-%m-%dT%H:%M:%S.%f\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def","not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return model_dict # lookup"],"string":"[\n \"[] model_out = [] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival =\",\n \"= open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in the arrival times to\",\n \"= 'P' times = key_lookup(event, phase, model_dict) if len(times) == 0: phase =\",\n \"model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return model_dict # lookup time in\",\n \"with open(filename) as f: for line in f: tmp = line.split() key =\",\n \"row[2].strip()]) formatted_time = datetime.strptime(row[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list\",\n \"+ 23 if sec_int > 59: sec_int = sec_int - 60 sec_int =\",\n \"datetime.strptime(row[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks\",\n \"if key in model_dict.keys(): times = model_dict[key] times = time_lookup(event[3], times) return times\",\n \"times # search for arrivals within the padding time window def time_lookup(t, time_arr):\",\n \"time_arr: if time > t_lower and time < t_upper: offset = t -\",\n \"key not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return model_dict #\",\n \"return times # search for arrivals within the padding time window def time_lookup(t,\",\n \"picks = {} for arr in arrivals: key = datetime.strftime(arr[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") key =\",\n \"f: for ln in f: entry = ln.split() entry = entry[0].strip() entry =\",\n \"time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf, comp_out): #\",\n \"and time < t_upper: offset = t - time # or format time\",\n \"import timedelta # params padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10)\",\n \"model_dict.keys(): times = model_dict[key] times = time_lookup(event[3], times) return times # search for\",\n \"f: tmp = line.split() key = tmp[0] + \\\"-\\\" + tmp[1] + \\\"-\\\"\",\n \"+ phase) for offset in times: outp_file.write(\\\" \\\" + str(offset)) outp_file.write('\\\\n') outp_file.close() for\",\n \"truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary (key=truncated timestamp) model_in =\",\n \"model_dict[key] times = time_lookup(event[3], times) return times # search for arrivals within the\",\n \"t_lower = t - timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets = []\",\n \"= datetime.strptime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") # ----------------------------------------------------- timestamps.append(time) return\",\n \"+ etype + \\\".out\\\") # ------------------ # read in UW arrival times as\",\n \"time = time + timedelta(seconds=23) + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") else: sec_int\",\n \".in file as a list truth_arr = filter_times(truth_dict, model_in) # filter arrivals to\",\n \"offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf, comp_out): # write outputs to file\",\n \"= timedelta(seconds=10) # file dirs parsed_arrivals = [] model_in = [] model_out =\",\n \"= entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \\\"-\\\" + entry[4:6] + \\\"-\\\" + entry[6:8]\",\n \"time.second <=51: time = time + timedelta(seconds=23) + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\")\",\n \"+ \\\"-\\\" + event[1] + \\\"-\\\" + phase times = [] if key\",\n \"SNS, SNP, PXS, PXP] # - phase [P, S, N] Note: N -\",\n \"+ timedelta(seconds=padding_time) offsets = [] for time in time_arr: if time > t_lower\",\n \"time + timedelta(seconds=23) + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") else: sec_int = time.second\",\n \"if key not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return model_dict\",\n \"event[1] + \\\"-\\\" + phase times = [] if key in model_dict.keys(): times\",\n \"using UW truth data # Test outputs: # - type of event tested\",\n \"\\\"\\\"\\\" # case 2: run if .mseed files have buggy minutes in the\",\n \"(.in file) model_dict = read_output_to_dict(outf) # read output file for event in truth_arr:\",\n \"+ entry[12:14] # ------------- TIME STAMP ISSUES -------------------- # case 1: run if\",\n \"filtered # read in Caltech model output and create a dictionary def read_output_to_dict(filename):\",\n \"arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) #\",\n \"datetime import timedelta # params padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff =\",\n \"\\\".out\\\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\\\"comparison_out/comp.\\\" + etype + \\\".out\\\") # ------------------ # read\",\n \"'P' times = key_lookup(event, phase, model_dict) if len(times) == 0: phase = 'N'\",\n \"list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary (key=truncated timestamp) model_in\",\n \"+ \\\"-\\\" + entry[4:6] + \\\"-\\\" + entry[6:8] + \\\"T\\\" + entry[8:10] +\",\n \"time < t_upper: offset = t - time # or format time to\",\n \"times = time_lookup(event[3], times) return times # search for arrivals within the padding\",\n \"sec_int - 60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") time = time[:-2]\",\n \"time > t_lower and time < t_upper: offset = t - time #\",\n \"key_lookup(event, phase, model_dict): key = event[0] + \\\"-\\\" + event[1] + \\\"-\\\" +\",\n \"offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf, comp_out): # write\",\n \"def read_arrivals_to_arr(filename): model_list = [] with open(filename) as f: for ln in f:\",\n \"key[0:-7] picks[key] = arr return picks def model_in_to_array(file): timestamps = [] with open(file)\",\n \"phase, model_dict) if len(times) == 0: if phase == 'P': phase = 'S'\",\n \"tested [EQS, EQP, SUS, SUP, THS, THP, SNS, SNP, PXS, PXP] # -\",\n \"in the dictionary def key_lookup(event, phase, model_dict): key = event[0] + \\\"-\\\" +\",\n \"= key_lookup(event, phase, model_dict) if len(times) == 0: phase = 'N' times =\",\n \"tmp[0] + \\\"-\\\" + tmp[1] + \\\"-\\\" + tmp[2] try: # fails if\",\n \"time[:-2] + sec_int time = datetime.strptime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\")\",\n \"\\\"%Y-%m-%dT%H:%M:%S\\\") if time.second >=37 and time.second <=51: time = time + timedelta(seconds=23) +\",\n \"# lookup time in the dictionary def key_lookup(event, phase, model_dict): key = event[0]\",\n \"+ event[1] + \\\"-\\\" + phase times = [] if key in model_dict.keys():\",\n \"timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets = [] for time in time_arr:\",\n \"+ timedelta(seconds=23) + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") else: sec_int = time.second +\",\n \"model_in_to_array(file): timestamps = [] with open(file) as f: for ln in f: entry\",\n \"open(file) as f: for ln in f: entry = ln.split() entry = entry[0].strip()\",\n \"output and create a dictionary def read_output_to_dict(filename): model_dict = {} with open(filename) as\",\n \"== 0: phase = 'N' times = ['nan'] outp_file.write(str(event[5]) + \\\" \\\" +\",\n \"timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs parsed_arrivals = [] model_in = []\",\n \"= [] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \\\"parsed_arrivals/\\\" +\",\n \"timedelta # params padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) #\",\n \"array def read_arrivals_to_arr(filename): model_list = [] with open(filename) as f: for ln in\",\n \"+ \\\":\\\" + entry[10:12] + \\\":\\\" + entry[12:14] # ------------- TIME STAMP ISSUES\",\n \"a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) # read in model .in file\",\n \"entry[8:10] + \\\":\\\" + entry[10:12] + \\\":\\\" + entry[12:14] # ------------- TIME STAMP\",\n \"time.second + 23 if sec_int > 59: sec_int = sec_int - 60 sec_int\",\n \"key in model_in: if key in arrivals: filtered.append(arrivals[key]) return filtered # read in\",\n \"= [] if key in model_dict.keys(): times = model_dict[key] times = time_lookup(event[3], times)\",\n \"return picks def model_in_to_array(file): timestamps = [] with open(file) as f: for ln\",\n \"were passed to the model (.in file) model_dict = read_output_to_dict(outf) # read output\",\n \"= datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") else: sec_int = time.second + 23 if sec_int > 59:\",\n \"EQP, SUS, SUP, THS, THP, SNS, SNP, PXS, PXP] # - phase [P,\",\n \"[] model_dict[key].append(formatted_time) except: pass return model_dict # lookup time in the dictionary def\",\n \"N - not detected # - model time offset (t_truth - t_model_pick) import\",\n \"key = key[0:-7] picks[key] = arr return picks def model_in_to_array(file): timestamps = []\",\n \"in Caltech model output and create a dictionary def read_output_to_dict(filename): model_dict = {}\",\n \"phase times = [] if key in model_dict.keys(): times = model_dict[key] times =\",\n \"# search for arrivals within the padding time window def time_lookup(t, time_arr): t_lower\",\n \"= {} for arr in arrivals: key = datetime.strftime(arr[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") key = key[0:-7]\",\n \"= {} with open(filename) as f: for line in f: tmp = line.split()\",\n \"len(times) == 0: if phase == 'P': phase = 'S' else: phase =\",\n \"time # or format time to absolute value: abs(t - time) offset =\",\n \"offsets = [] for time in time_arr: if time > t_lower and time\",\n \"arr return picks def model_in_to_array(file): timestamps = [] with open(file) as f: for\",\n \"key_lookup(event, phase, model_dict) if len(times) == 0: phase = 'N' times = ['nan']\",\n \"dictionary def key_lookup(event, phase, model_dict): key = event[0] + \\\"-\\\" + event[1] +\",\n \"read in model .in file as a list truth_arr = filter_times(truth_dict, model_in) #\",\n \"- timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets = [] for time in\",\n \"<=51: time = time + timedelta(seconds=23) + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") else:\",\n \"for line in f: tmp = line.split() key = tmp[0] + \\\"-\\\" +\",\n \"= key_lookup(event, phase, model_dict) if len(times) == 0: if phase == 'P': phase\",\n \"\\\" + str(offset)) outp_file.write('\\\\n') outp_file.close() for i in range(len(model_out)): execute_script(parsed_arrivals[i], model_in[i], model_out[i], comp_out[i])\",\n \"datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") \\\"\\\"\\\" # case 2: run if .mseed files have buggy minutes\",\n \"offset in times: outp_file.write(\\\" \\\" + str(offset)) outp_file.write('\\\\n') outp_file.close() for i in range(len(model_out)):\",\n \"model_dict): key = event[0] + \\\"-\\\" + event[1] + \\\"-\\\" + phase times\",\n \"the model (.in file) model_dict = read_output_to_dict(outf) # read output file for event\",\n \"picks that were passed to the model (.in file) model_dict = read_output_to_dict(outf) #\",\n \"+ entry[4:6] + \\\"-\\\" + entry[6:8] + \\\"T\\\" + entry[8:10] + \\\":\\\" +\",\n \"return timestamps def filter_times(arrivals, model_in): filtered = [] for key in model_in: if\",\n \"\\\"-\\\" + entry[6:8] + \\\"T\\\" + entry[8:10] + \\\":\\\" + entry[10:12] + \\\":\\\"\",\n \"in UW arrival times as an array def read_arrivals_to_arr(filename): model_list = [] with\",\n \"create a dictionary def read_output_to_dict(filename): model_dict = {} with open(filename) as f: for\",\n \"picks[key] = arr return picks def model_in_to_array(file): timestamps = [] with open(file) as\",\n \"= datetime.strptime(row[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals):\",\n \"time.second >=37 and time.second <=51: time = time + timedelta(seconds=23) + time_diff time\",\n \"f: row = ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3],\",\n \"\\\"%Y-%m-%dT%H:%M:%S\\\") time = time[:-2] + sec_int time = datetime.strptime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") + time_diff time\",\n \"[] with open(filename) as f: for ln in f: row = ln.split() line\",\n \"row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return\",\n \"[] for key in model_in: if key in arrivals: filtered.append(arrivals[key]) return filtered #\",\n \"TIME STAMP ISSUES -------------------- # case 1: run if .mseed files have correct\",\n \"open(filename) as f: for ln in f: row = ln.split() line = []\",\n \"ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") - fudge_factor\",\n \"else: phase = 'P' times = key_lookup(event, phase, model_dict) if len(times) == 0:\",\n \"- not detected # - model time offset (t_truth - t_model_pick) import numpy\",\n \"the arrival times to a list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to\",\n \"in model .in file as a list truth_arr = filter_times(truth_dict, model_in) # filter\",\n \"pass return model_dict # lookup time in the dictionary def key_lookup(event, phase, model_dict):\",\n \"for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \\\"parsed_arrivals/\\\" + etype + \\\".arrivals.txt\\\" infile =\",\n \"= datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") time = time[:-2] + sec_int time = datetime.strptime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") +\",\n \"+ entry[6:8] + \\\"T\\\" + entry[8:10] + \\\":\\\" + entry[10:12] + \\\":\\\" +\",\n \"numbers formatted_time = datetime.strptime(tmp[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") if key not in model_dict: model_dict[key] = []\",\n \"the timestamps time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") if time.second >=37 and time.second <=51: time\",\n \"+ tmp[1] + \\\"-\\\" + tmp[2] try: # fails if date is missing\",\n \"t + timedelta(seconds=padding_time) offsets = [] for time in time_arr: if time >\",\n \"times as an array def read_arrivals_to_arr(filename): model_list = [] with open(filename) as f:\",\n \"from datetime import datetime from datetime import timedelta # params padding_time = 10\",\n \"1: run if .mseed files have correct timestamps \\\"\\\"\\\" time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\")\",\n \"model (.in file) model_dict = read_output_to_dict(outf) # read output file for event in\",\n \"phase [P, S, N] Note: N - not detected # - model time\",\n \"comp_out): # write outputs to file outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival)\",\n \"= [] with open(file) as f: for ln in f: entry = ln.split()\",\n \">=37 and time.second <=51: time = time + timedelta(seconds=23) + time_diff time =\",\n \"times = model_dict[key] times = time_lookup(event[3], times) return times # search for arrivals\",\n \"string import datetime import sys import os import csv from datetime import datetime\",\n \"# Test outputs: # - type of event tested [EQS, EQP, SUS, SUP,\",\n \"THP, SNS, SNP, PXS, PXP] # - phase [P, S, N] Note: N\",\n \"= datetime.strptime(tmp[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") if key not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except:\",\n \"SUP, THS, THP, SNS, SNP, PXS, PXP] # - phase [P, S, N]\",\n \"file for event in truth_arr: phase = event[2] times = key_lookup(event, phase, model_dict)\",\n \"----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered = [] for key in\",\n \"= time_lookup(event[3], times) return times # search for arrivals within the padding time\",\n \"for arr in arrivals: key = datetime.strftime(arr[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") key = key[0:-7] picks[key] =\",\n \"model_out = [] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \\\"parsed_arrivals/\\\"\",\n \"- model time offset (t_truth - t_model_pick) import numpy import math import string\",\n \"\\\"%Y-%m-%dT%H:%M:%S\\\") + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") # ----------------------------------------------------- timestamps.append(time) return timestamps def\",\n \"line in f: tmp = line.split() key = tmp[0] + \\\"-\\\" + tmp[1]\",\n \"\\\".out\\\") # ------------------ # read in UW arrival times as an array def\",\n \"'P': phase = 'S' else: phase = 'P' times = key_lookup(event, phase, model_dict)\",\n \"# read in model .in file as a list truth_arr = filter_times(truth_dict, model_in)\",\n \"return offsets def execute_script(arrival, inf, outf, comp_out): # write outputs to file outp_file\",\n \"SUS, SUP, THS, THP, SNS, SNP, PXS, PXP] # - phase [P, S,\",\n \"return filtered # read in Caltech model output and create a dictionary def\",\n \"f: for ln in f: row = ln.split() line = [] line.extend([row[0].strip(), row[1].strip(),\",\n \"f: for line in f: tmp = line.split() key = tmp[0] + \\\"-\\\"\",\n \"entry = entry[0:4] + \\\"-\\\" + entry[4:6] + \\\"-\\\" + entry[6:8] + \\\"T\\\"\",\n \"value: abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf,\",\n \"event[2] times = key_lookup(event, phase, model_dict) if len(times) == 0: if phase ==\",\n \"= [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \\\"parsed_arrivals/\\\" + etype + \\\".arrivals.txt\\\"\",\n \"f: entry = ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4]\",\n \"truth data # Test outputs: # - type of event tested [EQS, EQP,\",\n \"of event tested [EQS, EQP, SUS, SUP, THS, THP, SNS, SNP, PXS, PXP]\",\n \"row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks = {} for arr in arrivals:\",\n \"+ tmp[2] try: # fails if date is missing floating point numbers formatted_time\",\n \"+ \\\"-\\\" + phase times = [] if key in model_dict.keys(): times =\",\n \"truth_arr = filter_times(truth_dict, model_in) # filter arrivals to picks that were passed to\",\n \"file outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in the arrival\",\n \"{} for arr in arrivals: key = datetime.strftime(arr[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") key = key[0:-7] picks[key]\",\n \"timestamps = [] with open(file) as f: for ln in f: entry =\",\n \"params padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs\",\n \"read_output_to_dict(filename): model_dict = {} with open(filename) as f: for line in f: tmp\",\n \"import numpy import math import string import datetime import sys import os import\",\n \"times = key_lookup(event, phase, model_dict) if len(times) == 0: if phase == 'P':\",\n \"# convert arrivals to a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) # read\",\n \"\\\"%Y-%m-%dT%H:%M:%S.%f\\\") key = key[0:-7] picks[key] = arr return picks def model_in_to_array(file): timestamps =\",\n \"[EQS, EQP, SUS, SUP, THS, THP, SNS, SNP, PXS, PXP] # - phase\",\n \"for ln in f: entry = ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6]\",\n \"\\\"%Y-%m-%dT%H:%M:%S\\\") - fudge_factor # + time_diff (might need to add this) time =\",\n \"entry[0:4] + \\\"-\\\" + entry[4:6] + \\\"-\\\" + entry[6:8] + \\\"T\\\" + entry[8:10]\",\n \"floating point numbers formatted_time = datetime.strptime(tmp[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") if key not in model_dict: model_dict[key]\",\n \"line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") - fudge_factor line.extend([formatted_time,\",\n \"else: sec_int = time.second + 23 if sec_int > 59: sec_int = sec_int\",\n \"return model_dict # lookup time in the dictionary def key_lookup(event, phase, model_dict): key\",\n \"abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf,\",\n \"'N' times = ['nan'] outp_file.write(str(event[5]) + \\\" \\\" + phase) for offset in\",\n \"time = time[:-2] + sec_int time = datetime.strptime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") + time_diff time =\",\n \"key in model_dict.keys(): times = model_dict[key] times = time_lookup(event[3], times) return times #\",\n \"SNP, PXS, PXP] # - phase [P, S, N] Note: N - not\",\n \"list truth_arr = filter_times(truth_dict, model_in) # filter arrivals to picks that were passed\",\n \"within the padding time window def time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time)\",\n \"= entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \\\"-\\\" + entry[4:6] +\",\n \"+ \\\" \\\" + phase) for offset in times: outp_file.write(\\\" \\\" + str(offset))\",\n \"= ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \\\"-\\\"\",\n \"missing floating point numbers formatted_time = datetime.strptime(tmp[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") if key not in model_dict:\",\n \"in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return model_dict # lookup time\",\n \"this) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") \\\"\\\"\\\" # case 2: run if .mseed files\",\n \"padding time window def time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper =\",\n \"line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line)\",\n \"execute_script(arrival, inf, outf, comp_out): # write outputs to file outp_file = open(comp_out, 'w')\",\n \"read_arrivals_to_arr(arrival) # read in the arrival times to a list truth_dict = arrivals_to_dictionary(truth_arr)\",\n \"tmp[2] try: # fails if date is missing floating point numbers formatted_time =\",\n \"+ \\\":\\\" + entry[12:14] # ------------- TIME STAMP ISSUES -------------------- # case 1:\",\n \"model_in): filtered = [] for key in model_in: if key in arrivals: filtered.append(arrivals[key])\",\n \"time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") time = time[:-2] + sec_int time = datetime.strptime(time, \\\"%Y-%m-%dT%H:%M:%S\\\")\",\n \"that were passed to the model (.in file) model_dict = read_output_to_dict(outf) # read\",\n \"+ \\\".arrivals.txt\\\" infile = \\\"input_files/GPD.\\\" + etype + \\\".in\\\" outfile = \\\"output_files/GPD.\\\" +\",\n \"= [] with open(filename) as f: for ln in f: row = ln.split()\",\n \"output file for event in truth_arr: phase = event[2] times = key_lookup(event, phase,\",\n \"[] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \\\"parsed_arrivals/\\\" + etype\",\n \"ln in f: entry = ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry\",\n \"datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") - fudge_factor # + time_diff (might need to add this) time\",\n \"as f: for ln in f: entry = ln.split() entry = entry[0].strip() entry\",\n \"case 2: run if .mseed files have buggy minutes in the timestamps time\",\n \"def execute_script(arrival, inf, outf, comp_out): # write outputs to file outp_file = open(comp_out,\",\n \"to add this) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") \\\"\\\"\\\" # case 2: run if\",\n \"+ sec_int time = datetime.strptime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") #\",\n \"write outputs to file outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read\",\n \"'w') truth_arr = read_arrivals_to_arr(arrival) # read in the arrival times to a list\",\n \"= 'N' times = ['nan'] outp_file.write(str(event[5]) + \\\" \\\" + phase) for offset\",\n \"len(times) == 0: phase = 'N' times = ['nan'] outp_file.write(str(event[5]) + \\\" \\\"\",\n \"entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \\\"-\\\" + entry[4:6] + \\\"-\\\"\",\n \"# Script tests GPD model using UW truth data # Test outputs: #\",\n \"model_list = [] with open(filename) as f: for ln in f: row =\",\n \"+ time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") else: sec_int = time.second + 23 if\",\n \"event[0] + \\\"-\\\" + event[1] + \\\"-\\\" + phase times = [] if\",\n \"correct timestamps \\\"\\\"\\\" time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") - fudge_factor # + time_diff (might\",\n \"run if .mseed files have correct timestamps \\\"\\\"\\\" time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") -\",\n \"sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") time = time[:-2] + sec_int time\",\n \"timedelta(seconds=padding_time) offsets = [] for time in time_arr: if time > t_lower and\",\n \"entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \\\"-\\\" + entry[4:6] + \\\"-\\\" +\",\n \"open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in the arrival times to a\",\n \"THS, THP, SNS, SNP, PXS, PXP] # - phase [P, S, N] Note:\",\n \"\\\"input_files/GPD.\\\" + etype + \\\".in\\\" outfile = \\\"output_files/GPD.\\\" + etype + \\\".out\\\" parsed_arrivals.append(arrival)\",\n \"\\\":\\\" + entry[10:12] + \\\":\\\" + entry[12:14] # ------------- TIME STAMP ISSUES --------------------\",\n \"model_in = [] model_out = [] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']:\",\n \"model_list def arrivals_to_dictionary(arrivals): picks = {} for arr in arrivals: key = datetime.strftime(arr[3],\",\n \"key = tmp[0] + \\\"-\\\" + tmp[1] + \\\"-\\\" + tmp[2] try: #\",\n \"10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs parsed_arrivals = []\",\n \"\\\" \\\" + phase) for offset in times: outp_file.write(\\\" \\\" + str(offset)) outp_file.write('\\\\n')\",\n \"if phase == 'P': phase = 'S' else: phase = 'P' times =\",\n \"= datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") \\\"\\\"\\\" # case 2: run if .mseed files have buggy\",\n \"times) return times # search for arrivals within the padding time window def\",\n \"model_dict # lookup time in the dictionary def key_lookup(event, phase, model_dict): key =\",\n \"format time to absolute value: abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return\",\n \"+ etype + \\\".out\\\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\\\"comparison_out/comp.\\\" + etype + \\\".out\\\") #\",\n \"import math import string import datetime import sys import os import csv from\",\n \"from datetime import timedelta # params padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff\",\n \"model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks = {} for arr in arrivals: key\",\n \"time = datetime.strptime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") # ----------------------------------------------------- timestamps.append(time)\",\n \"filter_times(arrivals, model_in): filtered = [] for key in model_in: if key in arrivals:\",\n \"for time in time_arr: if time > t_lower and time < t_upper: offset\",\n \"import datetime import sys import os import csv from datetime import datetime from\",\n \"model_out.append(outfile) comp_out.append(\\\"comparison_out/comp.\\\" + etype + \\\".out\\\") # ------------------ # read in UW arrival\",\n \"padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs parsed_arrivals\",\n \"time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") else: sec_int = time.second + 23 if sec_int >\",\n \"tmp = line.split() key = tmp[0] + \\\"-\\\" + tmp[1] + \\\"-\\\" +\",\n \"dictionary def read_output_to_dict(filename): model_dict = {} with open(filename) as f: for line in\",\n \"\\\"-\\\" + tmp[2] try: # fails if date is missing floating point numbers\",\n \"sys import os import csv from datetime import datetime from datetime import timedelta\",\n \"model_dict[key].append(formatted_time) except: pass return model_dict # lookup time in the dictionary def key_lookup(event,\",\n \"truth_arr: phase = event[2] times = key_lookup(event, phase, model_dict) if len(times) == 0:\",\n \"time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") if time.second >=37 and time.second <=51: time = time\",\n \"entry = ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] +\",\n \"file) model_dict = read_output_to_dict(outf) # read output file for event in truth_arr: phase\",\n \"model output and create a dictionary def read_output_to_dict(filename): model_dict = {} with open(filename)\",\n \"with open(filename) as f: for ln in f: row = ln.split() line =\",\n \"\\\"\\\"\\\" time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") - fudge_factor # + time_diff (might need to\",\n \"arrivals: filtered.append(arrivals[key]) return filtered # read in Caltech model output and create a\",\n \"time to absolute value: abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets\",\n \"2: run if .mseed files have buggy minutes in the timestamps time =\",\n \"== 'P': phase = 'S' else: phase = 'P' times = key_lookup(event, phase,\",\n \"= read_output_to_dict(outf) # read output file for event in truth_arr: phase = event[2]\",\n \"\\\"T\\\" + entry[8:10] + \\\":\\\" + entry[10:12] + \\\":\\\" + entry[12:14] # -------------\",\n \"timestamps \\\"\\\"\\\" time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") - fudge_factor # + time_diff (might need\",\n \"row = ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\")\",\n \"etype + \\\".in\\\" outfile = \\\"output_files/GPD.\\\" + etype + \\\".out\\\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile)\",\n \"case 1: run if .mseed files have correct timestamps \\\"\\\"\\\" time = datetime.strptime(entry,\",\n \"offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf, comp_out): # write outputs to\",\n \"- 60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") time = time[:-2] +\",\n \"in times: outp_file.write(\\\" \\\" + str(offset)) outp_file.write('\\\\n') outp_file.close() for i in range(len(model_out)): execute_script(parsed_arrivals[i],\",\n \"t_upper = t + timedelta(seconds=padding_time) offsets = [] for time in time_arr: if\",\n \"= model_in_to_array(inf) # read in model .in file as a list truth_arr =\",\n \"# or format time to absolute value: abs(t - time) offset = offset.total_seconds()\",\n \"minutes in the timestamps time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") if time.second >=37 and time.second\",\n \"return model_list def arrivals_to_dictionary(arrivals): picks = {} for arr in arrivals: key =\",\n \"= ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") -\",\n \"[] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()])\",\n \"# case 2: run if .mseed files have buggy minutes in the timestamps\",\n \"tmp[1] + \\\"-\\\" + tmp[2] try: # fails if date is missing floating\",\n \"times to a list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary\",\n \"if len(times) == 0: if phase == 'P': phase = 'S' else: phase\",\n \"STAMP ISSUES -------------------- # case 1: run if .mseed files have correct timestamps\",\n \"= [] model_in = [] model_out = [] comp_out = [] for etype\",\n \"add this) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") \\\"\\\"\\\" # case 2: run if .mseed\",\n \"= offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf, comp_out): # write outputs\",\n \"or format time to absolute value: abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset))\",\n \"if len(times) == 0: phase = 'N' times = ['nan'] outp_file.write(str(event[5]) + \\\"\",\n \"time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") - fudge_factor # + time_diff (might need to add\",\n \"line.split() key = tmp[0] + \\\"-\\\" + tmp[1] + \\\"-\\\" + tmp[2] try:\",\n \"UW truth data # Test outputs: # - type of event tested [EQS,\",\n \"\\\"-\\\" + phase times = [] if key in model_dict.keys(): times = model_dict[key]\",\n \"= t - timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets = [] for\",\n \"time offset (t_truth - t_model_pick) import numpy import math import string import datetime\",\n \"= [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time = datetime.strptime(row[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") - fudge_factor line.extend([formatted_time, row[4].strip(),\",\n \"time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets =\",\n \"offsets def execute_script(arrival, inf, outf, comp_out): # write outputs to file outp_file =\",\n \"if time.second >=37 and time.second <=51: time = time + timedelta(seconds=23) + time_diff\",\n \"arrivals to a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) # read in model\",\n \"datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") time = time[:-2] + sec_int time = datetime.strptime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") + time_diff\",\n \"phase, model_dict) if len(times) == 0: phase = 'N' times = ['nan'] outp_file.write(str(event[5])\",\n \"as an array def read_arrivals_to_arr(filename): model_list = [] with open(filename) as f: for\",\n \"\\\"-\\\" + entry[4:6] + \\\"-\\\" + entry[6:8] + \\\"T\\\" + entry[8:10] + \\\":\\\"\",\n \"model_dict) if len(times) == 0: phase = 'N' times = ['nan'] outp_file.write(str(event[5]) +\",\n \"ISSUES -------------------- # case 1: run if .mseed files have correct timestamps \\\"\\\"\\\"\",\n \"# read in Caltech model output and create a dictionary def read_output_to_dict(filename): model_dict\",\n \"type of event tested [EQS, EQP, SUS, SUP, THS, THP, SNS, SNP, PXS,\",\n \"\\\"%Y-%m-%dT%H:%M:%S\\\") else: sec_int = time.second + 23 if sec_int > 59: sec_int =\",\n \"to absolute value: abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def\",\n \"in model_dict.keys(): times = model_dict[key] times = time_lookup(event[3], times) return times # search\",\n \"datetime.strptime(tmp[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") if key not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass\",\n \"the dictionary def key_lookup(event, phase, model_dict): key = event[0] + \\\"-\\\" + event[1]\",\n \"timedelta(seconds=10) # file dirs parsed_arrivals = [] model_in = [] model_out = []\",\n \"phase = event[2] times = key_lookup(event, phase, model_dict) if len(times) == 0: if\",\n \"# read in UW arrival times as an array def read_arrivals_to_arr(filename): model_list =\",\n \"line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks = {} for arr\",\n \"timestamps time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") if time.second >=37 and time.second <=51: time =\",\n \"file as a list truth_arr = filter_times(truth_dict, model_in) # filter arrivals to picks\",\n \"datetime import sys import os import csv from datetime import datetime from datetime\",\n \"key_lookup(event, phase, model_dict) if len(times) == 0: if phase == 'P': phase =\",\n \"+ time_diff (might need to add this) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") \\\"\\\"\\\" #\",\n \"if .mseed files have buggy minutes in the timestamps time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\")\",\n \".mseed files have buggy minutes in the timestamps time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") if\",\n \"absolute value: abs(t - time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival,\",\n \"a list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary (key=truncated timestamp)\",\n \"- fudge_factor # + time_diff (might need to add this) time = datetime.strftime(time,\",\n \"= datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") if time.second >=37 and time.second <=51: time = time +\",\n \"[] with open(file) as f: for ln in f: entry = ln.split() entry\",\n \"time_diff (might need to add this) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") \\\"\\\"\\\" # case\",\n \"formatted_time = datetime.strptime(tmp[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") if key not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time)\",\n \"as f: for ln in f: row = ln.split() line = [] line.extend([row[0].strip(),\",\n \"t_upper: offset = t - time # or format time to absolute value:\",\n \"= arr return picks def model_in_to_array(file): timestamps = [] with open(file) as f:\",\n \"times: outp_file.write(\\\" \\\" + str(offset)) outp_file.write('\\\\n') outp_file.close() for i in range(len(model_out)): execute_script(parsed_arrivals[i], model_in[i],\",\n \"etype + \\\".out\\\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\\\"comparison_out/comp.\\\" + etype + \\\".out\\\") # ------------------\",\n \"= entry[0:4] + \\\"-\\\" + entry[4:6] + \\\"-\\\" + entry[6:8] + \\\"T\\\" +\",\n \"is missing floating point numbers formatted_time = datetime.strptime(tmp[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") if key not in\",\n \"offset (t_truth - t_model_pick) import numpy import math import string import datetime import\",\n \"in f: row = ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time =\",\n \"t - timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets = [] for time\",\n \"to file outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in the\",\n \"= t + timedelta(seconds=padding_time) offsets = [] for time in time_arr: if time\",\n \"entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \\\"-\\\" + entry[4:6] + \\\"-\\\" + entry[6:8] +\",\n \"and time.second <=51: time = time + timedelta(seconds=23) + time_diff time = datetime.strftime(time,\",\n \"parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\\\"comparison_out/comp.\\\" + etype + \\\".out\\\") # ------------------ # read in\",\n \"files have buggy minutes in the timestamps time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") if time.second\",\n \"- t_model_pick) import numpy import math import string import datetime import sys import\",\n \"# case 1: run if .mseed files have correct timestamps \\\"\\\"\\\" time =\",\n \"= [] for key in model_in: if key in arrivals: filtered.append(arrivals[key]) return filtered\",\n \"GPD model using UW truth data # Test outputs: # - type of\",\n \"S, N] Note: N - not detected # - model time offset (t_truth\",\n \"to picks that were passed to the model (.in file) model_dict = read_output_to_dict(outf)\",\n \"model using UW truth data # Test outputs: # - type of event\",\n \"23 if sec_int > 59: sec_int = sec_int - 60 sec_int = str(sec_int).zfill(2)\",\n \"time window def time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper = t\",\n \"row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks = {} for arr in\",\n \"date is missing floating point numbers formatted_time = datetime.strptime(tmp[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") if key not\",\n \"read_output_to_dict(outf) # read output file for event in truth_arr: phase = event[2] times\",\n \"event in truth_arr: phase = event[2] times = key_lookup(event, phase, model_dict) if len(times)\",\n \"phase == 'P': phase = 'S' else: phase = 'P' times = key_lookup(event,\",\n \"fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks = {} for\",\n \"# read output file for event in truth_arr: phase = event[2] times =\",\n \"(might need to add this) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") \\\"\\\"\\\" # case 2:\",\n \"ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \\\"-\\\" +\",\n \"sec_int = time.second + 23 if sec_int > 59: sec_int = sec_int -\",\n \"= datetime.strftime(arr[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") key = key[0:-7] picks[key] = arr return picks def model_in_to_array(file):\",\n \"= read_arrivals_to_arr(arrival) # read in the arrival times to a list truth_dict =\",\n \"def key_lookup(event, phase, model_dict): key = event[0] + \\\"-\\\" + event[1] + \\\"-\\\"\",\n \"= event[0] + \\\"-\\\" + event[1] + \\\"-\\\" + phase times = []\",\n \"# filter arrivals to picks that were passed to the model (.in file)\",\n \"math import string import datetime import sys import os import csv from datetime\",\n \"\\\"%Y-%m-%dT%H:%M:%S.%f\\\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks =\",\n \"time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") # ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in):\",\n \"in arrivals: filtered.append(arrivals[key]) return filtered # read in Caltech model output and create\",\n \"outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in the arrival times\",\n \"timestamp) model_in = model_in_to_array(inf) # read in model .in file as a list\",\n \"for ln in f: row = ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()])\",\n \"# - phase [P, S, N] Note: N - not detected # -\",\n \"= arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf)\",\n \"with open(file) as f: for ln in f: entry = ln.split() entry =\",\n \"numpy import math import string import datetime import sys import os import csv\",\n \"an array def read_arrivals_to_arr(filename): model_list = [] with open(filename) as f: for ln\",\n \"in f: tmp = line.split() key = tmp[0] + \\\"-\\\" + tmp[1] +\",\n \"model_in = model_in_to_array(inf) # read in model .in file as a list truth_arr\",\n \"= 'S' else: phase = 'P' times = key_lookup(event, phase, model_dict) if len(times)\",\n \"filtered.append(arrivals[key]) return filtered # read in Caltech model output and create a dictionary\",\n \"Script tests GPD model using UW truth data # Test outputs: # -\",\n \"run if .mseed files have buggy minutes in the timestamps time = datetime.strptime(entry,\",\n \".mseed files have correct timestamps \\\"\\\"\\\" time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") - fudge_factor #\",\n \"parsed_arrivals = [] model_in = [] model_out = [] comp_out = [] for\",\n \"read in Caltech model output and create a dictionary def read_output_to_dict(filename): model_dict =\",\n \"time_diff = timedelta(seconds=10) # file dirs parsed_arrivals = [] model_in = [] model_out\",\n \"in f: entry = ln.split() entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry =\",\n \"csv from datetime import datetime from datetime import timedelta # params padding_time =\",\n \"= model_dict[key] times = time_lookup(event[3], times) return times # search for arrivals within\",\n \"+ \\\".in\\\" outfile = \\\"output_files/GPD.\\\" + etype + \\\".out\\\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\\\"comparison_out/comp.\\\"\",\n \"+ \\\"-\\\" + entry[6:8] + \\\"T\\\" + entry[8:10] + \\\":\\\" + entry[10:12] +\",\n \"filtered = [] for key in model_in: if key in arrivals: filtered.append(arrivals[key]) return\",\n \"convert arrivals to a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) # read in\",\n \"as a list truth_arr = filter_times(truth_dict, model_in) # filter arrivals to picks that\",\n \"\\\" + phase) for offset in times: outp_file.write(\\\" \\\" + str(offset)) outp_file.write('\\\\n') outp_file.close()\",\n \"+ \\\"T\\\" + entry[8:10] + \\\":\\\" + entry[10:12] + \\\":\\\" + entry[12:14] #\",\n \"buggy minutes in the timestamps time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") if time.second >=37 and\",\n \"etype + \\\".out\\\") # ------------------ # read in UW arrival times as an\",\n \"arrivals_to_dictionary(arrivals): picks = {} for arr in arrivals: key = datetime.strftime(arr[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") key\",\n \"in the arrival times to a list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals\",\n \"arr in arrivals: key = datetime.strftime(arr[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") key = key[0:-7] picks[key] = arr\",\n \"model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return model_dict # lookup time in the\",\n \"filter arrivals to picks that were passed to the model (.in file) model_dict\",\n \"read_arrivals_to_arr(filename): model_list = [] with open(filename) as f: for ln in f: row\",\n \"sec_int time = datetime.strptime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") # -----------------------------------------------------\",\n \"timestamps def filter_times(arrivals, model_in): filtered = [] for key in model_in: if key\",\n \"+ time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") # ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals,\",\n \"timedelta(seconds=23) + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") else: sec_int = time.second + 23\",\n \"# ------------- TIME STAMP ISSUES -------------------- # case 1: run if .mseed files\",\n \"= tmp[0] + \\\"-\\\" + tmp[1] + \\\"-\\\" + tmp[2] try: # fails\",\n \"arrivals within the padding time window def time_lookup(t, time_arr): t_lower = t -\",\n \"Test outputs: # - type of event tested [EQS, EQP, SUS, SUP, THS,\",\n \"def read_output_to_dict(filename): model_dict = {} with open(filename) as f: for line in f:\",\n \"etype + \\\".arrivals.txt\\\" infile = \\\"input_files/GPD.\\\" + etype + \\\".in\\\" outfile = \\\"output_files/GPD.\\\"\",\n \"to the model (.in file) model_dict = read_output_to_dict(outf) # read output file for\",\n \"phase = 'S' else: phase = 'P' times = key_lookup(event, phase, model_dict) if\",\n \"import string import datetime import sys import os import csv from datetime import\",\n \"UW arrival times as an array def read_arrivals_to_arr(filename): model_list = [] with open(filename)\",\n \"- fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def arrivals_to_dictionary(arrivals): picks = {}\",\n \"= 10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs parsed_arrivals =\",\n \"timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered = [] for key in model_in:\",\n \"+ etype + \\\".in\\\" outfile = \\\"output_files/GPD.\\\" + etype + \\\".out\\\" parsed_arrivals.append(arrival) model_in.append(infile)\",\n \"0: phase = 'N' times = ['nan'] outp_file.write(str(event[5]) + \\\" \\\" + phase)\",\n \"= [] model_out = [] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival\",\n \"= \\\"parsed_arrivals/\\\" + etype + \\\".arrivals.txt\\\" infile = \\\"input_files/GPD.\\\" + etype + \\\".in\\\"\",\n \"for key in model_in: if key in arrivals: filtered.append(arrivals[key]) return filtered # read\",\n \"= t - time # or format time to absolute value: abs(t -\",\n \"entry[10:12] + \\\":\\\" + entry[12:14] # ------------- TIME STAMP ISSUES -------------------- # case\",\n \"event tested [EQS, EQP, SUS, SUP, THS, THP, SNS, SNP, PXS, PXP] #\",\n \"# - model time offset (t_truth - t_model_pick) import numpy import math import\",\n \"\\\".arrivals.txt\\\" infile = \\\"input_files/GPD.\\\" + etype + \\\".in\\\" outfile = \\\"output_files/GPD.\\\" + etype\",\n \"def time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time)\",\n \"os import csv from datetime import datetime from datetime import timedelta # params\",\n \"= str(sec_int).zfill(2) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") time = time[:-2] + sec_int time =\",\n \"in arrivals: key = datetime.strftime(arr[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") key = key[0:-7] picks[key] = arr return\",\n \"= \\\"output_files/GPD.\\\" + etype + \\\".out\\\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\\\"comparison_out/comp.\\\" + etype +\",\n \"open(filename) as f: for line in f: tmp = line.split() key = tmp[0]\",\n \"+ etype + \\\".arrivals.txt\\\" infile = \\\"input_files/GPD.\\\" + etype + \\\".in\\\" outfile =\",\n \"for event in truth_arr: phase = event[2] times = key_lookup(event, phase, model_dict) if\",\n \"except: pass return model_dict # lookup time in the dictionary def key_lookup(event, phase,\",\n \"lookup time in the dictionary def key_lookup(event, phase, model_dict): key = event[0] +\",\n \"have correct timestamps \\\"\\\"\\\" time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") - fudge_factor # + time_diff\",\n \"key = datetime.strftime(arr[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") key = key[0:-7] picks[key] = arr return picks def\",\n \"+ \\\".out\\\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\\\"comparison_out/comp.\\\" + etype + \\\".out\\\") # ------------------ #\",\n \"\\\".in\\\" outfile = \\\"output_files/GPD.\\\" + etype + \\\".out\\\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\\\"comparison_out/comp.\\\" +\",\n \"sec_int > 59: sec_int = sec_int - 60 sec_int = str(sec_int).zfill(2) time =\",\n \"datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") # ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered = []\",\n \"datetime from datetime import timedelta # params padding_time = 10 fudge_factor = timedelta(seconds=27)\",\n \"picks def model_in_to_array(file): timestamps = [] with open(file) as f: for ln in\",\n \"fails if date is missing floating point numbers formatted_time = datetime.strptime(tmp[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") if\",\n \"t - time # or format time to absolute value: abs(t - time)\",\n \"PXP] # - phase [P, S, N] Note: N - not detected #\",\n \"filter_times(truth_dict, model_in) # filter arrivals to picks that were passed to the model\",\n \"------------------ # read in UW arrival times as an array def read_arrivals_to_arr(filename): model_list\",\n \"-------------------- # case 1: run if .mseed files have correct timestamps \\\"\\\"\\\" time\",\n \"# fails if date is missing floating point numbers formatted_time = datetime.strptime(tmp[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\")\",\n \"(t_truth - t_model_pick) import numpy import math import string import datetime import sys\",\n \"comp_out.append(\\\"comparison_out/comp.\\\" + etype + \\\".out\\\") # ------------------ # read in UW arrival times\",\n \"ln in f: row = ln.split() line = [] line.extend([row[0].strip(), row[1].strip(), row[2].strip()]) formatted_time\",\n \"if .mseed files have correct timestamps \\\"\\\"\\\" time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") - fudge_factor\",\n \"[] model_in = [] model_out = [] comp_out = [] for etype in\",\n \"= ['nan'] outp_file.write(str(event[5]) + \\\" \\\" + phase) for offset in times: outp_file.write(\\\"\",\n \"= key[0:-7] picks[key] = arr return picks def model_in_to_array(file): timestamps = [] with\",\n \"if date is missing floating point numbers formatted_time = datetime.strptime(tmp[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") if key\",\n \"\\\":\\\" + entry[12:14] # ------------- TIME STAMP ISSUES -------------------- # case 1: run\",\n \"[] if key in model_dict.keys(): times = model_dict[key] times = time_lookup(event[3], times) return\",\n \"times = [] if key in model_dict.keys(): times = model_dict[key] times = time_lookup(event[3],\",\n \"comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \\\"parsed_arrivals/\\\" + etype +\",\n \"try: # fails if date is missing floating point numbers formatted_time = datetime.strptime(tmp[3],\",\n \"# ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered = [] for key\",\n \"\\\"%Y-%m-%dT%H:%M:%S\\\") # ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered = [] for\",\n \"< t_upper: offset = t - time # or format time to absolute\",\n \"PXS, PXP] # - phase [P, S, N] Note: N - not detected\",\n \"+ entry[10:12] + \\\":\\\" + entry[12:14] # ------------- TIME STAMP ISSUES -------------------- #\",\n \"datetime import datetime from datetime import timedelta # params padding_time = 10 fudge_factor\",\n \"in the timestamps time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") if time.second >=37 and time.second <=51:\",\n \"model .in file as a list truth_arr = filter_times(truth_dict, model_in) # filter arrivals\",\n \"phase = 'N' times = ['nan'] outp_file.write(str(event[5]) + \\\" \\\" + phase) for\",\n \"- phase [P, S, N] Note: N - not detected # - model\",\n \"59: sec_int = sec_int - 60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\")\",\n \"def filter_times(arrivals, model_in): filtered = [] for key in model_in: if key in\",\n \"= \\\"input_files/GPD.\\\" + etype + \\\".in\\\" outfile = \\\"output_files/GPD.\\\" + etype + \\\".out\\\"\",\n \"[] for time in time_arr: if time > t_lower and time < t_upper:\",\n \"['nan'] outp_file.write(str(event[5]) + \\\" \\\" + phase) for offset in times: outp_file.write(\\\" \\\"\",\n \"= [] for time in time_arr: if time > t_lower and time <\",\n \"have buggy minutes in the timestamps time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") if time.second >=37\",\n \"not detected # - model time offset (t_truth - t_model_pick) import numpy import\",\n \"model_in_to_array(inf) # read in model .in file as a list truth_arr = filter_times(truth_dict,\",\n \"in truth_arr: phase = event[2] times = key_lookup(event, phase, model_dict) if len(times) ==\",\n \"- type of event tested [EQS, EQP, SUS, SUP, THS, THP, SNS, SNP,\",\n \"times = ['nan'] outp_file.write(str(event[5]) + \\\" \\\" + phase) for offset in times:\",\n \"dirs parsed_arrivals = [] model_in = [] model_out = [] comp_out = []\",\n \"N] Note: N - not detected # - model time offset (t_truth -\",\n \"(key=truncated timestamp) model_in = model_in_to_array(inf) # read in model .in file as a\",\n \"read output file for event in truth_arr: phase = event[2] times = key_lookup(event,\",\n \"\\\"output_files/GPD.\\\" + etype + \\\".out\\\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\\\"comparison_out/comp.\\\" + etype + \\\".out\\\")\",\n \"model_dict = read_output_to_dict(outf) # read output file for event in truth_arr: phase =\",\n \"= time.second + 23 if sec_int > 59: sec_int = sec_int - 60\",\n \"and create a dictionary def read_output_to_dict(filename): model_dict = {} with open(filename) as f:\",\n \"# params padding_time = 10 fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) # file\",\n \"import datetime from datetime import timedelta # params padding_time = 10 fudge_factor =\",\n \"datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") else: sec_int = time.second + 23 if sec_int > 59: sec_int\",\n \"offset = t - time # or format time to absolute value: abs(t\",\n \"a list truth_arr = filter_times(truth_dict, model_in) # filter arrivals to picks that were\",\n \"read in the arrival times to a list truth_dict = arrivals_to_dictionary(truth_arr) # convert\",\n \"# ------------------ # read in UW arrival times as an array def read_arrivals_to_arr(filename):\",\n \"\\\"-\\\" + tmp[1] + \\\"-\\\" + tmp[2] try: # fails if date is\",\n \"= line.split() key = tmp[0] + \\\"-\\\" + tmp[1] + \\\"-\\\" + tmp[2]\",\n \"arrival = \\\"parsed_arrivals/\\\" + etype + \\\".arrivals.txt\\\" infile = \\\"input_files/GPD.\\\" + etype +\",\n \"as f: for line in f: tmp = line.split() key = tmp[0] +\",\n \"= timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs parsed_arrivals = [] model_in =\",\n \"str(sec_int).zfill(2) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") time = time[:-2] + sec_int time = datetime.strptime(time,\",\n \"def model_in_to_array(file): timestamps = [] with open(file) as f: for ln in f:\",\n \"key in arrivals: filtered.append(arrivals[key]) return filtered # read in Caltech model output and\",\n \"outp_file.write(\\\" \\\" + str(offset)) outp_file.write('\\\\n') outp_file.close() for i in range(len(model_out)): execute_script(parsed_arrivals[i], model_in[i], model_out[i],\",\n \"> 59: sec_int = sec_int - 60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time,\",\n \"phase, model_dict): key = event[0] + \\\"-\\\" + event[1] + \\\"-\\\" + phase\",\n \"arrival times to a list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to a\",\n \"\\\"%Y-%m-%dT%H:%M:%S.%f\\\") if key not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return\",\n \"time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper = t + timedelta(seconds=padding_time) offsets\",\n \"time_lookup(event[3], times) return times # search for arrivals within the padding time window\",\n \"files have correct timestamps \\\"\\\"\\\" time = datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") - fudge_factor # +\",\n \"file dirs parsed_arrivals = [] model_in = [] model_out = [] comp_out =\",\n \"= time[:-2] + sec_int time = datetime.strptime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") + time_diff time = datetime.strftime(time,\",\n \"\\\"-\\\" + event[1] + \\\"-\\\" + phase times = [] if key in\",\n \"need to add this) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") \\\"\\\"\\\" # case 2: run\",\n \"time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") \\\"\\\"\\\" # case 2: run if .mseed files have\",\n \"datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") if time.second >=37 and time.second <=51: time = time + timedelta(seconds=23)\",\n \"to a list truth_dict = arrivals_to_dictionary(truth_arr) # convert arrivals to a dictionary (key=truncated\",\n \"to a dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) # read in model .in\",\n \"time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") else: sec_int = time.second + 23 if sec_int\",\n \"def arrivals_to_dictionary(arrivals): picks = {} for arr in arrivals: key = datetime.strftime(arr[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\")\",\n \"read in UW arrival times as an array def read_arrivals_to_arr(filename): model_list = []\",\n \"entry[6:8] + \\\"T\\\" + entry[8:10] + \\\":\\\" + entry[10:12] + \\\":\\\" + entry[12:14]\",\n \"if sec_int > 59: sec_int = sec_int - 60 sec_int = str(sec_int).zfill(2) time\",\n \"key = event[0] + \\\"-\\\" + event[1] + \\\"-\\\" + phase times =\",\n \"+ \\\"-\\\" + tmp[1] + \\\"-\\\" + tmp[2] try: # fails if date\",\n \"'S' else: phase = 'P' times = key_lookup(event, phase, model_dict) if len(times) ==\",\n \"import os import csv from datetime import datetime from datetime import timedelta #\",\n \"arrival times as an array def read_arrivals_to_arr(filename): model_list = [] with open(filename) as\",\n \"for offset in times: outp_file.write(\\\" \\\" + str(offset)) outp_file.write('\\\\n') outp_file.close() for i in\",\n \"Note: N - not detected # - model time offset (t_truth - t_model_pick)\",\n \"entry = entry[0].strip() entry = entry[len(entry)-20:len(entry)-6] entry = entry[0:4] + \\\"-\\\" + entry[4:6]\",\n \"= [] model_dict[key].append(formatted_time) except: pass return model_dict # lookup time in the dictionary\",\n \"+ phase times = [] if key in model_dict.keys(): times = model_dict[key] times\",\n \"0: if phase == 'P': phase = 'S' else: phase = 'P' times\",\n \"outputs to file outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in\",\n \"search for arrivals within the padding time window def time_lookup(t, time_arr): t_lower =\",\n \"datetime.strptime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") # ----------------------------------------------------- timestamps.append(time) return timestamps\",\n \"[P, S, N] Note: N - not detected # - model time offset\",\n \"# file dirs parsed_arrivals = [] model_in = [] model_out = [] comp_out\",\n \"model_in: if key in arrivals: filtered.append(arrivals[key]) return filtered # read in Caltech model\",\n \"# + time_diff (might need to add this) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") \\\"\\\"\\\"\",\n \"in time_arr: if time > t_lower and time < t_upper: offset = t\",\n \"sec_int = sec_int - 60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") time\",\n \"model_in) # filter arrivals to picks that were passed to the model (.in\",\n \"------------- TIME STAMP ISSUES -------------------- # case 1: run if .mseed files have\",\n \"model time offset (t_truth - t_model_pick) import numpy import math import string import\",\n \"the padding time window def time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper\",\n \"import csv from datetime import datetime from datetime import timedelta # params padding_time\",\n \"if time > t_lower and time < t_upper: offset = t - time\",\n \"outf, comp_out): # write outputs to file outp_file = open(comp_out, 'w') truth_arr =\",\n \"entry[12:14] # ------------- TIME STAMP ISSUES -------------------- # case 1: run if .mseed\",\n \"[] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \\\"parsed_arrivals/\\\" + etype + \\\".arrivals.txt\\\" infile\",\n \"import sys import os import csv from datetime import datetime from datetime import\",\n \"arrivals to picks that were passed to the model (.in file) model_dict =\",\n \"{} with open(filename) as f: for line in f: tmp = line.split() key\",\n \"+ \\\".out\\\") # ------------------ # read in UW arrival times as an array\",\n \"detected # - model time offset (t_truth - t_model_pick) import numpy import math\",\n \"+ entry[8:10] + \\\":\\\" + entry[10:12] + \\\":\\\" + entry[12:14] # ------------- TIME\",\n \"> t_lower and time < t_upper: offset = t - time # or\",\n \"# read in the arrival times to a list truth_dict = arrivals_to_dictionary(truth_arr) #\",\n \"60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") time = time[:-2] + sec_int\",\n \"outputs: # - type of event tested [EQS, EQP, SUS, SUP, THS, THP,\",\n \"outfile = \\\"output_files/GPD.\\\" + etype + \\\".out\\\" parsed_arrivals.append(arrival) model_in.append(infile) model_out.append(outfile) comp_out.append(\\\"comparison_out/comp.\\\" + etype\",\n \"t_model_pick) import numpy import math import string import datetime import sys import os\",\n \"model_dict = {} with open(filename) as f: for line in f: tmp =\",\n \"model_dict) if len(times) == 0: if phase == 'P': phase = 'S' else:\",\n \"= datetime.strptime(entry, \\\"%Y-%m-%dT%H:%M:%S\\\") - fudge_factor # + time_diff (might need to add this)\",\n \"+ \\\"-\\\" + tmp[2] try: # fails if date is missing floating point\",\n \"outp_file.write(str(event[5]) + \\\" \\\" + phase) for offset in times: outp_file.write(\\\" \\\" +\",\n \"# - type of event tested [EQS, EQP, SUS, SUP, THS, THP, SNS,\",\n \"in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \\\"parsed_arrivals/\\\" + etype + \\\".arrivals.txt\\\" infile = \\\"input_files/GPD.\\\" +\",\n \"# write outputs to file outp_file = open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) #\",\n \"fudge_factor # + time_diff (might need to add this) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\")\",\n \"= time + timedelta(seconds=23) + time_diff time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") else: sec_int =\",\n \"['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \\\"parsed_arrivals/\\\" + etype + \\\".arrivals.txt\\\" infile = \\\"input_files/GPD.\\\" + etype\",\n \"fudge_factor = timedelta(seconds=27) time_diff = timedelta(seconds=10) # file dirs parsed_arrivals = [] model_in\",\n \"== 0: if phase == 'P': phase = 'S' else: phase = 'P'\",\n \"time in the dictionary def key_lookup(event, phase, model_dict): key = event[0] + \\\"-\\\"\",\n \"= datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") # ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered =\",\n \"- time) offset = offset.total_seconds() offsets.append('{:.6f}'.format(offset)) return offsets def execute_script(arrival, inf, outf, comp_out):\",\n \"etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival = \\\"parsed_arrivals/\\\" + etype + \\\".arrivals.txt\\\" infile = \\\"input_files/GPD.\\\"\",\n \"window def time_lookup(t, time_arr): t_lower = t - timedelta(seconds=padding_time) t_upper = t +\",\n \"tests GPD model using UW truth data # Test outputs: # - type\",\n \"for arrivals within the padding time window def time_lookup(t, time_arr): t_lower = t\",\n \"truth_arr = read_arrivals_to_arr(arrival) # read in the arrival times to a list truth_dict\",\n \"= sec_int - 60 sec_int = str(sec_int).zfill(2) time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") time =\",\n \"in model_in: if key in arrivals: filtered.append(arrivals[key]) return filtered # read in Caltech\",\n \"- time # or format time to absolute value: abs(t - time) offset\",\n \"\\\"parsed_arrivals/\\\" + etype + \\\".arrivals.txt\\\" infile = \\\"input_files/GPD.\\\" + etype + \\\".in\\\" outfile\",\n \"inf, outf, comp_out): # write outputs to file outp_file = open(comp_out, 'w') truth_arr\",\n \"= event[2] times = key_lookup(event, phase, model_dict) if len(times) == 0: if phase\",\n \"\\\"%Y-%m-%dT%H:%M:%S\\\") \\\"\\\"\\\" # case 2: run if .mseed files have buggy minutes in\",\n \"arrivals: key = datetime.strftime(arr[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") key = key[0:-7] picks[key] = arr return picks\",\n \"data # Test outputs: # - type of event tested [EQS, EQP, SUS,\",\n \"if key in arrivals: filtered.append(arrivals[key]) return filtered # read in Caltech model output\",\n \"datetime.strftime(arr[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") key = key[0:-7] picks[key] = arr return picks def model_in_to_array(file): timestamps\",\n \"point numbers formatted_time = datetime.strptime(tmp[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") if key not in model_dict: model_dict[key] =\",\n \"t_lower and time < t_upper: offset = t - time # or format\",\n \"time in time_arr: if time > t_lower and time < t_upper: offset =\",\n \"phase) for offset in times: outp_file.write(\\\" \\\" + str(offset)) outp_file.write('\\\\n') outp_file.close() for i\",\n \"a dictionary def read_output_to_dict(filename): model_dict = {} with open(filename) as f: for line\",\n \"time = datetime.strftime(time, \\\"%Y-%m-%dT%H:%M:%S\\\") # ----------------------------------------------------- timestamps.append(time) return timestamps def filter_times(arrivals, model_in): filtered\",\n \"Caltech model output and create a dictionary def read_output_to_dict(filename): model_dict = {} with\",\n \"entry[4:6] + \\\"-\\\" + entry[6:8] + \\\"T\\\" + entry[8:10] + \\\":\\\" + entry[10:12]\",\n \"= filter_times(truth_dict, model_in) # filter arrivals to picks that were passed to the\",\n \"times = key_lookup(event, phase, model_dict) if len(times) == 0: phase = 'N' times\",\n \"model_in.append(infile) model_out.append(outfile) comp_out.append(\\\"comparison_out/comp.\\\" + etype + \\\".out\\\") # ------------------ # read in UW\",\n \"dictionary (key=truncated timestamp) model_in = model_in_to_array(inf) # read in model .in file as\",\n \"infile = \\\"input_files/GPD.\\\" + etype + \\\".in\\\" outfile = \\\"output_files/GPD.\\\" + etype +\",\n \"passed to the model (.in file) model_dict = read_output_to_dict(outf) # read output file\",\n \"phase = 'P' times = key_lookup(event, phase, model_dict) if len(times) == 0: phase\",\n \"formatted_time = datetime.strptime(row[3], \\\"%Y-%m-%dT%H:%M:%S.%f\\\") - fudge_factor line.extend([formatted_time, row[4].strip(), row[5].strip()]) model_list.append(line) return model_list def\",\n \"not in model_dict: model_dict[key] = [] model_dict[key].append(formatted_time) except: pass return model_dict # lookup\"\n]","isConversational":false}}},{"rowIdx":1477,"cells":{"ngram":{"kind":"list like","value":["chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command =","Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger =","os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\"bucket\") parser.add_argument(\"video_filename\") parser.add_argument(\"thumbnail_filename\") parser.add_argument(\"video_key\") parser.add_argument(\"thumbnail_key\")","[\"s3://\" + posixpath.join(frame[\"bucket\"], frame[\"key\"]) for frame in aws_lambda_response[\"frames\"]] img_types = [\"png\" for frame","from concurrent import futures from multiprocessing import Pool from ultitrackerapi import get_backend, get_logger,","in aws_lambda_response[\"frames\"]] img_types = [\"png\" for frame in aws_lambda_response[\"frames\"]] metadatas = [ {\"bucket\":","* chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command",") ) logger.debug(\"extract_and_upload_video: Finished uploading video chunks\") logger.debug(\"extract_and_upload_video: Submitting lambda frame extraction\") aws_lambda_payloads","= get_s3Client() def update_game_video_length(game_id, video_length): command = \"\"\" UPDATE ultitracker.game_metadata SET data =","video to S3\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\"extract_and_upload_video: Finished uploading video to","img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command = \"\"\" INSERT INTO ultitracker.img_location (img_id,","thumbnail\") logger.debug(\"extract_and_upload_video: Uploading thumbnail\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\"extract_and_upload_video: Finished uploading thumbnail\")",") backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1]) return chunk_number","Finished uploading thumbnail\") logger.debug(\"extract_and_upload_video: Uploading video to S3\") s3Client.upload_file( video_filename, bucket, video_key )",") logger.debug(\"extract_and_upload_video: Finished uploading thumbnail\") logger.debug(\"extract_and_upload_video: Uploading video to S3\") s3Client.upload_file( video_filename, bucket,","shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\"bucket\") parser.add_argument(\"video_filename\") parser.add_argument(\"thumbnail_filename\") parser.add_argument(\"video_key\") parser.add_argument(\"thumbnail_key\") parser.add_argument(\"game_id\") args","= jsonb_set(data, '{{length}}', '\"{video_length}\"', true) WHERE game_id = '{game_id}' \"\"\".format( video_length=video_length, game_id=game_id )","metadata\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\"bucket\") parser.add_argument(\"video_filename\") parser.add_argument(\"thumbnail_filename\") parser.add_argument(\"video_key\")","video chunks\") with futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir,","update_game_video_length(game_id, video_length): command = \"\"\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\"{video_length}\"',","def update_game_video_length(game_id, video_length): command = \"\"\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}',","game_id = '{game_id}' \"\"\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number =","Finished updating length in db\") logger.debug(\"extract_and_upload_video: Extracting thumbnail\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2)","Extracting thumbnail\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\"extract_and_upload_video: Finished extracting thumbnail\") logger.debug(\"extract_and_upload_video: Uploading","os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \"chunks\", vid ) ) logger.debug(\"extract_and_upload_video: Finished uploading video","video_length) logger.debug(\"extract_and_upload_video: Finished updating length in db\") logger.debug(\"extract_and_upload_video: Extracting thumbnail\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds","s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\"extract_and_upload_video: Finished uploading video to S3\") logger.debug(\"extract_and_upload_video: Chunking","to S3\") logger.debug(\"extract_and_upload_video: Chunking video\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\"extract_and_upload_video: Finished","ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\"{video_length}\"', true) WHERE game_id = '{game_id}' \"\"\".format(","logger.debug(\"extract_and_upload_video: Updating length in db\") update_game_video_length(game_id, video_length) logger.debug(\"extract_and_upload_video: Finished updating length in db\")","aws_lambda_response[\"frames\"] ] frame_numbers = [-1 for frame in aws_lambda_response[\"frames\"]] insert_images( raw_paths, img_types, metadatas,","chunks\") with futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid),","for frame in aws_lambda_response[\"frames\"]] img_types = [\"png\" for frame in aws_lambda_response[\"frames\"]] metadatas =","Finished getting video length\") logger.debug(\"extract_and_upload_video: Getting video height and width\") video_height_width = video.get_video_height_width(video_filename)","= \"\"\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\"{video_length}\"', true) WHERE game_id","uploading video to S3\") logger.debug(\"extract_and_upload_video: Chunking video\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60)","// 2) logger.debug(\"extract_and_upload_video: Finished extracting thumbnail\") logger.debug(\"extract_and_upload_video: Uploading thumbnail\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key","img_types, img_metadatas, game_id, frame_numbers ): command = \"\"\" INSERT INTO ultitracker.img_location (img_id, img_raw_path,",") backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\"extract_and_upload_video: Getting","game_id ): logger.debug(\"extract_and_upload_video: Getting video length\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\"extract_and_upload_video:","2) logger.debug(\"extract_and_upload_video: Finished extracting thumbnail\") logger.debug(\"extract_and_upload_video: Uploading thumbnail\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key )","\"frames\", posixpath.splitext(basename)[0]), \"video_metadata\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda')","parser.add_argument(\"video_filename\") parser.add_argument(\"thumbnail_filename\") parser.add_argument(\"video_key\") parser.add_argument(\"thumbnail_key\") parser.add_argument(\"game_id\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key,","as ex: result_futures = [] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\"extractFrames\", #","return chunk_number * chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers","Getting video height and width\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\"extract_and_upload_video: Finished getting height and","(img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \"\"\"('{img_id}', '{img_raw_path}',","frame in aws_lambda_response[\"frames\"]] metadatas = [ {\"bucket\": bucket} for frame in aws_lambda_response[\"frames\"] ]","chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1]) return chunk_number * chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types,","boto3 import datetime import json import os import posixpath import re import shutil","'{img_metadata}', '{game_id}', {frame_number}){include_comma} \"\"\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\",\" if i","[-1 for frame in aws_lambda_response[\"frames\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\"extract_and_upload_video:","logger.debug(\"extract_and_upload_video: Uploading video to S3\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\"extract_and_upload_video: Finished uploading","= '{game_id}' \"\"\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1])","logger.debug(\"extract_and_upload_video: Finished extracting thumbnail\") logger.debug(\"extract_and_upload_video: Uploading thumbnail\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\"extract_and_upload_video:","INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \"\"\" for i, (img_raw_path,","else \"\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ):","video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\"extract_and_upload_video: Finished chunking video\") logger.debug(\"extract_and_upload_video: Uploading video chunks\") with futures.ThreadPoolExecutor(8)","import boto3 import datetime import json import os import posixpath import re import","extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\"extract_and_upload_video: Getting video length\") video_length_seconds","in db\") logger.debug(\"extract_and_upload_video: Extracting thumbnail\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\"extract_and_upload_video: Finished extracting","video\") logger.debug(\"extract_and_upload_video: Uploading video chunks\") with futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir):","i < (len(img_raw_paths) - 1) else \"\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename,","video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses = []","s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \"chunks\", vid ) ) logger.debug(\"extract_and_upload_video: Finished uploading","int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1]) return chunk_number * chunk_multiplier + frame_number def insert_images( img_raw_paths,","logger.debug(\"extract_and_upload_video: Finished uploading thumbnail\") logger.debug(\"extract_and_upload_video: Uploading video to S3\") s3Client.upload_file( video_filename, bucket, video_key","video backend_instance = get_backend() logger = get_logger(__name__, level=\"DEBUG\") s3Client = get_s3Client() def update_game_video_length(game_id,","'{{length}}', '\"{video_length}\"', true) WHERE game_id = '{game_id}' \"\"\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def","img_types = [\"png\" for frame in aws_lambda_response[\"frames\"]] metadatas = [ {\"bucket\": bucket} for","logger.debug(\"extract_and_upload_video: Getting video length\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\"extract_and_upload_video: Finished getting","(img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \"\"\" for i, (img_raw_path, img_type, img_metadata,","'{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \"\"\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\",\"","aws_lambda_response = json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\"s3://\" + posixpath.join(frame[\"bucket\"], frame[\"key\"]) for frame in","\"\"\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\",\" if i < (len(img_raw_paths) -","import uuid from concurrent import futures from multiprocessing import Pool from ultitrackerapi import","get_s3Client() def update_game_video_length(game_id, video_length): command = \"\"\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data,","= tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\"extract_and_upload_video: Finished chunking video\") logger.debug(\"extract_and_upload_video: Uploading video chunks\")","logger.debug(\"extract_and_upload_video: Uploading thumbnail\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\"extract_and_upload_video: Finished uploading thumbnail\") logger.debug(\"extract_and_upload_video:","get_logger, get_s3Client, video backend_instance = get_backend() logger = get_logger(__name__, level=\"DEBUG\") s3Client = get_s3Client()","aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for payload in","logger.debug(\"extract_and_upload_video: Finished uploading video chunks\") logger.debug(\"extract_and_upload_video: Submitting lambda frame extraction\") aws_lambda_payloads = [","length\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\"extract_and_upload_video: Finished getting video length\") logger.debug(\"extract_and_upload_video:","thumbnail_filename, time=video_length_seconds // 2) logger.debug(\"extract_and_upload_video: Finished extracting thumbnail\") logger.debug(\"extract_and_upload_video: Uploading thumbnail\") s3Client.upload_file( thumbnail_filename,","command += \"\"\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \"\"\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata),","= video.get_video_height_width(video_filename) logger.debug(\"extract_and_upload_video: Finished getting height and width\") logger.debug(\"extract_and_upload_video: Updating length in db\")","game_id=game_id, frame_number=frame_number, include_comma=\",\" if i < (len(img_raw_paths) - 1) else \"\" ) backend_instance.client.execute(command)","+ frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command = \"\"\"","): command = \"\"\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number)","def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1]) return chunk_number * chunk_multiplier","import json import os import posixpath import re import shutil import tempfile import","Finished uploading video to S3\") logger.debug(\"extract_and_upload_video: Chunking video\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir,",") logger.debug(\"extract_and_upload_video: Received all lambda responses\") logger.debug(\"extract_and_upload_video: Finished inserting image metadata\") os.remove(video_filename) os.remove(thumbnail_filename)","thumbnail\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\"extract_and_upload_video: Finished uploading thumbnail\") logger.debug(\"extract_and_upload_video: Uploading video","= [\"s3://\" + posixpath.join(frame[\"bucket\"], frame[\"key\"]) for frame in aws_lambda_response[\"frames\"]] img_types = [\"png\" for","parser.add_argument(\"thumbnail_filename\") parser.add_argument(\"video_key\") parser.add_argument(\"thumbnail_key\") parser.add_argument(\"game_id\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key,","img_types, metadatas, game_id, frame_numbers ) logger.debug(\"extract_and_upload_video: Received all lambda responses\") logger.debug(\"extract_and_upload_video: Finished inserting","re import shutil import tempfile import uuid from concurrent import futures from multiprocessing","logger.debug(\"extract_and_upload_video: Chunking video\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\"extract_and_upload_video: Finished chunking video\")","img_metadatas, game_id, frame_numbers ): command = \"\"\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type,","= [] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\"extractFrames\", # InvocationType=\"Event\", Payload=payload ))","lambda frame extraction\") for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\")) aws_lambda_responses.append(aws_lambda_response) raw_paths =","str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\"extract_and_upload_video: Finished getting video length\") logger.debug(\"extract_and_upload_video: Getting video height and width\") video_height_width","ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger = get_logger(__name__, level=\"DEBUG\")",")) logger.debug(\"extract_and_upload_video: Submitted lambda frame extraction\") for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\"))","ex: result_futures = [] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\"extractFrames\", # InvocationType=\"Event\",","] client = boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures =","INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \"\"\" for i,","= int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\"extract_and_upload_video: Finished getting video length\") logger.debug(\"extract_and_upload_video: Getting video","video height and width\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\"extract_and_upload_video: Finished getting height and width\")","thumbnail_filename, bucket, thumbnail_key ) logger.debug(\"extract_and_upload_video: Finished uploading thumbnail\") logger.debug(\"extract_and_upload_video: Uploading video to S3\")","uploading thumbnail\") logger.debug(\"extract_and_upload_video: Uploading video to S3\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\"extract_and_upload_video:","parser.add_argument(\"game_id\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id ) if","in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex:","= [\"png\" for frame in aws_lambda_response[\"frames\"]] metadatas = [ {\"bucket\": bucket} for frame","get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1]) return chunk_number * chunk_multiplier +","+= \"\"\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \"\"\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id,","vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \"chunks\", vid )","bucket} for frame in aws_lambda_response[\"frames\"] ] frame_numbers = [-1 for frame in aws_lambda_response[\"frames\"]]","thumbnail_key ) logger.debug(\"extract_and_upload_video: Finished uploading thumbnail\") logger.debug(\"extract_and_upload_video: Uploading video to S3\") s3Client.upload_file( video_filename,","\"s3_output_frames_path\": posixpath.join(posixpath.dirname(video_key), \"frames\", posixpath.splitext(basename)[0]), \"video_metadata\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ] client","payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\"extractFrames\", # InvocationType=\"Event\", Payload=payload )) logger.debug(\"extract_and_upload_video: Submitted lambda","height and width\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\"extract_and_upload_video: Finished getting height and width\") logger.debug(\"extract_and_upload_video:","video to S3\") logger.debug(\"extract_and_upload_video: Chunking video\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\"extract_and_upload_video:","include_comma=\",\" if i < (len(img_raw_paths) - 1) else \"\" ) backend_instance.client.execute(command) def extract_and_upload_video(","game_id, frame_numbers ) logger.debug(\"extract_and_upload_video: Received all lambda responses\") logger.debug(\"extract_and_upload_video: Finished inserting image metadata\")","insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\"extract_and_upload_video: Received all lambda responses\") logger.debug(\"extract_and_upload_video:","argparse import boto3 import datetime import json import os import posixpath import re","- 1) else \"\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key,","\"\"\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \"\"\" for","FunctionName=\"extractFrames\", # InvocationType=\"Event\", Payload=payload )) logger.debug(\"extract_and_upload_video: Submitted lambda frame extraction\") for result_future in","get_s3Client, video backend_instance = get_backend() logger = get_logger(__name__, level=\"DEBUG\") s3Client = get_s3Client() def","[] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\"extractFrames\", # InvocationType=\"Event\", Payload=payload )) logger.debug(\"extract_and_upload_video:","in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \"\"\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma}","tempfile import uuid from concurrent import futures from multiprocessing import Pool from ultitrackerapi","import shutil import tempfile import uuid from concurrent import futures from multiprocessing import","= [ json.dumps({ \"s3_bucket_path\": bucket, \"s3_video_path\": posixpath.join(posixpath.dirname(video_key), \"chunks\", basename), \"s3_output_frames_path\": posixpath.join(posixpath.dirname(video_key), \"frames\", posixpath.splitext(basename)[0]),","parser = argparse.ArgumentParser() parser.add_argument(\"bucket\") parser.add_argument(\"video_filename\") parser.add_argument(\"thumbnail_filename\") parser.add_argument(\"video_key\") parser.add_argument(\"thumbnail_key\") parser.add_argument(\"game_id\") args = parser.parse_args() extract_and_upload_video(","video chunks\") logger.debug(\"extract_and_upload_video: Submitting lambda frame extraction\") aws_lambda_payloads = [ json.dumps({ \"s3_bucket_path\": bucket,","'{game_id}', {frame_number}){include_comma} \"\"\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\",\" if i <","json.dumps({ \"s3_bucket_path\": bucket, \"s3_video_path\": posixpath.join(posixpath.dirname(video_key), \"chunks\", basename), \"s3_output_frames_path\": posixpath.join(posixpath.dirname(video_key), \"frames\", posixpath.splitext(basename)[0]), \"video_metadata\": video_height_width","image metadata\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\"bucket\") parser.add_argument(\"video_filename\") parser.add_argument(\"thumbnail_filename\")","parser.add_argument(\"thumbnail_key\") parser.add_argument(\"game_id\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id )","{frame_number}){include_comma} \"\"\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\",\" if i < (len(img_raw_paths)","aws_lambda_response[\"frames\"]] metadatas = [ {\"bucket\": bucket} for frame in aws_lambda_response[\"frames\"] ] frame_numbers =","frame_numbers ) logger.debug(\"extract_and_upload_video: Received all lambda responses\") logger.debug(\"extract_and_upload_video: Finished inserting image metadata\") os.remove(video_filename)","= get_backend() logger = get_logger(__name__, level=\"DEBUG\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command","+ posixpath.join(frame[\"bucket\"], frame[\"key\"]) for frame in aws_lambda_response[\"frames\"]] img_types = [\"png\" for frame in","video_filename, bucket, video_key ) logger.debug(\"extract_and_upload_video: Finished uploading video to S3\") logger.debug(\"extract_and_upload_video: Chunking video\")","frame_numbers)): command += \"\"\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \"\"\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type,","chunk_number * chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ):","logger.debug(\"extract_and_upload_video: Finished inserting image metadata\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser()","jsonb_set(data, '{{length}}', '\"{video_length}\"', true) WHERE game_id = '{game_id}' \"\"\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command)","json import os import posixpath import re import shutil import tempfile import uuid","length in db\") logger.debug(\"extract_and_upload_video: Extracting thumbnail\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\"extract_and_upload_video: Finished","def main(): parser = argparse.ArgumentParser() parser.add_argument(\"bucket\") parser.add_argument(\"video_filename\") parser.add_argument(\"thumbnail_filename\") parser.add_argument(\"video_key\") parser.add_argument(\"thumbnail_key\") parser.add_argument(\"game_id\") args =","= argparse.ArgumentParser() parser.add_argument(\"bucket\") parser.add_argument(\"video_filename\") parser.add_argument(\"thumbnail_filename\") parser.add_argument(\"video_key\") parser.add_argument(\"thumbnail_key\") parser.add_argument(\"game_id\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket,","img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\",\" if i < (len(img_raw_paths) - 1)","= get_logger(__name__, level=\"DEBUG\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command = \"\"\" UPDATE","lambda frame extraction\") aws_lambda_payloads = [ json.dumps({ \"s3_bucket_path\": bucket, \"s3_video_path\": posixpath.join(posixpath.dirname(video_key), \"chunks\", basename),","result_futures.append(ex.submit( client.invoke, FunctionName=\"extractFrames\", # InvocationType=\"Event\", Payload=payload )) logger.debug(\"extract_and_upload_video: Submitted lambda frame extraction\") for","Uploading thumbnail\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\"extract_and_upload_video: Finished uploading thumbnail\") logger.debug(\"extract_and_upload_video: Uploading","= boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for","img_metadata, game_id, frame_number) VALUES \"\"\" for i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths,","frame_number=frame_number, include_comma=\",\" if i < (len(img_raw_paths) - 1) else \"\" ) backend_instance.client.execute(command) def","raw_paths = [\"s3://\" + posixpath.join(frame[\"bucket\"], frame[\"key\"]) for frame in aws_lambda_response[\"frames\"]] img_types = [\"png\"","Finished inserting image metadata\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\"bucket\")","with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke,","frame[\"key\"]) for frame in aws_lambda_response[\"frames\"]] img_types = [\"png\" for frame in aws_lambda_response[\"frames\"]] metadatas","command = \"\"\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\"{video_length}\"', true) WHERE","all lambda responses\") logger.debug(\"extract_and_upload_video: Finished inserting image metadata\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main():","int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\"extract_and_upload_video: Finished getting video length\") logger.debug(\"extract_and_upload_video: Getting video height","int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1]) return chunk_number * chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id,","thumbnail_key, game_id ): logger.debug(\"extract_and_upload_video: Getting video length\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds))","metadatas, game_id, frame_numbers ) logger.debug(\"extract_and_upload_video: Received all lambda responses\") logger.debug(\"extract_and_upload_video: Finished inserting image","chunk_size=60) logger.debug(\"extract_and_upload_video: Finished chunking video\") logger.debug(\"extract_and_upload_video: Uploading video chunks\") with futures.ThreadPoolExecutor(8) as ex:","with futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket,","\"chunks\", basename), \"s3_output_frames_path\": posixpath.join(posixpath.dirname(video_key), \"frames\", posixpath.splitext(basename)[0]), \"video_metadata\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir)","bucket, thumbnail_key ) logger.debug(\"extract_and_upload_video: Finished uploading thumbnail\") logger.debug(\"extract_and_upload_video: Uploading video to S3\") s3Client.upload_file(","getting height and width\") logger.debug(\"extract_and_upload_video: Updating length in db\") update_game_video_length(game_id, video_length) logger.debug(\"extract_and_upload_video: Finished","Received all lambda responses\") logger.debug(\"extract_and_upload_video: Finished inserting image metadata\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def","= [ {\"bucket\": bucket} for frame in aws_lambda_response[\"frames\"] ] frame_numbers = [-1 for","result_futures = [] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\"extractFrames\", # InvocationType=\"Event\", Payload=payload","logger.debug(\"extract_and_upload_video: Received all lambda responses\") logger.debug(\"extract_and_upload_video: Finished inserting image metadata\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir)","i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \"\"\"('{img_id}',","def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\"extract_and_upload_video: Getting video length\")","getting video length\") logger.debug(\"extract_and_upload_video: Getting video height and width\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\"extract_and_upload_video:","in aws_lambda_response[\"frames\"] ] frame_numbers = [-1 for frame in aws_lambda_response[\"frames\"]] insert_images( raw_paths, img_types,","os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures","1) else \"\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id","in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\"extractFrames\", # InvocationType=\"Event\", Payload=payload )) logger.debug(\"extract_and_upload_video: Submitted lambda frame","logger.debug(\"extract_and_upload_video: Submitted lambda frame extraction\") for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\")) aws_lambda_responses.append(aws_lambda_response)","in aws_lambda_response[\"frames\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\"extract_and_upload_video: Received all lambda","s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command = \"\"\" UPDATE ultitracker.game_metadata SET data","S3\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\"extract_and_upload_video: Finished uploading video to S3\") logger.debug(\"extract_and_upload_video:","posixpath.join( posixpath.dirname(video_key), \"chunks\", vid ) ) logger.debug(\"extract_and_upload_video: Finished uploading video chunks\") logger.debug(\"extract_and_upload_video: Submitting","'{game_id}' \"\"\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1]) chunk_number","\"\"\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1]) chunk_number =","import datetime import json import os import posixpath import re import shutil import","extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id ) if __name__ == \"__main__\": main()","Finished uploading video chunks\") logger.debug(\"extract_and_upload_video: Submitting lambda frame extraction\") aws_lambda_payloads = [ json.dumps({","aws_lambda_responses.append(aws_lambda_response) raw_paths = [\"s3://\" + posixpath.join(frame[\"bucket\"], frame[\"key\"]) for frame in aws_lambda_response[\"frames\"]] img_types =","width\") logger.debug(\"extract_and_upload_video: Updating length in db\") update_game_video_length(game_id, video_length) logger.debug(\"extract_and_upload_video: Finished updating length in","bucket, posixpath.join( posixpath.dirname(video_key), \"chunks\", vid ) ) logger.debug(\"extract_and_upload_video: Finished uploading video chunks\") logger.debug(\"extract_and_upload_video:","posixpath import re import shutil import tempfile import uuid from concurrent import futures","ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \"chunks\", vid ) ) logger.debug(\"extract_and_upload_video: Finished","in aws_lambda_response[\"frames\"]] metadatas = [ {\"bucket\": bucket} for frame in aws_lambda_response[\"frames\"] ] frame_numbers","vid ) ) logger.debug(\"extract_and_upload_video: Finished uploading video chunks\") logger.debug(\"extract_and_upload_video: Submitting lambda frame extraction\")","img_metadatas, frame_numbers)): command += \"\"\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \"\"\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path,","video_key, thumbnail_key, game_id ): logger.debug(\"extract_and_upload_video: Getting video length\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length =","concurrent import futures from multiprocessing import Pool from ultitrackerapi import get_backend, get_logger, get_s3Client,","ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \"chunks\",","Finished extracting thumbnail\") logger.debug(\"extract_and_upload_video: Uploading thumbnail\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\"extract_and_upload_video: Finished","video length\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\"extract_and_upload_video: Finished getting video length\")","frame_numbers = [-1 for frame in aws_lambda_response[\"frames\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers","(len(img_raw_paths) - 1) else \"\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key,","= [-1 for frame in aws_lambda_response[\"frames\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers )",") logger.debug(\"extract_and_upload_video: Finished uploading video chunks\") logger.debug(\"extract_and_upload_video: Submitting lambda frame extraction\") aws_lambda_payloads =","chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\"extract_and_upload_video: Finished chunking video\") logger.debug(\"extract_and_upload_video: Uploading video","import futures from multiprocessing import Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video","import posixpath import re import shutil import tempfile import uuid from concurrent import","db\") update_game_video_length(game_id, video_length) logger.debug(\"extract_and_upload_video: Finished updating length in db\") logger.debug(\"extract_and_upload_video: Extracting thumbnail\") video.get_thumbnail(video_filename,","chunks\") logger.debug(\"extract_and_upload_video: Submitting lambda frame extraction\") aws_lambda_payloads = [ json.dumps({ \"s3_bucket_path\": bucket, \"s3_video_path\":","db\") logger.debug(\"extract_and_upload_video: Extracting thumbnail\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\"extract_and_upload_video: Finished extracting thumbnail\")","}).encode() for basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses = [] with","basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as","img_types, img_metadatas, frame_numbers)): command += \"\"\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \"\"\".format( img_id=uuid.uuid4(),","SET data = jsonb_set(data, '{{length}}', '\"{video_length}\"', true) WHERE game_id = '{game_id}' \"\"\".format( video_length=video_length,","posixpath.splitext(basename)[0]), \"video_metadata\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses","basename), \"s3_output_frames_path\": posixpath.join(posixpath.dirname(video_key), \"frames\", posixpath.splitext(basename)[0]), \"video_metadata\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ]","chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1]) return chunk_number * chunk_multiplier + frame_number","game_id, frame_number) VALUES \"\"\" for i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types,","logger.debug(\"extract_and_upload_video: Getting video height and width\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\"extract_and_upload_video: Finished getting height","img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\",\" if i < (len(img_raw_paths) - 1) else \"\"","posixpath.dirname(video_key), \"chunks\", vid ) ) logger.debug(\"extract_and_upload_video: Finished uploading video chunks\") logger.debug(\"extract_and_upload_video: Submitting lambda","\"s3_bucket_path\": bucket, \"s3_video_path\": posixpath.join(posixpath.dirname(video_key), \"chunks\", basename), \"s3_output_frames_path\": posixpath.join(posixpath.dirname(video_key), \"frames\", posixpath.splitext(basename)[0]), \"video_metadata\": video_height_width }).encode()","tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\"extract_and_upload_video: Finished chunking video\") logger.debug(\"extract_and_upload_video: Uploading video chunks\") with","game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1]) return","frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1]) return chunk_number * chunk_multiplier + frame_number def","\"s3_video_path\": posixpath.join(posixpath.dirname(video_key), \"chunks\", basename), \"s3_output_frames_path\": posixpath.join(posixpath.dirname(video_key), \"frames\", posixpath.splitext(basename)[0]), \"video_metadata\": video_height_width }).encode() for basename","frame_numbers ): command = \"\"\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id,","to S3\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\"extract_and_upload_video: Finished uploading video to S3\")","aws_lambda_response[\"frames\"]] img_types = [\"png\" for frame in aws_lambda_response[\"frames\"]] metadatas = [ {\"bucket\": bucket}","\"video_metadata\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses =","for frame in aws_lambda_response[\"frames\"]] metadatas = [ {\"bucket\": bucket} for frame in aws_lambda_response[\"frames\"]","'\"{video_length}\"', true) WHERE game_id = '{game_id}' \"\"\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key,","\"\"\" for i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command","img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\",\" if i < (len(img_raw_paths) - 1) else","posixpath.join(posixpath.dirname(video_key), \"chunks\", basename), \"s3_output_frames_path\": posixpath.join(posixpath.dirname(video_key), \"frames\", posixpath.splitext(basename)[0]), \"video_metadata\": video_height_width }).encode() for basename in","command = \"\"\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES","logger.debug(\"extract_and_upload_video: Finished getting video length\") logger.debug(\"extract_and_upload_video: Getting video height and width\") video_height_width =","video length\") logger.debug(\"extract_and_upload_video: Getting video height and width\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\"extract_and_upload_video: Finished","thumbnail\") logger.debug(\"extract_and_upload_video: Uploading video to S3\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\"extract_and_upload_video: Finished","= str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\"extract_and_upload_video: Finished getting video length\") logger.debug(\"extract_and_upload_video: Getting video height and width\")","WHERE game_id = '{game_id}' \"\"\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number","shutil import tempfile import uuid from concurrent import futures from multiprocessing import Pool","multiprocessing import Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance = get_backend()","frame extraction\") aws_lambda_payloads = [ json.dumps({ \"s3_bucket_path\": bucket, \"s3_video_path\": posixpath.join(posixpath.dirname(video_key), \"chunks\", basename), \"s3_output_frames_path\":","frame_number) VALUES \"\"\" for i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas,","video\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\"extract_and_upload_video: Finished chunking video\") logger.debug(\"extract_and_upload_video: Uploading","futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join(","game_id, frame_numbers ): command = \"\"\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata,","futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\"extractFrames\",","for i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command +=","height and width\") logger.debug(\"extract_and_upload_video: Updating length in db\") update_game_video_length(game_id, video_length) logger.debug(\"extract_and_upload_video: Finished updating","'{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \"\"\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\",\" if","UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\"{video_length}\"', true) WHERE game_id = '{game_id}'","= parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id ) if __name__ ==","logger.debug(\"extract_and_upload_video: Finished getting height and width\") logger.debug(\"extract_and_upload_video: Updating length in db\") update_game_video_length(game_id, video_length)","true) WHERE game_id = '{game_id}' \"\"\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60):","vid), bucket, posixpath.join( posixpath.dirname(video_key), \"chunks\", vid ) ) logger.debug(\"extract_and_upload_video: Finished uploading video chunks\")","in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\"s3://\" + posixpath.join(frame[\"bucket\"], frame[\"key\"]) for","thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\"extract_and_upload_video: Getting video length\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length","Updating length in db\") update_game_video_length(game_id, video_length) logger.debug(\"extract_and_upload_video: Finished updating length in db\") logger.debug(\"extract_and_upload_video:","frame in aws_lambda_response[\"frames\"]] img_types = [\"png\" for frame in aws_lambda_response[\"frames\"]] metadatas = [","extraction\") for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\"s3://\" +","inserting image metadata\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\"bucket\") parser.add_argument(\"video_filename\")","json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\"s3://\" + posixpath.join(frame[\"bucket\"], frame[\"key\"]) for frame in aws_lambda_response[\"frames\"]] img_types","client = boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = []","logger.debug(\"extract_and_upload_video: Submitting lambda frame extraction\") aws_lambda_payloads = [ json.dumps({ \"s3_bucket_path\": bucket, \"s3_video_path\": posixpath.join(posixpath.dirname(video_key),","= [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for payload in aws_lambda_payloads:","def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command = \"\"\" INSERT INTO","= int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1]) return chunk_number * chunk_multiplier + frame_number def insert_images(","backend_instance = get_backend() logger = get_logger(__name__, level=\"DEBUG\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length):","from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger = get_logger(__name__,","video_height_width = video.get_video_height_width(video_filename) logger.debug(\"extract_and_upload_video: Finished getting height and width\") logger.debug(\"extract_and_upload_video: Updating length in","datetime import json import os import posixpath import re import shutil import tempfile","): logger.debug(\"extract_and_upload_video: Getting video length\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\"extract_and_upload_video: Finished","parser.add_argument(\"bucket\") parser.add_argument(\"video_filename\") parser.add_argument(\"thumbnail_filename\") parser.add_argument(\"video_key\") parser.add_argument(\"thumbnail_key\") parser.add_argument(\"game_id\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename,","parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id ) if __name__ == \"__main__\":","logger.debug(\"extract_and_upload_video: Extracting thumbnail\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\"extract_and_upload_video: Finished extracting thumbnail\") logger.debug(\"extract_and_upload_video:","logger.debug(\"extract_and_upload_video: Uploading video chunks\") with futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir): ex.submit(","aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\"extractFrames\", # InvocationType=\"Event\", Payload=payload )) logger.debug(\"extract_and_upload_video: Submitted lambda frame extraction\")","= int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1]) return chunk_number * chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas,","img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \"\"\" for i, (img_raw_path, img_type, img_metadata, frame_number)","extracting thumbnail\") logger.debug(\"extract_and_upload_video: Uploading thumbnail\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\"extract_and_upload_video: Finished uploading","{\"bucket\": bucket} for frame in aws_lambda_response[\"frames\"] ] frame_numbers = [-1 for frame in","Uploading video chunks\") with futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file,","uuid from concurrent import futures from multiprocessing import Pool from ultitrackerapi import get_backend,","get_backend() logger = get_logger(__name__, level=\"DEBUG\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command =","as ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key),","s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\"extract_and_upload_video: Finished uploading thumbnail\") logger.debug(\"extract_and_upload_video: Uploading video to","\"chunks\", vid ) ) logger.debug(\"extract_and_upload_video: Finished uploading video chunks\") logger.debug(\"extract_and_upload_video: Submitting lambda frame","lambda responses\") logger.debug(\"extract_and_upload_video: Finished inserting image metadata\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser","Payload=payload )) logger.debug(\"extract_and_upload_video: Submitted lambda frame extraction\") for result_future in futures.as_completed(result_futures): aws_lambda_response =","futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\"s3://\" + posixpath.join(frame[\"bucket\"], frame[\"key\"]) for frame","if i < (len(img_raw_paths) - 1) else \"\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket,","img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \"\"\"('{img_id}', '{img_raw_path}', '{img_type}',","= json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\"s3://\" + posixpath.join(frame[\"bucket\"], frame[\"key\"]) for frame in aws_lambda_response[\"frames\"]]","for frame in aws_lambda_response[\"frames\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\"extract_and_upload_video: Received","chunking video\") logger.debug(\"extract_and_upload_video: Uploading video chunks\") with futures.ThreadPoolExecutor(8) as ex: for vid in","[ json.dumps({ \"s3_bucket_path\": bucket, \"s3_video_path\": posixpath.join(posixpath.dirname(video_key), \"chunks\", basename), \"s3_output_frames_path\": posixpath.join(posixpath.dirname(video_key), \"frames\", posixpath.splitext(basename)[0]), \"video_metadata\":","] frame_numbers = [-1 for frame in aws_lambda_response[\"frames\"]] insert_images( raw_paths, img_types, metadatas, game_id,","backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\"extract_and_upload_video: Getting video","posixpath.join(frame[\"bucket\"], frame[\"key\"]) for frame in aws_lambda_response[\"frames\"]] img_types = [\"png\" for frame in aws_lambda_response[\"frames\"]]","frame extraction\") for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\"s3://\"","import argparse import boto3 import datetime import json import os import posixpath import","import Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger","length in db\") update_game_video_length(game_id, video_length) logger.debug(\"extract_and_upload_video: Finished updating length in db\") logger.debug(\"extract_and_upload_video: Extracting","responses\") logger.debug(\"extract_and_upload_video: Finished inserting image metadata\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser =","logger.debug(\"extract_and_upload_video: Finished chunking video\") logger.debug(\"extract_and_upload_video: Uploading video chunks\") with futures.ThreadPoolExecutor(8) as ex: for","< (len(img_raw_paths) - 1) else \"\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename,","\"\"\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\"{video_length}\"', true) WHERE game_id =",") logger.debug(\"extract_and_upload_video: Finished uploading video to S3\") logger.debug(\"extract_and_upload_video: Chunking video\") chunked_video_dir = tempfile.mkdtemp()","import os import posixpath import re import shutil import tempfile import uuid from","InvocationType=\"Event\", Payload=payload )) logger.debug(\"extract_and_upload_video: Submitted lambda frame extraction\") for result_future in futures.as_completed(result_futures): aws_lambda_response","level=\"DEBUG\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command = \"\"\" UPDATE ultitracker.game_metadata SET","bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\"extract_and_upload_video: Getting video length\") video_length_seconds =","frame in aws_lambda_response[\"frames\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\"extract_and_upload_video: Received all","metadatas = [ {\"bucket\": bucket} for frame in aws_lambda_response[\"frames\"] ] frame_numbers = [-1","enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \"\"\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \"\"\".format(","S3\") logger.debug(\"extract_and_upload_video: Chunking video\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\"extract_and_upload_video: Finished chunking","data = jsonb_set(data, '{{length}}', '\"{video_length}\"', true) WHERE game_id = '{game_id}' \"\"\".format( video_length=video_length, game_id=game_id","get_logger(__name__, level=\"DEBUG\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command = \"\"\" UPDATE ultitracker.game_metadata","img_type, img_metadata, game_id, frame_number) VALUES \"\"\" for i, (img_raw_path, img_type, img_metadata, frame_number) in","[\"png\" for frame in aws_lambda_response[\"frames\"]] metadatas = [ {\"bucket\": bucket} for frame in","bucket, \"s3_video_path\": posixpath.join(posixpath.dirname(video_key), \"chunks\", basename), \"s3_output_frames_path\": posixpath.join(posixpath.dirname(video_key), \"frames\", posixpath.splitext(basename)[0]), \"video_metadata\": video_height_width }).encode() for","os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \"chunks\", vid ) ) logger.debug(\"extract_and_upload_video:","Submitting lambda frame extraction\") aws_lambda_payloads = [ json.dumps({ \"s3_bucket_path\": bucket, \"s3_video_path\": posixpath.join(posixpath.dirname(video_key), \"chunks\",","result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\"s3://\" + posixpath.join(frame[\"bucket\"], frame[\"key\"])","in db\") update_game_video_length(game_id, video_length) logger.debug(\"extract_and_upload_video: Finished updating length in db\") logger.debug(\"extract_and_upload_video: Extracting thumbnail\")","and width\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\"extract_and_upload_video: Finished getting height and width\") logger.debug(\"extract_and_upload_video: Updating","\"\"\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \"\"\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number,","# InvocationType=\"Event\", Payload=payload )) logger.debug(\"extract_and_upload_video: Submitted lambda frame extraction\") for result_future in futures.as_completed(result_futures):","\"\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\"extract_and_upload_video:","= \"\"\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \"\"\"","ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \"\"\" for i, (img_raw_path, img_type,","from multiprocessing import Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance =","for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \"chunks\", vid","length\") logger.debug(\"extract_and_upload_video: Getting video height and width\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\"extract_and_upload_video: Finished getting","import re import shutil import tempfile import uuid from concurrent import futures from","get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger = get_logger(__name__, level=\"DEBUG\") s3Client =","uploading video chunks\") logger.debug(\"extract_and_upload_video: Submitting lambda frame extraction\") aws_lambda_payloads = [ json.dumps({ \"s3_bucket_path\":","extraction\") aws_lambda_payloads = [ json.dumps({ \"s3_bucket_path\": bucket, \"s3_video_path\": posixpath.join(posixpath.dirname(video_key), \"chunks\", basename), \"s3_output_frames_path\": posixpath.join(posixpath.dirname(video_key),","frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \"\"\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}',","os import posixpath import re import shutil import tempfile import uuid from concurrent","argparse.ArgumentParser() parser.add_argument(\"bucket\") parser.add_argument(\"video_filename\") parser.add_argument(\"thumbnail_filename\") parser.add_argument(\"video_key\") parser.add_argument(\"thumbnail_key\") parser.add_argument(\"game_id\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename,","Chunking video\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\"extract_and_upload_video: Finished chunking video\") logger.debug(\"extract_and_upload_video:","updating length in db\") logger.debug(\"extract_and_upload_video: Extracting thumbnail\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\"extract_and_upload_video:","Finished chunking video\") logger.debug(\"extract_and_upload_video: Uploading video chunks\") with futures.ThreadPoolExecutor(8) as ex: for vid","import get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger = get_logger(__name__, level=\"DEBUG\") s3Client","time=video_length_seconds // 2) logger.debug(\"extract_and_upload_video: Finished extracting thumbnail\") logger.debug(\"extract_and_upload_video: Uploading thumbnail\") s3Client.upload_file( thumbnail_filename, bucket,","logger = get_logger(__name__, level=\"DEBUG\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command = \"\"\"","video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\"extract_and_upload_video: Getting video length\") video_length_seconds = int(video.get_video_duration(video_filename))","boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for payload","os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\"bucket\") parser.add_argument(\"video_filename\") parser.add_argument(\"thumbnail_filename\") parser.add_argument(\"video_key\") parser.add_argument(\"thumbnail_key\") parser.add_argument(\"game_id\")","VALUES \"\"\" for i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)):","Finished getting height and width\") logger.debug(\"extract_and_upload_video: Updating length in db\") update_game_video_length(game_id, video_length) logger.debug(\"extract_and_upload_video:","backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1]) return chunk_number *","[] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for payload in aws_lambda_payloads: result_futures.append(ex.submit(","video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\"extract_and_upload_video: Finished getting video length\") logger.debug(\"extract_and_upload_video: Getting video height and","update_game_video_length(game_id, video_length) logger.debug(\"extract_and_upload_video: Finished updating length in db\") logger.debug(\"extract_and_upload_video: Extracting thumbnail\") video.get_thumbnail(video_filename, thumbnail_filename,","video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\"extract_and_upload_video: Finished extracting thumbnail\") logger.debug(\"extract_and_upload_video: Uploading thumbnail\") s3Client.upload_file(","insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command = \"\"\" INSERT INTO ultitracker.img_location","video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\"_\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\"_\")[1])","logger.debug(\"extract_and_upload_video: Finished updating length in db\") logger.debug(\"extract_and_upload_video: Extracting thumbnail\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds //","Uploading video to S3\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\"extract_and_upload_video: Finished uploading video","client.invoke, FunctionName=\"extractFrames\", # InvocationType=\"Event\", Payload=payload )) logger.debug(\"extract_and_upload_video: Submitted lambda frame extraction\") for result_future","aws_lambda_payloads = [ json.dumps({ \"s3_bucket_path\": bucket, \"s3_video_path\": posixpath.join(posixpath.dirname(video_key), \"chunks\", basename), \"s3_output_frames_path\": posixpath.join(posixpath.dirname(video_key), \"frames\",","img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \"\"\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}',","raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\"extract_and_upload_video: Received all lambda responses\") logger.debug(\"extract_and_upload_video: Finished","Submitted lambda frame extraction\") for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\")) aws_lambda_responses.append(aws_lambda_response) raw_paths","args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id ) if __name__","img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\",\" if i < (len(img_raw_paths) - 1) else \"\" )","in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \"chunks\", vid ) )","for basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16)","Getting video length\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\"extract_and_upload_video: Finished getting video","width\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\"extract_and_upload_video: Finished getting height and width\") logger.debug(\"extract_and_upload_video: Updating length","frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command = \"\"\" INSERT","thumbnail\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\"extract_and_upload_video: Finished extracting thumbnail\") logger.debug(\"extract_and_upload_video: Uploading thumbnail\")","[ {\"bucket\": bucket} for frame in aws_lambda_response[\"frames\"] ] frame_numbers = [-1 for frame","for frame in aws_lambda_response[\"frames\"] ] frame_numbers = [-1 for frame in aws_lambda_response[\"frames\"]] insert_images(","aws_lambda_response[\"frames\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\"extract_and_upload_video: Received all lambda responses\")","video.get_video_height_width(video_filename) logger.debug(\"extract_and_upload_video: Finished getting height and width\") logger.debug(\"extract_and_upload_video: Updating length in db\") update_game_video_length(game_id,","bucket, video_key ) logger.debug(\"extract_and_upload_video: Finished uploading video to S3\") logger.debug(\"extract_and_upload_video: Chunking video\") chunked_video_dir","for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\"Payload\"].read().decode(\"utf-8\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\"s3://\" + posixpath.join(frame[\"bucket\"],","chunked_video_dir, chunk_size=60) logger.debug(\"extract_and_upload_video: Finished chunking video\") logger.debug(\"extract_and_upload_video: Uploading video chunks\") with futures.ThreadPoolExecutor(8) as","for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\"extractFrames\", # InvocationType=\"Event\", Payload=payload )) logger.debug(\"extract_and_upload_video: Submitted","futures from multiprocessing import Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance","and width\") logger.debug(\"extract_and_upload_video: Updating length in db\") update_game_video_length(game_id, video_length) logger.debug(\"extract_and_upload_video: Finished updating length","main(): parser = argparse.ArgumentParser() parser.add_argument(\"bucket\") parser.add_argument(\"video_filename\") parser.add_argument(\"thumbnail_filename\") parser.add_argument(\"video_key\") parser.add_argument(\"thumbnail_key\") parser.add_argument(\"game_id\") args = parser.parse_args()","video_length): command = \"\"\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\"{video_length}\"', true)","posixpath.join(posixpath.dirname(video_key), \"frames\", posixpath.splitext(basename)[0]), \"video_metadata\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ] client =","logger.debug(\"extract_and_upload_video: Finished uploading video to S3\") logger.debug(\"extract_and_upload_video: Chunking video\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename,","import tempfile import uuid from concurrent import futures from multiprocessing import Pool from","video_key ) logger.debug(\"extract_and_upload_video: Finished uploading video to S3\") logger.debug(\"extract_and_upload_video: Chunking video\") chunked_video_dir =","frame in aws_lambda_response[\"frames\"] ] frame_numbers = [-1 for frame in aws_lambda_response[\"frames\"]] insert_images( raw_paths,","video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\"extract_and_upload_video: Finished getting video length\") logger.debug(\"extract_and_upload_video: Getting","parser.add_argument(\"video_key\") parser.add_argument(\"thumbnail_key\") parser.add_argument(\"game_id\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id"],"string":"[\n \"chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command =\",\n \"Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger =\",\n \"os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\\\"bucket\\\") parser.add_argument(\\\"video_filename\\\") parser.add_argument(\\\"thumbnail_filename\\\") parser.add_argument(\\\"video_key\\\") parser.add_argument(\\\"thumbnail_key\\\")\",\n \"[\\\"s3://\\\" + posixpath.join(frame[\\\"bucket\\\"], frame[\\\"key\\\"]) for frame in aws_lambda_response[\\\"frames\\\"]] img_types = [\\\"png\\\" for frame\",\n \"from concurrent import futures from multiprocessing import Pool from ultitrackerapi import get_backend, get_logger,\",\n \"in aws_lambda_response[\\\"frames\\\"]] img_types = [\\\"png\\\" for frame in aws_lambda_response[\\\"frames\\\"]] metadatas = [ {\\\"bucket\\\":\",\n \"* chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command\",\n \") ) logger.debug(\\\"extract_and_upload_video: Finished uploading video chunks\\\") logger.debug(\\\"extract_and_upload_video: Submitting lambda frame extraction\\\") aws_lambda_payloads\",\n \"= get_s3Client() def update_game_video_length(game_id, video_length): command = \\\"\\\"\\\" UPDATE ultitracker.game_metadata SET data =\",\n \"video to S3\\\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading video to\",\n \"img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command = \\\"\\\"\\\" INSERT INTO ultitracker.img_location (img_id,\",\n \"thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading thumbnail\\\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading thumbnail\\\")\",\n \") backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1]) return chunk_number\",\n \"Finished uploading thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading video to S3\\\") s3Client.upload_file( video_filename, bucket, video_key )\",\n \") logger.debug(\\\"extract_and_upload_video: Finished uploading thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading video to S3\\\") s3Client.upload_file( video_filename, bucket,\",\n \"shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\\\"bucket\\\") parser.add_argument(\\\"video_filename\\\") parser.add_argument(\\\"thumbnail_filename\\\") parser.add_argument(\\\"video_key\\\") parser.add_argument(\\\"thumbnail_key\\\") parser.add_argument(\\\"game_id\\\") args\",\n \"= jsonb_set(data, '{{length}}', '\\\"{video_length}\\\"', true) WHERE game_id = '{game_id}' \\\"\\\"\\\".format( video_length=video_length, game_id=game_id )\",\n \"metadata\\\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\\\"bucket\\\") parser.add_argument(\\\"video_filename\\\") parser.add_argument(\\\"thumbnail_filename\\\") parser.add_argument(\\\"video_key\\\")\",\n \"video chunks\\\") with futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir,\",\n \"update_game_video_length(game_id, video_length): command = \\\"\\\"\\\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\\\"{video_length}\\\"',\",\n \"def update_game_video_length(game_id, video_length): command = \\\"\\\"\\\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}',\",\n \"game_id = '{game_id}' \\\"\\\"\\\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number =\",\n \"Finished updating length in db\\\") logger.debug(\\\"extract_and_upload_video: Extracting thumbnail\\\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2)\",\n \"Extracting thumbnail\\\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\\\"extract_and_upload_video: Finished extracting thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading\",\n \"os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \\\"chunks\\\", vid ) ) logger.debug(\\\"extract_and_upload_video: Finished uploading video\",\n \"video_length) logger.debug(\\\"extract_and_upload_video: Finished updating length in db\\\") logger.debug(\\\"extract_and_upload_video: Extracting thumbnail\\\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds\",\n \"s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading video to S3\\\") logger.debug(\\\"extract_and_upload_video: Chunking\",\n \"to S3\\\") logger.debug(\\\"extract_and_upload_video: Chunking video\\\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\\\"extract_and_upload_video: Finished\",\n \"ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\\\"{video_length}\\\"', true) WHERE game_id = '{game_id}' \\\"\\\"\\\".format(\",\n \"logger.debug(\\\"extract_and_upload_video: Updating length in db\\\") update_game_video_length(game_id, video_length) logger.debug(\\\"extract_and_upload_video: Finished updating length in db\\\")\",\n \"aws_lambda_response[\\\"frames\\\"] ] frame_numbers = [-1 for frame in aws_lambda_response[\\\"frames\\\"]] insert_images( raw_paths, img_types, metadatas,\",\n \"chunks\\\") with futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid),\",\n \"for frame in aws_lambda_response[\\\"frames\\\"]] img_types = [\\\"png\\\" for frame in aws_lambda_response[\\\"frames\\\"]] metadatas =\",\n \"Finished getting video length\\\") logger.debug(\\\"extract_and_upload_video: Getting video height and width\\\") video_height_width = video.get_video_height_width(video_filename)\",\n \"= \\\"\\\"\\\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\\\"{video_length}\\\"', true) WHERE game_id\",\n \"uploading video to S3\\\") logger.debug(\\\"extract_and_upload_video: Chunking video\\\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60)\",\n \"// 2) logger.debug(\\\"extract_and_upload_video: Finished extracting thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading thumbnail\\\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key\",\n \"img_types, img_metadatas, game_id, frame_numbers ): command = \\\"\\\"\\\" INSERT INTO ultitracker.img_location (img_id, img_raw_path,\",\n \") backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\\\"extract_and_upload_video: Getting\",\n \"game_id ): logger.debug(\\\"extract_and_upload_video: Getting video length\\\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\\\"extract_and_upload_video:\",\n \"2) logger.debug(\\\"extract_and_upload_video: Finished extracting thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading thumbnail\\\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key )\",\n \"\\\"frames\\\", posixpath.splitext(basename)[0]), \\\"video_metadata\\\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda')\",\n \"parser.add_argument(\\\"video_filename\\\") parser.add_argument(\\\"thumbnail_filename\\\") parser.add_argument(\\\"video_key\\\") parser.add_argument(\\\"thumbnail_key\\\") parser.add_argument(\\\"game_id\\\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key,\",\n \"as ex: result_futures = [] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\\\"extractFrames\\\", #\",\n \"return chunk_number * chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers\",\n \"Getting video height and width\\\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\\\"extract_and_upload_video: Finished getting height and\",\n \"(img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \\\"\\\"\\\"('{img_id}', '{img_raw_path}',\",\n \"frame in aws_lambda_response[\\\"frames\\\"]] metadatas = [ {\\\"bucket\\\": bucket} for frame in aws_lambda_response[\\\"frames\\\"] ]\",\n \"chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1]) return chunk_number * chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types,\",\n \"boto3 import datetime import json import os import posixpath import re import shutil\",\n \"'{img_metadata}', '{game_id}', {frame_number}){include_comma} \\\"\\\"\\\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\\\",\\\" if i\",\n \"[-1 for frame in aws_lambda_response[\\\"frames\\\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\\\"extract_and_upload_video:\",\n \"logger.debug(\\\"extract_and_upload_video: Uploading video to S3\\\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading\",\n \"= '{game_id}' \\\"\\\"\\\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1])\",\n \"logger.debug(\\\"extract_and_upload_video: Finished extracting thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading thumbnail\\\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\\\"extract_and_upload_video:\",\n \"INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \\\"\\\"\\\" for i, (img_raw_path,\",\n \"else \\\"\\\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ):\",\n \"video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\\\"extract_and_upload_video: Finished chunking video\\\") logger.debug(\\\"extract_and_upload_video: Uploading video chunks\\\") with futures.ThreadPoolExecutor(8)\",\n \"import boto3 import datetime import json import os import posixpath import re import\",\n \"extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\\\"extract_and_upload_video: Getting video length\\\") video_length_seconds\",\n \"in db\\\") logger.debug(\\\"extract_and_upload_video: Extracting thumbnail\\\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\\\"extract_and_upload_video: Finished extracting\",\n \"video\\\") logger.debug(\\\"extract_and_upload_video: Uploading video chunks\\\") with futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir):\",\n \"i < (len(img_raw_paths) - 1) else \\\"\\\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename,\",\n \"video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses = []\",\n \"s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \\\"chunks\\\", vid ) ) logger.debug(\\\"extract_and_upload_video: Finished uploading\",\n \"int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1]) return chunk_number * chunk_multiplier + frame_number def insert_images( img_raw_paths,\",\n \"logger.debug(\\\"extract_and_upload_video: Finished uploading thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading video to S3\\\") s3Client.upload_file( video_filename, bucket, video_key\",\n \"video backend_instance = get_backend() logger = get_logger(__name__, level=\\\"DEBUG\\\") s3Client = get_s3Client() def update_game_video_length(game_id,\",\n \"'{{length}}', '\\\"{video_length}\\\"', true) WHERE game_id = '{game_id}' \\\"\\\"\\\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def\",\n \"img_types = [\\\"png\\\" for frame in aws_lambda_response[\\\"frames\\\"]] metadatas = [ {\\\"bucket\\\": bucket} for\",\n \"logger.debug(\\\"extract_and_upload_video: Getting video length\\\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\\\"extract_and_upload_video: Finished getting\",\n \"(img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \\\"\\\"\\\" for i, (img_raw_path, img_type, img_metadata,\",\n \"'{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \\\"\\\"\\\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\\\",\\\"\",\n \"aws_lambda_response = json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\\\"s3://\\\" + posixpath.join(frame[\\\"bucket\\\"], frame[\\\"key\\\"]) for frame in\",\n \"\\\"\\\"\\\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\\\",\\\" if i < (len(img_raw_paths) -\",\n \"import uuid from concurrent import futures from multiprocessing import Pool from ultitrackerapi import\",\n \"get_s3Client() def update_game_video_length(game_id, video_length): command = \\\"\\\"\\\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data,\",\n \"= tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\\\"extract_and_upload_video: Finished chunking video\\\") logger.debug(\\\"extract_and_upload_video: Uploading video chunks\\\")\",\n \"logger.debug(\\\"extract_and_upload_video: Uploading thumbnail\\\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading thumbnail\\\") logger.debug(\\\"extract_and_upload_video:\",\n \"get_logger, get_s3Client, video backend_instance = get_backend() logger = get_logger(__name__, level=\\\"DEBUG\\\") s3Client = get_s3Client()\",\n \"aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for payload in\",\n \"logger.debug(\\\"extract_and_upload_video: Finished uploading video chunks\\\") logger.debug(\\\"extract_and_upload_video: Submitting lambda frame extraction\\\") aws_lambda_payloads = [\",\n \"length\\\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\\\"extract_and_upload_video: Finished getting video length\\\") logger.debug(\\\"extract_and_upload_video:\",\n \"thumbnail_filename, time=video_length_seconds // 2) logger.debug(\\\"extract_and_upload_video: Finished extracting thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading thumbnail\\\") s3Client.upload_file( thumbnail_filename,\",\n \"command += \\\"\\\"\\\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \\\"\\\"\\\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata),\",\n \"= video.get_video_height_width(video_filename) logger.debug(\\\"extract_and_upload_video: Finished getting height and width\\\") logger.debug(\\\"extract_and_upload_video: Updating length in db\\\")\",\n \"game_id=game_id, frame_number=frame_number, include_comma=\\\",\\\" if i < (len(img_raw_paths) - 1) else \\\"\\\" ) backend_instance.client.execute(command)\",\n \"+ frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command = \\\"\\\"\\\"\",\n \"): command = \\\"\\\"\\\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number)\",\n \"def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1]) return chunk_number * chunk_multiplier\",\n \"import json import os import posixpath import re import shutil import tempfile import\",\n \"Finished uploading video to S3\\\") logger.debug(\\\"extract_and_upload_video: Chunking video\\\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir,\",\n \") logger.debug(\\\"extract_and_upload_video: Received all lambda responses\\\") logger.debug(\\\"extract_and_upload_video: Finished inserting image metadata\\\") os.remove(video_filename) os.remove(thumbnail_filename)\",\n \"thumbnail\\\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading video\",\n \"= [\\\"s3://\\\" + posixpath.join(frame[\\\"bucket\\\"], frame[\\\"key\\\"]) for frame in aws_lambda_response[\\\"frames\\\"]] img_types = [\\\"png\\\" for\",\n \"parser.add_argument(\\\"thumbnail_filename\\\") parser.add_argument(\\\"video_key\\\") parser.add_argument(\\\"thumbnail_key\\\") parser.add_argument(\\\"game_id\\\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key,\",\n \"img_types, metadatas, game_id, frame_numbers ) logger.debug(\\\"extract_and_upload_video: Received all lambda responses\\\") logger.debug(\\\"extract_and_upload_video: Finished inserting\",\n \"re import shutil import tempfile import uuid from concurrent import futures from multiprocessing\",\n \"logger.debug(\\\"extract_and_upload_video: Chunking video\\\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\\\"extract_and_upload_video: Finished chunking video\\\")\",\n \"img_metadatas, game_id, frame_numbers ): command = \\\"\\\"\\\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type,\",\n \"= [] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\\\"extractFrames\\\", # InvocationType=\\\"Event\\\", Payload=payload ))\",\n \"lambda frame extraction\\\") for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\")) aws_lambda_responses.append(aws_lambda_response) raw_paths =\",\n \"str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\\\"extract_and_upload_video: Finished getting video length\\\") logger.debug(\\\"extract_and_upload_video: Getting video height and width\\\") video_height_width\",\n \"ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger = get_logger(__name__, level=\\\"DEBUG\\\")\",\n \")) logger.debug(\\\"extract_and_upload_video: Submitted lambda frame extraction\\\") for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\"))\",\n \"ex: result_futures = [] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\\\"extractFrames\\\", # InvocationType=\\\"Event\\\",\",\n \"] client = boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures =\",\n \"INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \\\"\\\"\\\" for i,\",\n \"= int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\\\"extract_and_upload_video: Finished getting video length\\\") logger.debug(\\\"extract_and_upload_video: Getting video\",\n \"video height and width\\\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\\\"extract_and_upload_video: Finished getting height and width\\\")\",\n \"thumbnail_filename, bucket, thumbnail_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading video to S3\\\")\",\n \"uploading thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading video to S3\\\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\\\"extract_and_upload_video:\",\n \"parser.add_argument(\\\"game_id\\\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id ) if\",\n \"in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex:\",\n \"= [\\\"png\\\" for frame in aws_lambda_response[\\\"frames\\\"]] metadatas = [ {\\\"bucket\\\": bucket} for frame\",\n \"get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1]) return chunk_number * chunk_multiplier +\",\n \"+= \\\"\\\"\\\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \\\"\\\"\\\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id,\",\n \"vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \\\"chunks\\\", vid )\",\n \"bucket} for frame in aws_lambda_response[\\\"frames\\\"] ] frame_numbers = [-1 for frame in aws_lambda_response[\\\"frames\\\"]]\",\n \"thumbnail_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading video to S3\\\") s3Client.upload_file( video_filename,\",\n \"\\\"s3_output_frames_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"frames\\\", posixpath.splitext(basename)[0]), \\\"video_metadata\\\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ] client\",\n \"payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\\\"extractFrames\\\", # InvocationType=\\\"Event\\\", Payload=payload )) logger.debug(\\\"extract_and_upload_video: Submitted lambda\",\n \"height and width\\\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\\\"extract_and_upload_video: Finished getting height and width\\\") logger.debug(\\\"extract_and_upload_video:\",\n \"video to S3\\\") logger.debug(\\\"extract_and_upload_video: Chunking video\\\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\\\"extract_and_upload_video:\",\n \"include_comma=\\\",\\\" if i < (len(img_raw_paths) - 1) else \\\"\\\" ) backend_instance.client.execute(command) def extract_and_upload_video(\",\n \"game_id, frame_numbers ) logger.debug(\\\"extract_and_upload_video: Received all lambda responses\\\") logger.debug(\\\"extract_and_upload_video: Finished inserting image metadata\\\")\",\n \"insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\\\"extract_and_upload_video: Received all lambda responses\\\") logger.debug(\\\"extract_and_upload_video:\",\n \"argparse import boto3 import datetime import json import os import posixpath import re\",\n \"- 1) else \\\"\\\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key,\",\n \"\\\"\\\"\\\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \\\"\\\"\\\" for\",\n \"FunctionName=\\\"extractFrames\\\", # InvocationType=\\\"Event\\\", Payload=payload )) logger.debug(\\\"extract_and_upload_video: Submitted lambda frame extraction\\\") for result_future in\",\n \"get_s3Client, video backend_instance = get_backend() logger = get_logger(__name__, level=\\\"DEBUG\\\") s3Client = get_s3Client() def\",\n \"[] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\\\"extractFrames\\\", # InvocationType=\\\"Event\\\", Payload=payload )) logger.debug(\\\"extract_and_upload_video:\",\n \"in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \\\"\\\"\\\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma}\",\n \"tempfile import uuid from concurrent import futures from multiprocessing import Pool from ultitrackerapi\",\n \"import shutil import tempfile import uuid from concurrent import futures from multiprocessing import\",\n \"= [ json.dumps({ \\\"s3_bucket_path\\\": bucket, \\\"s3_video_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"chunks\\\", basename), \\\"s3_output_frames_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"frames\\\", posixpath.splitext(basename)[0]),\",\n \"parser = argparse.ArgumentParser() parser.add_argument(\\\"bucket\\\") parser.add_argument(\\\"video_filename\\\") parser.add_argument(\\\"thumbnail_filename\\\") parser.add_argument(\\\"video_key\\\") parser.add_argument(\\\"thumbnail_key\\\") parser.add_argument(\\\"game_id\\\") args = parser.parse_args() extract_and_upload_video(\",\n \"video chunks\\\") logger.debug(\\\"extract_and_upload_video: Submitting lambda frame extraction\\\") aws_lambda_payloads = [ json.dumps({ \\\"s3_bucket_path\\\": bucket,\",\n \"'{game_id}', {frame_number}){include_comma} \\\"\\\"\\\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\\\",\\\" if i <\",\n \"json.dumps({ \\\"s3_bucket_path\\\": bucket, \\\"s3_video_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"chunks\\\", basename), \\\"s3_output_frames_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"frames\\\", posixpath.splitext(basename)[0]), \\\"video_metadata\\\": video_height_width\",\n \"image metadata\\\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\\\"bucket\\\") parser.add_argument(\\\"video_filename\\\") parser.add_argument(\\\"thumbnail_filename\\\")\",\n \"parser.add_argument(\\\"thumbnail_key\\\") parser.add_argument(\\\"game_id\\\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id )\",\n \"{frame_number}){include_comma} \\\"\\\"\\\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\\\",\\\" if i < (len(img_raw_paths)\",\n \"aws_lambda_response[\\\"frames\\\"]] metadatas = [ {\\\"bucket\\\": bucket} for frame in aws_lambda_response[\\\"frames\\\"] ] frame_numbers =\",\n \"frame_numbers ) logger.debug(\\\"extract_and_upload_video: Received all lambda responses\\\") logger.debug(\\\"extract_and_upload_video: Finished inserting image metadata\\\") os.remove(video_filename)\",\n \"= get_backend() logger = get_logger(__name__, level=\\\"DEBUG\\\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command\",\n \"+ posixpath.join(frame[\\\"bucket\\\"], frame[\\\"key\\\"]) for frame in aws_lambda_response[\\\"frames\\\"]] img_types = [\\\"png\\\" for frame in\",\n \"video_filename, bucket, video_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading video to S3\\\") logger.debug(\\\"extract_and_upload_video: Chunking video\\\")\",\n \"frame_numbers)): command += \\\"\\\"\\\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \\\"\\\"\\\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type,\",\n \"chunk_number * chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ):\",\n \"logger.debug(\\\"extract_and_upload_video: Finished inserting image metadata\\\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser()\",\n \"jsonb_set(data, '{{length}}', '\\\"{video_length}\\\"', true) WHERE game_id = '{game_id}' \\\"\\\"\\\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command)\",\n \"json import os import posixpath import re import shutil import tempfile import uuid\",\n \"length in db\\\") logger.debug(\\\"extract_and_upload_video: Extracting thumbnail\\\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\\\"extract_and_upload_video: Finished\",\n \"def main(): parser = argparse.ArgumentParser() parser.add_argument(\\\"bucket\\\") parser.add_argument(\\\"video_filename\\\") parser.add_argument(\\\"thumbnail_filename\\\") parser.add_argument(\\\"video_key\\\") parser.add_argument(\\\"thumbnail_key\\\") parser.add_argument(\\\"game_id\\\") args =\",\n \"= argparse.ArgumentParser() parser.add_argument(\\\"bucket\\\") parser.add_argument(\\\"video_filename\\\") parser.add_argument(\\\"thumbnail_filename\\\") parser.add_argument(\\\"video_key\\\") parser.add_argument(\\\"thumbnail_key\\\") parser.add_argument(\\\"game_id\\\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket,\",\n \"img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\\\",\\\" if i < (len(img_raw_paths) - 1)\",\n \"= get_logger(__name__, level=\\\"DEBUG\\\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command = \\\"\\\"\\\" UPDATE\",\n \"lambda frame extraction\\\") aws_lambda_payloads = [ json.dumps({ \\\"s3_bucket_path\\\": bucket, \\\"s3_video_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"chunks\\\", basename),\",\n \"result_futures.append(ex.submit( client.invoke, FunctionName=\\\"extractFrames\\\", # InvocationType=\\\"Event\\\", Payload=payload )) logger.debug(\\\"extract_and_upload_video: Submitted lambda frame extraction\\\") for\",\n \"Uploading thumbnail\\\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading\",\n \"= boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for\",\n \"img_metadata, game_id, frame_number) VALUES \\\"\\\"\\\" for i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths,\",\n \"frame_number=frame_number, include_comma=\\\",\\\" if i < (len(img_raw_paths) - 1) else \\\"\\\" ) backend_instance.client.execute(command) def\",\n \"raw_paths = [\\\"s3://\\\" + posixpath.join(frame[\\\"bucket\\\"], frame[\\\"key\\\"]) for frame in aws_lambda_response[\\\"frames\\\"]] img_types = [\\\"png\\\"\",\n \"Finished inserting image metadata\\\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\\\"bucket\\\")\",\n \"with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke,\",\n \"frame[\\\"key\\\"]) for frame in aws_lambda_response[\\\"frames\\\"]] img_types = [\\\"png\\\" for frame in aws_lambda_response[\\\"frames\\\"]] metadatas\",\n \"command = \\\"\\\"\\\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\\\"{video_length}\\\"', true) WHERE\",\n \"all lambda responses\\\") logger.debug(\\\"extract_and_upload_video: Finished inserting image metadata\\\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main():\",\n \"int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\\\"extract_and_upload_video: Finished getting video length\\\") logger.debug(\\\"extract_and_upload_video: Getting video height\",\n \"int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1]) return chunk_number * chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id,\",\n \"thumbnail_key, game_id ): logger.debug(\\\"extract_and_upload_video: Getting video length\\\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds))\",\n \"metadatas, game_id, frame_numbers ) logger.debug(\\\"extract_and_upload_video: Received all lambda responses\\\") logger.debug(\\\"extract_and_upload_video: Finished inserting image\",\n \"chunk_size=60) logger.debug(\\\"extract_and_upload_video: Finished chunking video\\\") logger.debug(\\\"extract_and_upload_video: Uploading video chunks\\\") with futures.ThreadPoolExecutor(8) as ex:\",\n \"with futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket,\",\n \"\\\"chunks\\\", basename), \\\"s3_output_frames_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"frames\\\", posixpath.splitext(basename)[0]), \\\"video_metadata\\\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir)\",\n \"bucket, thumbnail_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading video to S3\\\") s3Client.upload_file(\",\n \"getting height and width\\\") logger.debug(\\\"extract_and_upload_video: Updating length in db\\\") update_game_video_length(game_id, video_length) logger.debug(\\\"extract_and_upload_video: Finished\",\n \"Received all lambda responses\\\") logger.debug(\\\"extract_and_upload_video: Finished inserting image metadata\\\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def\",\n \"= [ {\\\"bucket\\\": bucket} for frame in aws_lambda_response[\\\"frames\\\"] ] frame_numbers = [-1 for\",\n \"result_futures = [] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\\\"extractFrames\\\", # InvocationType=\\\"Event\\\", Payload=payload\",\n \"logger.debug(\\\"extract_and_upload_video: Received all lambda responses\\\") logger.debug(\\\"extract_and_upload_video: Finished inserting image metadata\\\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir)\",\n \"i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \\\"\\\"\\\"('{img_id}',\",\n \"def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\\\"extract_and_upload_video: Getting video length\\\")\",\n \"getting video length\\\") logger.debug(\\\"extract_and_upload_video: Getting video height and width\\\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\\\"extract_and_upload_video:\",\n \"in aws_lambda_response[\\\"frames\\\"] ] frame_numbers = [-1 for frame in aws_lambda_response[\\\"frames\\\"]] insert_images( raw_paths, img_types,\",\n \"os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures\",\n \"1) else \\\"\\\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id\",\n \"in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\\\"extractFrames\\\", # InvocationType=\\\"Event\\\", Payload=payload )) logger.debug(\\\"extract_and_upload_video: Submitted lambda frame\",\n \"logger.debug(\\\"extract_and_upload_video: Submitted lambda frame extraction\\\") for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\")) aws_lambda_responses.append(aws_lambda_response)\",\n \"in aws_lambda_response[\\\"frames\\\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\\\"extract_and_upload_video: Received all lambda\",\n \"s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command = \\\"\\\"\\\" UPDATE ultitracker.game_metadata SET data\",\n \"S3\\\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading video to S3\\\") logger.debug(\\\"extract_and_upload_video:\",\n \"posixpath.join( posixpath.dirname(video_key), \\\"chunks\\\", vid ) ) logger.debug(\\\"extract_and_upload_video: Finished uploading video chunks\\\") logger.debug(\\\"extract_and_upload_video: Submitting\",\n \"'{game_id}' \\\"\\\"\\\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1]) chunk_number\",\n \"\\\"\\\"\\\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1]) chunk_number =\",\n \"import datetime import json import os import posixpath import re import shutil import\",\n \"extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id ) if __name__ == \\\"__main__\\\": main()\",\n \"Finished uploading video chunks\\\") logger.debug(\\\"extract_and_upload_video: Submitting lambda frame extraction\\\") aws_lambda_payloads = [ json.dumps({\",\n \"aws_lambda_responses.append(aws_lambda_response) raw_paths = [\\\"s3://\\\" + posixpath.join(frame[\\\"bucket\\\"], frame[\\\"key\\\"]) for frame in aws_lambda_response[\\\"frames\\\"]] img_types =\",\n \"width\\\") logger.debug(\\\"extract_and_upload_video: Updating length in db\\\") update_game_video_length(game_id, video_length) logger.debug(\\\"extract_and_upload_video: Finished updating length in\",\n \"bucket, posixpath.join( posixpath.dirname(video_key), \\\"chunks\\\", vid ) ) logger.debug(\\\"extract_and_upload_video: Finished uploading video chunks\\\") logger.debug(\\\"extract_and_upload_video:\",\n \"posixpath import re import shutil import tempfile import uuid from concurrent import futures\",\n \"ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \\\"chunks\\\", vid ) ) logger.debug(\\\"extract_and_upload_video: Finished\",\n \"in aws_lambda_response[\\\"frames\\\"]] metadatas = [ {\\\"bucket\\\": bucket} for frame in aws_lambda_response[\\\"frames\\\"] ] frame_numbers\",\n \"vid ) ) logger.debug(\\\"extract_and_upload_video: Finished uploading video chunks\\\") logger.debug(\\\"extract_and_upload_video: Submitting lambda frame extraction\\\")\",\n \"img_metadatas, frame_numbers)): command += \\\"\\\"\\\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \\\"\\\"\\\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path,\",\n \"video_key, thumbnail_key, game_id ): logger.debug(\\\"extract_and_upload_video: Getting video length\\\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length =\",\n \"concurrent import futures from multiprocessing import Pool from ultitrackerapi import get_backend, get_logger, get_s3Client,\",\n \"ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \\\"chunks\\\",\",\n \"Finished extracting thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading thumbnail\\\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\\\"extract_and_upload_video: Finished\",\n \"video length\\\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\\\"extract_and_upload_video: Finished getting video length\\\")\",\n \"frame_numbers = [-1 for frame in aws_lambda_response[\\\"frames\\\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers\",\n \"(len(img_raw_paths) - 1) else \\\"\\\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key,\",\n \"= [-1 for frame in aws_lambda_response[\\\"frames\\\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers )\",\n \") logger.debug(\\\"extract_and_upload_video: Finished uploading video chunks\\\") logger.debug(\\\"extract_and_upload_video: Submitting lambda frame extraction\\\") aws_lambda_payloads =\",\n \"chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\\\"extract_and_upload_video: Finished chunking video\\\") logger.debug(\\\"extract_and_upload_video: Uploading video\",\n \"import futures from multiprocessing import Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video\",\n \"import posixpath import re import shutil import tempfile import uuid from concurrent import\",\n \"db\\\") update_game_video_length(game_id, video_length) logger.debug(\\\"extract_and_upload_video: Finished updating length in db\\\") logger.debug(\\\"extract_and_upload_video: Extracting thumbnail\\\") video.get_thumbnail(video_filename,\",\n \"chunks\\\") logger.debug(\\\"extract_and_upload_video: Submitting lambda frame extraction\\\") aws_lambda_payloads = [ json.dumps({ \\\"s3_bucket_path\\\": bucket, \\\"s3_video_path\\\":\",\n \"db\\\") logger.debug(\\\"extract_and_upload_video: Extracting thumbnail\\\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\\\"extract_and_upload_video: Finished extracting thumbnail\\\")\",\n \"}).encode() for basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses = [] with\",\n \"basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as\",\n \"img_types, img_metadatas, frame_numbers)): command += \\\"\\\"\\\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \\\"\\\"\\\".format( img_id=uuid.uuid4(),\",\n \"SET data = jsonb_set(data, '{{length}}', '\\\"{video_length}\\\"', true) WHERE game_id = '{game_id}' \\\"\\\"\\\".format( video_length=video_length,\",\n \"posixpath.splitext(basename)[0]), \\\"video_metadata\\\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses\",\n \"basename), \\\"s3_output_frames_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"frames\\\", posixpath.splitext(basename)[0]), \\\"video_metadata\\\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ]\",\n \"chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1]) return chunk_number * chunk_multiplier + frame_number\",\n \"game_id, frame_number) VALUES \\\"\\\"\\\" for i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types,\",\n \"logger.debug(\\\"extract_and_upload_video: Getting video height and width\\\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\\\"extract_and_upload_video: Finished getting height\",\n \"img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\\\",\\\" if i < (len(img_raw_paths) - 1) else \\\"\\\"\",\n \"posixpath.dirname(video_key), \\\"chunks\\\", vid ) ) logger.debug(\\\"extract_and_upload_video: Finished uploading video chunks\\\") logger.debug(\\\"extract_and_upload_video: Submitting lambda\",\n \"\\\"s3_bucket_path\\\": bucket, \\\"s3_video_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"chunks\\\", basename), \\\"s3_output_frames_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"frames\\\", posixpath.splitext(basename)[0]), \\\"video_metadata\\\": video_height_width }).encode()\",\n \"tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\\\"extract_and_upload_video: Finished chunking video\\\") logger.debug(\\\"extract_and_upload_video: Uploading video chunks\\\") with\",\n \"game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1]) return\",\n \"frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1]) return chunk_number * chunk_multiplier + frame_number def\",\n \"\\\"s3_video_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"chunks\\\", basename), \\\"s3_output_frames_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"frames\\\", posixpath.splitext(basename)[0]), \\\"video_metadata\\\": video_height_width }).encode() for basename\",\n \"frame_numbers ): command = \\\"\\\"\\\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id,\",\n \"to S3\\\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading video to S3\\\")\",\n \"aws_lambda_response[\\\"frames\\\"]] img_types = [\\\"png\\\" for frame in aws_lambda_response[\\\"frames\\\"]] metadatas = [ {\\\"bucket\\\": bucket}\",\n \"\\\"video_metadata\\\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses =\",\n \"for frame in aws_lambda_response[\\\"frames\\\"]] metadatas = [ {\\\"bucket\\\": bucket} for frame in aws_lambda_response[\\\"frames\\\"]\",\n \"'\\\"{video_length}\\\"', true) WHERE game_id = '{game_id}' \\\"\\\"\\\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key,\",\n \"\\\"\\\"\\\" for i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command\",\n \"img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\\\",\\\" if i < (len(img_raw_paths) - 1) else\",\n \"posixpath.join(posixpath.dirname(video_key), \\\"chunks\\\", basename), \\\"s3_output_frames_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"frames\\\", posixpath.splitext(basename)[0]), \\\"video_metadata\\\": video_height_width }).encode() for basename in\",\n \"command = \\\"\\\"\\\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES\",\n \"logger.debug(\\\"extract_and_upload_video: Finished getting video length\\\") logger.debug(\\\"extract_and_upload_video: Getting video height and width\\\") video_height_width =\",\n \"video length\\\") logger.debug(\\\"extract_and_upload_video: Getting video height and width\\\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\\\"extract_and_upload_video: Finished\",\n \"thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading video to S3\\\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\\\"extract_and_upload_video: Finished\",\n \"= str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\\\"extract_and_upload_video: Finished getting video length\\\") logger.debug(\\\"extract_and_upload_video: Getting video height and width\\\")\",\n \"WHERE game_id = '{game_id}' \\\"\\\"\\\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number\",\n \"shutil import tempfile import uuid from concurrent import futures from multiprocessing import Pool\",\n \"multiprocessing import Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance = get_backend()\",\n \"frame extraction\\\") aws_lambda_payloads = [ json.dumps({ \\\"s3_bucket_path\\\": bucket, \\\"s3_video_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"chunks\\\", basename), \\\"s3_output_frames_path\\\":\",\n \"frame_number) VALUES \\\"\\\"\\\" for i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas,\",\n \"video\\\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\\\"extract_and_upload_video: Finished chunking video\\\") logger.debug(\\\"extract_and_upload_video: Uploading\",\n \"futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join(\",\n \"game_id, frame_numbers ): command = \\\"\\\"\\\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata,\",\n \"futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\\\"extractFrames\\\",\",\n \"for i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command +=\",\n \"height and width\\\") logger.debug(\\\"extract_and_upload_video: Updating length in db\\\") update_game_video_length(game_id, video_length) logger.debug(\\\"extract_and_upload_video: Finished updating\",\n \"'{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \\\"\\\"\\\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\\\",\\\" if\",\n \"UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\\\"{video_length}\\\"', true) WHERE game_id = '{game_id}'\",\n \"= parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id ) if __name__ ==\",\n \"logger.debug(\\\"extract_and_upload_video: Finished getting height and width\\\") logger.debug(\\\"extract_and_upload_video: Updating length in db\\\") update_game_video_length(game_id, video_length)\",\n \"true) WHERE game_id = '{game_id}' \\\"\\\"\\\".format( video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60):\",\n \"vid), bucket, posixpath.join( posixpath.dirname(video_key), \\\"chunks\\\", vid ) ) logger.debug(\\\"extract_and_upload_video: Finished uploading video chunks\\\")\",\n \"in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\\\"s3://\\\" + posixpath.join(frame[\\\"bucket\\\"], frame[\\\"key\\\"]) for\",\n \"thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\\\"extract_and_upload_video: Getting video length\\\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length\",\n \"Updating length in db\\\") update_game_video_length(game_id, video_length) logger.debug(\\\"extract_and_upload_video: Finished updating length in db\\\") logger.debug(\\\"extract_and_upload_video:\",\n \"frame in aws_lambda_response[\\\"frames\\\"]] img_types = [\\\"png\\\" for frame in aws_lambda_response[\\\"frames\\\"]] metadatas = [\",\n \"extraction\\\") for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\\\"s3://\\\" +\",\n \"inserting image metadata\\\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\\\"bucket\\\") parser.add_argument(\\\"video_filename\\\")\",\n \"json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\\\"s3://\\\" + posixpath.join(frame[\\\"bucket\\\"], frame[\\\"key\\\"]) for frame in aws_lambda_response[\\\"frames\\\"]] img_types\",\n \"client = boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = []\",\n \"logger.debug(\\\"extract_and_upload_video: Submitting lambda frame extraction\\\") aws_lambda_payloads = [ json.dumps({ \\\"s3_bucket_path\\\": bucket, \\\"s3_video_path\\\": posixpath.join(posixpath.dirname(video_key),\",\n \"= [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for payload in aws_lambda_payloads:\",\n \"def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command = \\\"\\\"\\\" INSERT INTO\",\n \"= int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1]) return chunk_number * chunk_multiplier + frame_number def insert_images(\",\n \"backend_instance = get_backend() logger = get_logger(__name__, level=\\\"DEBUG\\\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length):\",\n \"from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger = get_logger(__name__,\",\n \"video_height_width = video.get_video_height_width(video_filename) logger.debug(\\\"extract_and_upload_video: Finished getting height and width\\\") logger.debug(\\\"extract_and_upload_video: Updating length in\",\n \"datetime import json import os import posixpath import re import shutil import tempfile\",\n \"): logger.debug(\\\"extract_and_upload_video: Getting video length\\\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\\\"extract_and_upload_video: Finished\",\n \"parser.add_argument(\\\"bucket\\\") parser.add_argument(\\\"video_filename\\\") parser.add_argument(\\\"thumbnail_filename\\\") parser.add_argument(\\\"video_key\\\") parser.add_argument(\\\"thumbnail_key\\\") parser.add_argument(\\\"game_id\\\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename,\",\n \"parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id ) if __name__ == \\\"__main__\\\":\",\n \"logger.debug(\\\"extract_and_upload_video: Extracting thumbnail\\\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\\\"extract_and_upload_video: Finished extracting thumbnail\\\") logger.debug(\\\"extract_and_upload_video:\",\n \"logger.debug(\\\"extract_and_upload_video: Uploading video chunks\\\") with futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir): ex.submit(\",\n \"aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\\\"extractFrames\\\", # InvocationType=\\\"Event\\\", Payload=payload )) logger.debug(\\\"extract_and_upload_video: Submitted lambda frame extraction\\\")\",\n \"= int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1]) return chunk_number * chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas,\",\n \"img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \\\"\\\"\\\" for i, (img_raw_path, img_type, img_metadata, frame_number)\",\n \"extracting thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading thumbnail\\\") s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading\",\n \"{\\\"bucket\\\": bucket} for frame in aws_lambda_response[\\\"frames\\\"] ] frame_numbers = [-1 for frame in\",\n \"Uploading video chunks\\\") with futures.ThreadPoolExecutor(8) as ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file,\",\n \"uuid from concurrent import futures from multiprocessing import Pool from ultitrackerapi import get_backend,\",\n \"get_backend() logger = get_logger(__name__, level=\\\"DEBUG\\\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command =\",\n \"as ex: for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key),\",\n \"s3Client.upload_file( thumbnail_filename, bucket, thumbnail_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading video to\",\n \"\\\"chunks\\\", vid ) ) logger.debug(\\\"extract_and_upload_video: Finished uploading video chunks\\\") logger.debug(\\\"extract_and_upload_video: Submitting lambda frame\",\n \"lambda responses\\\") logger.debug(\\\"extract_and_upload_video: Finished inserting image metadata\\\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser\",\n \"Payload=payload )) logger.debug(\\\"extract_and_upload_video: Submitted lambda frame extraction\\\") for result_future in futures.as_completed(result_futures): aws_lambda_response =\",\n \"futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\\\"s3://\\\" + posixpath.join(frame[\\\"bucket\\\"], frame[\\\"key\\\"]) for frame\",\n \"if i < (len(img_raw_paths) - 1) else \\\"\\\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket,\",\n \"img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \\\"\\\"\\\"('{img_id}', '{img_raw_path}', '{img_type}',\",\n \"= json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\\\"s3://\\\" + posixpath.join(frame[\\\"bucket\\\"], frame[\\\"key\\\"]) for frame in aws_lambda_response[\\\"frames\\\"]]\",\n \"for frame in aws_lambda_response[\\\"frames\\\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\\\"extract_and_upload_video: Received\",\n \"chunking video\\\") logger.debug(\\\"extract_and_upload_video: Uploading video chunks\\\") with futures.ThreadPoolExecutor(8) as ex: for vid in\",\n \"[ json.dumps({ \\\"s3_bucket_path\\\": bucket, \\\"s3_video_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"chunks\\\", basename), \\\"s3_output_frames_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"frames\\\", posixpath.splitext(basename)[0]), \\\"video_metadata\\\":\",\n \"] frame_numbers = [-1 for frame in aws_lambda_response[\\\"frames\\\"]] insert_images( raw_paths, img_types, metadatas, game_id,\",\n \"backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\\\"extract_and_upload_video: Getting video\",\n \"posixpath.join(frame[\\\"bucket\\\"], frame[\\\"key\\\"]) for frame in aws_lambda_response[\\\"frames\\\"]] img_types = [\\\"png\\\" for frame in aws_lambda_response[\\\"frames\\\"]]\",\n \"frame extraction\\\") for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\\\"s3://\\\"\",\n \"import argparse import boto3 import datetime import json import os import posixpath import\",\n \"import Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger\",\n \"length in db\\\") update_game_video_length(game_id, video_length) logger.debug(\\\"extract_and_upload_video: Finished updating length in db\\\") logger.debug(\\\"extract_and_upload_video: Extracting\",\n \"responses\\\") logger.debug(\\\"extract_and_upload_video: Finished inserting image metadata\\\") os.remove(video_filename) os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser =\",\n \"logger.debug(\\\"extract_and_upload_video: Finished chunking video\\\") logger.debug(\\\"extract_and_upload_video: Uploading video chunks\\\") with futures.ThreadPoolExecutor(8) as ex: for\",\n \"< (len(img_raw_paths) - 1) else \\\"\\\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename,\",\n \"\\\"\\\"\\\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\\\"{video_length}\\\"', true) WHERE game_id =\",\n \") logger.debug(\\\"extract_and_upload_video: Finished uploading video to S3\\\") logger.debug(\\\"extract_and_upload_video: Chunking video\\\") chunked_video_dir = tempfile.mkdtemp()\",\n \"import os import posixpath import re import shutil import tempfile import uuid from\",\n \"InvocationType=\\\"Event\\\", Payload=payload )) logger.debug(\\\"extract_and_upload_video: Submitted lambda frame extraction\\\") for result_future in futures.as_completed(result_futures): aws_lambda_response\",\n \"level=\\\"DEBUG\\\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command = \\\"\\\"\\\" UPDATE ultitracker.game_metadata SET\",\n \"bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\\\"extract_and_upload_video: Getting video length\\\") video_length_seconds =\",\n \"frame in aws_lambda_response[\\\"frames\\\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\\\"extract_and_upload_video: Received all\",\n \"metadatas = [ {\\\"bucket\\\": bucket} for frame in aws_lambda_response[\\\"frames\\\"] ] frame_numbers = [-1\",\n \"enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \\\"\\\"\\\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \\\"\\\"\\\".format(\",\n \"S3\\\") logger.debug(\\\"extract_and_upload_video: Chunking video\\\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\\\"extract_and_upload_video: Finished chunking\",\n \"data = jsonb_set(data, '{{length}}', '\\\"{video_length}\\\"', true) WHERE game_id = '{game_id}' \\\"\\\"\\\".format( video_length=video_length, game_id=game_id\",\n \"get_logger(__name__, level=\\\"DEBUG\\\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command = \\\"\\\"\\\" UPDATE ultitracker.game_metadata\",\n \"img_type, img_metadata, game_id, frame_number) VALUES \\\"\\\"\\\" for i, (img_raw_path, img_type, img_metadata, frame_number) in\",\n \"[\\\"png\\\" for frame in aws_lambda_response[\\\"frames\\\"]] metadatas = [ {\\\"bucket\\\": bucket} for frame in\",\n \"bucket, \\\"s3_video_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"chunks\\\", basename), \\\"s3_output_frames_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"frames\\\", posixpath.splitext(basename)[0]), \\\"video_metadata\\\": video_height_width }).encode() for\",\n \"os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \\\"chunks\\\", vid ) ) logger.debug(\\\"extract_and_upload_video:\",\n \"Submitting lambda frame extraction\\\") aws_lambda_payloads = [ json.dumps({ \\\"s3_bucket_path\\\": bucket, \\\"s3_video_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"chunks\\\",\",\n \"result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\\\"s3://\\\" + posixpath.join(frame[\\\"bucket\\\"], frame[\\\"key\\\"])\",\n \"in db\\\") update_game_video_length(game_id, video_length) logger.debug(\\\"extract_and_upload_video: Finished updating length in db\\\") logger.debug(\\\"extract_and_upload_video: Extracting thumbnail\\\")\",\n \"and width\\\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\\\"extract_and_upload_video: Finished getting height and width\\\") logger.debug(\\\"extract_and_upload_video: Updating\",\n \"\\\"\\\"\\\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}', {frame_number}){include_comma} \\\"\\\"\\\".format( img_id=uuid.uuid4(), img_raw_path=img_raw_path, img_type=img_type, img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number,\",\n \"# InvocationType=\\\"Event\\\", Payload=payload )) logger.debug(\\\"extract_and_upload_video: Submitted lambda frame extraction\\\") for result_future in futures.as_completed(result_futures):\",\n \"\\\"\\\" ) backend_instance.client.execute(command) def extract_and_upload_video( bucket, video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\\\"extract_and_upload_video:\",\n \"= \\\"\\\"\\\" INSERT INTO ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \\\"\\\"\\\"\",\n \"ultitracker.img_location (img_id, img_raw_path, img_type, img_metadata, game_id, frame_number) VALUES \\\"\\\"\\\" for i, (img_raw_path, img_type,\",\n \"from multiprocessing import Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance =\",\n \"for vid in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \\\"chunks\\\", vid\",\n \"length\\\") logger.debug(\\\"extract_and_upload_video: Getting video height and width\\\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\\\"extract_and_upload_video: Finished getting\",\n \"import re import shutil import tempfile import uuid from concurrent import futures from\",\n \"get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger = get_logger(__name__, level=\\\"DEBUG\\\") s3Client =\",\n \"uploading video chunks\\\") logger.debug(\\\"extract_and_upload_video: Submitting lambda frame extraction\\\") aws_lambda_payloads = [ json.dumps({ \\\"s3_bucket_path\\\":\",\n \"extraction\\\") aws_lambda_payloads = [ json.dumps({ \\\"s3_bucket_path\\\": bucket, \\\"s3_video_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"chunks\\\", basename), \\\"s3_output_frames_path\\\": posixpath.join(posixpath.dirname(video_key),\",\n \"frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \\\"\\\"\\\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}', '{game_id}',\",\n \"os import posixpath import re import shutil import tempfile import uuid from concurrent\",\n \"argparse.ArgumentParser() parser.add_argument(\\\"bucket\\\") parser.add_argument(\\\"video_filename\\\") parser.add_argument(\\\"thumbnail_filename\\\") parser.add_argument(\\\"video_key\\\") parser.add_argument(\\\"thumbnail_key\\\") parser.add_argument(\\\"game_id\\\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename,\",\n \"Chunking video\\\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename, chunked_video_dir, chunk_size=60) logger.debug(\\\"extract_and_upload_video: Finished chunking video\\\") logger.debug(\\\"extract_and_upload_video:\",\n \"updating length in db\\\") logger.debug(\\\"extract_and_upload_video: Extracting thumbnail\\\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\\\"extract_and_upload_video:\",\n \"Finished chunking video\\\") logger.debug(\\\"extract_and_upload_video: Uploading video chunks\\\") with futures.ThreadPoolExecutor(8) as ex: for vid\",\n \"import get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger = get_logger(__name__, level=\\\"DEBUG\\\") s3Client\",\n \"time=video_length_seconds // 2) logger.debug(\\\"extract_and_upload_video: Finished extracting thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading thumbnail\\\") s3Client.upload_file( thumbnail_filename, bucket,\",\n \"logger = get_logger(__name__, level=\\\"DEBUG\\\") s3Client = get_s3Client() def update_game_video_length(game_id, video_length): command = \\\"\\\"\\\"\",\n \"video_filename, thumbnail_filename, video_key, thumbnail_key, game_id ): logger.debug(\\\"extract_and_upload_video: Getting video length\\\") video_length_seconds = int(video.get_video_duration(video_filename))\",\n \"boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for payload\",\n \"os.remove(thumbnail_filename) shutil.rmtree(chunked_video_dir) def main(): parser = argparse.ArgumentParser() parser.add_argument(\\\"bucket\\\") parser.add_argument(\\\"video_filename\\\") parser.add_argument(\\\"thumbnail_filename\\\") parser.add_argument(\\\"video_key\\\") parser.add_argument(\\\"thumbnail_key\\\") parser.add_argument(\\\"game_id\\\")\",\n \"VALUES \\\"\\\"\\\" for i, (img_raw_path, img_type, img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)):\",\n \"Finished getting height and width\\\") logger.debug(\\\"extract_and_upload_video: Updating length in db\\\") update_game_video_length(game_id, video_length) logger.debug(\\\"extract_and_upload_video:\",\n \"backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1]) return chunk_number *\",\n \"[] with futures.ThreadPoolExecutor(max_workers=16) as ex: result_futures = [] for payload in aws_lambda_payloads: result_futures.append(ex.submit(\",\n \"video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\\\"extract_and_upload_video: Finished getting video length\\\") logger.debug(\\\"extract_and_upload_video: Getting video height and\",\n \"update_game_video_length(game_id, video_length) logger.debug(\\\"extract_and_upload_video: Finished updating length in db\\\") logger.debug(\\\"extract_and_upload_video: Extracting thumbnail\\\") video.get_thumbnail(video_filename, thumbnail_filename,\",\n \"video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\\\"extract_and_upload_video: Finished extracting thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading thumbnail\\\") s3Client.upload_file(\",\n \"insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command = \\\"\\\"\\\" INSERT INTO ultitracker.img_location\",\n \"video_length=video_length, game_id=game_id ) backend_instance.client.execute(command) def get_frame_number(key, chunk_multiplier=60): frame_number = int(posixpath.splitext(posixpath.basename(key))[0].split(\\\"_\\\")[1]) chunk_number = int(posixpath.basename(posixpath.dirname(key)).split(\\\"_\\\")[1])\",\n \"logger.debug(\\\"extract_and_upload_video: Finished updating length in db\\\") logger.debug(\\\"extract_and_upload_video: Extracting thumbnail\\\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds //\",\n \"Uploading video to S3\\\") s3Client.upload_file( video_filename, bucket, video_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading video\",\n \"client.invoke, FunctionName=\\\"extractFrames\\\", # InvocationType=\\\"Event\\\", Payload=payload )) logger.debug(\\\"extract_and_upload_video: Submitted lambda frame extraction\\\") for result_future\",\n \"aws_lambda_payloads = [ json.dumps({ \\\"s3_bucket_path\\\": bucket, \\\"s3_video_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"chunks\\\", basename), \\\"s3_output_frames_path\\\": posixpath.join(posixpath.dirname(video_key), \\\"frames\\\",\",\n \"img_metadata, frame_number) in enumerate(zip(img_raw_paths, img_types, img_metadatas, frame_numbers)): command += \\\"\\\"\\\"('{img_id}', '{img_raw_path}', '{img_type}', '{img_metadata}',\",\n \"raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\\\"extract_and_upload_video: Received all lambda responses\\\") logger.debug(\\\"extract_and_upload_video: Finished\",\n \"Submitted lambda frame extraction\\\") for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\")) aws_lambda_responses.append(aws_lambda_response) raw_paths\",\n \"args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id ) if __name__\",\n \"img_metadata=json.dumps(img_metadata), game_id=game_id, frame_number=frame_number, include_comma=\\\",\\\" if i < (len(img_raw_paths) - 1) else \\\"\\\" )\",\n \"in os.listdir(chunked_video_dir): ex.submit( s3Client.upload_file, os.path.join(chunked_video_dir, vid), bucket, posixpath.join( posixpath.dirname(video_key), \\\"chunks\\\", vid ) )\",\n \"for basename in os.listdir(chunked_video_dir) ] client = boto3.client('lambda') aws_lambda_responses = [] with futures.ThreadPoolExecutor(max_workers=16)\",\n \"Getting video length\\\") video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\\\"extract_and_upload_video: Finished getting video\",\n \"width\\\") video_height_width = video.get_video_height_width(video_filename) logger.debug(\\\"extract_and_upload_video: Finished getting height and width\\\") logger.debug(\\\"extract_and_upload_video: Updating length\",\n \"frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command = \\\"\\\"\\\" INSERT\",\n \"thumbnail\\\") video.get_thumbnail(video_filename, thumbnail_filename, time=video_length_seconds // 2) logger.debug(\\\"extract_and_upload_video: Finished extracting thumbnail\\\") logger.debug(\\\"extract_and_upload_video: Uploading thumbnail\\\")\",\n \"[ {\\\"bucket\\\": bucket} for frame in aws_lambda_response[\\\"frames\\\"] ] frame_numbers = [-1 for frame\",\n \"for frame in aws_lambda_response[\\\"frames\\\"] ] frame_numbers = [-1 for frame in aws_lambda_response[\\\"frames\\\"]] insert_images(\",\n \"aws_lambda_response[\\\"frames\\\"]] insert_images( raw_paths, img_types, metadatas, game_id, frame_numbers ) logger.debug(\\\"extract_and_upload_video: Received all lambda responses\\\")\",\n \"video.get_video_height_width(video_filename) logger.debug(\\\"extract_and_upload_video: Finished getting height and width\\\") logger.debug(\\\"extract_and_upload_video: Updating length in db\\\") update_game_video_length(game_id,\",\n \"bucket, video_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading video to S3\\\") logger.debug(\\\"extract_and_upload_video: Chunking video\\\") chunked_video_dir\",\n \"for result_future in futures.as_completed(result_futures): aws_lambda_response = json.loads(result_future.result()[\\\"Payload\\\"].read().decode(\\\"utf-8\\\")) aws_lambda_responses.append(aws_lambda_response) raw_paths = [\\\"s3://\\\" + posixpath.join(frame[\\\"bucket\\\"],\",\n \"chunked_video_dir, chunk_size=60) logger.debug(\\\"extract_and_upload_video: Finished chunking video\\\") logger.debug(\\\"extract_and_upload_video: Uploading video chunks\\\") with futures.ThreadPoolExecutor(8) as\",\n \"for payload in aws_lambda_payloads: result_futures.append(ex.submit( client.invoke, FunctionName=\\\"extractFrames\\\", # InvocationType=\\\"Event\\\", Payload=payload )) logger.debug(\\\"extract_and_upload_video: Submitted\",\n \"futures from multiprocessing import Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance\",\n \"and width\\\") logger.debug(\\\"extract_and_upload_video: Updating length in db\\\") update_game_video_length(game_id, video_length) logger.debug(\\\"extract_and_upload_video: Finished updating length\",\n \"main(): parser = argparse.ArgumentParser() parser.add_argument(\\\"bucket\\\") parser.add_argument(\\\"video_filename\\\") parser.add_argument(\\\"thumbnail_filename\\\") parser.add_argument(\\\"video_key\\\") parser.add_argument(\\\"thumbnail_key\\\") parser.add_argument(\\\"game_id\\\") args = parser.parse_args()\",\n \"video_length): command = \\\"\\\"\\\" UPDATE ultitracker.game_metadata SET data = jsonb_set(data, '{{length}}', '\\\"{video_length}\\\"', true)\",\n \"posixpath.join(posixpath.dirname(video_key), \\\"frames\\\", posixpath.splitext(basename)[0]), \\\"video_metadata\\\": video_height_width }).encode() for basename in os.listdir(chunked_video_dir) ] client =\",\n \"logger.debug(\\\"extract_and_upload_video: Finished uploading video to S3\\\") logger.debug(\\\"extract_and_upload_video: Chunking video\\\") chunked_video_dir = tempfile.mkdtemp() video.chunk_video(video_filename,\",\n \"import tempfile import uuid from concurrent import futures from multiprocessing import Pool from\",\n \"video_key ) logger.debug(\\\"extract_and_upload_video: Finished uploading video to S3\\\") logger.debug(\\\"extract_and_upload_video: Chunking video\\\") chunked_video_dir =\",\n \"frame in aws_lambda_response[\\\"frames\\\"] ] frame_numbers = [-1 for frame in aws_lambda_response[\\\"frames\\\"]] insert_images( raw_paths,\",\n \"video_length_seconds = int(video.get_video_duration(video_filename)) video_length = str(datetime.timedelta(seconds=video_length_seconds)) logger.debug(\\\"extract_and_upload_video: Finished getting video length\\\") logger.debug(\\\"extract_and_upload_video: Getting\",\n \"parser.add_argument(\\\"video_key\\\") parser.add_argument(\\\"thumbnail_key\\\") parser.add_argument(\\\"game_id\\\") args = parser.parse_args() extract_and_upload_video( bucket=args.bucket, video_filename=args.video_filename, thumbnail_filename=args.thumbnail_filename, video_key=args.video_key, thumbnail_key=args.thumbnail_key, game_id=args.game_id\"\n]","isConversational":false}}},{"rowIdx":1478,"cells":{"ngram":{"kind":"list like","value":["Predict the most probable class hard_predictions = voting.predict(x_test) # --- SECTION 6 ---","# --- SECTION 1 --- # Import the required libraries import matplotlib as","Import the required libraries import matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper')","2 --- # Get the wrongly predicted instances # and the predicted probabilities","learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- # Instantiate","= learner_3.predict(x_test) # --- SECTION 7 --- # Accuracies of base learners print('L1:',","x[-test_samples:], y[-test_samples:] # --- SECTION 2 --- # Instantiate the learners (classifiers) learner_1","y = breast_cancer.data, breast_cancer.target # Split the train and test samples test_samples =","probability for # each wrongly predicted instance, for each base learner # as","7 --- # Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2))","instance, for each base learner # as well as the average predicted probability","accuracy_score # Load the dataset breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target","the required libraries import matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') #","the base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test)","neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score # Load the dataset","learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION 5 --- # Predict","learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION 7 --- #","# Fit classifier with the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train)","1 --- # Import the required libraries import matplotlib as mpl import matplotlib.pyplot","100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] # ---","accuracy_score(y_test, predictions_3)) # Accuracy of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) #","libraries from sklearn import datasets, naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier from","Split the train and test samples test_samples = 100 x_train, y_train = x[:-test_samples],","2 --- # Store the predicted probability for # each wrongly predicted instance,","(classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION","# a bar and the average probability as an X plt.bar(x, y_1, 3,","learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2 --- # Store the predicted","import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION 2 --- # Get the","as an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3,","for # each wrongly predicted instance, for each base learner # as well","well as the average predicted probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for","predictions_3)) # Accuracy of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # ---","classifier with the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train)","as well as the average predicted probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[]","= learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2 --- # Store the","for the whole test set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 =","required libraries from sklearn import datasets, naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier","--- # Get the base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test)","datasets, naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score #","instances # and the predicted probabilities for the whole test set errors =","the average predicted probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i in","# Get the base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3","errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 ---","# --- SECTION 2 --- # Store the predicted probability for # each","learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION 5 --- # Predict the most","('50NN', learner_3)], voting='soft') # --- SECTION 4 --- # Fit classifier with the","each base learner # as well as the average predicted probability # x=[]","= naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- # Instantiate the","SECTION 1 --- # Import the required libraries import matplotlib as mpl import","y_train = x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] # --- SECTION 2","== 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- #","predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION 7","# Instantiate the voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)],","probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2","neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- #","= learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION 7 --- # Accuracies of","hard_predictions)) # --- SECTION 1 --- # Import the required libraries import matplotlib","y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION","and the predicted probabilities for the whole test set errors = y_test-hard_predictions probabilities_1","VotingClassifier from sklearn.metrics import accuracy_score # Load the dataset breast_cancer = datasets.load_breast_cancer() x,","2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive',","learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION 7 --- # Accuracies of base","y = [0.5 for x in range(len(errors))] plt.plot(y, c='k', linestyle='--') plt.title('Positive Probability') plt.xlabel('Test","Instantiate the voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft')","sklearn import datasets, naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics import","for i in range(len(errors)): if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0])","as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION 2 --- #","the voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') #","4 --- # Fit classifier with the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train)","wrongly predicted instances # and the predicted probabilities for the whole test set","set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test)","3 --- # Instantiate the voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2),","--- # Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:',","voting.predict(x_test) # --- SECTION 6 --- # Get the base learner predictions predictions_1","probaiblity of each base learner as # a bar and the average probability","base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) #","predicted probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i in range(len(errors)): if","SECTION 2 --- # Get the wrongly predicted instances # and the predicted","for x in range(len(errors))] plt.plot(y, c='k', linestyle='--') plt.title('Positive Probability') plt.xlabel('Test sample') plt.ylabel('probability') plt.legend()","svm, neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score # Load the","samples test_samples = 100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:],","Accuracy of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1","test_samples = 100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:]","y[-test_samples:] # --- SECTION 2 --- # Instantiate the learners (classifiers) learner_1 =","learner_3.predict_proba(x_test) # --- SECTION 2 --- # Store the predicted probability for #","the predicted probabilities for the whole test set errors = y_test-hard_predictions probabilities_1 =","Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3))","= learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2 ---","--- # Store the predicted probability for # each wrongly predicted instance, for","wrongly predicted instance, for each base learner # as well as the average","Get the wrongly predicted instances # and the predicted probabilities for the whole","Load the dataset breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target # Split","= y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # ---","breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target # Split the train and","as the average predicted probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i","y_3=[] y_avg=[] for i in range(len(errors)): if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0])","= x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] # --- SECTION 2 ---","Get the base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 =","libraries import matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION","dataset breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target # Split the train","SECTION 4 --- # Fit classifier with the training data voting.fit(x_train, y_train) learner_1.fit(x_train,","probability as an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x,","learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2 --- #","average probability as an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB')","matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION 2 --- # Get the wrongly","--- SECTION 2 --- # Store the predicted probability for # each wrongly","for each base learner # as well as the average predicted probability #","plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x,","learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION 4 --- # Fit","= learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION 7 ---","= learner_3.predict_proba(x_test) # --- SECTION 2 --- # Store the predicted probability for","y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- # Plot the predicted probaiblity of each","# Load the dataset breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target #","naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- # Instantiate the voting","# --- SECTION 4 --- # Fit classifier with the training data voting.fit(x_train,","the train and test samples test_samples = 100 x_train, y_train = x[:-test_samples], y[:-test_samples]","# Plot the predicted probaiblity of each base learner as # a bar","= neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- # Instantiate the voting classifier voting","accuracy_score(y_test, hard_predictions)) # --- SECTION 1 --- # Import the required libraries import","import accuracy_score # Load the dataset breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data,","print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions))","2 --- # Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB()","--- SECTION 1 --- # Import the required libraries from sklearn import datasets,","--- SECTION 4 --- # Fit classifier with the training data voting.fit(x_train, y_train)","# Import the required libraries from sklearn import datasets, naive_bayes, svm, neighbors from","--- # Predict the most probable class hard_predictions = voting.predict(x_test) # --- SECTION","as plt mpl.style.use('seaborn-paper') # --- SECTION 2 --- # Get the wrongly predicted","y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] # --- SECTION 2 --- # Instantiate","learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # ---","--- SECTION 3 --- # Plot the predicted probaiblity of each base learner","learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3","from sklearn import datasets, naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics","# --- SECTION 2 --- # Get the wrongly predicted instances # and","with the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) #","the dataset breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target # Split the","the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) #","# --- SECTION 6 --- # Get the base learner predictions predictions_1 =","--- # Import the required libraries from sklearn import datasets, naive_bayes, svm, neighbors","print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1 --- # Import the","0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- # Plot","= neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 ---","predicted instances # and the predicted probabilities for the whole test set errors","predicted probability for # each wrongly predicted instance, for each base learner #","y_train) learner_3.fit(x_train, y_train) # --- SECTION 5 --- # Predict the most probable","Import the required libraries from sklearn import datasets, naive_bayes, svm, neighbors from sklearn.ensemble","the wrongly predicted instances # and the predicted probabilities for the whole test","= VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION 4 ---","# --- SECTION 1 --- # Import the required libraries from sklearn import","1 --- # Import the required libraries from sklearn import datasets, naive_bayes, svm,","VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION 4 --- #","print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard voting print('-'*30) print('Hard","SECTION 5 --- # Predict the most probable class hard_predictions = voting.predict(x_test) #","most probable class hard_predictions = voting.predict(x_test) # --- SECTION 6 --- # Get","import VotingClassifier from sklearn.metrics import accuracy_score # Load the dataset breast_cancer = datasets.load_breast_cancer()","x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] # --- SECTION","y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- # Plot the predicted","voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION 5 ---","a bar and the average probability as an X plt.bar(x, y_1, 3, label='5NN')","5 --- # Predict the most probable class hard_predictions = voting.predict(x_test) # ---","--- # Fit classifier with the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train,","Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50)","voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION 4","--- # Get the wrongly predicted instances # and the predicted probabilities for","from sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score # Load the dataset breast_cancer","neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- # Instantiate the voting classifier voting =","class hard_predictions = voting.predict(x_test) # --- SECTION 6 --- # Get the base","x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] # --- SECTION 2 --- #","each base learner as # a bar and the average probability as an","y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10) y = [0.5 for x in","of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1 ---","y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg,","mpl.style.use('seaborn-paper') # --- SECTION 2 --- # Get the wrongly predicted instances #","test samples test_samples = 100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test =","y_avg=[] for i in range(len(errors)): if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0])","sklearn.metrics import accuracy_score # Load the dataset breast_cancer = datasets.load_breast_cancer() x, y =","the whole test set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test)","# Get the wrongly predicted instances # and the predicted probabilities for the","predictions_3 = learner_3.predict(x_test) # --- SECTION 7 --- # Accuracies of base learners","and the average probability as an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2,","= voting.predict(x_test) # --- SECTION 6 --- # Get the base learner predictions","bar and the average probability as an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x,","learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # ---","plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150,","probable class hard_predictions = voting.predict(x_test) # --- SECTION 6 --- # Get the","predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION","train and test samples test_samples = 100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test,","import matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION 2","probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2 --- # Store","base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy","y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- # Plot the predicted probaiblity","predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard voting print('-'*30)","probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i in range(len(errors)): if not","s=150, label='Average Positive', zorder=10) y = [0.5 for x in range(len(errors))] plt.plot(y, c='k',","voting='soft') # --- SECTION 4 --- # Fit classifier with the training data","the predicted probability for # each wrongly predicted instance, for each base learner","# Predict the most probable class hard_predictions = voting.predict(x_test) # --- SECTION 6","if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION","label='Average Positive', zorder=10) y = [0.5 for x in range(len(errors))] plt.plot(y, c='k', linestyle='--')","import datasets, naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score","x_test, y_test = x[-test_samples:], y[-test_samples:] # --- SECTION 2 --- # Instantiate the","= 100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] #","# Split the train and test samples test_samples = 100 x_train, y_train =","--- SECTION 7 --- # Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:',","predicted probabilities for the whole test set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test)","each wrongly predicted instance, for each base learner # as well as the","= [0.5 for x in range(len(errors))] plt.plot(y, c='k', linestyle='--') plt.title('Positive Probability') plt.xlabel('Test sample')","x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- # Plot the","the most probable class hard_predictions = voting.predict(x_test) # --- SECTION 6 --- #","learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- # Instantiate the voting classifier","label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10) y = [0.5 for","and test samples test_samples = 100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test","SECTION 6 --- # Get the base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2","the required libraries from sklearn import datasets, naive_bayes, svm, neighbors from sklearn.ensemble import","3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x',","c='k', s=150, label='Average Positive', zorder=10) y = [0.5 for x in range(len(errors))] plt.plot(y,","SECTION 3 --- # Instantiate the voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB',","plt mpl.style.use('seaborn-paper') # --- SECTION 2 --- # Get the wrongly predicted instances","--- SECTION 2 --- # Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2","--- # Plot the predicted probaiblity of each base learner as # a","('NB', learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION 4 --- # Fit classifier","from sklearn.metrics import accuracy_score # Load the dataset breast_cancer = datasets.load_breast_cancer() x, y","not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3","voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1 --- # Import","errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) #","# Accuracy of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION","average predicted probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i in range(len(errors)):","the predicted probaiblity of each base learner as # a bar and the","# each wrongly predicted instance, for each base learner # as well as","mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION 2 --- # Get","test set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 =","breast_cancer.target # Split the train and test samples test_samples = 100 x_train, y_train","y_train) # --- SECTION 5 --- # Predict the most probable class hard_predictions","data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION 5","--- SECTION 5 --- # Predict the most probable class hard_predictions = voting.predict(x_test)","X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN')","6 --- # Get the base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 =","# Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 =","--- # Instantiate the voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN',","range(len(errors)): if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # ---","marker='x', c='k', s=150, label='Average Positive', zorder=10) y = [0.5 for x in range(len(errors))]","y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10) y =","learner_3)], voting='soft') # --- SECTION 4 --- # Fit classifier with the training","Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1 --- # Import the required libraries","base learner # as well as the average predicted probability # x=[] y_1=[]","learner as # a bar and the average probability as an X plt.bar(x,","SECTION 2 --- # Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 =","# and the predicted probabilities for the whole test set errors = y_test-hard_predictions","# as well as the average predicted probability # x=[] y_1=[] y_2=[] y_3=[]","of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) #","x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i in range(len(errors)): if not errors[i] ==","an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1,","# --- SECTION 2 --- # Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5)","naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score # Load","y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average","Plot the predicted probaiblity of each base learner as # a bar and","--- SECTION 2 --- # Get the wrongly predicted instances # and the","base learner as # a bar and the average probability as an X","accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard voting print('-'*30) print('Hard Voting:',","matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION 2 ---","--- SECTION 3 --- # Instantiate the voting classifier voting = VotingClassifier([('5NN', learner_1),","hard_predictions = voting.predict(x_test) # --- SECTION 6 --- # Get the base learner","Fit classifier with the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train,","probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2 --- # Store the predicted probability","--- # Import the required libraries import matplotlib as mpl import matplotlib.pyplot as","y_1=[] y_2=[] y_3=[] y_avg=[] for i in range(len(errors)): if not errors[i] == 0:","x, y = breast_cancer.data, breast_cancer.target # Split the train and test samples test_samples","plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10) y","datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target # Split the train and test samples","Store the predicted probability for # each wrongly predicted instance, for each base","whole test set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3","zorder=10) y = [0.5 for x in range(len(errors))] plt.plot(y, c='k', linestyle='--') plt.title('Positive Probability')","learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION 4 --- # Fit classifier with","SECTION 3 --- # Plot the predicted probaiblity of each base learner as","learner_3.predict(x_test) # --- SECTION 7 --- # Accuracies of base learners print('L1:', accuracy_score(y_test,","predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION 7 --- # Accuracies","y_test = x[-test_samples:], y[-test_samples:] # --- SECTION 2 --- # Instantiate the learners","# --- SECTION 5 --- # Predict the most probable class hard_predictions =","[0.5 for x in range(len(errors))] plt.plot(y, c='k', linestyle='--') plt.title('Positive Probability') plt.xlabel('Test sample') plt.ylabel('probability')","SECTION 2 --- # Store the predicted probability for # each wrongly predicted","predicted probaiblity of each base learner as # a bar and the average","--- SECTION 6 --- # Get the base learner predictions predictions_1 = learner_1.predict(x_test)","# Import the required libraries import matplotlib as mpl import matplotlib.pyplot as plt","= x[-test_samples:], y[-test_samples:] # --- SECTION 2 --- # Instantiate the learners (classifiers)","label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k',","sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score # Load the dataset breast_cancer =","# Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test,","print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1 --- # Import the required","y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION 5 --- #","# --- SECTION 3 --- # Instantiate the voting classifier voting = VotingClassifier([('5NN',","plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10) y = [0.5 for x","predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test,","y_2=[] y_3=[] y_avg=[] for i in range(len(errors)): if not errors[i] == 0: x.append(i)","probabilities for the whole test set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2","Positive', zorder=10) y = [0.5 for x in range(len(errors))] plt.plot(y, c='k', linestyle='--') plt.title('Positive","# x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i in range(len(errors)): if not errors[i]","1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10) y = [0.5","learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of","accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard voting","i in range(len(errors)): if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3)","the average probability as an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2,","--- # Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3","SECTION 1 --- # Import the required libraries from sklearn import datasets, naive_bayes,","learner_3.fit(x_train, y_train) # --- SECTION 5 --- # Predict the most probable class","breast_cancer.data, breast_cancer.target # Split the train and test samples test_samples = 100 x_train,","in range(len(errors)): if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) #","required libraries import matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # ---","of each base learner as # a bar and the average probability as","print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard","SECTION 7 --- # Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test,","training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION","# --- SECTION 3 --- # Plot the predicted probaiblity of each base","3 --- # Plot the predicted probaiblity of each base learner as #","y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- # Plot the predicted probaiblity of","classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION","= datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target # Split the train and test","as # a bar and the average probability as an X plt.bar(x, y_1,","label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10)","learner # as well as the average predicted probability # x=[] y_1=[] y_2=[]","= breast_cancer.data, breast_cancer.target # Split the train and test samples test_samples = 100","the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # ---","y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION 5 --- # Predict the","hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1 --- #","predicted instance, for each base learner # as well as the average predicted","# Store the predicted probability for # each wrongly predicted instance, for each","# --- SECTION 7 --- # Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1))","voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') # ---","--- SECTION 1 --- # Import the required libraries import matplotlib as mpl"],"string":"[\n \"Predict the most probable class hard_predictions = voting.predict(x_test) # --- SECTION 6 ---\",\n \"# --- SECTION 1 --- # Import the required libraries import matplotlib as\",\n \"Import the required libraries import matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper')\",\n \"2 --- # Get the wrongly predicted instances # and the predicted probabilities\",\n \"learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- # Instantiate\",\n \"= learner_3.predict(x_test) # --- SECTION 7 --- # Accuracies of base learners print('L1:',\",\n \"x[-test_samples:], y[-test_samples:] # --- SECTION 2 --- # Instantiate the learners (classifiers) learner_1\",\n \"y = breast_cancer.data, breast_cancer.target # Split the train and test samples test_samples =\",\n \"probability for # each wrongly predicted instance, for each base learner # as\",\n \"7 --- # Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2))\",\n \"instance, for each base learner # as well as the average predicted probability\",\n \"accuracy_score # Load the dataset breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target\",\n \"the required libraries import matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') #\",\n \"the base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test)\",\n \"neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score # Load the dataset\",\n \"learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION 5 --- # Predict\",\n \"learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION 7 --- #\",\n \"# Fit classifier with the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train)\",\n \"1 --- # Import the required libraries import matplotlib as mpl import matplotlib.pyplot\",\n \"100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] # ---\",\n \"accuracy_score(y_test, predictions_3)) # Accuracy of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) #\",\n \"libraries from sklearn import datasets, naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier from\",\n \"Split the train and test samples test_samples = 100 x_train, y_train = x[:-test_samples],\",\n \"2 --- # Store the predicted probability for # each wrongly predicted instance,\",\n \"(classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION\",\n \"# a bar and the average probability as an X plt.bar(x, y_1, 3,\",\n \"learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2 --- # Store the predicted\",\n \"import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION 2 --- # Get the\",\n \"as an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3,\",\n \"for # each wrongly predicted instance, for each base learner # as well\",\n \"well as the average predicted probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for\",\n \"predictions_3)) # Accuracy of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # ---\",\n \"classifier with the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train)\",\n \"as well as the average predicted probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[]\",\n \"= learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2 --- # Store the\",\n \"for the whole test set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 =\",\n \"required libraries from sklearn import datasets, naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier\",\n \"--- # Get the base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test)\",\n \"datasets, naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score #\",\n \"instances # and the predicted probabilities for the whole test set errors =\",\n \"the average predicted probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i in\",\n \"# Get the base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3\",\n \"errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 ---\",\n \"# --- SECTION 2 --- # Store the predicted probability for # each\",\n \"learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION 5 --- # Predict the most\",\n \"('50NN', learner_3)], voting='soft') # --- SECTION 4 --- # Fit classifier with the\",\n \"each base learner # as well as the average predicted probability # x=[]\",\n \"= naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- # Instantiate the\",\n \"SECTION 1 --- # Import the required libraries import matplotlib as mpl import\",\n \"y_train = x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] # --- SECTION 2\",\n \"== 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- #\",\n \"predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION 7\",\n \"# Instantiate the voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)],\",\n \"probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2\",\n \"neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- #\",\n \"= learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION 7 --- # Accuracies of\",\n \"hard_predictions)) # --- SECTION 1 --- # Import the required libraries import matplotlib\",\n \"y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION\",\n \"and the predicted probabilities for the whole test set errors = y_test-hard_predictions probabilities_1\",\n \"VotingClassifier from sklearn.metrics import accuracy_score # Load the dataset breast_cancer = datasets.load_breast_cancer() x,\",\n \"2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive',\",\n \"learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION 7 --- # Accuracies of base\",\n \"y = [0.5 for x in range(len(errors))] plt.plot(y, c='k', linestyle='--') plt.title('Positive Probability') plt.xlabel('Test\",\n \"Instantiate the voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft')\",\n \"sklearn import datasets, naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics import\",\n \"for i in range(len(errors)): if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0])\",\n \"as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION 2 --- #\",\n \"the voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') #\",\n \"4 --- # Fit classifier with the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train)\",\n \"wrongly predicted instances # and the predicted probabilities for the whole test set\",\n \"set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test)\",\n \"3 --- # Instantiate the voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2),\",\n \"--- # Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:',\",\n \"voting.predict(x_test) # --- SECTION 6 --- # Get the base learner predictions predictions_1\",\n \"probaiblity of each base learner as # a bar and the average probability\",\n \"base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) #\",\n \"predicted probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i in range(len(errors)): if\",\n \"SECTION 2 --- # Get the wrongly predicted instances # and the predicted\",\n \"for x in range(len(errors))] plt.plot(y, c='k', linestyle='--') plt.title('Positive Probability') plt.xlabel('Test sample') plt.ylabel('probability') plt.legend()\",\n \"svm, neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score # Load the\",\n \"samples test_samples = 100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:],\",\n \"Accuracy of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1\",\n \"test_samples = 100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:]\",\n \"y[-test_samples:] # --- SECTION 2 --- # Instantiate the learners (classifiers) learner_1 =\",\n \"learner_3.predict_proba(x_test) # --- SECTION 2 --- # Store the predicted probability for #\",\n \"the predicted probabilities for the whole test set errors = y_test-hard_predictions probabilities_1 =\",\n \"Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3))\",\n \"= learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2 ---\",\n \"--- # Store the predicted probability for # each wrongly predicted instance, for\",\n \"wrongly predicted instance, for each base learner # as well as the average\",\n \"Get the wrongly predicted instances # and the predicted probabilities for the whole\",\n \"Load the dataset breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target # Split\",\n \"= y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # ---\",\n \"breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target # Split the train and\",\n \"as the average predicted probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i\",\n \"y_3=[] y_avg=[] for i in range(len(errors)): if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0])\",\n \"= x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] # --- SECTION 2 ---\",\n \"Get the base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 =\",\n \"libraries import matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION\",\n \"dataset breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target # Split the train\",\n \"SECTION 4 --- # Fit classifier with the training data voting.fit(x_train, y_train) learner_1.fit(x_train,\",\n \"probability as an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x,\",\n \"learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2 --- #\",\n \"average probability as an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB')\",\n \"matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION 2 --- # Get the wrongly\",\n \"--- SECTION 2 --- # Store the predicted probability for # each wrongly\",\n \"for each base learner # as well as the average predicted probability #\",\n \"plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x,\",\n \"learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION 4 --- # Fit\",\n \"= learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION 7 ---\",\n \"= learner_3.predict_proba(x_test) # --- SECTION 2 --- # Store the predicted probability for\",\n \"y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- # Plot the predicted probaiblity of each\",\n \"# Load the dataset breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target #\",\n \"naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- # Instantiate the voting\",\n \"# --- SECTION 4 --- # Fit classifier with the training data voting.fit(x_train,\",\n \"the train and test samples test_samples = 100 x_train, y_train = x[:-test_samples], y[:-test_samples]\",\n \"# Plot the predicted probaiblity of each base learner as # a bar\",\n \"= neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- # Instantiate the voting classifier voting\",\n \"accuracy_score(y_test, hard_predictions)) # --- SECTION 1 --- # Import the required libraries import\",\n \"import accuracy_score # Load the dataset breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data,\",\n \"print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions))\",\n \"2 --- # Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB()\",\n \"--- SECTION 1 --- # Import the required libraries from sklearn import datasets,\",\n \"--- SECTION 4 --- # Fit classifier with the training data voting.fit(x_train, y_train)\",\n \"# Import the required libraries from sklearn import datasets, naive_bayes, svm, neighbors from\",\n \"--- # Predict the most probable class hard_predictions = voting.predict(x_test) # --- SECTION\",\n \"as plt mpl.style.use('seaborn-paper') # --- SECTION 2 --- # Get the wrongly predicted\",\n \"y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] # --- SECTION 2 --- # Instantiate\",\n \"learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # ---\",\n \"--- SECTION 3 --- # Plot the predicted probaiblity of each base learner\",\n \"learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3\",\n \"from sklearn import datasets, naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics\",\n \"# --- SECTION 2 --- # Get the wrongly predicted instances # and\",\n \"with the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) #\",\n \"the dataset breast_cancer = datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target # Split the\",\n \"the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) #\",\n \"# --- SECTION 6 --- # Get the base learner predictions predictions_1 =\",\n \"--- # Import the required libraries from sklearn import datasets, naive_bayes, svm, neighbors\",\n \"print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1 --- # Import the\",\n \"0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- # Plot\",\n \"= neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 ---\",\n \"predicted instances # and the predicted probabilities for the whole test set errors\",\n \"predicted probability for # each wrongly predicted instance, for each base learner #\",\n \"y_train) learner_3.fit(x_train, y_train) # --- SECTION 5 --- # Predict the most probable\",\n \"Import the required libraries from sklearn import datasets, naive_bayes, svm, neighbors from sklearn.ensemble\",\n \"the wrongly predicted instances # and the predicted probabilities for the whole test\",\n \"= VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION 4 ---\",\n \"# --- SECTION 1 --- # Import the required libraries from sklearn import\",\n \"1 --- # Import the required libraries from sklearn import datasets, naive_bayes, svm,\",\n \"VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION 4 --- #\",\n \"print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard voting print('-'*30) print('Hard\",\n \"SECTION 5 --- # Predict the most probable class hard_predictions = voting.predict(x_test) #\",\n \"most probable class hard_predictions = voting.predict(x_test) # --- SECTION 6 --- # Get\",\n \"import VotingClassifier from sklearn.metrics import accuracy_score # Load the dataset breast_cancer = datasets.load_breast_cancer()\",\n \"x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] # --- SECTION\",\n \"y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- # Plot the predicted\",\n \"voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION 5 ---\",\n \"a bar and the average probability as an X plt.bar(x, y_1, 3, label='5NN')\",\n \"5 --- # Predict the most probable class hard_predictions = voting.predict(x_test) # ---\",\n \"--- # Fit classifier with the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train,\",\n \"Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50)\",\n \"voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION 4\",\n \"--- # Get the wrongly predicted instances # and the predicted probabilities for\",\n \"from sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score # Load the dataset breast_cancer\",\n \"neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- # Instantiate the voting classifier voting =\",\n \"class hard_predictions = voting.predict(x_test) # --- SECTION 6 --- # Get the base\",\n \"x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] # --- SECTION 2 --- #\",\n \"each base learner as # a bar and the average probability as an\",\n \"y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10) y = [0.5 for x in\",\n \"of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1 ---\",\n \"y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg,\",\n \"mpl.style.use('seaborn-paper') # --- SECTION 2 --- # Get the wrongly predicted instances #\",\n \"test samples test_samples = 100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test =\",\n \"y_avg=[] for i in range(len(errors)): if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0])\",\n \"sklearn.metrics import accuracy_score # Load the dataset breast_cancer = datasets.load_breast_cancer() x, y =\",\n \"the whole test set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test)\",\n \"# Get the wrongly predicted instances # and the predicted probabilities for the\",\n \"predictions_3 = learner_3.predict(x_test) # --- SECTION 7 --- # Accuracies of base learners\",\n \"and the average probability as an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2,\",\n \"= voting.predict(x_test) # --- SECTION 6 --- # Get the base learner predictions\",\n \"bar and the average probability as an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x,\",\n \"learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # ---\",\n \"plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150,\",\n \"probable class hard_predictions = voting.predict(x_test) # --- SECTION 6 --- # Get the\",\n \"predictions predictions_1 = learner_1.predict(x_test) predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION\",\n \"train and test samples test_samples = 100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test,\",\n \"import matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION 2\",\n \"probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2 --- # Store\",\n \"base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy\",\n \"y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- # Plot the predicted probaiblity\",\n \"predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard voting print('-'*30)\",\n \"probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i in range(len(errors)): if not\",\n \"s=150, label='Average Positive', zorder=10) y = [0.5 for x in range(len(errors))] plt.plot(y, c='k',\",\n \"voting='soft') # --- SECTION 4 --- # Fit classifier with the training data\",\n \"the predicted probability for # each wrongly predicted instance, for each base learner\",\n \"# Predict the most probable class hard_predictions = voting.predict(x_test) # --- SECTION 6\",\n \"if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION\",\n \"label='Average Positive', zorder=10) y = [0.5 for x in range(len(errors))] plt.plot(y, c='k', linestyle='--')\",\n \"import datasets, naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score\",\n \"x_test, y_test = x[-test_samples:], y[-test_samples:] # --- SECTION 2 --- # Instantiate the\",\n \"= 100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test = x[-test_samples:], y[-test_samples:] #\",\n \"# Split the train and test samples test_samples = 100 x_train, y_train =\",\n \"--- SECTION 7 --- # Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:',\",\n \"predicted probabilities for the whole test set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test)\",\n \"each wrongly predicted instance, for each base learner # as well as the\",\n \"= [0.5 for x in range(len(errors))] plt.plot(y, c='k', linestyle='--') plt.title('Positive Probability') plt.xlabel('Test sample')\",\n \"x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- # Plot the\",\n \"the most probable class hard_predictions = voting.predict(x_test) # --- SECTION 6 --- #\",\n \"learner_3 = neighbors.KNeighborsClassifier(n_neighbors=50) # --- SECTION 3 --- # Instantiate the voting classifier\",\n \"label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10) y = [0.5 for\",\n \"and test samples test_samples = 100 x_train, y_train = x[:-test_samples], y[:-test_samples] x_test, y_test\",\n \"SECTION 6 --- # Get the base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2\",\n \"the required libraries from sklearn import datasets, naive_bayes, svm, neighbors from sklearn.ensemble import\",\n \"3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x',\",\n \"c='k', s=150, label='Average Positive', zorder=10) y = [0.5 for x in range(len(errors))] plt.plot(y,\",\n \"SECTION 3 --- # Instantiate the voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB',\",\n \"plt mpl.style.use('seaborn-paper') # --- SECTION 2 --- # Get the wrongly predicted instances\",\n \"--- SECTION 2 --- # Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2\",\n \"--- # Plot the predicted probaiblity of each base learner as # a\",\n \"('NB', learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION 4 --- # Fit classifier\",\n \"from sklearn.metrics import accuracy_score # Load the dataset breast_cancer = datasets.load_breast_cancer() x, y\",\n \"not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3\",\n \"voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1 --- # Import\",\n \"errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 = learner_3.predict_proba(x_test) #\",\n \"# Accuracy of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION\",\n \"average predicted probability # x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i in range(len(errors)):\",\n \"the predicted probaiblity of each base learner as # a bar and the\",\n \"# each wrongly predicted instance, for each base learner # as well as\",\n \"mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION 2 --- # Get\",\n \"test set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3 =\",\n \"breast_cancer.target # Split the train and test samples test_samples = 100 x_train, y_train\",\n \"y_train) # --- SECTION 5 --- # Predict the most probable class hard_predictions\",\n \"data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION 5\",\n \"--- SECTION 5 --- # Predict the most probable class hard_predictions = voting.predict(x_test)\",\n \"X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN')\",\n \"6 --- # Get the base learner predictions predictions_1 = learner_1.predict(x_test) predictions_2 =\",\n \"# Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3 =\",\n \"--- # Instantiate the voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN',\",\n \"range(len(errors)): if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # ---\",\n \"marker='x', c='k', s=150, label='Average Positive', zorder=10) y = [0.5 for x in range(len(errors))]\",\n \"y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10) y =\",\n \"learner_3)], voting='soft') # --- SECTION 4 --- # Fit classifier with the training\",\n \"Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1 --- # Import the required libraries\",\n \"base learner # as well as the average predicted probability # x=[] y_1=[]\",\n \"learner as # a bar and the average probability as an X plt.bar(x,\",\n \"SECTION 2 --- # Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 =\",\n \"# and the predicted probabilities for the whole test set errors = y_test-hard_predictions\",\n \"# as well as the average predicted probability # x=[] y_1=[] y_2=[] y_3=[]\",\n \"of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) #\",\n \"x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i in range(len(errors)): if not errors[i] ==\",\n \"an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1,\",\n \"# --- SECTION 2 --- # Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5)\",\n \"naive_bayes, svm, neighbors from sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score # Load\",\n \"y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average\",\n \"Plot the predicted probaiblity of each base learner as # a bar and\",\n \"--- SECTION 2 --- # Get the wrongly predicted instances # and the\",\n \"base learner as # a bar and the average probability as an X\",\n \"accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard voting print('-'*30) print('Hard Voting:',\",\n \"matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # --- SECTION 2 ---\",\n \"--- SECTION 3 --- # Instantiate the voting classifier voting = VotingClassifier([('5NN', learner_1),\",\n \"hard_predictions = voting.predict(x_test) # --- SECTION 6 --- # Get the base learner\",\n \"Fit classifier with the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train,\",\n \"probabilities_3 = learner_3.predict_proba(x_test) # --- SECTION 2 --- # Store the predicted probability\",\n \"--- # Import the required libraries import matplotlib as mpl import matplotlib.pyplot as\",\n \"y_1=[] y_2=[] y_3=[] y_avg=[] for i in range(len(errors)): if not errors[i] == 0:\",\n \"x, y = breast_cancer.data, breast_cancer.target # Split the train and test samples test_samples\",\n \"plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10) y\",\n \"datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target # Split the train and test samples\",\n \"Store the predicted probability for # each wrongly predicted instance, for each base\",\n \"whole test set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2 = learner_2.predict_proba(x_test) probabilities_3\",\n \"zorder=10) y = [0.5 for x in range(len(errors))] plt.plot(y, c='k', linestyle='--') plt.title('Positive Probability')\",\n \"learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION 4 --- # Fit classifier with\",\n \"SECTION 3 --- # Plot the predicted probaiblity of each base learner as\",\n \"learner_3.predict(x_test) # --- SECTION 7 --- # Accuracies of base learners print('L1:', accuracy_score(y_test,\",\n \"predictions_2 = learner_2.predict(x_test) predictions_3 = learner_3.predict(x_test) # --- SECTION 7 --- # Accuracies\",\n \"y_test = x[-test_samples:], y[-test_samples:] # --- SECTION 2 --- # Instantiate the learners\",\n \"# --- SECTION 5 --- # Predict the most probable class hard_predictions =\",\n \"[0.5 for x in range(len(errors))] plt.plot(y, c='k', linestyle='--') plt.title('Positive Probability') plt.xlabel('Test sample') plt.ylabel('probability')\",\n \"SECTION 2 --- # Store the predicted probability for # each wrongly predicted\",\n \"predicted probaiblity of each base learner as # a bar and the average\",\n \"--- SECTION 6 --- # Get the base learner predictions predictions_1 = learner_1.predict(x_test)\",\n \"# Import the required libraries import matplotlib as mpl import matplotlib.pyplot as plt\",\n \"= x[-test_samples:], y[-test_samples:] # --- SECTION 2 --- # Instantiate the learners (classifiers)\",\n \"label='5NN') plt.bar(x, y_2, 2, label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k',\",\n \"sklearn.ensemble import VotingClassifier from sklearn.metrics import accuracy_score # Load the dataset breast_cancer =\",\n \"# Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test,\",\n \"print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1 --- # Import the required\",\n \"y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION 5 --- #\",\n \"# --- SECTION 3 --- # Instantiate the voting classifier voting = VotingClassifier([('5NN',\",\n \"plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10) y = [0.5 for x\",\n \"predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test,\",\n \"y_2=[] y_3=[] y_avg=[] for i in range(len(errors)): if not errors[i] == 0: x.append(i)\",\n \"probabilities for the whole test set errors = y_test-hard_predictions probabilities_1 = learner_1.predict_proba(x_test) probabilities_2\",\n \"Positive', zorder=10) y = [0.5 for x in range(len(errors))] plt.plot(y, c='k', linestyle='--') plt.title('Positive\",\n \"# x=[] y_1=[] y_2=[] y_3=[] y_avg=[] for i in range(len(errors)): if not errors[i]\",\n \"1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10) y = [0.5\",\n \"learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of\",\n \"accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard voting\",\n \"i in range(len(errors)): if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3)\",\n \"the average probability as an X plt.bar(x, y_1, 3, label='5NN') plt.bar(x, y_2, 2,\",\n \"--- # Instantiate the learners (classifiers) learner_1 = neighbors.KNeighborsClassifier(n_neighbors=5) learner_2 = naive_bayes.GaussianNB() learner_3\",\n \"SECTION 1 --- # Import the required libraries from sklearn import datasets, naive_bayes,\",\n \"learner_3.fit(x_train, y_train) # --- SECTION 5 --- # Predict the most probable class\",\n \"breast_cancer.data, breast_cancer.target # Split the train and test samples test_samples = 100 x_train,\",\n \"in range(len(errors)): if not errors[i] == 0: x.append(i) y_1.append(probabilities_1[i][0]) y_2.append(probabilities_2[i][0]) y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) #\",\n \"required libraries import matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper') # ---\",\n \"of each base learner as # a bar and the average probability as\",\n \"print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test, predictions_2)) print('L3:', accuracy_score(y_test, predictions_3)) # Accuracy of hard\",\n \"SECTION 7 --- # Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1)) print('L2:', accuracy_score(y_test,\",\n \"training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION\",\n \"# --- SECTION 3 --- # Plot the predicted probaiblity of each base\",\n \"3 --- # Plot the predicted probaiblity of each base learner as #\",\n \"y_3.append(probabilities_3[i][0]) y_avg.append((probabilities_1[i][0]+probabilities_2[i][0]+probabilities_3[i][0])/3) # --- SECTION 3 --- # Plot the predicted probaiblity of\",\n \"classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') # --- SECTION\",\n \"= datasets.load_breast_cancer() x, y = breast_cancer.data, breast_cancer.target # Split the train and test\",\n \"as # a bar and the average probability as an X plt.bar(x, y_1,\",\n \"label='NB') plt.bar(x, y_3, 1, label='50NN') plt.scatter(x, y_avg, marker='x', c='k', s=150, label='Average Positive', zorder=10)\",\n \"learner # as well as the average predicted probability # x=[] y_1=[] y_2=[]\",\n \"= breast_cancer.data, breast_cancer.target # Split the train and test samples test_samples = 100\",\n \"the training data voting.fit(x_train, y_train) learner_1.fit(x_train, y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # ---\",\n \"y_train) learner_2.fit(x_train, y_train) learner_3.fit(x_train, y_train) # --- SECTION 5 --- # Predict the\",\n \"hard voting print('-'*30) print('Hard Voting:', accuracy_score(y_test, hard_predictions)) # --- SECTION 1 --- #\",\n \"predicted instance, for each base learner # as well as the average predicted\",\n \"# Store the predicted probability for # each wrongly predicted instance, for each\",\n \"# --- SECTION 7 --- # Accuracies of base learners print('L1:', accuracy_score(y_test, predictions_1))\",\n \"voting classifier voting = VotingClassifier([('5NN', learner_1), ('NB', learner_2), ('50NN', learner_3)], voting='soft') # ---\",\n \"--- SECTION 1 --- # Import the required libraries import matplotlib as mpl\"\n]","isConversational":false}}},{"rowIdx":1479,"cells":{"ngram":{"kind":"list like","value":["] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17,","django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations","migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)), ), migrations.AlterField( model_name='news',","import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('API',","dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022,","4.0.3 on 2022-03-23 14:31 import datetime from django.db import migrations, models class Migration(migrations.Migration):","[ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23,","operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)),","Generated by Django 4.0.3 on 2022-03-23 14:31 import datetime from django.db import migrations,","Django 4.0.3 on 2022-03-23 14:31 import datetime from django.db import migrations, models class","14:31 import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies = [","from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ]","('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17,","'0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31,","# Generated by Django 4.0.3 on 2022-03-23 14:31 import datetime from django.db import","2022-03-23 14:31 import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies =","model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)), ), migrations.AlterField( model_name='news', name='headline',","[ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)), ), migrations.AlterField(","models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField(","datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'),","import migrations, models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations =","= [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3,","migrations, models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [","name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)), ), migrations.AlterField( model_name='news', name='headline', field=models.CharField(max_length=100),","by Django 4.0.3 on 2022-03-23 14:31 import datetime from django.db import migrations, models","3, 23, 17, 31, 17, 27766)), ), migrations.AlterField( model_name='news', name='headline', field=models.CharField(max_length=100), ), ]","field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)), ), migrations.AlterField( model_name='news', name='headline', field=models.CharField(max_length=100), ),","= [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)), ),","<gh_stars>0 # Generated by Django 4.0.3 on 2022-03-23 14:31 import datetime from django.db","on 2022-03-23 14:31 import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies","class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news',","Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news', name='date_time',"],"string":"[\n \"] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17,\",\n \"django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations\",\n \"migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)), ), migrations.AlterField( model_name='news',\",\n \"import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('API',\",\n \"dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022,\",\n \"4.0.3 on 2022-03-23 14:31 import datetime from django.db import migrations, models class Migration(migrations.Migration):\",\n \"[ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23,\",\n \"operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)),\",\n \"Generated by Django 4.0.3 on 2022-03-23 14:31 import datetime from django.db import migrations,\",\n \"Django 4.0.3 on 2022-03-23 14:31 import datetime from django.db import migrations, models class\",\n \"14:31 import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies = [\",\n \"from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ]\",\n \"('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17,\",\n \"'0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31,\",\n \"# Generated by Django 4.0.3 on 2022-03-23 14:31 import datetime from django.db import\",\n \"2022-03-23 14:31 import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies =\",\n \"model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)), ), migrations.AlterField( model_name='news', name='headline',\",\n \"[ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)), ), migrations.AlterField(\",\n \"models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField(\",\n \"datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'),\",\n \"import migrations, models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations =\",\n \"= [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3,\",\n \"migrations, models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [\",\n \"name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)), ), migrations.AlterField( model_name='news', name='headline', field=models.CharField(max_length=100),\",\n \"by Django 4.0.3 on 2022-03-23 14:31 import datetime from django.db import migrations, models\",\n \"3, 23, 17, 31, 17, 27766)), ), migrations.AlterField( model_name='news', name='headline', field=models.CharField(max_length=100), ), ]\",\n \"field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)), ), migrations.AlterField( model_name='news', name='headline', field=models.CharField(max_length=100), ),\",\n \"= [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17, 27766)), ),\",\n \"<gh_stars>0 # Generated by Django 4.0.3 on 2022-03-23 14:31 import datetime from django.db\",\n \"on 2022-03-23 14:31 import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies\",\n \"class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news',\",\n \"Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] operations = [ migrations.AlterField( model_name='news', name='date_time',\"\n]","isConversational":false}}},{"rowIdx":1480,"cells":{"ngram":{"kind":"list like","value":["1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size number of","from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError","sample_test, label_train, label_test = \\ train_test_split(data, target, test_size=1, random_state=42) # Now we standardize","sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError def","ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex for k in","gaussian around 0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test","the LICENSE.txt file in the root directory # of this source tree or","std_scale.transform(sample_test) # Now reduce number of features to number of qubits pca =","key in enumerate(class_labels)} test_input = {key: (sample_test[label_test == k, :])[:test_size] for k, key","this license in the LICENSE.txt file in the root directory # of this","target, test_size=1, random_state=42) # Now we standardize for gaussian around 0 with unit","of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale","of this code must retain this # copyright notice, and modified files need","iris dataset \"\"\" import numpy as np from sklearn import datasets from sklearn.model_selection","they have been altered from the originals. \"\"\" iris dataset \"\"\" import numpy","enumerate(class_labels)} test_input = {key: (sample_test[label_test == k, :])[:test_size] for k, key in enumerate(class_labels)}","{key: (sample_test[label_test == k, :])[:test_size] for k, key in enumerate(class_labels)} if plot_data: try:","# This code is licensed under the Apache License, Version 2.0. You may","a notice indicating # that they have been altered from the originals. \"\"\"","in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as plt except ImportError as ex:","3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\"Iris dataset\") plt.show() return","the range (-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train","(sample_train[label_train == k, :])[:training_size] for k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test","k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test == k, :])[:test_size] for k,","training_input = {key: (sample_train[label_train == k, :])[:training_size] for k, key in enumerate(class_labels)} test_input","for k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test == k, :])[:test_size] for","this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works","need to carry a notice indicating # that they have been altered from","sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number of features to","range (-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train =","modified files need to carry a notice indicating # that they have been","the Apache License, Version 2.0. You may # obtain a copy of this","random_state=42) # Now we standardize for gaussian around 0 with unit variance std_scale","originals. \"\"\" iris dataset \"\"\" import numpy as np from sklearn import datasets","variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce","raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex for k in range(0,","sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from","Scale to the range (-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1,","pip_install='pip install matplotlib') from ex for k in range(0, 3): plt.scatter(sample_train[label_train == k,","except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex","is part of Qiskit. # # (C) Copyright IBM 2018, 2020. # #","from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \"\"\" returns iris dataset","[r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\","import matplotlib.pyplot as plt except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip","copyright notice, and modified files need to carry a notice indicating # that","as plt except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib')","http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this code must retain","\"\"\" iris dataset \"\"\" import numpy as np from sklearn import datasets from","from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler","\"\"\" import numpy as np from sklearn import datasets from sklearn.model_selection import train_test_split","test_size=1, random_state=42) # Now we standardize for gaussian around 0 with unit variance","k in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\"Iris","MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n,","k, :])[:test_size] for k, key in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as","qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \"\"\" returns iris dataset \"\"\"","sample_test = pca.transform(sample_test) # Scale to the range (-1,+1) samples = np.append(sample_train, sample_test,","PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to the range (-1,+1)","ex for k in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k,","must retain this # copyright notice, and modified files need to carry a","range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\"Iris dataset\") plt.show()","target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\ train_test_split(data, target, test_size=1, random_state=42)","qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to","(sample_test[label_test == k, :])[:test_size] for k, key in enumerate(class_labels)} if plot_data: try: import","axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick","plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\"Iris dataset\") plt.show() return sample_train,","from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA","# that they have been altered from the originals. \"\"\" iris dataset \"\"\"","StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size,","files need to carry a notice indicating # that they have been altered","test_input = {key: (sample_test[label_test == k, :])[:test_size] for k, key in enumerate(class_labels)} if","of Qiskit. # # (C) Copyright IBM 2018, 2020. # # This code","license in the LICENSE.txt file in the root directory # of this source","or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this code","to carry a notice indicating # that they have been altered from the","indicating # that they have been altered from the originals. \"\"\" iris dataset","= PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to the range","= {key: (sample_train[label_train == k, :])[:training_size] for k, key in enumerate(class_labels)} test_input =","License, Version 2.0. You may # obtain a copy of this license in","\\ train_test_split(data, target, test_size=1, random_state=42) # Now we standardize for gaussian around 0","each distro training_input = {key: (sample_train[label_train == k, :])[:training_size] for k, key in","of this license in the LICENSE.txt file in the root directory # of","derivative works of this code must retain this # copyright notice, and modified",":])[:training_size] for k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test == k, :])[:test_size]","import PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \"\"\" returns","dataset \"\"\" import numpy as np from sklearn import datasets from sklearn.model_selection import","this # copyright notice, and modified files need to carry a notice indicating","Any modifications or derivative works of this code must retain this # copyright","label_test = \\ train_test_split(data, target, test_size=1, random_state=42) # Now we standardize for gaussian","minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training","size number of samples from each distro training_input = {key: (sample_train[label_train == k,","libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex for k in range(0, 3): plt.scatter(sample_train[label_train","data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\ train_test_split(data, target, test_size=1,","= StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number of","# # Any modifications or derivative works of this code must retain this","as np from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import","to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test)","PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \"\"\" returns iris","for gaussian around 0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train)","may # obtain a copy of this license in the LICENSE.txt file in","r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\ train_test_split(data,","plot_data=False): \"\"\" returns iris dataset \"\"\" class_labels = [r'A', r'B', r'C'] data, target","= std_scale.transform(sample_test) # Now reduce number of features to number of qubits pca","# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or","around 0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test =","sample_test = std_scale.transform(sample_test) # Now reduce number of features to number of qubits","samples from each distro training_input = {key: (sample_train[label_train == k, :])[:training_size] for k,","import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \"\"\" returns iris dataset \"\"\" class_labels","= minmax_scale.transform(sample_test) # Pick training size number of samples from each distro training_input","to the range (-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples)","You may # obtain a copy of this license in the LICENSE.txt file","dataset \"\"\" class_labels = [r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test,","source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of","altered from the originals. \"\"\" iris dataset \"\"\" import numpy as np from","{key: (sample_train[label_train == k, :])[:training_size] for k, key in enumerate(class_labels)} test_input = {key:","try: import matplotlib.pyplot as plt except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris',","training size number of samples from each distro training_input = {key: (sample_train[label_train ==","== k, :])[:training_size] for k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test ==","\"\"\" class_labels = [r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train,","under the Apache License, Version 2.0. You may # obtain a copy of","in the LICENSE.txt file in the root directory # of this source tree","or derivative works of this code must retain this # copyright notice, and","MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex for k in range(0, 3):","MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size number","This code is part of Qiskit. # # (C) Copyright IBM 2018, 2020.","(-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train)","been altered from the originals. \"\"\" iris dataset \"\"\" import numpy as np","r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\ train_test_split(data, target,","class_labels = [r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test","= datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\ train_test_split(data, target, test_size=1, random_state=42) #","np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test)","of samples from each distro training_input = {key: (sample_train[label_train == k, :])[:training_size] for","k, key in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as plt except ImportError","== k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\"Iris dataset\") plt.show() return sample_train, training_input,","2020. # # This code is licensed under the Apache License, Version 2.0.","retain this # copyright notice, and modified files need to carry a notice","plot_data: try: import matplotlib.pyplot as plt except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib',","notice, and modified files need to carry a notice indicating # that they","the originals. \"\"\" iris dataset \"\"\" import numpy as np from sklearn import","file in the root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.","k, :])[:training_size] for k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test == k,","for k in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size])","= \\ train_test_split(data, target, test_size=1, random_state=42) # Now we standardize for gaussian around","# Pick training size number of samples from each distro training_input = {key:","part of Qiskit. # # (C) Copyright IBM 2018, 2020. # # This","= {key: (sample_test[label_test == k, :])[:test_size] for k, key in enumerate(class_labels)} if plot_data:","that they have been altered from the originals. \"\"\" iris dataset \"\"\" import","we standardize for gaussian around 0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train","StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number of features","this code must retain this # copyright notice, and modified files need to","key in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as plt except ImportError as","plt except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from","0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\"Iris dataset\") plt.show() return sample_train, training_input, test_input, class_labels","Version 2.0. You may # obtain a copy of this license in the","== k, :])[:test_size] for k, key in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot","features to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test =","matplotlib') from ex for k in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train","import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua","works of this code must retain this # copyright notice, and modified files","a copy of this license in the LICENSE.txt file in the root directory","of features to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test","modifications or derivative works of this code must retain this # copyright notice,","pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to the range (-1,+1) samples = np.append(sample_train,","= np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test =","Now reduce number of features to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train","= minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size number of samples from","Pick training size number of samples from each distro training_input = {key: (sample_train[label_train","in enumerate(class_labels)} test_input = {key: (sample_test[label_test == k, :])[:test_size] for k, key in","# This code is part of Qiskit. # # (C) Copyright IBM 2018,","# (C) Copyright IBM 2018, 2020. # # This code is licensed under","sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to the range (-1,+1) samples","n, plot_data=False): \"\"\" returns iris dataset \"\"\" class_labels = [r'A', r'B', r'C'] data,","for k, key in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as plt except","notice indicating # that they have been altered from the originals. \"\"\" iris","This code is licensed under the Apache License, Version 2.0. You may #","datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import","sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size number of samples","= pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to the range (-1,+1) samples =","from each distro training_input = {key: (sample_train[label_train == k, :])[:training_size] for k, key","import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size,","sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \"\"\"","Qiskit. # # (C) Copyright IBM 2018, 2020. # # This code is","IBM 2018, 2020. # # This code is licensed under the Apache License,","# Now we standardize for gaussian around 0 with unit variance std_scale =","Now we standardize for gaussian around 0 with unit variance std_scale = StandardScaler().fit(sample_train)","= std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number of features to number","sample_train, sample_test, label_train, label_test = \\ train_test_split(data, target, test_size=1, random_state=42) # Now we","code must retain this # copyright notice, and modified files need to carry",":])[:test_size] for k, key in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as plt","# Now reduce number of features to number of qubits pca = PCA(n_components=n).fit(sample_train)","in the root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. #","# copyright notice, and modified files need to carry a notice indicating #","sample_test = minmax_scale.transform(sample_test) # Pick training size number of samples from each distro","copy of this license in the LICENSE.txt file in the root directory #","minmax_scale.transform(sample_test) # Pick training size number of samples from each distro training_input =","minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size number of samples from each","= MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size","sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) #","reduce number of features to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train =","MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \"\"\" returns iris dataset \"\"\" class_labels =","from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False):","number of samples from each distro training_input = {key: (sample_train[label_train == k, :])[:training_size]","directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications","(C) Copyright IBM 2018, 2020. # # This code is licensed under the","# # This code is licensed under the Apache License, Version 2.0. You","# Any modifications or derivative works of this code must retain this #","and modified files need to carry a notice indicating # that they have","sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from","def iris(training_size, test_size, n, plot_data=False): \"\"\" returns iris dataset \"\"\" class_labels = [r'A',","train_test_split(data, target, test_size=1, random_state=42) # Now we standardize for gaussian around 0 with","Copyright IBM 2018, 2020. # # This code is licensed under the Apache","standardize for gaussian around 0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train =","= pca.transform(sample_test) # Scale to the range (-1,+1) samples = np.append(sample_train, sample_test, axis=0)","Apache License, Version 2.0. You may # obtain a copy of this license","ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex for","= [r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test =","label_train, label_test = \\ train_test_split(data, target, test_size=1, random_state=42) # Now we standardize for","the root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # #","\"\"\" returns iris dataset \"\"\" class_labels = [r'A', r'B', r'C'] data, target =","distro training_input = {key: (sample_train[label_train == k, :])[:training_size] for k, key in enumerate(class_labels)}","samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test","from ex for k in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train ==","code is part of Qiskit. # # (C) Copyright IBM 2018, 2020. #","matplotlib.pyplot as plt except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install","carry a notice indicating # that they have been altered from the originals.","train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import","2018, 2020. # # This code is licensed under the Apache License, Version","number of features to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train)","pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to the","std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number","tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this","# # (C) Copyright IBM 2018, 2020. # # This code is licensed","enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as plt except ImportError as ex: raise","install matplotlib') from ex for k in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size],","# obtain a copy of this license in the LICENSE.txt file in the","test_size, n, plot_data=False): \"\"\" returns iris dataset \"\"\" class_labels = [r'A', r'B', r'C']","LICENSE.txt file in the root directory # of this source tree or at","numpy as np from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing","unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now","import numpy as np from sklearn import datasets from sklearn.model_selection import train_test_split from","0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test)","in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\"Iris dataset\")","datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\ train_test_split(data, target, test_size=1, random_state=42) # Now","at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this code must","number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) #","std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number of features to number of","as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex for k","is licensed under the Apache License, Version 2.0. You may # obtain a","np from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler,","with unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) #","from the originals. \"\"\" iris dataset \"\"\" import numpy as np from sklearn","have been altered from the originals. \"\"\" iris dataset \"\"\" import numpy as","if plot_data: try: import matplotlib.pyplot as plt except ImportError as ex: raise MissingOptionalLibraryError(","iris dataset \"\"\" class_labels = [r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train,","pca.transform(sample_test) # Scale to the range (-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale","2.0. You may # obtain a copy of this license in the LICENSE.txt","import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition","licensed under the Apache License, Version 2.0. You may # obtain a copy","returns iris dataset \"\"\" class_labels = [r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True)","obtain a copy of this license in the LICENSE.txt file in the root","root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any","iris(training_size, test_size, n, plot_data=False): \"\"\" returns iris dataset \"\"\" class_labels = [r'A', r'B',","of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative","code is licensed under the Apache License, Version 2.0. You may # obtain","# Scale to the range (-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale =","k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\"Iris dataset\") plt.show() return sample_train, training_input, test_input,","name='iris', pip_install='pip install matplotlib') from ex for k in range(0, 3): plt.scatter(sample_train[label_train =="],"string":"[\n \"1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size number of\",\n \"from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError\",\n \"sample_test, label_train, label_test = \\\\ train_test_split(data, target, test_size=1, random_state=42) # Now we standardize\",\n \"sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError def\",\n \"ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex for k in\",\n \"gaussian around 0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test\",\n \"the LICENSE.txt file in the root directory # of this source tree or\",\n \"std_scale.transform(sample_test) # Now reduce number of features to number of qubits pca =\",\n \"key in enumerate(class_labels)} test_input = {key: (sample_test[label_test == k, :])[:test_size] for k, key\",\n \"this license in the LICENSE.txt file in the root directory # of this\",\n \"target, test_size=1, random_state=42) # Now we standardize for gaussian around 0 with unit\",\n \"of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale\",\n \"of this code must retain this # copyright notice, and modified files need\",\n \"iris dataset \\\"\\\"\\\" import numpy as np from sklearn import datasets from sklearn.model_selection\",\n \"they have been altered from the originals. \\\"\\\"\\\" iris dataset \\\"\\\"\\\" import numpy\",\n \"enumerate(class_labels)} test_input = {key: (sample_test[label_test == k, :])[:test_size] for k, key in enumerate(class_labels)}\",\n \"{key: (sample_test[label_test == k, :])[:test_size] for k, key in enumerate(class_labels)} if plot_data: try:\",\n \"# This code is licensed under the Apache License, Version 2.0. You may\",\n \"a notice indicating # that they have been altered from the originals. \\\"\\\"\\\"\",\n \"in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as plt except ImportError as ex:\",\n \"3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\\\"Iris dataset\\\") plt.show() return\",\n \"the range (-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train\",\n \"(sample_train[label_train == k, :])[:training_size] for k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test\",\n \"k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test == k, :])[:test_size] for k,\",\n \"training_input = {key: (sample_train[label_train == k, :])[:training_size] for k, key in enumerate(class_labels)} test_input\",\n \"for k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test == k, :])[:test_size] for\",\n \"this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works\",\n \"need to carry a notice indicating # that they have been altered from\",\n \"sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number of features to\",\n \"range (-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train =\",\n \"modified files need to carry a notice indicating # that they have been\",\n \"the Apache License, Version 2.0. You may # obtain a copy of this\",\n \"random_state=42) # Now we standardize for gaussian around 0 with unit variance std_scale\",\n \"originals. \\\"\\\"\\\" iris dataset \\\"\\\"\\\" import numpy as np from sklearn import datasets\",\n \"variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce\",\n \"raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex for k in range(0,\",\n \"sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from\",\n \"Scale to the range (-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1,\",\n \"pip_install='pip install matplotlib') from ex for k in range(0, 3): plt.scatter(sample_train[label_train == k,\",\n \"except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex\",\n \"is part of Qiskit. # # (C) Copyright IBM 2018, 2020. # #\",\n \"from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \\\"\\\"\\\" returns iris dataset\",\n \"[r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\\\\",\n \"import matplotlib.pyplot as plt except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip\",\n \"copyright notice, and modified files need to carry a notice indicating # that\",\n \"as plt except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib')\",\n \"http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this code must retain\",\n \"\\\"\\\"\\\" iris dataset \\\"\\\"\\\" import numpy as np from sklearn import datasets from\",\n \"from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler\",\n \"\\\"\\\"\\\" import numpy as np from sklearn import datasets from sklearn.model_selection import train_test_split\",\n \"test_size=1, random_state=42) # Now we standardize for gaussian around 0 with unit variance\",\n \"k in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\\\"Iris\",\n \"MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n,\",\n \"k, :])[:test_size] for k, key in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as\",\n \"qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \\\"\\\"\\\" returns iris dataset \\\"\\\"\\\"\",\n \"sample_test = pca.transform(sample_test) # Scale to the range (-1,+1) samples = np.append(sample_train, sample_test,\",\n \"PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to the range (-1,+1)\",\n \"ex for k in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k,\",\n \"must retain this # copyright notice, and modified files need to carry a\",\n \"range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\\\"Iris dataset\\\") plt.show()\",\n \"target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\\\ train_test_split(data, target, test_size=1, random_state=42)\",\n \"qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to\",\n \"(sample_test[label_test == k, :])[:test_size] for k, key in enumerate(class_labels)} if plot_data: try: import\",\n \"axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick\",\n \"plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\\\"Iris dataset\\\") plt.show() return sample_train,\",\n \"from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA\",\n \"# that they have been altered from the originals. \\\"\\\"\\\" iris dataset \\\"\\\"\\\"\",\n \"StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size,\",\n \"files need to carry a notice indicating # that they have been altered\",\n \"test_input = {key: (sample_test[label_test == k, :])[:test_size] for k, key in enumerate(class_labels)} if\",\n \"of Qiskit. # # (C) Copyright IBM 2018, 2020. # # This code\",\n \"license in the LICENSE.txt file in the root directory # of this source\",\n \"or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this code\",\n \"to carry a notice indicating # that they have been altered from the\",\n \"indicating # that they have been altered from the originals. \\\"\\\"\\\" iris dataset\",\n \"= PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to the range\",\n \"= {key: (sample_train[label_train == k, :])[:training_size] for k, key in enumerate(class_labels)} test_input =\",\n \"License, Version 2.0. You may # obtain a copy of this license in\",\n \"\\\\ train_test_split(data, target, test_size=1, random_state=42) # Now we standardize for gaussian around 0\",\n \"each distro training_input = {key: (sample_train[label_train == k, :])[:training_size] for k, key in\",\n \"of this license in the LICENSE.txt file in the root directory # of\",\n \"derivative works of this code must retain this # copyright notice, and modified\",\n \":])[:training_size] for k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test == k, :])[:test_size]\",\n \"import PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \\\"\\\"\\\" returns\",\n \"dataset \\\"\\\"\\\" import numpy as np from sklearn import datasets from sklearn.model_selection import\",\n \"this # copyright notice, and modified files need to carry a notice indicating\",\n \"Any modifications or derivative works of this code must retain this # copyright\",\n \"label_test = \\\\ train_test_split(data, target, test_size=1, random_state=42) # Now we standardize for gaussian\",\n \"minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training\",\n \"size number of samples from each distro training_input = {key: (sample_train[label_train == k,\",\n \"libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex for k in range(0, 3): plt.scatter(sample_train[label_train\",\n \"data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\\\ train_test_split(data, target, test_size=1,\",\n \"= StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number of\",\n \"# # Any modifications or derivative works of this code must retain this\",\n \"as np from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import\",\n \"to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test)\",\n \"PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \\\"\\\"\\\" returns iris\",\n \"for gaussian around 0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train)\",\n \"may # obtain a copy of this license in the LICENSE.txt file in\",\n \"r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\\\ train_test_split(data,\",\n \"plot_data=False): \\\"\\\"\\\" returns iris dataset \\\"\\\"\\\" class_labels = [r'A', r'B', r'C'] data, target\",\n \"= std_scale.transform(sample_test) # Now reduce number of features to number of qubits pca\",\n \"# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or\",\n \"around 0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test =\",\n \"sample_test = std_scale.transform(sample_test) # Now reduce number of features to number of qubits\",\n \"samples from each distro training_input = {key: (sample_train[label_train == k, :])[:training_size] for k,\",\n \"import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \\\"\\\"\\\" returns iris dataset \\\"\\\"\\\" class_labels\",\n \"= minmax_scale.transform(sample_test) # Pick training size number of samples from each distro training_input\",\n \"to the range (-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples)\",\n \"You may # obtain a copy of this license in the LICENSE.txt file\",\n \"dataset \\\"\\\"\\\" class_labels = [r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test,\",\n \"source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of\",\n \"altered from the originals. \\\"\\\"\\\" iris dataset \\\"\\\"\\\" import numpy as np from\",\n \"{key: (sample_train[label_train == k, :])[:training_size] for k, key in enumerate(class_labels)} test_input = {key:\",\n \"try: import matplotlib.pyplot as plt except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris',\",\n \"training size number of samples from each distro training_input = {key: (sample_train[label_train ==\",\n \"== k, :])[:training_size] for k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test ==\",\n \"\\\"\\\"\\\" class_labels = [r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train,\",\n \"under the Apache License, Version 2.0. You may # obtain a copy of\",\n \"in the LICENSE.txt file in the root directory # of this source tree\",\n \"or derivative works of this code must retain this # copyright notice, and\",\n \"MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex for k in range(0, 3):\",\n \"MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size number\",\n \"This code is part of Qiskit. # # (C) Copyright IBM 2018, 2020.\",\n \"(-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train)\",\n \"been altered from the originals. \\\"\\\"\\\" iris dataset \\\"\\\"\\\" import numpy as np\",\n \"r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\\\ train_test_split(data, target,\",\n \"class_labels = [r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test\",\n \"= datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\\\ train_test_split(data, target, test_size=1, random_state=42) #\",\n \"np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test)\",\n \"of samples from each distro training_input = {key: (sample_train[label_train == k, :])[:training_size] for\",\n \"k, key in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as plt except ImportError\",\n \"== k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\\\"Iris dataset\\\") plt.show() return sample_train, training_input,\",\n \"2020. # # This code is licensed under the Apache License, Version 2.0.\",\n \"retain this # copyright notice, and modified files need to carry a notice\",\n \"plot_data: try: import matplotlib.pyplot as plt except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib',\",\n \"notice, and modified files need to carry a notice indicating # that they\",\n \"the originals. \\\"\\\"\\\" iris dataset \\\"\\\"\\\" import numpy as np from sklearn import\",\n \"file in the root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.\",\n \"k, :])[:training_size] for k, key in enumerate(class_labels)} test_input = {key: (sample_test[label_test == k,\",\n \"for k in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size])\",\n \"= \\\\ train_test_split(data, target, test_size=1, random_state=42) # Now we standardize for gaussian around\",\n \"# Pick training size number of samples from each distro training_input = {key:\",\n \"part of Qiskit. # # (C) Copyright IBM 2018, 2020. # # This\",\n \"= {key: (sample_test[label_test == k, :])[:test_size] for k, key in enumerate(class_labels)} if plot_data:\",\n \"that they have been altered from the originals. \\\"\\\"\\\" iris dataset \\\"\\\"\\\" import\",\n \"we standardize for gaussian around 0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train\",\n \"StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number of features\",\n \"this code must retain this # copyright notice, and modified files need to\",\n \"key in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as plt except ImportError as\",\n \"plt except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from\",\n \"0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\\\"Iris dataset\\\") plt.show() return sample_train, training_input, test_input, class_labels\",\n \"Version 2.0. You may # obtain a copy of this license in the\",\n \"== k, :])[:test_size] for k, key in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot\",\n \"features to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test =\",\n \"matplotlib') from ex for k in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train\",\n \"import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua\",\n \"works of this code must retain this # copyright notice, and modified files\",\n \"a copy of this license in the LICENSE.txt file in the root directory\",\n \"of features to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test\",\n \"modifications or derivative works of this code must retain this # copyright notice,\",\n \"pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to the range (-1,+1) samples = np.append(sample_train,\",\n \"= np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test =\",\n \"Now reduce number of features to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train\",\n \"= minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size number of samples from\",\n \"Pick training size number of samples from each distro training_input = {key: (sample_train[label_train\",\n \"in enumerate(class_labels)} test_input = {key: (sample_test[label_test == k, :])[:test_size] for k, key in\",\n \"# This code is part of Qiskit. # # (C) Copyright IBM 2018,\",\n \"# (C) Copyright IBM 2018, 2020. # # This code is licensed under\",\n \"sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to the range (-1,+1) samples\",\n \"n, plot_data=False): \\\"\\\"\\\" returns iris dataset \\\"\\\"\\\" class_labels = [r'A', r'B', r'C'] data,\",\n \"for k, key in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as plt except\",\n \"notice indicating # that they have been altered from the originals. \\\"\\\"\\\" iris\",\n \"This code is licensed under the Apache License, Version 2.0. You may #\",\n \"datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import\",\n \"sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size number of samples\",\n \"= pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to the range (-1,+1) samples =\",\n \"from each distro training_input = {key: (sample_train[label_train == k, :])[:training_size] for k, key\",\n \"import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size,\",\n \"sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \\\"\\\"\\\"\",\n \"Qiskit. # # (C) Copyright IBM 2018, 2020. # # This code is\",\n \"IBM 2018, 2020. # # This code is licensed under the Apache License,\",\n \"# Now we standardize for gaussian around 0 with unit variance std_scale =\",\n \"Now we standardize for gaussian around 0 with unit variance std_scale = StandardScaler().fit(sample_train)\",\n \"= std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number of features to number\",\n \"sample_train, sample_test, label_train, label_test = \\\\ train_test_split(data, target, test_size=1, random_state=42) # Now we\",\n \"code must retain this # copyright notice, and modified files need to carry\",\n \":])[:test_size] for k, key in enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as plt\",\n \"# Now reduce number of features to number of qubits pca = PCA(n_components=n).fit(sample_train)\",\n \"in the root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. #\",\n \"# copyright notice, and modified files need to carry a notice indicating #\",\n \"sample_test = minmax_scale.transform(sample_test) # Pick training size number of samples from each distro\",\n \"copy of this license in the LICENSE.txt file in the root directory #\",\n \"minmax_scale.transform(sample_test) # Pick training size number of samples from each distro training_input =\",\n \"minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size number of samples from each\",\n \"= MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size\",\n \"sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) #\",\n \"reduce number of features to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train =\",\n \"MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False): \\\"\\\"\\\" returns iris dataset \\\"\\\"\\\" class_labels =\",\n \"from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError def iris(training_size, test_size, n, plot_data=False):\",\n \"number of samples from each distro training_input = {key: (sample_train[label_train == k, :])[:training_size]\",\n \"directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications\",\n \"(C) Copyright IBM 2018, 2020. # # This code is licensed under the\",\n \"# # This code is licensed under the Apache License, Version 2.0. You\",\n \"# Any modifications or derivative works of this code must retain this #\",\n \"and modified files need to carry a notice indicating # that they have\",\n \"sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from\",\n \"def iris(training_size, test_size, n, plot_data=False): \\\"\\\"\\\" returns iris dataset \\\"\\\"\\\" class_labels = [r'A',\",\n \"train_test_split(data, target, test_size=1, random_state=42) # Now we standardize for gaussian around 0 with\",\n \"Copyright IBM 2018, 2020. # # This code is licensed under the Apache\",\n \"standardize for gaussian around 0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train =\",\n \"= pca.transform(sample_test) # Scale to the range (-1,+1) samples = np.append(sample_train, sample_test, axis=0)\",\n \"Apache License, Version 2.0. You may # obtain a copy of this license\",\n \"ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex for\",\n \"= [r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test =\",\n \"label_train, label_test = \\\\ train_test_split(data, target, test_size=1, random_state=42) # Now we standardize for\",\n \"the root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # #\",\n \"\\\"\\\"\\\" returns iris dataset \\\"\\\"\\\" class_labels = [r'A', r'B', r'C'] data, target =\",\n \"distro training_input = {key: (sample_train[label_train == k, :])[:training_size] for k, key in enumerate(class_labels)}\",\n \"samples = np.append(sample_train, sample_test, axis=0) minmax_scale = MinMaxScaler((-1, 1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test\",\n \"from ex for k in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train ==\",\n \"code is part of Qiskit. # # (C) Copyright IBM 2018, 2020. #\",\n \"matplotlib.pyplot as plt except ImportError as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install\",\n \"carry a notice indicating # that they have been altered from the originals.\",\n \"train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import\",\n \"2018, 2020. # # This code is licensed under the Apache License, Version\",\n \"number of features to number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train)\",\n \"pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) # Scale to the\",\n \"std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number\",\n \"tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this\",\n \"# # (C) Copyright IBM 2018, 2020. # # This code is licensed\",\n \"enumerate(class_labels)} if plot_data: try: import matplotlib.pyplot as plt except ImportError as ex: raise\",\n \"install matplotlib') from ex for k in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size],\",\n \"# obtain a copy of this license in the LICENSE.txt file in the\",\n \"test_size, n, plot_data=False): \\\"\\\"\\\" returns iris dataset \\\"\\\"\\\" class_labels = [r'A', r'B', r'C']\",\n \"LICENSE.txt file in the root directory # of this source tree or at\",\n \"numpy as np from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing\",\n \"unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now\",\n \"import numpy as np from sklearn import datasets from sklearn.model_selection import train_test_split from\",\n \"0 with unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test)\",\n \"in range(0, 3): plt.scatter(sample_train[label_train == k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\\\"Iris dataset\\\")\",\n \"datasets.load_iris(return_X_y=True) sample_train, sample_test, label_train, label_test = \\\\ train_test_split(data, target, test_size=1, random_state=42) # Now\",\n \"at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this code must\",\n \"number of qubits pca = PCA(n_components=n).fit(sample_train) sample_train = pca.transform(sample_train) sample_test = pca.transform(sample_test) #\",\n \"std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) # Now reduce number of features to number of\",\n \"as ex: raise MissingOptionalLibraryError( libname='Matplotlib', name='iris', pip_install='pip install matplotlib') from ex for k\",\n \"is licensed under the Apache License, Version 2.0. You may # obtain a\",\n \"np from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler,\",\n \"with unit variance std_scale = StandardScaler().fit(sample_train) sample_train = std_scale.transform(sample_train) sample_test = std_scale.transform(sample_test) #\",\n \"from the originals. \\\"\\\"\\\" iris dataset \\\"\\\"\\\" import numpy as np from sklearn\",\n \"have been altered from the originals. \\\"\\\"\\\" iris dataset \\\"\\\"\\\" import numpy as\",\n \"if plot_data: try: import matplotlib.pyplot as plt except ImportError as ex: raise MissingOptionalLibraryError(\",\n \"iris dataset \\\"\\\"\\\" class_labels = [r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True) sample_train,\",\n \"pca.transform(sample_test) # Scale to the range (-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale\",\n \"2.0. You may # obtain a copy of this license in the LICENSE.txt\",\n \"import datasets from sklearn.model_selection import train_test_split from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition\",\n \"licensed under the Apache License, Version 2.0. You may # obtain a copy\",\n \"returns iris dataset \\\"\\\"\\\" class_labels = [r'A', r'B', r'C'] data, target = datasets.load_iris(return_X_y=True)\",\n \"obtain a copy of this license in the LICENSE.txt file in the root\",\n \"root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any\",\n \"iris(training_size, test_size, n, plot_data=False): \\\"\\\"\\\" returns iris dataset \\\"\\\"\\\" class_labels = [r'A', r'B',\",\n \"of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative\",\n \"code is licensed under the Apache License, Version 2.0. You may # obtain\",\n \"# Scale to the range (-1,+1) samples = np.append(sample_train, sample_test, axis=0) minmax_scale =\",\n \"k, 0][:training_size], sample_train[label_train == k, 1][:training_size]) plt.title(\\\"Iris dataset\\\") plt.show() return sample_train, training_input, test_input,\",\n \"name='iris', pip_install='pip install matplotlib') from ex for k in range(0, 3): plt.scatter(sample_train[label_train ==\"\n]","isConversational":false}}},{"rowIdx":1481,"cells":{"ngram":{"kind":"list like","value":["controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with","controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client):","'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self,","response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self,","== 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response = controller.get_web_message()","\\ '&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user')","getattr(controller, view_name) assert view() == { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type':","def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'}","as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token does not exist","'{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller,","= fake_fetch return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object):","credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect =","api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def","import ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import","{'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({},","OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService","pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path","authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted","'1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({},","views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture","test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True view = getattr(controller, view_name)","controller, auth_client): response = controller.post_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com',","return svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def","pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response'])","pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture","+ \\ '&state=foobar' + \\ '&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url,","response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self, controller,","pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid):","None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token","user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid: return user","\\ '&state=foobar' + \\ '&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user':","pyramid_request, view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def","pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token =","assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result","+ \\ '&response_type=code' + \\ '&state=foobar' + \\ '&scope=exploit' view = getattr(controller, view_name)","== 'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type') result = views.api_token_error(context,","= 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc","ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES","= '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer","exc.value.type == 'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request):","test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token","svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url","views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token is missing' in exc.value.message def","factories): authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires)","oauthlib.common import Request as OAuthRequest from pyramid import httpexceptions from h._compat import urlparse","views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token does not exist or is","@pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True","context = OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def","['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\","import OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import","expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer is None","= ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request):","def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description'","'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self,","import mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request as","getattr(controller, view_name) view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response =","+ datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object):","h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user","authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\ '&response_type=code' + \\ '&state=foobar' + \\","exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request,","== 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as","= json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post()","controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response =","'{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.post_web_message() assert response['state'] is None","= getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query)","response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return","@pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code'","view = getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert","def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider')","controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers,","authenticated_user, pyramid_request, view_name): auth_client.trusted = True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url,","pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\ '&response_type=code' + \\ '&state=foobar' + \\ '&scope=exploit' view","'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name):","= None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self,","{'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired}","oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient,","scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response = controller.get()","= True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response =","'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None","message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context","return user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login')","None status = 302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc","test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer","'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider):","view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url],","'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True","body = None status = 302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider')","utc_iso8601 from h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user')","fake_fetch return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def","def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response = controller.get() expected","pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config):","views.api_token_error(context, pyramid_request) assert 'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('',","pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token does not","= {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302 svc.create_authorization_response.return_value = (headers, body,","oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service,","'error_type') result = views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context","@pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self):","oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id,","'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token","factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self,","expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response =","body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body == body @pytest.fixture def","test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not","utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value =","error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request):","= response_mode view = getattr(controller, view_name) assert view() == { 'client_id': auth_client.id, 'client_name':","test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response = controller.get_web_message() assert response == {","controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name)","({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token","['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user,","= True assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def","{ 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider):","= 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return","= views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at':","def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers","return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes","svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories):","import unicode_literals import datetime import json import mock import pytest from oauthlib.oauth2 import","controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post()","@pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response = controller.get_web_message() assert response","= factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid: return user user_svc.fetch.side_effect =","= 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value =","getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user,","is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted","auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self,","@pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError)","@pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller, view_name)","test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value =","pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request)","pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code)","controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name) view() parsed_url","302) response = controller.post_web_message() assert response['state'] is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer","h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator","class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request)","pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request","def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400)","= mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class","controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True view = getattr(controller, view_name) view()","= ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body == body","oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token","'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view","= developer_token result = views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at':","True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def","pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type')","('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode =","status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback',","mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar'","controller.post() assert response == {} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'})","oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post() ==","({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request,","controller.post() assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type']","+ \\ '&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES)","datetime import json import mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common","authenticated_user, pyramid_request): auth_client.trusted = True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location","pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user","import httpexceptions from h._compat import urlparse from h.exceptions import OAuthTokenError from h.models.auth_client import","return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None,","= (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302","views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description',","'{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert","exc.value.type == 'missing_token' assert 'Bearer token does not exist or is expired' in","{'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.post_web_message() assert response['state'] is","user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def","oauth_token result = views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name':","auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name',","developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert result ==","@pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories,","result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def token_service(self,","svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self, factories): authclient","== 403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request)","exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result","datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class","result = views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context","credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response","== body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code']","response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller,","def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write']","controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body","def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider):","= None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer","pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc","from h.services.user import user_service_factory from h.util.datetime import utc_iso8601 from h.views import api_auth as","result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires),","= getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client,","controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\ '&response_type=code' + \\ '&state=foobar'","]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view","body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc:","auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with(","test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get',","oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return","oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status","auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None,","view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def","exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code'","== { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client,","from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest from pyramid import","oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller,","pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc","as exc: controller.post() assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method =","test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error'] ==","name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture","does not exist or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token):","pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config):","'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body","views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200)","pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'}","exc.value.type == 'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_validates_token(self, pyramid_request,","result = views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context =","OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime import utc_iso8601","= ({}, body, 200) assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider):","== {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config,","@pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc","controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user,","pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\ '&response_type=code' + \\ '&state=foobar' +","svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc:","result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type') result =","token is missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request)","assert 'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result","== {} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({},","pyramid import httpexceptions from h._compat import urlparse from h.exceptions import OAuthTokenError from h.models.auth_client","controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest)","test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request)","= ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self,","svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method,","assert 'Bearer token is missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token =","pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result","pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid: return user user_svc.fetch.side_effect = fake_fetch return","token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert result","pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response == {}","headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.get_web_message() assert","exist or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token =","view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self,","h.services.user import user_service_factory from h.util.datetime import utc_iso8601 from h.views import api_auth as views","'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token')","response = controller.get_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar',","oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body =","@pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID':","@pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request,","['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True view","urlparse from h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory","= views.api_token_error(context, pyramid_request) assert 'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request): context =","@pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc","pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError)","{ 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username,","= mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url =","= (headers, None, 302) response = controller.post_web_message() assert response['state'] is None @pytest.fixture def","def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type","pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with","def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\ '&response_type=code' +","token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def","TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller,","assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def","response = controller.post() assert response == {} def test_it_raises_when_error(self, controller, oauth_provider): body =","pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post()","pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID':","mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object):","= OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def","== { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller,","pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True","'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc =","'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value","pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response == {} def","test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with","pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name) view() parsed_url =","view_name) assert view() == { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value,","'{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token =","as exc: view = getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path ==","'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user,","'1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({},","oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest from pyramid import httpexceptions","factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid: return user user_svc.fetch.side_effect = fake_fetch","'Bearer token does not exist or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request,","= (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories): return","view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view()","import utc_iso8601 from h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object):","(scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302 svc.create_authorization_response.return_value","user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid: return user user_svc.fetch.side_effect","view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post',","['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes,","{'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value =","h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime import utc_iso8601 from h.views","True response = controller.get_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state':","def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result =","mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest","class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers)","pyramid_request): context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in","pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert","pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self,","pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider):","controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name):","'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request)","= True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def","assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self,","credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers","pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest from pyramid","scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with","test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller,","oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as","exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token is missing' in exc.value.message","OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description' def","assert 'Bearer token does not exist or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self,","@pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config,","'/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method,","from h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from","OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in result def test_it_skips_description_when_empty(self,","controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True","= getattr(controller, view_name) view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response","pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response == {} def test_it_raises_when_error(self,","pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value =","pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires","pyramid_request): context = OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description'] ==","response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer","name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture","403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert","'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc:","redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user')","view_name): oauth_request.response_mode = response_mode view = getattr(controller, view_name) assert view() == { 'client_id':","description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert","def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description'","= views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False}","name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with(","is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as","-*- from __future__ import unicode_literals import datetime import json import mock import pytest","def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response == {} def test_it_raises_when_error(self, controller,","auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message'])","test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response == {} def test_it_raises_when_error(self, controller, oauth_provider):","view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\ '&response_type=code' + \\ '&state=foobar' + \\ '&scope=exploit'","from h._compat import urlparse from h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType from","'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc =","pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert","} def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)}","['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with(","auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)}","pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response","'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc =","-*- coding: utf-8 -*- from __future__ import unicode_literals import datetime import json import","exc: controller.post() assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST'","user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class","@pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)}","import datetime import json import mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError from","test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view = getattr(controller,","oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302)","from oauthlib.common import Request as OAuthRequest from pyramid import httpexceptions from h._compat import","controller): response = controller.post() assert response == {} def test_it_raises_when_error(self, controller, oauth_provider): body","oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body ==","pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url,","view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted","h._compat import urlparse from h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token","'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client,","'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, }","def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200)","400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body == body @pytest.fixture def controller(self,","view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!')","response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert response ==","token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert","from h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name',","view_name): auth_client.trusted = True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user},","= controller.post_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', }","coding: utf-8 -*- from __future__ import unicode_literals import datetime import json import mock","OAuthRequest from pyramid import httpexceptions from h._compat import urlparse from h.exceptions import OAuthTokenError","pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture","oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body ==","assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] =","@pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context =","getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) ==","developer_token result = views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None,","status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('',","= urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']}","= ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value =","factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc =","'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response = controller.get_web_message() assert","with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request):","'&response_type=code' + \\ '&state=foobar' + \\ '&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with(","[pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller,","userid == user.userid: return user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def routes(self,","@pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10)","'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context =","assert response == {} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value","'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode","import InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest from pyramid import httpexceptions from","{ 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client,","controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert","= getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message'])","= controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request,","'{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc,","Request as OAuthRequest from pyramid import httpexceptions from h._compat import urlparse from h.exceptions","= {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value","import urlparse from h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token import","svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class","TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def","'expires_at': None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request))","authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!')","'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self,","pyramid_request): context = OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code ==","auth_client.trusted = True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected","@pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc,","200) assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error':","def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request) assert","json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post() == {'access_token': 'the-access-token'} def","view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request):","svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider')","not in result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context,","controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response =","auth_client): auth_client.trusted = True response = controller.get_web_message() assert response == { 'code': 'abcdef123456',","return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}',","body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post() == {'access_token':","= mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar',","name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError)","'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body =","{'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value =","True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.post_web_message()","parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth':","authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response =","def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service):","'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None","result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result =","'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request):","OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self,","import json import mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import","DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime import utc_iso8601 from h.views import api_auth","test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\ '&response_type=code' + \\","response_mode view = getattr(controller, view_name) assert view() == { 'client_id': auth_client.id, 'client_name': auth_client.name,","unicode_literals import datetime import json import mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError","pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc","httpexceptions from h._compat import urlparse from h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType","== body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers","(headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test","def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture","is missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token')","= controller.post() assert response == {} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error':","exc: view = getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login'","exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller,","pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token is missing'","utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value","routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post()","response_mode, view_name): oauth_request.response_mode = response_mode view = getattr(controller, view_name) assert view() == {","= mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object):","pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert result == {'userid':","def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request):","{} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body,","def test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name',","def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture","controller, auth_client): auth_client.trusted = True response = controller.get_web_message() assert response == { 'code':","pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request)","{'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self,","= 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc","None, 302) response = controller.post_web_message() assert response['state'] is None @pytest.fixture def controller(self, pyramid_request):","'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get',","= OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description'","test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller,","False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return","views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None,","is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value","(headers, None, 302) response = controller.post_web_message() assert response['state'] is None @pytest.fixture def controller(self,","exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound)","def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return","user.userid: return user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login',","controller, pyramid_request, view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message'])","as OAuthRequest from pyramid import httpexceptions from h._compat import urlparse from h.exceptions import","pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method","pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token'","= 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type ==","= views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context =","= {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers =","'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True","h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get',","test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code","oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials","def fake_fetch(userid): if userid == user.userid: return user user_svc.fetch.side_effect = fake_fetch return user","auth_client.trusted = True assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user')","pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response'])","'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token","'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True view =","'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted =","== {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired':","def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name)","= controller.get_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', }","def authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid","exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)","'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body","= True response = controller.get_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com',","mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def","controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert","response = controller.post_web_message() assert response['state'] is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer =","== {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value =","developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at':","None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc,","response = controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller,","assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] =","= {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.get_web_message() assert response['state']","pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({},","oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True)","= 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def","result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context, pyramid_request) assert","if userid == user.userid: return user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def","assert exc.value.type == 'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self,","controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest)","in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token","response == {} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value =","utf-8 -*- from __future__ import unicode_literals import datetime import json import mock import","test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response = controller.get() expected =","parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None,","expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted","'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\ '&response_type=code'","controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers =","return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url,","'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token'","auth_client.trusted = True response = controller.get_web_message() assert response == { 'code': 'abcdef123456', 'origin':","'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url)","'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials)","auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view = getattr(controller, view_name) assert","return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self,","'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request,","'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller,","== 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert","token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert","context = OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error","response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self,","def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as","@pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as","'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location':","= '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message()","with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token does","'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers =","pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid: return","assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [","expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value =","getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def","body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] =","context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in result","assert response['state'] is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None,","controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name)","getattr(controller, view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller,","controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted =","context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in result","context = OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403","def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self,","} @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted =","'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted","return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client,","= getattr(controller, view_name) assert view() == { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode,","'missing_token' assert 'Bearer token does not exist or is expired' in exc.value.message def","body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc:","as exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self,","def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self,","= 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def","missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc:","'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view","return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}',","assert exc.value.type == 'missing_token' assert 'Bearer token does not exist or is expired'","= '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted =","auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client,","'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers","302) response = controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self,","oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.post_web_message() assert response['state'] is None @pytest.fixture","return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def","= getattr(controller, view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self,","h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime","TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def","views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller,","view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view()","controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/')","test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert","test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc:","return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self,","pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect","credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302 svc.create_authorization_response.return_value =","None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config,","assert exc.value.type == 'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_validates_token(self,","body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers =","auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory","assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response","response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url","Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories):","'{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True","{'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.get_web_message() assert response['state'] is","assert result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at':","test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description']","developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc","200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None","@pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request,","view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name):","view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location)","oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def","import Request as OAuthRequest from pyramid import httpexceptions from h._compat import urlparse from","developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error","factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message',","= None status = 302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return","controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value","assert view() == { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state':","'/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message',","assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'})","controller.post() assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token']","result = views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name},","= developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid,","fake_fetch(userid): if userid == user.userid: return user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture","class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view =","@pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read',","return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as","exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert","token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created),","TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert","test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected","{'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request,","def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer is None controller.get_web_message() assert","headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.post_web_message() assert","pyramid_request): context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in","as exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get',","pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert","user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider')","test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller):","controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response","auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id':","token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client': {'id':","pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture","def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view =","__future__ import unicode_literals import datetime import json import mock import pytest from oauthlib.oauth2","@pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' +","h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider","'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self,","oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert result ==","= 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build()","'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode","@pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc,","pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user =","controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)","pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client')","view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect =","urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ])","oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client':","body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client',","def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert","= oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid,","TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request)","token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError)","test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value =","def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True view = getattr(controller,","is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture","pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value","import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message'])","import pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest from","'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted =","auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response","@pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view","def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config,","svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self,","pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' def","view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller,","pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials =","def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value","view_name) view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response = controller.post()","oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'})","def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view =","'&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name',","from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime import utc_iso8601 from","'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token =","'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers","pyramid_request): context = OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type'","user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request,","= controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller,","pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc):","body, 200) assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body =","'Bearer token is missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token'","'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body,","token does not exist or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service,","'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view","def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error']","controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client):","missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def","response = controller.post_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar',","'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid)","is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url =","import user_service_factory from h.util.datetime import utc_iso8601 from h.views import api_auth as views @pytest.mark.usefixtures('routes',","== expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert response == {","def controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return","'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def","from h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory from","test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not","{'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location':","controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert","== 'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service):","from h.util.datetime import utc_iso8601 from h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc')","True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self,","from pyramid import httpexceptions from h._compat import urlparse from h.exceptions import OAuthTokenError from","pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value","pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert result == {'userid':","assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert","result = views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired':","pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def","authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view = getattr(controller, view_name) assert view()","pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token'","oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result","as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token is missing' in","return svc @pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow()","test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name) view()","as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self,","= datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken()","headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302 svc.create_authorization_response.return_value = (headers,","['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc:","'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result =","assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller,","== { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username':","user_service_factory from h.util.datetime import utc_iso8601 from h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider',","'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name):","token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert result","pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result = views.api_token_error(context,","expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return","test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller,","assert response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert response","pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self, factories):","factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid:","svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self,","authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture","getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect","controller.get_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user')","from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory from","assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with","# -*- coding: utf-8 -*- from __future__ import unicode_literals import datetime import json","oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name',","'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted","pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert","factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request):","OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes =","views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type')","auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc","or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value","def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider')","view() == { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar',","def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view =","= mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self, factories): authclient =","= views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error","controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer ==","= {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value","\\ '&response_type=code' + \\ '&state=foobar' + \\ '&scope=exploit' view = getattr(controller, view_name) view()","controller.post_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def","'Bearer token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with","(None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name):","= 'http://example.com/auth?client_id=the-client-id' + \\ '&response_type=code' + \\ '&state=foobar' + \\ '&scope=exploit' view =","json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert","from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from","'' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token","h.util.datetime import utc_iso8601 from h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class","svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state':","= OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in result def","exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token'","view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller,","controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token':","test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type ==","def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response = controller.get_web_message() assert response ==","'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller,","token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token'","assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type') result","@pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as","Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc,","oauth_request.response_mode = response_mode view = getattr(controller, view_name) assert view() == { 'client_id': auth_client.id,","import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime import","auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert","'{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.get_web_message() assert response['state'] is None","import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import","pyramid_request, view_name): auth_client.trusted = True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user':","== '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'),","InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert exc.value.description ==","expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert response == { 'code':","== {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ]) def","in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self,","urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name',","== 'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token","== 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context,","= (headers, None, 302) response = controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post',","def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert response == { 'code': 'abcdef123456',","== expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer is","svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def","{'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request):","= getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name):","mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request':","view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self,","controller.post_web_message() assert response['state'] is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None return","(headers, None, 302) response = controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message'])","'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request)","True assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self,","class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers)","def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type","= oauth_token result = views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id,","return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message', 'error_type',","'boom!' def test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location","exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token does not exist or","['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc:","views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with","json import mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request","pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name',","pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type","response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self,","pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body,","def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value","= controller.post_web_message() assert response['state'] is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None","= True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user')","pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request):","assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'),","@pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST,","views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200)","def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result =","mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example","= json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post()","controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view = getattr(controller, view_name)","'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token =","InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest from pyramid import httpexceptions from h._compat","pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self,","view = getattr(controller, view_name) assert view() == { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode':","view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request,","assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected =","svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status =","instance=True) scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request}","with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!'","== 'missing_token' assert 'Bearer token does not exist or is expired' in exc.value.message","views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created),","'error description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request)","({}, body, 200) assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body","utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None,","None, 302) response = controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def","svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self,","oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as","True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.get_web_message()","view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client):","assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def","result = views.api_token_error(context, pyramid_request) assert 'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request): context","'http://example.com/auth?client_id=the-client-id' + \\ '&response_type=code' + \\ '&state=foobar' + \\ '&scope=exploit' view = getattr(controller,","expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context","= InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert exc.value.description","['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view =","assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name):","view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next':","@pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if","not exist or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token","= controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client):","with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token is","OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request):","controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return","json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert","description', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self,","test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type ==","= factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def","@pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller,","200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider):","test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request)","pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return","pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response ==","controller, auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def","response['state'] is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request)","pyramid_request) assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request')","datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def","'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers =","None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id'","authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid ==","[ (None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode,","auth_client.trusted = True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES)","@pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc =","{'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302 svc.create_authorization_response.return_value = (headers, body, status)","test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with","'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request):","({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body == body @pytest.fixture","view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected","auth_client): response = controller.post_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state':","302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self,","exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message'])","'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body","from __future__ import unicode_literals import datetime import json import mock import pytest from","assert 'Bearer token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = ''","status = 302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture","None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted =","return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def","oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response","= 302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def","pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with(","view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller,","'&state=foobar' + \\ '&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user},","svc @pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() +","oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post()","@pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller, view_name) view()","} @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location':","None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def","oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return","'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token):","def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService,","= json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post() == {'access_token': 'the-access-token'}","assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result =","views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request):","= OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self,","@pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer is None controller.get_web_message()","pyramid_request) assert 'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request')","token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError)","== user.userid: return user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def routes(self, pyramid_config):","def test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location ==","class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context,","in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request)","pyramid_request): auth_client.trusted = True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location ==","def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400)","auth_client): auth_client.trusted = True assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2'","factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request))","factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message', 'error_type', status_code=403)","oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view = getattr(controller, view_name) assert view() ==","= {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.post_web_message() assert response['state']","scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value","test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert response == { 'code': 'abcdef123456', 'origin':","name='auth_token') return svc @pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires =","import DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime import utc_iso8601 from h.views import","@pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST,","def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the","in result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context, pyramid_request)","with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert"],"string":"[\n \"controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with\",\n \"controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client):\",\n \"'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self,\",\n \"response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self,\",\n \"== 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response = controller.get_web_message()\",\n \"\\\\ '&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user')\",\n \"getattr(controller, view_name) assert view() == { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type':\",\n \"def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'}\",\n \"as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token does not exist\",\n \"'{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller,\",\n \"= fake_fetch return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object):\",\n \"credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect =\",\n \"api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def\",\n \"import ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import\",\n \"{'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({},\",\n \"OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService\",\n \"pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path\",\n \"authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted\",\n \"'1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({},\",\n \"views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture\",\n \"test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True view = getattr(controller, view_name)\",\n \"controller, auth_client): response = controller.post_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com',\",\n \"return svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def\",\n \"pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response'])\",\n \"pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture\",\n \"+ \\\\ '&state=foobar' + \\\\ '&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url,\",\n \"response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self, controller,\",\n \"pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid):\",\n \"None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token\",\n \"user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid: return user\",\n \"\\\\ '&state=foobar' + \\\\ '&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user':\",\n \"pyramid_request, view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def\",\n \"pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token =\",\n \"assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result\",\n \"+ \\\\ '&response_type=code' + \\\\ '&state=foobar' + \\\\ '&scope=exploit' view = getattr(controller, view_name)\",\n \"== 'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type') result = views.api_token_error(context,\",\n \"= 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc\",\n \"ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES\",\n \"= '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer\",\n \"exc.value.type == 'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request):\",\n \"test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token\",\n \"svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url\",\n \"views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token is missing' in exc.value.message def\",\n \"factories): authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires)\",\n \"oauthlib.common import Request as OAuthRequest from pyramid import httpexceptions from h._compat import urlparse\",\n \"views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token does not exist or is\",\n \"@pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True\",\n \"context = OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def\",\n \"['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\\\\",\n \"import OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import\",\n \"expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer is None\",\n \"= ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request):\",\n \"def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description'\",\n \"'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self,\",\n \"import mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request as\",\n \"getattr(controller, view_name) view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response =\",\n \"+ datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object):\",\n \"h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user\",\n \"authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\\\ '&response_type=code' + \\\\ '&state=foobar' + \\\\\",\n \"exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request,\",\n \"== 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as\",\n \"= json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post()\",\n \"controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response =\",\n \"'{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.post_web_message() assert response['state'] is None\",\n \"= getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query)\",\n \"response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return\",\n \"@pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code'\",\n \"view = getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert\",\n \"def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider')\",\n \"controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers,\",\n \"authenticated_user, pyramid_request, view_name): auth_client.trusted = True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url,\",\n \"pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\\\ '&response_type=code' + \\\\ '&state=foobar' + \\\\ '&scope=exploit' view\",\n \"'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name):\",\n \"= None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self,\",\n \"{'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired}\",\n \"oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient,\",\n \"scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response = controller.get()\",\n \"= True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response =\",\n \"'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None\",\n \"message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context\",\n \"return user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login')\",\n \"None status = 302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc\",\n \"test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer\",\n \"'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider):\",\n \"view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url],\",\n \"'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True\",\n \"body = None status = 302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider')\",\n \"utc_iso8601 from h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user')\",\n \"fake_fetch return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def\",\n \"def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response = controller.get() expected\",\n \"pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config):\",\n \"views.api_token_error(context, pyramid_request) assert 'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('',\",\n \"pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token does not\",\n \"= {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302 svc.create_authorization_response.return_value = (headers, body,\",\n \"oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service,\",\n \"'error_type') result = views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context\",\n \"@pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self):\",\n \"oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id,\",\n \"'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token\",\n \"factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self,\",\n \"expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response =\",\n \"body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body == body @pytest.fixture def\",\n \"test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not\",\n \"utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value =\",\n \"error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request):\",\n \"= response_mode view = getattr(controller, view_name) assert view() == { 'client_id': auth_client.id, 'client_name':\",\n \"test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response = controller.get_web_message() assert response == {\",\n \"controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name)\",\n \"({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token\",\n \"['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user,\",\n \"= True assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def\",\n \"{ 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider):\",\n \"= 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return\",\n \"= views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at':\",\n \"def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers\",\n \"return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes\",\n \"svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories):\",\n \"import unicode_literals import datetime import json import mock import pytest from oauthlib.oauth2 import\",\n \"controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post()\",\n \"@pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response = controller.get_web_message() assert response\",\n \"= factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid: return user user_svc.fetch.side_effect =\",\n \"= 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value =\",\n \"getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user,\",\n \"is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted\",\n \"auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self,\",\n \"@pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError)\",\n \"@pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller, view_name)\",\n \"test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value =\",\n \"pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request)\",\n \"pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code)\",\n \"controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name) view() parsed_url\",\n \"302) response = controller.post_web_message() assert response['state'] is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer\",\n \"h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator\",\n \"class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request)\",\n \"pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request\",\n \"def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400)\",\n \"= mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class\",\n \"controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True view = getattr(controller, view_name) view()\",\n \"= ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body == body\",\n \"oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token\",\n \"'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view\",\n \"= developer_token result = views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at':\",\n \"True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def\",\n \"pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type')\",\n \"('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode =\",\n \"status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback',\",\n \"mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar'\",\n \"controller.post() assert response == {} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'})\",\n \"oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post() ==\",\n \"({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request,\",\n \"controller.post() assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type']\",\n \"+ \\\\ '&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES)\",\n \"datetime import json import mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common\",\n \"authenticated_user, pyramid_request): auth_client.trusted = True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location\",\n \"pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user\",\n \"import httpexceptions from h._compat import urlparse from h.exceptions import OAuthTokenError from h.models.auth_client import\",\n \"return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None,\",\n \"= (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302\",\n \"views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description',\",\n \"'{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert\",\n \"exc.value.type == 'missing_token' assert 'Bearer token does not exist or is expired' in\",\n \"{'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.post_web_message() assert response['state'] is\",\n \"user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def\",\n \"oauth_token result = views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name':\",\n \"auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name',\",\n \"developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert result ==\",\n \"@pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories,\",\n \"result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def token_service(self,\",\n \"svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self, factories): authclient\",\n \"== 403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request)\",\n \"exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result\",\n \"datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class\",\n \"result = views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context\",\n \"credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response\",\n \"== body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code']\",\n \"response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller,\",\n \"def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write']\",\n \"controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body\",\n \"def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider):\",\n \"= None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer\",\n \"pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc\",\n \"from h.services.user import user_service_factory from h.util.datetime import utc_iso8601 from h.views import api_auth as\",\n \"result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires),\",\n \"= getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client,\",\n \"controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\\\ '&response_type=code' + \\\\ '&state=foobar'\",\n \"]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view\",\n \"body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc:\",\n \"auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with(\",\n \"test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get',\",\n \"oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return\",\n \"oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status\",\n \"auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None,\",\n \"view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def\",\n \"exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code'\",\n \"== { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client,\",\n \"from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest from pyramid import\",\n \"oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller,\",\n \"pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc\",\n \"as exc: controller.post() assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method =\",\n \"test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error'] ==\",\n \"name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture\",\n \"does not exist or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token):\",\n \"pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config):\",\n \"'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body\",\n \"views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200)\",\n \"pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'}\",\n \"exc.value.type == 'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_validates_token(self, pyramid_request,\",\n \"result = views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context =\",\n \"OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime import utc_iso8601\",\n \"= ({}, body, 200) assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider):\",\n \"== {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config,\",\n \"@pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc\",\n \"controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user,\",\n \"pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\\\ '&response_type=code' + \\\\ '&state=foobar' +\",\n \"svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc:\",\n \"result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type') result =\",\n \"token is missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request)\",\n \"assert 'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result\",\n \"== {} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({},\",\n \"pyramid import httpexceptions from h._compat import urlparse from h.exceptions import OAuthTokenError from h.models.auth_client\",\n \"controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest)\",\n \"test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request)\",\n \"= ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self,\",\n \"svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method,\",\n \"assert 'Bearer token is missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token =\",\n \"pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result\",\n \"pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid: return user user_svc.fetch.side_effect = fake_fetch return\",\n \"token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert result\",\n \"pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response == {}\",\n \"headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.get_web_message() assert\",\n \"exist or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token =\",\n \"view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self,\",\n \"h.services.user import user_service_factory from h.util.datetime import utc_iso8601 from h.views import api_auth as views\",\n \"'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token')\",\n \"response = controller.get_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar',\",\n \"oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body =\",\n \"@pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID':\",\n \"@pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request,\",\n \"['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True view\",\n \"urlparse from h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory\",\n \"= views.api_token_error(context, pyramid_request) assert 'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request): context =\",\n \"@pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc\",\n \"pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError)\",\n \"{ 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username,\",\n \"= mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url =\",\n \"= (headers, None, 302) response = controller.post_web_message() assert response['state'] is None @pytest.fixture def\",\n \"def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type\",\n \"pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with\",\n \"def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\\\ '&response_type=code' +\",\n \"token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def\",\n \"TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller,\",\n \"assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def\",\n \"response = controller.post() assert response == {} def test_it_raises_when_error(self, controller, oauth_provider): body =\",\n \"pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post()\",\n \"pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID':\",\n \"mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object):\",\n \"= OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def\",\n \"== { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller,\",\n \"pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True\",\n \"'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc =\",\n \"'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value\",\n \"pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response == {} def\",\n \"test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with\",\n \"pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name) view() parsed_url =\",\n \"view_name) assert view() == { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value,\",\n \"'{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token =\",\n \"as exc: view = getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path ==\",\n \"'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user,\",\n \"'1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({},\",\n \"oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest from pyramid import httpexceptions\",\n \"factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid: return user user_svc.fetch.side_effect = fake_fetch\",\n \"'Bearer token does not exist or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request,\",\n \"= (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories): return\",\n \"view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view()\",\n \"import utc_iso8601 from h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object):\",\n \"(scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302 svc.create_authorization_response.return_value\",\n \"user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid: return user user_svc.fetch.side_effect\",\n \"view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post',\",\n \"['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes,\",\n \"{'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value =\",\n \"h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime import utc_iso8601 from h.views\",\n \"True response = controller.get_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state':\",\n \"def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result =\",\n \"mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest\",\n \"class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers)\",\n \"pyramid_request): context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in\",\n \"pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert\",\n \"pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self,\",\n \"pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider):\",\n \"controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name):\",\n \"'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request)\",\n \"= True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def\",\n \"assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self,\",\n \"credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers\",\n \"pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest from pyramid\",\n \"scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with\",\n \"test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller,\",\n \"oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as\",\n \"exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token is missing' in exc.value.message\",\n \"OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description' def\",\n \"assert 'Bearer token does not exist or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self,\",\n \"@pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config,\",\n \"'/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method,\",\n \"from h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from\",\n \"OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in result def test_it_skips_description_when_empty(self,\",\n \"controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True\",\n \"= getattr(controller, view_name) view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response\",\n \"pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response == {} def test_it_raises_when_error(self,\",\n \"pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value =\",\n \"pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires\",\n \"pyramid_request): context = OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description'] ==\",\n \"response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer\",\n \"name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture\",\n \"403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert\",\n \"'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc:\",\n \"redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user')\",\n \"view_name): oauth_request.response_mode = response_mode view = getattr(controller, view_name) assert view() == { 'client_id':\",\n \"description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert\",\n \"def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description'\",\n \"= views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False}\",\n \"name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with(\",\n \"is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as\",\n \"-*- from __future__ import unicode_literals import datetime import json import mock import pytest\",\n \"def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response == {} def test_it_raises_when_error(self, controller,\",\n \"auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message'])\",\n \"test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response == {} def test_it_raises_when_error(self, controller, oauth_provider):\",\n \"view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\\\ '&response_type=code' + \\\\ '&state=foobar' + \\\\ '&scope=exploit'\",\n \"from h._compat import urlparse from h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType from\",\n \"'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc =\",\n \"pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert\",\n \"} def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)}\",\n \"['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with(\",\n \"auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)}\",\n \"pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response\",\n \"'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc =\",\n \"-*- coding: utf-8 -*- from __future__ import unicode_literals import datetime import json import\",\n \"exc: controller.post() assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST'\",\n \"user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class\",\n \"@pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)}\",\n \"import datetime import json import mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError from\",\n \"test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view = getattr(controller,\",\n \"oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302)\",\n \"from oauthlib.common import Request as OAuthRequest from pyramid import httpexceptions from h._compat import\",\n \"controller): response = controller.post() assert response == {} def test_it_raises_when_error(self, controller, oauth_provider): body\",\n \"oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body ==\",\n \"pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url,\",\n \"view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted\",\n \"h._compat import urlparse from h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token\",\n \"'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client,\",\n \"'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, }\",\n \"def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200)\",\n \"400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body == body @pytest.fixture def controller(self,\",\n \"view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!')\",\n \"response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert response ==\",\n \"token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert\",\n \"from h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name',\",\n \"view_name): auth_client.trusted = True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user},\",\n \"= controller.post_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', }\",\n \"coding: utf-8 -*- from __future__ import unicode_literals import datetime import json import mock\",\n \"OAuthRequest from pyramid import httpexceptions from h._compat import urlparse from h.exceptions import OAuthTokenError\",\n \"pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture\",\n \"oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body ==\",\n \"assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] =\",\n \"@pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context =\",\n \"getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) ==\",\n \"developer_token result = views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None,\",\n \"status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('',\",\n \"= urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']}\",\n \"= ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value =\",\n \"factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc =\",\n \"'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response = controller.get_web_message() assert\",\n \"with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request):\",\n \"'&response_type=code' + \\\\ '&state=foobar' + \\\\ '&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with(\",\n \"[pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller,\",\n \"userid == user.userid: return user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def routes(self,\",\n \"@pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10)\",\n \"'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context =\",\n \"assert response == {} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value\",\n \"'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode\",\n \"import InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest from pyramid import httpexceptions from\",\n \"{ 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client,\",\n \"controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert\",\n \"= getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message'])\",\n \"= controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request,\",\n \"'{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc,\",\n \"Request as OAuthRequest from pyramid import httpexceptions from h._compat import urlparse from h.exceptions\",\n \"= {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value\",\n \"import urlparse from h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token import\",\n \"svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class\",\n \"TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def\",\n \"'expires_at': None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request))\",\n \"authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!')\",\n \"'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self,\",\n \"pyramid_request): context = OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code ==\",\n \"auth_client.trusted = True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected\",\n \"@pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc,\",\n \"200) assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error':\",\n \"def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request) assert\",\n \"json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post() == {'access_token': 'the-access-token'} def\",\n \"view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request):\",\n \"svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider')\",\n \"not in result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context,\",\n \"controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response =\",\n \"auth_client): auth_client.trusted = True response = controller.get_web_message() assert response == { 'code': 'abcdef123456',\",\n \"return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}',\",\n \"body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post() == {'access_token':\",\n \"= mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar',\",\n \"name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError)\",\n \"'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body =\",\n \"{'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value =\",\n \"True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.post_web_message()\",\n \"parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth':\",\n \"authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response =\",\n \"def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service):\",\n \"'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None\",\n \"result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result =\",\n \"'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request):\",\n \"OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self,\",\n \"import json import mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import\",\n \"DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime import utc_iso8601 from h.views import api_auth\",\n \"test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\\\ '&response_type=code' + \\\\\",\n \"response_mode view = getattr(controller, view_name) assert view() == { 'client_id': auth_client.id, 'client_name': auth_client.name,\",\n \"unicode_literals import datetime import json import mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError\",\n \"pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc\",\n \"httpexceptions from h._compat import urlparse from h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType\",\n \"== body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers\",\n \"(headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test\",\n \"def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture\",\n \"is missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token')\",\n \"= controller.post() assert response == {} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error':\",\n \"exc: view = getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login'\",\n \"exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller,\",\n \"pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token is missing'\",\n \"utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value\",\n \"routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post()\",\n \"response_mode, view_name): oauth_request.response_mode = response_mode view = getattr(controller, view_name) assert view() == {\",\n \"= mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object):\",\n \"pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert result == {'userid':\",\n \"def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request):\",\n \"{} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body,\",\n \"def test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name',\",\n \"def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture\",\n \"controller, auth_client): auth_client.trusted = True response = controller.get_web_message() assert response == { 'code':\",\n \"pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request)\",\n \"{'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self,\",\n \"= 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc\",\n \"None, 302) response = controller.post_web_message() assert response['state'] is None @pytest.fixture def controller(self, pyramid_request):\",\n \"'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get',\",\n \"= OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description'\",\n \"test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller,\",\n \"False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return\",\n \"views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None,\",\n \"is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value\",\n \"(headers, None, 302) response = controller.post_web_message() assert response['state'] is None @pytest.fixture def controller(self,\",\n \"exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound)\",\n \"def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return\",\n \"user.userid: return user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login',\",\n \"controller, pyramid_request, view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message'])\",\n \"as OAuthRequest from pyramid import httpexceptions from h._compat import urlparse from h.exceptions import\",\n \"pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method\",\n \"pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token'\",\n \"= 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type ==\",\n \"= views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context =\",\n \"= {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers =\",\n \"'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True\",\n \"h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get',\",\n \"test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code\",\n \"oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials\",\n \"def fake_fetch(userid): if userid == user.userid: return user user_svc.fetch.side_effect = fake_fetch return user\",\n \"auth_client.trusted = True assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user')\",\n \"pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response'])\",\n \"'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token\",\n \"'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True view =\",\n \"'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted =\",\n \"== {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired':\",\n \"def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name)\",\n \"= controller.get_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', }\",\n \"def authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid\",\n \"exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)\",\n \"'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body\",\n \"= True response = controller.get_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com',\",\n \"mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def\",\n \"controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert\",\n \"response = controller.post_web_message() assert response['state'] is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer =\",\n \"== {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value =\",\n \"developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at':\",\n \"None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc,\",\n \"response = controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller,\",\n \"assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] =\",\n \"= {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.get_web_message() assert response['state']\",\n \"pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({},\",\n \"oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True)\",\n \"= 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def\",\n \"result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context, pyramid_request) assert\",\n \"if userid == user.userid: return user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def\",\n \"assert exc.value.type == 'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self,\",\n \"controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest)\",\n \"in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token\",\n \"response == {} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value =\",\n \"utf-8 -*- from __future__ import unicode_literals import datetime import json import mock import\",\n \"test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response = controller.get() expected =\",\n \"parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None,\",\n \"expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted\",\n \"'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' + \\\\ '&response_type=code'\",\n \"controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers =\",\n \"return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url,\",\n \"'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token'\",\n \"auth_client.trusted = True response = controller.get_web_message() assert response == { 'code': 'abcdef123456', 'origin':\",\n \"'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url)\",\n \"'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials)\",\n \"auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view = getattr(controller, view_name) assert\",\n \"return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self,\",\n \"'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request,\",\n \"'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller,\",\n \"== 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert\",\n \"token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert\",\n \"context = OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error\",\n \"response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self,\",\n \"def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as\",\n \"@pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as\",\n \"'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location':\",\n \"= '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message()\",\n \"with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token does\",\n \"'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers =\",\n \"pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid: return\",\n \"assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [\",\n \"expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value =\",\n \"getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def\",\n \"body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] =\",\n \"context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in result\",\n \"assert response['state'] is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None,\",\n \"controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name)\",\n \"getattr(controller, view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller,\",\n \"controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted =\",\n \"context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in result\",\n \"context = OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403\",\n \"def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self,\",\n \"} @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted =\",\n \"'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted\",\n \"return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client,\",\n \"= getattr(controller, view_name) assert view() == { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode,\",\n \"'missing_token' assert 'Bearer token does not exist or is expired' in exc.value.message def\",\n \"body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc:\",\n \"as exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self,\",\n \"def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self,\",\n \"= 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthRevocationController(pyramid_request) @pytest.fixture def\",\n \"missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc:\",\n \"'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view\",\n \"return views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}',\",\n \"assert exc.value.type == 'missing_token' assert 'Bearer token does not exist or is expired'\",\n \"= '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted =\",\n \"auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client,\",\n \"'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers\",\n \"302) response = controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self,\",\n \"oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.post_web_message() assert response['state'] is None @pytest.fixture\",\n \"return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def\",\n \"= getattr(controller, view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self,\",\n \"h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime\",\n \"TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def\",\n \"views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller,\",\n \"view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view()\",\n \"controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/')\",\n \"test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert\",\n \"test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc:\",\n \"return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self,\",\n \"pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect\",\n \"credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302 svc.create_authorization_response.return_value =\",\n \"None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config,\",\n \"assert exc.value.type == 'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_validates_token(self,\",\n \"body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers =\",\n \"auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory\",\n \"assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response\",\n \"response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url\",\n \"Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories):\",\n \"'{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True\",\n \"{'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.get_web_message() assert response['state'] is\",\n \"assert result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at':\",\n \"test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description']\",\n \"developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc\",\n \"200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None\",\n \"@pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request,\",\n \"view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name):\",\n \"view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location)\",\n \"oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def\",\n \"import Request as OAuthRequest from pyramid import httpexceptions from h._compat import urlparse from\",\n \"developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error\",\n \"factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message',\",\n \"= None status = 302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return\",\n \"controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value\",\n \"assert view() == { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state':\",\n \"'/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message',\",\n \"assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'})\",\n \"controller.post() assert exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token']\",\n \"result = views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name},\",\n \"= developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid,\",\n \"fake_fetch(userid): if userid == user.userid: return user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture\",\n \"class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view =\",\n \"@pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read',\",\n \"return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as\",\n \"exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert\",\n \"token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created),\",\n \"TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert\",\n \"test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected\",\n \"{'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request,\",\n \"def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer is None controller.get_web_message() assert\",\n \"headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.post_web_message() assert\",\n \"pyramid_request): context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in\",\n \"as exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get',\",\n \"pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert\",\n \"user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider')\",\n \"test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller):\",\n \"controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response\",\n \"auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id':\",\n \"token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client': {'id':\",\n \"pyramid_request.POST['grant_type'] = 'authorization_code' pyramid_request.POST['code'] = 'the-authz-code' pyramid_request.headers = {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture\",\n \"def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view =\",\n \"__future__ import unicode_literals import datetime import json import mock import pytest from oauthlib.oauth2\",\n \"@pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id' +\",\n \"h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider\",\n \"'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self,\",\n \"oauth_token): pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert result ==\",\n \"= 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build()\",\n \"'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode\",\n \"@pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc,\",\n \"pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user =\",\n \"controller, auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)\",\n \"pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client')\",\n \"view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect =\",\n \"urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ])\",\n \"oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client':\",\n \"body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client',\",\n \"def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request) assert\",\n \"= oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid,\",\n \"TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context, pyramid_request)\",\n \"token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError)\",\n \"test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value =\",\n \"def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name): auth_client.trusted = True view = getattr(controller,\",\n \"is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture\",\n \"pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value\",\n \"import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message'])\",\n \"import pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest from\",\n \"'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted =\",\n \"auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response\",\n \"@pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view\",\n \"def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config,\",\n \"svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc class TestDebugToken(object): def test_it_raises_error_when_token_is_missing(self,\",\n \"pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' def\",\n \"view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self, controller,\",\n \"pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials =\",\n \"def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value\",\n \"view_name) view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response = controller.post()\",\n \"oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'})\",\n \"def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view =\",\n \"'&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name',\",\n \"from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime import utc_iso8601 from\",\n \"'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token =\",\n \"'http://client.com', 'state': 'foobar', } def test_post_web_message_allows_empty_state_in_context(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers\",\n \"pyramid_request): context = OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type'\",\n \"user @pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request,\",\n \"= controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller,\",\n \"pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc):\",\n \"body, 200) assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body =\",\n \"'Bearer token is missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token'\",\n \"'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body,\",\n \"token does not exist or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service,\",\n \"'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view\",\n \"def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error']\",\n \"controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client):\",\n \"missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def\",\n \"response = controller.post_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar',\",\n \"'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid)\",\n \"is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url =\",\n \"import user_service_factory from h.util.datetime import utc_iso8601 from h.views import api_auth as views @pytest.mark.usefixtures('routes',\",\n \"== expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert response == {\",\n \"def controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return\",\n \"'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def\",\n \"from h.exceptions import OAuthTokenError from h.models.auth_client import ResponseType from h.services.auth_token import auth_token_service_factory from\",\n \"test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not\",\n \"{'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location':\",\n \"controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert\",\n \"== 'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_validates_token(self, pyramid_request, token_service):\",\n \"from h.util.datetime import utc_iso8601 from h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc')\",\n \"True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) def test_get_returns_redirect_immediately_for_trusted_clients(self,\",\n \"from pyramid import httpexceptions from h._compat import urlparse from h.exceptions import OAuthTokenError from\",\n \"pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value\",\n \"pyramid_request.auth_token = oauth_token.value token_service.fetch.return_value = oauth_token result = views.debug_token(pyramid_request) assert result == {'userid':\",\n \"assert response.location == expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert\",\n \"result = views.debug_token(pyramid_request) assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired':\",\n \"pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def\",\n \"authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view = getattr(controller, view_name) assert view()\",\n \"pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token'\",\n \"oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result\",\n \"as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token is missing' in\",\n \"return svc @pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow()\",\n \"test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name) view()\",\n \"as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class TestOAuthAuthorizeController(object): @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self,\",\n \"= datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken()\",\n \"headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302 svc.create_authorization_response.return_value = (headers,\",\n \"['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc:\",\n \"'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result =\",\n \"assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller,\",\n \"== { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username':\",\n \"user_service_factory from h.util.datetime import utc_iso8601 from h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider',\",\n \"'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self, controller, auth_client, authenticated_user, pyramid_request, view_name):\",\n \"token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request) assert result\",\n \"pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result = views.api_token_error(context,\",\n \"expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return\",\n \"test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller,\",\n \"assert response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert response\",\n \"pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self, factories):\",\n \"factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid == user.userid:\",\n \"svc @pytest.fixture def auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self,\",\n \"authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture\",\n \"getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect\",\n \"controller.get_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user')\",\n \"from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory from\",\n \"assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with\",\n \"# -*- coding: utf-8 -*- from __future__ import unicode_literals import datetime import json\",\n \"oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name',\",\n \"'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted\",\n \"pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert\",\n \"factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request):\",\n \"OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService, instance=True) scopes =\",\n \"views.api_token_error(context, pyramid_request) assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type')\",\n \"auth_client(self, factories): return factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc\",\n \"or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token = oauth_token.value\",\n \"def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider')\",\n \"view() == { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode': response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar',\",\n \"def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view =\",\n \"= mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self, factories): authclient =\",\n \"= views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error\",\n \"controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer ==\",\n \"= {'X-Test-ID': '1234'} return views.OAuthAccessTokenController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value\",\n \"\\\\ '&response_type=code' + \\\\ '&state=foobar' + \\\\ '&scope=exploit' view = getattr(controller, view_name) view()\",\n \"controller.post_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state': 'foobar', } def\",\n \"'Bearer token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with\",\n \"(None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode, view_name):\",\n \"= 'http://example.com/auth?client_id=the-client-id' + \\\\ '&response_type=code' + \\\\ '&state=foobar' + \\\\ '&scope=exploit' view =\",\n \"json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert\",\n \"from h.services.auth_token import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from\",\n \"'' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token\",\n \"h.util.datetime import utc_iso8601 from h.views import api_auth as views @pytest.mark.usefixtures('routes', 'oauth_provider', 'user_svc') class\",\n \"svc = mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state':\",\n \"= OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request) assert 'error_description' not in result def\",\n \"exc.value.body == body @pytest.fixture def controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token'\",\n \"view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller,\",\n \"controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token':\",\n \"test_it_raises_error_when_token_is_missing(self, pyramid_request): pyramid_request.auth_token = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type ==\",\n \"def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True response = controller.get_web_message() assert response ==\",\n \"'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller,\",\n \"token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token'\",\n \"assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type') result\",\n \"@pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as\",\n \"Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc,\",\n \"oauth_request.response_mode = response_mode view = getattr(controller, view_name) assert view() == { 'client_id': auth_client.id,\",\n \"import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime import\",\n \"auth_client, authenticated_user, pyramid_request): auth_client.trusted = True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert\",\n \"'{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.get_web_message() assert response['state'] is None\",\n \"import auth_token_service_factory from h.services.oauth_provider import OAuthProviderService from h.services.oauth_validator import DEFAULT_SCOPES from h.services.user import\",\n \"pyramid_request, view_name): auth_client.trusted = True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user':\",\n \"== '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'),\",\n \"InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert exc.value.description ==\",\n \"expected def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert response == { 'code':\",\n \"== {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'), ]) def\",\n \"in exc.value.message def test_it_validates_token(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-access-token' views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self,\",\n \"urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name',\",\n \"== 'missing_token' assert 'Bearer token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token\",\n \"== 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context,\",\n \"= (headers, None, 302) response = controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post',\",\n \"def test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert response == { 'code': 'abcdef123456',\",\n \"== expected @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer is\",\n \"svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def\",\n \"{'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request):\",\n \"= getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name):\",\n \"mock.create_autospec(OAuthProviderService, instance=True) scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request':\",\n \"view_name): view = getattr(controller, view_name) view() controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self,\",\n \"controller.post_web_message() assert response['state'] is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None return\",\n \"(headers, None, 302) response = controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message'])\",\n \"'error_type' def test_it_returns_error_description(self, pyramid_request): context = OAuthTokenError('error description', 'error_type') result = views.api_token_error(context, pyramid_request)\",\n \"True assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self,\",\n \"class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers)\",\n \"def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type\",\n \"= oauth_token result = views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id,\",\n \"return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message', 'error_type',\",\n \"'boom!' def test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location\",\n \"exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token does not exist or\",\n \"['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller, view_name): controller.oauth.create_authorization_response.side_effect = InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc:\",\n \"views.debug_token(pyramid_request) token_service.validate.assert_called_once_with('the-access-token') def test_it_raises_error_when_token_is_invalid(self, pyramid_request, token_service): pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with\",\n \"json import mock import pytest from oauthlib.oauth2 import InvalidRequestFatalError from oauthlib.common import Request\",\n \"pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name',\",\n \"pyramid_request.auth_token = 'the-token' token_service.validate.return_value = None with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type\",\n \"response_mode, 'response_type': auth_client.response_type.value, 'state': 'foobar', 'username': authenticated_user.username, } @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_creates_authorization_response_for_trusted_clients(self,\",\n \"pyramid_request.headers) def test_it_returns_correct_response_on_success(self, controller, oauth_provider): body = json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body,\",\n \"def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value\",\n \"= controller.post_web_message() assert response['state'] is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None\",\n \"= True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected @pytest.mark.usefixtures('authenticated_user')\",\n \"pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request):\",\n \"assert urlparse.parse_qs(parsed_url.query) == {'next': [pyramid_request.url], 'for_oauth': ['True']} @pytest.mark.parametrize('response_mode,view_name', [ (None, 'get'), ('web_message', 'get_web_message'),\",\n \"@pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST,\",\n \"views.OAuthRevocationController(pyramid_request) @pytest.fixture def oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_revocation_response']) svc.create_revocation_response.return_value = ({}, '{}', 200)\",\n \"def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result =\",\n \"mock.Mock(spec_set=auth_token_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='auth_token') return svc @pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example\",\n \"= json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post()\",\n \"controller, auth_client, authenticated_user, oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view = getattr(controller, view_name)\",\n \"'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token =\",\n \"InvalidRequestFatalError from oauthlib.common import Request as OAuthRequest from pyramid import httpexceptions from h._compat\",\n \"pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self,\",\n \"view = getattr(controller, view_name) assert view() == { 'client_id': auth_client.id, 'client_name': auth_client.name, 'response_mode':\",\n \"view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request,\",\n \"assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected =\",\n \"svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status =\",\n \"instance=True) scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request}\",\n \"with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!'\",\n \"== 'missing_token' assert 'Bearer token does not exist or is expired' in exc.value.message\",\n \"views.debug_token(pyramid_request) assert result == {'userid': oauth_token.userid, 'client': {'id': oauth_token.authclient.id, 'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created),\",\n \"'error description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request') result = views.api_token_error(context, pyramid_request)\",\n \"({}, body, 200) assert controller.post() == {'access_token': 'the-access-token'} def test_it_raises_when_error(self, controller, oauth_provider): body\",\n \"utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def token_service(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=auth_token_service_factory(None,\",\n \"None, 302) response = controller.get_web_message() assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def\",\n \"svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return pyramid_request @pytest.fixture def authenticated_user(self,\",\n \"oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as\",\n \"True headers = {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.get_web_message()\",\n \"view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client):\",\n \"assert result == {'userid': developer_token.userid, 'issued_at': utc_iso8601(developer_token.created), 'expires_at': None, 'expired': False} @pytest.fixture def\",\n \"result = views.api_token_error(context, pyramid_request) assert 'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request): context\",\n \"'http://example.com/auth?client_id=the-client-id' + \\\\ '&response_type=code' + \\\\ '&state=foobar' + \\\\ '&scope=exploit' view = getattr(controller,\",\n \"expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context\",\n \"= InvalidRequestFatalError('boom!') with pytest.raises(InvalidRequestFatalError) as exc: view = getattr(controller, view_name) view() assert exc.value.description\",\n \"['get', 'get_web_message']) def test_get_redirects_to_login_when_not_authenticated(self, controller, pyramid_request, view_name): with pytest.raises(httpexceptions.HTTPFound) as exc: view =\",\n \"assert response['state'] is None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name):\",\n \"view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert parsed_url.path == '/login' assert urlparse.parse_qs(parsed_url.query) == {'next':\",\n \"@pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if\",\n \"not exist or is expired' in exc.value.message def test_returns_debug_data_for_oauth_token(self, pyramid_request, token_service, oauth_token): pyramid_request.auth_token\",\n \"= controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def test_post_web_message_returns_expected_context(self, controller, auth_client):\",\n \"with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type == 'missing_token' assert 'Bearer token is\",\n \"OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self, pyramid_request):\",\n \"controller(self, pyramid_request): pyramid_request.method = 'POST' pyramid_request.POST['token'] = 'the-token' pyramid_request.headers = {'X-Test-ID': '1234'} return\",\n \"json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert\",\n \"description', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self,\",\n \"test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request) assert exc.value.type ==\",\n \"= factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() + datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def\",\n \"@pytest.fixture def routes(self, pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller,\",\n \"200) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.mark.usefixtures('oauth_provider') class TestOAuthRevocationController(object): def test_it_creates_revocation_response(self, pyramid_request, controller, oauth_provider):\",\n \"test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token): pyramid_request.auth_token = developer_token.value token_service.fetch.return_value = developer_token result = views.debug_token(pyramid_request)\",\n \"pyramid_request)) pyramid_config.register_service(svc, name='user') return svc @pytest.fixture def pyramid_request(self, pyramid_request): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id&response_type=code&state=foobar' return\",\n \"pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response ==\",\n \"controller, auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location == expected def\",\n \"response['state'] is None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request)\",\n \"pyramid_request) assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request): context = OAuthTokenError(None, 'invalid_request')\",\n \"datetime.timedelta(minutes=10) return factories.DeveloperToken(authclient=authclient, expires=expires) @pytest.fixture def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def\",\n \"'foobar', } @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers =\",\n \"None @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_creates_authorization_response(self, controller, pyramid_request, authenticated_user, view_name): pyramid_request.url = 'http://example.com/auth?client_id=the-client-id'\",\n \"authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def fake_fetch(userid): if userid ==\",\n \"[ (None, 'get'), ('web_message', 'get_web_message'), ]) def test_get_returns_expected_context(self, controller, auth_client, authenticated_user, oauth_request, response_mode,\",\n \"auth_client.trusted = True view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES)\",\n \"@pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc =\",\n \"{'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body = None status = 302 svc.create_authorization_response.return_value = (headers, body, status)\",\n \"test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_token_response.return_value = ({}, body, 400) with\",\n \"'error_type') result = views.api_token_error(context, pyramid_request) assert result['error_description'] == 'error description' def test_it_skips_description_when_missing(self, pyramid_request):\",\n \"({}, body, 400) with pytest.raises(httpexceptions.HTTPBadRequest) as exc: controller.post() assert exc.value.body == body @pytest.fixture\",\n \"view() assert exc.value.description == 'boom!' def test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected\",\n \"auth_client): response = controller.post_web_message() assert response == { 'code': 'abcdef123456', 'origin': 'http://client.com', 'state':\",\n \"302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def auth_client(self,\",\n \"exc: view = getattr(controller, view_name) view() assert exc.value.description == 'boom!' @pytest.mark.parametrize('view_name', ['get', 'get_web_message'])\",\n \"'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value = (scopes, credentials) headers = {'Location': '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri)} body\",\n \"from __future__ import unicode_literals import datetime import json import mock import pytest from\",\n \"assert 'Bearer token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = ''\",\n \"status = 302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture\",\n \"None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2' @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_returns_context_for_trusted_clients(self, controller, auth_client): auth_client.trusted =\",\n \"return pyramid_request @pytest.fixture def authenticated_user(self, factories, pyramid_config, user_svc): user = factories.User.build() pyramid_config.testing_securitypolicy(user.userid) def\",\n \"oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post() assert response\",\n \"= 302 svc.create_authorization_response.return_value = (headers, body, status) pyramid_config.register_service(svc, name='oauth_provider') return svc @pytest.fixture def\",\n \"pyramid_config): pyramid_config.add_route('login', '/login') @pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with(\",\n \"view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user}, scopes=DEFAULT_SCOPES) @pytest.mark.usefixtures('authenticated_user') @pytest.mark.parametrize('view_name', ['post', 'post_web_message']) def test_post_raises_for_invalid_request(self, controller,\",\n \"'&state=foobar' + \\\\ '&scope=exploit' view = getattr(controller, view_name) view() controller.oauth.create_authorization_response.assert_called_once_with( pyramid_request.url, credentials={'user': authenticated_user},\",\n \"svc @pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires = datetime.datetime.utcnow() +\",\n \"oauth_provider): controller.post() oauth_provider.create_revocation_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST, pyramid_request.headers) def test_it_returns_empty_response_on_success(self, controller): response = controller.post()\",\n \"@pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_validates_request(self, controller, pyramid_request, view_name): view = getattr(controller, view_name) view()\",\n \"} @pytest.mark.usefixtures('authenticated_user') def test_get_web_message_allows_empty_state_in_context_for_trusted_clients(self, controller, auth_client, oauth_provider): auth_client.trusted = True headers = {'Location':\",\n \"None @pytest.fixture def controller(self, pyramid_request): pyramid_request.override_renderer = None return views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def\",\n \"oauth_provider(self, pyramid_config): svc = mock.Mock(spec_set=['create_token_response']) svc.create_token_response.return_value = ({}, '{}', 200) pyramid_config.register_service(svc, name='oauth_provider') return\",\n \"'name': oauth_token.authclient.name}, 'issued_at': utc_iso8601(oauth_token.created), 'expires_at': utc_iso8601(oauth_token.expires), 'expired': oauth_token.expired} def test_returns_debug_data_for_developer_token(self, pyramid_request, token_service, developer_token):\",\n \"def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request): svc = mock.create_autospec(OAuthProviderService,\",\n \"= json.dumps({'access_token': 'the-access-token'}) oauth_provider.create_token_response.return_value = ({}, body, 200) assert controller.post() == {'access_token': 'the-access-token'}\",\n \"assert pyramid_request.response.status_code == 403 def test_it_returns_the_error(self, pyramid_request): context = OAuthTokenError('', 'error_type') result =\",\n \"views.OAuthAuthorizeController(None, pyramid_request) @pytest.fixture def oauth_request(self): return OAuthRequest('/') @pytest.fixture def oauth_provider(self, pyramid_config, auth_client, oauth_request):\",\n \"= OAuthTokenError('', 'error_type') result = views.api_token_error(context, pyramid_request) assert result['error'] == 'error_type' def test_it_returns_error_description(self,\",\n \"@pytest.mark.usefixtures('authenticated_user') def test_get_web_message_renders_template_for_trusted_clients(self, controller, auth_client): auth_client.trusted = True assert controller.request.override_renderer is None controller.get_web_message()\",\n \"pyramid_request) assert 'error_description' not in result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request')\",\n \"token is missing' in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError)\",\n \"== user.userid: return user user_svc.fetch.side_effect = fake_fetch return user @pytest.fixture def routes(self, pyramid_config):\",\n \"def test_post_redirects_to_client(self, controller, auth_client): response = controller.post() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location ==\",\n \"class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message', 'error_type', status_code=403) views.api_token_error(context,\",\n \"in exc.value.message def test_it_raises_error_when_token_is_empty(self, pyramid_request): pyramid_request.auth_token = '' with pytest.raises(OAuthTokenError) as exc: views.debug_token(pyramid_request)\",\n \"pyramid_request): auth_client.trusted = True response = controller.get() expected = '{}?code=abcdef123456&state=foobar'.format(auth_client.redirect_uri) assert response.location ==\",\n \"def test_it_raises_when_error(self, controller, oauth_provider): body = json.dumps({'error': 'invalid_request'}) oauth_provider.create_revocation_response.return_value = ({}, body, 400)\",\n \"auth_client): auth_client.trusted = True assert controller.request.override_renderer is None controller.get_web_message() assert controller.request.override_renderer == 'h:templates/oauth/authorize_web_message.html.jinja2'\",\n \"factories.AuthClient(name='Test Client', redirect_uri='http://client.com/auth/callback', response_type=ResponseType.code) @pytest.fixture def user_svc(self, pyramid_config, pyramid_request): svc = mock.Mock(spec_set=user_service_factory(None, pyramid_request))\",\n \"factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the error message', 'error_type', status_code=403)\",\n \"oauth_request, response_mode, view_name): oauth_request.response_mode = response_mode view = getattr(controller, view_name) assert view() ==\",\n \"= {'Location': '{}?code=abcdef123456'.format(auth_client.redirect_uri)} oauth_provider.create_authorization_response.return_value = (headers, None, 302) response = controller.post_web_message() assert response['state']\",\n \"scopes = ['annotation:read', 'annotation:write'] credentials = {'client_id': auth_client.id, 'state': 'foobar', 'request': oauth_request} svc.validate_authorization_request.return_value\",\n \"test_post_web_message_returns_expected_context(self, controller, auth_client): response = controller.post_web_message() assert response == { 'code': 'abcdef123456', 'origin':\",\n \"name='auth_token') return svc @pytest.fixture def oauth_token(self, factories): authclient = factories.AuthClient(name='Example Client') expires =\",\n \"import DEFAULT_SCOPES from h.services.user import user_service_factory from h.util.datetime import utc_iso8601 from h.views import\",\n \"@pytest.mark.usefixtures('oauth_provider') class TestOAuthAccessTokenController(object): def test_it_creates_token_response(self, pyramid_request, controller, oauth_provider): controller.post() oauth_provider.create_token_response.assert_called_once_with( pyramid_request.url, pyramid_request.method, pyramid_request.POST,\",\n \"def developer_token(self, factories): return factories.DeveloperToken() class TestAPITokenError(object): def test_it_sets_the_response_status_code(self, pyramid_request): context = OAuthTokenError('the\",\n \"in result def test_it_skips_description_when_empty(self, pyramid_request): context = OAuthTokenError('', 'invalid_request') result = views.api_token_error(context, pyramid_request)\",\n \"with pytest.raises(httpexceptions.HTTPFound) as exc: view = getattr(controller, view_name) view() parsed_url = urlparse.urlparse(exc.value.location) assert\"\n]","isConversational":false}}},{"rowIdx":1482,"cells":{"ngram":{"kind":"list like","value":["file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild","Arrange a project which will build only if 'a.cpp' is compiled with \"STATIC\"","if 'a.cpp' is compiled with \"STATIC\" # define. t.write(\"a.cpp\", \"\"\"\\ #ifdef STATIC int","int main() {} #endif \"\"\") # Test conditionals in target requirements. t.write(\"jamroot.jam\", \"exe","# define. t.write(\"a.cpp\", \"\"\"\\ #ifdef STATIC int main() {} #endif \"\"\") # Test","Boost Software License, Version 1.0. # (See accompanying file LICENSE_1_0.txt or copy at",": : : <link>static:<define>STATIC ; exe a : a.cpp l ; \"\"\") t.write(\"l.cpp\",",": a.cpp ; \"\"\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Regression test for a bug","# http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild t = BoostBuild.Tester() # Arrange","Conditionals inside # usage requirement were not being evaluated. t.write(\"jamroot.jam\", \"\"\" lib l","Software License, Version 1.0. # (See accompanying file LICENSE_1_0.txt or copy at #","inside # usage requirement were not being evaluated. t.write(\"jamroot.jam\", \"\"\" lib l :","Version 1.0. # (See accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) #","with \"STATIC\" # define. t.write(\"a.cpp\", \"\"\"\\ #ifdef STATIC int main() {} #endif \"\"\")","t.write(\"a.cpp\", \"\"\"\\ #ifdef STATIC int main() {} #endif \"\"\") # Test conditionals in","in target requirements. t.write(\"jamroot.jam\", \"exe a : a.cpp : <link>static:<define>STATIC ;\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\")","# Distributed under the Boost Software License, Version 1.0. # (See accompanying file","a : a.cpp : <link>static:<define>STATIC ;\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Test conditionals in","\"\"\" project : requirements <link>static:<define>STATIC ; exe a : a.cpp ; \"\"\") t.run_build_system([\"link=static\"])","BoostBuild t = BoostBuild.Tester() # Arrange a project which will build only if","which will build only if 'a.cpp' is compiled with \"STATIC\" # define. t.write(\"a.cpp\",","t.write(\"jamroot.jam\", \"exe a : a.cpp : <link>static:<define>STATIC ;\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Test","not being evaluated. t.write(\"jamroot.jam\", \"\"\" lib l : l.cpp : : : <link>static:<define>STATIC",": a.cpp : <link>static:<define>STATIC ;\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Test conditionals in project","requirement were not being evaluated. t.write(\"jamroot.jam\", \"\"\" lib l : l.cpp : :","= BoostBuild.Tester() # Arrange a project which will build only if 'a.cpp' is","t.write(\"jamroot.jam\", \"\"\" project : requirements <link>static:<define>STATIC ; exe a : a.cpp ; \"\"\")","requirements <link>static:<define>STATIC ; exe a : a.cpp ; \"\"\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") #","import BoostBuild t = BoostBuild.Tester() # Arrange a project which will build only","# Test conditionals in project requirements. t.write(\"jamroot.jam\", \"\"\" project : requirements <link>static:<define>STATIC ;","compiled with \"STATIC\" # define. t.write(\"a.cpp\", \"\"\"\\ #ifdef STATIC int main() {} #endif","t.rm(\"bin\") # Regression test for a bug found by <NAME>ani. Conditionals inside #","a bug found by <NAME>ani. Conditionals inside # usage requirement were not being","#ifdef STATIC int main() {} #endif \"\"\") # Test conditionals in target requirements.","project which will build only if 'a.cpp' is compiled with \"STATIC\" # define.","\"\"\"\\ #ifdef STATIC int main() {} #endif \"\"\") # Test conditionals in target","Distributed under the Boost Software License, Version 1.0. # (See accompanying file LICENSE_1_0.txt","is compiled with \"STATIC\" # define. t.write(\"a.cpp\", \"\"\"\\ #ifdef STATIC int main() {}","# Copyright 2003 <NAME> # Copyright 2002, 2003, 2004 <NAME> # Distributed under","for a bug found by <NAME>ani. Conditionals inside # usage requirement were not","were not being evaluated. t.write(\"jamroot.jam\", \"\"\" lib l : l.cpp : : :","<link>static:<define>STATIC ; exe a : a.cpp ; \"\"\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Regression","Regression test for a bug found by <NAME>ani. Conditionals inside # usage requirement","t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Regression test for a bug found by <NAME>ani. Conditionals inside","lib l : l.cpp : : : <link>static:<define>STATIC ; exe a : a.cpp","# (See accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional","Test conditionals in target requirements. t.write(\"jamroot.jam\", \"exe a : a.cpp : <link>static:<define>STATIC ;\")","LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild t","by <NAME>ani. Conditionals inside # usage requirement were not being evaluated. t.write(\"jamroot.jam\", \"\"\"","main() {} #endif \"\"\") # Test conditionals in target requirements. t.write(\"jamroot.jam\", \"exe a",": l.cpp : : : <link>static:<define>STATIC ; exe a : a.cpp l ;","in project requirements. t.write(\"jamroot.jam\", \"\"\" project : requirements <link>static:<define>STATIC ; exe a :","conditional properties. import BoostBuild t = BoostBuild.Tester() # Arrange a project which will","l : l.cpp : : : <link>static:<define>STATIC ; exe a : a.cpp l","a project which will build only if 'a.cpp' is compiled with \"STATIC\" #","\"exe a : a.cpp : <link>static:<define>STATIC ;\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Test conditionals","(See accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties.","Test conditionals in project requirements. t.write(\"jamroot.jam\", \"\"\" project : requirements <link>static:<define>STATIC ; exe","STATIC int main() {} #endif \"\"\") # Test conditionals in target requirements. t.write(\"jamroot.jam\",","<NAME> # Copyright 2002, 2003, 2004 <NAME> # Distributed under the Boost Software",": requirements <link>static:<define>STATIC ; exe a : a.cpp ; \"\"\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\")","usage requirement were not being evaluated. t.write(\"jamroot.jam\", \"\"\" lib l : l.cpp :","a.cpp : <link>static:<define>STATIC ;\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Test conditionals in project requirements.","# Copyright 2002, 2003, 2004 <NAME> # Distributed under the Boost Software License,","; exe a : a.cpp l ; \"\"\") t.write(\"l.cpp\", \"int i;\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\")","# Test conditional properties. import BoostBuild t = BoostBuild.Tester() # Arrange a project","# Regression test for a bug found by <NAME>ani. Conditionals inside # usage","conditionals in target requirements. t.write(\"jamroot.jam\", \"exe a : a.cpp : <link>static:<define>STATIC ;\") t.run_build_system([\"link=static\"])","'a.cpp' is compiled with \"STATIC\" # define. t.write(\"a.cpp\", \"\"\"\\ #ifdef STATIC int main()","{} #endif \"\"\") # Test conditionals in target requirements. t.write(\"jamroot.jam\", \"exe a :","requirements. t.write(\"jamroot.jam\", \"\"\" project : requirements <link>static:<define>STATIC ; exe a : a.cpp ;","bug found by <NAME>ani. Conditionals inside # usage requirement were not being evaluated.","t.rm(\"bin\") # Test conditionals in project requirements. t.write(\"jamroot.jam\", \"\"\" project : requirements <link>static:<define>STATIC","#!/usr/bin/python # Copyright 2003 <NAME> # Copyright 2002, 2003, 2004 <NAME> # Distributed","the Boost Software License, Version 1.0. # (See accompanying file LICENSE_1_0.txt or copy","; exe a : a.cpp ; \"\"\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Regression test","# usage requirement were not being evaluated. t.write(\"jamroot.jam\", \"\"\" lib l : l.cpp","accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import","License, Version 1.0. # (See accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt)","#endif \"\"\") # Test conditionals in target requirements. t.write(\"jamroot.jam\", \"exe a : a.cpp","<NAME>ani. Conditionals inside # usage requirement were not being evaluated. t.write(\"jamroot.jam\", \"\"\" lib","evaluated. t.write(\"jamroot.jam\", \"\"\" lib l : l.cpp : : : <link>static:<define>STATIC ; exe","being evaluated. t.write(\"jamroot.jam\", \"\"\" lib l : l.cpp : : : <link>static:<define>STATIC ;","l.cpp : : : <link>static:<define>STATIC ; exe a : a.cpp l ; \"\"\")","2004 <NAME> # Distributed under the Boost Software License, Version 1.0. # (See","Test conditional properties. import BoostBuild t = BoostBuild.Tester() # Arrange a project which","exe a : a.cpp l ; \"\"\") t.write(\"l.cpp\", \"int i;\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.cleanup()","copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild t = BoostBuild.Tester()","test for a bug found by <NAME>ani. Conditionals inside # usage requirement were","2003, 2004 <NAME> # Distributed under the Boost Software License, Version 1.0. #","project requirements. t.write(\"jamroot.jam\", \"\"\" project : requirements <link>static:<define>STATIC ; exe a : a.cpp","; \"\"\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Regression test for a bug found by","conditionals in project requirements. t.write(\"jamroot.jam\", \"\"\" project : requirements <link>static:<define>STATIC ; exe a","t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Regression test for a bug found by <NAME>ani. Conditionals","\"STATIC\" # define. t.write(\"a.cpp\", \"\"\"\\ #ifdef STATIC int main() {} #endif \"\"\") #","<NAME> # Distributed under the Boost Software License, Version 1.0. # (See accompanying","build only if 'a.cpp' is compiled with \"STATIC\" # define. t.write(\"a.cpp\", \"\"\"\\ #ifdef","\"\"\" lib l : l.cpp : : : <link>static:<define>STATIC ; exe a :","found by <NAME>ani. Conditionals inside # usage requirement were not being evaluated. t.write(\"jamroot.jam\",","will build only if 'a.cpp' is compiled with \"STATIC\" # define. t.write(\"a.cpp\", \"\"\"\\",": <link>static:<define>STATIC ;\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Test conditionals in project requirements. t.write(\"jamroot.jam\",","t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Test conditionals in project requirements. t.write(\"jamroot.jam\", \"\"\" project : requirements","t = BoostBuild.Tester() # Arrange a project which will build only if 'a.cpp'","under the Boost Software License, Version 1.0. # (See accompanying file LICENSE_1_0.txt or","2002, 2003, 2004 <NAME> # Distributed under the Boost Software License, Version 1.0.","properties. import BoostBuild t = BoostBuild.Tester() # Arrange a project which will build","<filename>tools/build/v2/test/conditionals.py #!/usr/bin/python # Copyright 2003 <NAME> # Copyright 2002, 2003, 2004 <NAME> #","only if 'a.cpp' is compiled with \"STATIC\" # define. t.write(\"a.cpp\", \"\"\"\\ #ifdef STATIC","requirements. t.write(\"jamroot.jam\", \"exe a : a.cpp : <link>static:<define>STATIC ;\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") #",": <link>static:<define>STATIC ; exe a : a.cpp l ; \"\"\") t.write(\"l.cpp\", \"int i;\")","http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild t = BoostBuild.Tester() # Arrange a","at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild t = BoostBuild.Tester() #","<link>static:<define>STATIC ; exe a : a.cpp l ; \"\"\") t.write(\"l.cpp\", \"int i;\") t.run_build_system([\"link=static\"])","\"\"\") # Test conditionals in target requirements. t.write(\"jamroot.jam\", \"exe a : a.cpp :","<link>static:<define>STATIC ;\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Test conditionals in project requirements. t.write(\"jamroot.jam\", \"\"\"","# Arrange a project which will build only if 'a.cpp' is compiled with","project : requirements <link>static:<define>STATIC ; exe a : a.cpp ; \"\"\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\")","\"\"\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Regression test for a bug found by <NAME>ani.","Copyright 2002, 2003, 2004 <NAME> # Distributed under the Boost Software License, Version","t.write(\"jamroot.jam\", \"\"\" lib l : l.cpp : : : <link>static:<define>STATIC ; exe a","BoostBuild.Tester() # Arrange a project which will build only if 'a.cpp' is compiled",": : <link>static:<define>STATIC ; exe a : a.cpp l ; \"\"\") t.write(\"l.cpp\", \"int","or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild t =",";\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Test conditionals in project requirements. t.write(\"jamroot.jam\", \"\"\" project","exe a : a.cpp ; \"\"\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Regression test for","a : a.cpp ; \"\"\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Regression test for a","t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Test conditionals in project requirements. t.write(\"jamroot.jam\", \"\"\" project :","2003 <NAME> # Copyright 2002, 2003, 2004 <NAME> # Distributed under the Boost","Copyright 2003 <NAME> # Copyright 2002, 2003, 2004 <NAME> # Distributed under the","1.0. # (See accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test","# Test conditionals in target requirements. t.write(\"jamroot.jam\", \"exe a : a.cpp : <link>static:<define>STATIC","define. t.write(\"a.cpp\", \"\"\"\\ #ifdef STATIC int main() {} #endif \"\"\") # Test conditionals","a.cpp ; \"\"\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\") # Regression test for a bug found","target requirements. t.write(\"jamroot.jam\", \"exe a : a.cpp : <link>static:<define>STATIC ;\") t.run_build_system([\"link=static\"]) t.expect_addition(\"bin/$toolset/debug/link-static/a.exe\") t.rm(\"bin\")"],"string":"[\n \"file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild\",\n \"Arrange a project which will build only if 'a.cpp' is compiled with \\\"STATIC\\\"\",\n \"if 'a.cpp' is compiled with \\\"STATIC\\\" # define. t.write(\\\"a.cpp\\\", \\\"\\\"\\\"\\\\ #ifdef STATIC int\",\n \"int main() {} #endif \\\"\\\"\\\") # Test conditionals in target requirements. t.write(\\\"jamroot.jam\\\", \\\"exe\",\n \"# define. t.write(\\\"a.cpp\\\", \\\"\\\"\\\"\\\\ #ifdef STATIC int main() {} #endif \\\"\\\"\\\") # Test\",\n \"Boost Software License, Version 1.0. # (See accompanying file LICENSE_1_0.txt or copy at\",\n \": : : <link>static:<define>STATIC ; exe a : a.cpp l ; \\\"\\\"\\\") t.write(\\\"l.cpp\\\",\",\n \": a.cpp ; \\\"\\\"\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Regression test for a bug\",\n \"# http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild t = BoostBuild.Tester() # Arrange\",\n \"Conditionals inside # usage requirement were not being evaluated. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" lib l\",\n \"Software License, Version 1.0. # (See accompanying file LICENSE_1_0.txt or copy at #\",\n \"inside # usage requirement were not being evaluated. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" lib l :\",\n \"Version 1.0. # (See accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) #\",\n \"with \\\"STATIC\\\" # define. t.write(\\\"a.cpp\\\", \\\"\\\"\\\"\\\\ #ifdef STATIC int main() {} #endif \\\"\\\"\\\")\",\n \"t.write(\\\"a.cpp\\\", \\\"\\\"\\\"\\\\ #ifdef STATIC int main() {} #endif \\\"\\\"\\\") # Test conditionals in\",\n \"in target requirements. t.write(\\\"jamroot.jam\\\", \\\"exe a : a.cpp : <link>static:<define>STATIC ;\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\")\",\n \"# Distributed under the Boost Software License, Version 1.0. # (See accompanying file\",\n \"a : a.cpp : <link>static:<define>STATIC ;\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Test conditionals in\",\n \"\\\"\\\"\\\" project : requirements <link>static:<define>STATIC ; exe a : a.cpp ; \\\"\\\"\\\") t.run_build_system([\\\"link=static\\\"])\",\n \"BoostBuild t = BoostBuild.Tester() # Arrange a project which will build only if\",\n \"which will build only if 'a.cpp' is compiled with \\\"STATIC\\\" # define. t.write(\\\"a.cpp\\\",\",\n \"t.write(\\\"jamroot.jam\\\", \\\"exe a : a.cpp : <link>static:<define>STATIC ;\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Test\",\n \"not being evaluated. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" lib l : l.cpp : : : <link>static:<define>STATIC\",\n \": a.cpp : <link>static:<define>STATIC ;\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Test conditionals in project\",\n \"requirement were not being evaluated. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" lib l : l.cpp : :\",\n \"= BoostBuild.Tester() # Arrange a project which will build only if 'a.cpp' is\",\n \"t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" project : requirements <link>static:<define>STATIC ; exe a : a.cpp ; \\\"\\\"\\\")\",\n \"requirements <link>static:<define>STATIC ; exe a : a.cpp ; \\\"\\\"\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") #\",\n \"import BoostBuild t = BoostBuild.Tester() # Arrange a project which will build only\",\n \"# Test conditionals in project requirements. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" project : requirements <link>static:<define>STATIC ;\",\n \"compiled with \\\"STATIC\\\" # define. t.write(\\\"a.cpp\\\", \\\"\\\"\\\"\\\\ #ifdef STATIC int main() {} #endif\",\n \"t.rm(\\\"bin\\\") # Regression test for a bug found by <NAME>ani. Conditionals inside #\",\n \"a bug found by <NAME>ani. Conditionals inside # usage requirement were not being\",\n \"#ifdef STATIC int main() {} #endif \\\"\\\"\\\") # Test conditionals in target requirements.\",\n \"project which will build only if 'a.cpp' is compiled with \\\"STATIC\\\" # define.\",\n \"\\\"\\\"\\\"\\\\ #ifdef STATIC int main() {} #endif \\\"\\\"\\\") # Test conditionals in target\",\n \"Distributed under the Boost Software License, Version 1.0. # (See accompanying file LICENSE_1_0.txt\",\n \"is compiled with \\\"STATIC\\\" # define. t.write(\\\"a.cpp\\\", \\\"\\\"\\\"\\\\ #ifdef STATIC int main() {}\",\n \"# Copyright 2003 <NAME> # Copyright 2002, 2003, 2004 <NAME> # Distributed under\",\n \"for a bug found by <NAME>ani. Conditionals inside # usage requirement were not\",\n \"were not being evaluated. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" lib l : l.cpp : : :\",\n \"<link>static:<define>STATIC ; exe a : a.cpp ; \\\"\\\"\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Regression\",\n \"Regression test for a bug found by <NAME>ani. Conditionals inside # usage requirement\",\n \"t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Regression test for a bug found by <NAME>ani. Conditionals inside\",\n \"lib l : l.cpp : : : <link>static:<define>STATIC ; exe a : a.cpp\",\n \"# (See accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional\",\n \"Test conditionals in target requirements. t.write(\\\"jamroot.jam\\\", \\\"exe a : a.cpp : <link>static:<define>STATIC ;\\\")\",\n \"LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild t\",\n \"by <NAME>ani. Conditionals inside # usage requirement were not being evaluated. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\"\",\n \"main() {} #endif \\\"\\\"\\\") # Test conditionals in target requirements. t.write(\\\"jamroot.jam\\\", \\\"exe a\",\n \": l.cpp : : : <link>static:<define>STATIC ; exe a : a.cpp l ;\",\n \"in project requirements. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" project : requirements <link>static:<define>STATIC ; exe a :\",\n \"conditional properties. import BoostBuild t = BoostBuild.Tester() # Arrange a project which will\",\n \"l : l.cpp : : : <link>static:<define>STATIC ; exe a : a.cpp l\",\n \"a project which will build only if 'a.cpp' is compiled with \\\"STATIC\\\" #\",\n \"\\\"exe a : a.cpp : <link>static:<define>STATIC ;\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Test conditionals\",\n \"(See accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties.\",\n \"Test conditionals in project requirements. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" project : requirements <link>static:<define>STATIC ; exe\",\n \"STATIC int main() {} #endif \\\"\\\"\\\") # Test conditionals in target requirements. t.write(\\\"jamroot.jam\\\",\",\n \"<NAME> # Copyright 2002, 2003, 2004 <NAME> # Distributed under the Boost Software\",\n \": requirements <link>static:<define>STATIC ; exe a : a.cpp ; \\\"\\\"\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\")\",\n \"usage requirement were not being evaluated. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" lib l : l.cpp :\",\n \"a.cpp : <link>static:<define>STATIC ;\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Test conditionals in project requirements.\",\n \"# Copyright 2002, 2003, 2004 <NAME> # Distributed under the Boost Software License,\",\n \"; exe a : a.cpp l ; \\\"\\\"\\\") t.write(\\\"l.cpp\\\", \\\"int i;\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\")\",\n \"# Test conditional properties. import BoostBuild t = BoostBuild.Tester() # Arrange a project\",\n \"# Regression test for a bug found by <NAME>ani. Conditionals inside # usage\",\n \"conditionals in target requirements. t.write(\\\"jamroot.jam\\\", \\\"exe a : a.cpp : <link>static:<define>STATIC ;\\\") t.run_build_system([\\\"link=static\\\"])\",\n \"'a.cpp' is compiled with \\\"STATIC\\\" # define. t.write(\\\"a.cpp\\\", \\\"\\\"\\\"\\\\ #ifdef STATIC int main()\",\n \"{} #endif \\\"\\\"\\\") # Test conditionals in target requirements. t.write(\\\"jamroot.jam\\\", \\\"exe a :\",\n \"requirements. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" project : requirements <link>static:<define>STATIC ; exe a : a.cpp ;\",\n \"bug found by <NAME>ani. Conditionals inside # usage requirement were not being evaluated.\",\n \"t.rm(\\\"bin\\\") # Test conditionals in project requirements. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" project : requirements <link>static:<define>STATIC\",\n \"#!/usr/bin/python # Copyright 2003 <NAME> # Copyright 2002, 2003, 2004 <NAME> # Distributed\",\n \"the Boost Software License, Version 1.0. # (See accompanying file LICENSE_1_0.txt or copy\",\n \"; exe a : a.cpp ; \\\"\\\"\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Regression test\",\n \"# usage requirement were not being evaluated. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" lib l : l.cpp\",\n \"accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import\",\n \"License, Version 1.0. # (See accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt)\",\n \"#endif \\\"\\\"\\\") # Test conditionals in target requirements. t.write(\\\"jamroot.jam\\\", \\\"exe a : a.cpp\",\n \"<NAME>ani. Conditionals inside # usage requirement were not being evaluated. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" lib\",\n \"evaluated. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" lib l : l.cpp : : : <link>static:<define>STATIC ; exe\",\n \"being evaluated. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" lib l : l.cpp : : : <link>static:<define>STATIC ;\",\n \"l.cpp : : : <link>static:<define>STATIC ; exe a : a.cpp l ; \\\"\\\"\\\")\",\n \"2004 <NAME> # Distributed under the Boost Software License, Version 1.0. # (See\",\n \"Test conditional properties. import BoostBuild t = BoostBuild.Tester() # Arrange a project which\",\n \"exe a : a.cpp l ; \\\"\\\"\\\") t.write(\\\"l.cpp\\\", \\\"int i;\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.cleanup()\",\n \"copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild t = BoostBuild.Tester()\",\n \"test for a bug found by <NAME>ani. Conditionals inside # usage requirement were\",\n \"2003, 2004 <NAME> # Distributed under the Boost Software License, Version 1.0. #\",\n \"project requirements. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" project : requirements <link>static:<define>STATIC ; exe a : a.cpp\",\n \"; \\\"\\\"\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Regression test for a bug found by\",\n \"conditionals in project requirements. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" project : requirements <link>static:<define>STATIC ; exe a\",\n \"t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Regression test for a bug found by <NAME>ani. Conditionals\",\n \"\\\"STATIC\\\" # define. t.write(\\\"a.cpp\\\", \\\"\\\"\\\"\\\\ #ifdef STATIC int main() {} #endif \\\"\\\"\\\") #\",\n \"<NAME> # Distributed under the Boost Software License, Version 1.0. # (See accompanying\",\n \"build only if 'a.cpp' is compiled with \\\"STATIC\\\" # define. t.write(\\\"a.cpp\\\", \\\"\\\"\\\"\\\\ #ifdef\",\n \"\\\"\\\"\\\" lib l : l.cpp : : : <link>static:<define>STATIC ; exe a :\",\n \"found by <NAME>ani. Conditionals inside # usage requirement were not being evaluated. t.write(\\\"jamroot.jam\\\",\",\n \"will build only if 'a.cpp' is compiled with \\\"STATIC\\\" # define. t.write(\\\"a.cpp\\\", \\\"\\\"\\\"\\\\\",\n \": <link>static:<define>STATIC ;\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Test conditionals in project requirements. t.write(\\\"jamroot.jam\\\",\",\n \"t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Test conditionals in project requirements. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" project : requirements\",\n \"t = BoostBuild.Tester() # Arrange a project which will build only if 'a.cpp'\",\n \"under the Boost Software License, Version 1.0. # (See accompanying file LICENSE_1_0.txt or\",\n \"2002, 2003, 2004 <NAME> # Distributed under the Boost Software License, Version 1.0.\",\n \"properties. import BoostBuild t = BoostBuild.Tester() # Arrange a project which will build\",\n \"<filename>tools/build/v2/test/conditionals.py #!/usr/bin/python # Copyright 2003 <NAME> # Copyright 2002, 2003, 2004 <NAME> #\",\n \"only if 'a.cpp' is compiled with \\\"STATIC\\\" # define. t.write(\\\"a.cpp\\\", \\\"\\\"\\\"\\\\ #ifdef STATIC\",\n \"requirements. t.write(\\\"jamroot.jam\\\", \\\"exe a : a.cpp : <link>static:<define>STATIC ;\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") #\",\n \": <link>static:<define>STATIC ; exe a : a.cpp l ; \\\"\\\"\\\") t.write(\\\"l.cpp\\\", \\\"int i;\\\")\",\n \"http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild t = BoostBuild.Tester() # Arrange a\",\n \"at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild t = BoostBuild.Tester() #\",\n \"<link>static:<define>STATIC ; exe a : a.cpp l ; \\\"\\\"\\\") t.write(\\\"l.cpp\\\", \\\"int i;\\\") t.run_build_system([\\\"link=static\\\"])\",\n \"\\\"\\\"\\\") # Test conditionals in target requirements. t.write(\\\"jamroot.jam\\\", \\\"exe a : a.cpp :\",\n \"<link>static:<define>STATIC ;\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Test conditionals in project requirements. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\"\",\n \"# Arrange a project which will build only if 'a.cpp' is compiled with\",\n \"project : requirements <link>static:<define>STATIC ; exe a : a.cpp ; \\\"\\\"\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\")\",\n \"\\\"\\\"\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Regression test for a bug found by <NAME>ani.\",\n \"Copyright 2002, 2003, 2004 <NAME> # Distributed under the Boost Software License, Version\",\n \"t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" lib l : l.cpp : : : <link>static:<define>STATIC ; exe a\",\n \"BoostBuild.Tester() # Arrange a project which will build only if 'a.cpp' is compiled\",\n \": : <link>static:<define>STATIC ; exe a : a.cpp l ; \\\"\\\"\\\") t.write(\\\"l.cpp\\\", \\\"int\",\n \"or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild t =\",\n \";\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Test conditionals in project requirements. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" project\",\n \"exe a : a.cpp ; \\\"\\\"\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Regression test for\",\n \"a : a.cpp ; \\\"\\\"\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Regression test for a\",\n \"t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Test conditionals in project requirements. t.write(\\\"jamroot.jam\\\", \\\"\\\"\\\" project :\",\n \"2003 <NAME> # Copyright 2002, 2003, 2004 <NAME> # Distributed under the Boost\",\n \"Copyright 2003 <NAME> # Copyright 2002, 2003, 2004 <NAME> # Distributed under the\",\n \"1.0. # (See accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test\",\n \"# Test conditionals in target requirements. t.write(\\\"jamroot.jam\\\", \\\"exe a : a.cpp : <link>static:<define>STATIC\",\n \"define. t.write(\\\"a.cpp\\\", \\\"\\\"\\\"\\\\ #ifdef STATIC int main() {} #endif \\\"\\\"\\\") # Test conditionals\",\n \"a.cpp ; \\\"\\\"\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\") # Regression test for a bug found\",\n \"target requirements. t.write(\\\"jamroot.jam\\\", \\\"exe a : a.cpp : <link>static:<define>STATIC ;\\\") t.run_build_system([\\\"link=static\\\"]) t.expect_addition(\\\"bin/$toolset/debug/link-static/a.exe\\\") t.rm(\\\"bin\\\")\"\n]","isConversational":false}}},{"rowIdx":1483,"cells":{"ngram":{"kind":"list like","value":["<gh_stars>1-10 from setuptools_rust_starter import PythonClass, ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10)","= PythonClass(value=10) assert py_class.value == 10 def test_example_class() -> None: example = ExampleClass(value=11)","PythonClass, ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value == 10","import PythonClass, ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value ==","test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value == 10 def test_example_class() ->","from setuptools_rust_starter import PythonClass, ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10) assert","assert py_class.value == 10 def test_example_class() -> None: example = ExampleClass(value=11) assert example.value","== 10 def test_example_class() -> None: example = ExampleClass(value=11) assert example.value == 11","py_class = PythonClass(value=10) assert py_class.value == 10 def test_example_class() -> None: example =","py_class.value == 10 def test_example_class() -> None: example = ExampleClass(value=11) assert example.value ==","PythonClass(value=10) assert py_class.value == 10 def test_example_class() -> None: example = ExampleClass(value=11) assert","ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value == 10 def","def test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value == 10 def test_example_class()","setuptools_rust_starter import PythonClass, ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value","-> None: py_class = PythonClass(value=10) assert py_class.value == 10 def test_example_class() -> None:","None: py_class = PythonClass(value=10) assert py_class.value == 10 def test_example_class() -> None: example"],"string":"[\n \"<gh_stars>1-10 from setuptools_rust_starter import PythonClass, ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10)\",\n \"= PythonClass(value=10) assert py_class.value == 10 def test_example_class() -> None: example = ExampleClass(value=11)\",\n \"PythonClass, ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value == 10\",\n \"import PythonClass, ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value ==\",\n \"test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value == 10 def test_example_class() ->\",\n \"from setuptools_rust_starter import PythonClass, ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10) assert\",\n \"assert py_class.value == 10 def test_example_class() -> None: example = ExampleClass(value=11) assert example.value\",\n \"== 10 def test_example_class() -> None: example = ExampleClass(value=11) assert example.value == 11\",\n \"py_class = PythonClass(value=10) assert py_class.value == 10 def test_example_class() -> None: example =\",\n \"py_class.value == 10 def test_example_class() -> None: example = ExampleClass(value=11) assert example.value ==\",\n \"PythonClass(value=10) assert py_class.value == 10 def test_example_class() -> None: example = ExampleClass(value=11) assert\",\n \"ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value == 10 def\",\n \"def test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value == 10 def test_example_class()\",\n \"setuptools_rust_starter import PythonClass, ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10) assert py_class.value\",\n \"-> None: py_class = PythonClass(value=10) assert py_class.value == 10 def test_example_class() -> None:\",\n \"None: py_class = PythonClass(value=10) assert py_class.value == 10 def test_example_class() -> None: example\"\n]","isConversational":false}}},{"rowIdx":1484,"cells":{"ngram":{"kind":"list like","value":["self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data: List","login_params if \"uid\" in d][ 0 ].replace(\"uid=\", \"\") self._login_token = [d for d","next_page_variable = personal_blog[\"verifyCreatedAt\"] if self._response_data[\"d\"][\"total\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\"获取个人博客数据成功!\")","错误原因: {err}\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\"token\"] self._login_uid","!= 0: total_pages += 1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\"d\"][\"entryList\"] if len(entry_list)","def _check_username(self) -> Optional[Tuple[str, Dict]]: \"\"\" 解析用户名 :return: 结果 \"\"\" phone_login = check_is_phone_number(data=self._login_username)","test_json_response[\"s\"] == 1: logger.info(f\"当前掘金账号为: {self._login_username}, 状态: 已登录\") return True else: logger.error(f\"当前掘金账号登录状态: 已退出!\") return","self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\"token\"] self._login_uid = self._response_data[\"userId\"]","params = self.get_data(spider_name=f\"{self._spider_name}:params\") if params is None: return False test_user_url: str = f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\"","= check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\"password\": self._login_password} if phone_login is","重要参数持久化 params: str = f\"?src=web&uid={self._login_uid}\" f\"&token={self._login_token}\" f\"&device_id={self._login_client_id}\" f\"¤t_uid={self._login_uid}\" self.set_data(spider_name=f\"{self._spider_name}:params\", data=params) # 个人数据 username","username is illegal!\") if phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\"{self._main_url}/phoneNumber\", login_data if","200 or check_is_json(test_response.content.decode()) is not True ): logger.error(f\"当前掘金账号登录状态: 已退出!\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response","followee = self._response_data[\"user\"][\"followeesCount\"] follower = self._response_data[\"user\"][\"followersCount\"] like_blogs = self._response_data[\"user\"][\"collectedEntriesCount\"] personal_data: Dict = {","login_params if \"device_id\" in d ][0].replace(\"device_id=\", \"\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as","CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\"登录失败!\")","\"blogViewers\": personal_blog[\"viewsCount\"], \"blogCreateTime\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\"verifyCreatedAt\"] if self._response_data[\"d\"][\"total\"] > 20:","= { \"src\": \"web\", \"uid\": self._login_uid, \"device_id\": self._login_client_id, \"token\": self._login_token, \"targetUid\": self._login_uid, \"type\":",") raise ParseDataException() def _test_cookies(self, cookies: Optional[str] = None) -> bool: params =","url=test_user_url, headers=test_request_headers ) if ( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not True","List = [] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self)","import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5,","f\"&{data[0]}={data[1]}\" blogs_url: str = f\"{self._blogs_url}{url_params}\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \"\":","self._response_data is not None and self._response_data[\"m\"] == \"success\" ): logger.info(f\"当前正在获取第{page_no + 1}页的数据!\") if","f\"{self._blogs_url}{url_params}\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data = response.json() if","spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\"登录失败!\") raise LoginException() else: get_result: str","[ d for d in login_params if \"device_id\" in d ][0].replace(\"device_id=\", \"\") self.parse_data_with_method(","utils.exception_utils import LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import","\"blogTitle\": entry_data[\"title\"], \"blogHref\": entry_data[\"originalUrl\"], \"blogViewers\": entry_data[\"viewsCount\"], \"blogCreateTime\": datetime_str_change_fmt( time_str=entry_data[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ), } self._like_blogs_data.append(blog_data)","= \"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\" self._like_blogs_url = \"https://user-like-wrapper-ms.juejin.im/v1/user\" self._task_id = task_id self._login_username = username self._login_password =","in login_params if \"token\" in d][ 0 ].replace(\"token=\", \"\") self._login_client_id = [ d","\"token\": self._login_token, \"targetUid\": self._login_uid, \"type\": \"post\", \"limit\": \"20\", \"order\": \"createdAt\", } if next_params","response.content.decode() != \"\": self._response_data = response.json() if self._response_data is not None and self._response_data[\"m\"]","self._response_data = response.json() if self._response_data is not None and self._response_data[\"m\"] == \"ok\": next_page_variable","20 if rest_count != 0: total_pages += 1 self._like_blogs_total_page = total_pages entry_list =","= LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str,","LoginException() def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str = f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\" self._common_headers.update( {","entry_list: if entry_data is None: continue blog_data: Dict = { \"blogId\": entry_data[\"objectId\"], \"blogTitle\":","return False test_json_response = test_response.json() if test_json_response[\"s\"] == 1: logger.info(f\"当前掘金账号为: {self._login_username}, 状态: 已登录\")","if email_login is not None: login_data.update(email=self._login_username) return f\"{self._main_url}/email\", login_data return None def parse_data_with_method(self,","self._login_client_id = [ d for d in login_params if \"device_id\" in d ][0].replace(\"device_id=\",","for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ) blog_data: Dict =","\"blogHref\": personal_blog[\"originalUrl\"], \"blogViewers\": personal_blog[\"viewsCount\"], \"blogCreateTime\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\"verifyCreatedAt\"] if self._response_data[\"d\"][\"total\"]","if self._response_data[\"d\"][\"total\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\"获取个人博客数据成功!\") else: logger.error(\"查询个人博客失败!\") self.update_task_status(","str = f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\" self._common_headers.update( { \"X-Juejin-Client\": str(self._login_client_id), \"X-Juejin-Src\": \"web\", \"X-Juejin-Token\": self._login_token, \"X-Juejin-Uid\": self._login_uid,","个人数据 username = self._response_data[\"user\"][\"username\"] description = self._response_data[\"user\"][\"selfDescription\"] avatar_img = self._response_data[\"user\"][\"avatarLarge\"] followee = self._response_data[\"user\"][\"followeesCount\"]","logger.info(\"获取个人点赞博客成功!\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\"查询个人点赞博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def","# logger.debug(self._like_blogs_data) logger.debug(f\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\"获取个人点赞博客成功!\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else:","= datetime_str_change_fmt( time_str=personal_blog[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ) blog_data: Dict = { \"blogId\": personal_blog[\"objectId\"], \"blogTitle\": personal_blog[\"title\"],","ParseDataException() def _test_cookies(self, cookies: Optional[str] = None) -> bool: params = self.get_data(spider_name=f\"{self._spider_name}:params\") if","total_count % 20 if rest_count != 0: total_pages += 1 self._like_blogs_total_page = total_pages","\"\"\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\"password\": self._login_password} if","str): self._main_url = \"https://juejin.im/auth/type\" self._blogs_url = \"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\" self._like_blogs_url = \"https://user-like-wrapper-ms.juejin.im/v1/user\" self._task_id = task_id","method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method ==",").to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\"登录失败!\") raise LoginException()","Optional[str] = None) -> bool: params = self.get_data(spider_name=f\"{self._spider_name}:params\") if params is None: return","import LogManager from utils.str_utils import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils","else: try: login_params = get_result.split(\"&\")[1:-1] self._login_uid = [d for d in login_params if","headers=test_request_headers ) if ( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not True ):","== 0: url_params += f\"?{data[0]}={data[1]}\" else: url_params += f\"&{data[0]}={data[1]}\" blogs_url: str = f\"{self._blogs_url}{url_params}\"","d in login_params if \"device_id\" in d ][0].replace(\"device_id=\", \"\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except","else: get_result: str = self.get_data(spider_name=f\"{self._spider_name}:params\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else:","( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not True ): logger.error(f\"当前掘金账号登录状态: 已退出!\") self._async_task.remove_async_scheduler(job_id=self._spider_name)","self._response_data[\"m\"] == \"ok\": next_page_variable = None entry_list = self._response_data[\"d\"][\"entrylist\"] if len(entry_list) > 0:","return None def parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method","self._response_data[\"d\"][\"entryList\"] if len(entry_list) > 0: for entry_data in entry_list: if entry_data is None:","= \"https://user-like-wrapper-ms.juejin.im/v1/user\" self._task_id = task_id self._login_username = username self._login_password = password self._spider_name: str","check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id: str,","{ \"blogId\": personal_blog[\"objectId\"], \"blogTitle\": personal_blog[\"title\"], \"blogHref\": personal_blog[\"originalUrl\"], \"blogViewers\": personal_blog[\"viewsCount\"], \"blogCreateTime\": blog_create_time, } self._blogs_data.append(blog_data)","[d for d in login_params if \"uid\" in d][ 0 ].replace(\"uid=\", \"\") self._login_token","= 0): like_blogs_url: str = f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\" self._common_headers.update( { \"X-Juejin-Client\": str(self._login_client_id), \"X-Juejin-Src\": \"web\", \"X-Juejin-Token\":","is not None: req_data.update(before=next_params) url_params: str = \"\" for index, data in enumerate(req_data.items()):","is None: raise ValueError(\"Your login username is illegal!\") if phone_login is not None:","response.content.decode() != \"\": logger.info(\"登录成功!\") self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies)","self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\") self.data_model.set_personal_like_blogs_data(","if rest_count != 0: total_pages += 1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\"d\"][\"entryList\"]","Optional[str] = None): req_data: dict = { \"src\": \"web\", \"uid\": self._login_uid, \"device_id\": self._login_client_id,","\"limit\": \"20\", \"order\": \"createdAt\", } if next_params is not None: req_data.update(before=next_params) url_params: str","follower, \"likeBlogs\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None):","return f\"{self._main_url}/email\", login_data return None def parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult:","def login(self): if self._login_cookies is None: login_url, login_data = self._check_username() response = self.make_request(","self._login_password} if phone_login is None and email_login is None: raise ValueError(\"Your login username","self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code != 200 or","self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\"POST\", json=login_data, ) if response.content.decode() != \"\":","from utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider):","= self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \"\"\" 解析用户名 :return: 结果 \"\"\" phone_login","} logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict =","= 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \"\"\" 解析用户名","\"\": logger.info(\"登录成功!\") self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name,","= self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data = response.json() if ( self._response_data","+ 1}页的数据!\") if page_no == 0: total_count = self._response_data[\"d\"][\"total\"] total_pages = total_count //","= None self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data: List = []","\"blogId\": entry_data[\"objectId\"], \"blogTitle\": entry_data[\"title\"], \"blogHref\": entry_data[\"originalUrl\"], \"blogViewers\": entry_data[\"viewsCount\"], \"blogCreateTime\": datetime_str_change_fmt( time_str=entry_data[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ),","Optional[str] = None self._response_data = None self._blogs_data: List = [] self._like_blogs_data: List =","utils.str_utils import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from","LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str, password:","f\"{self._main_url}/phoneNumber\", login_data if email_login is not None: login_data.update(email=self._login_username) return f\"{self._main_url}/email\", login_data return None","已退出!\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if test_json_response[\"s\"] == 1: logger.info(f\"当前掘金账号为: {self._login_username},","headers=self._common_headers, method=\"POST\", json=login_data, ) if response.content.decode() != \"\": logger.info(\"登录成功!\") self._response_data = response.json() self._login_cookies","\"X-Juejin-Uid\": self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data","Optional[str] = None self._login_token: Optional[str] = None self._login_uid: Optional[str] = None self._login_client_id: Optional[str]","password self._spider_name: str = f\"juejin:{self._login_username}\" self._login_cookies: Optional[str] = None self._login_token: Optional[str] = None","self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def","logger.error(\"查询个人点赞博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies: Optional[str] = None)",") raise LoginException() def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str = f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\"","\"https://juejin.im/auth/type\" self._blogs_url = \"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\" self._like_blogs_url = \"https://user-like-wrapper-ms.juejin.im/v1/user\" self._task_id = task_id self._login_username = username","= CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else:",") if ( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not True ): logger.error(f\"当前掘金账号登录状态:","blog_data: Dict = { \"blogId\": personal_blog[\"objectId\"], \"blogTitle\": personal_blog[\"title\"], \"blogHref\": personal_blog[\"originalUrl\"], \"blogViewers\": personal_blog[\"viewsCount\"], \"blogCreateTime\":","email_login is not None: login_data.update(email=self._login_username) return f\"{self._main_url}/email\", login_data return None def parse_data_with_method(self, method:","self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data =","self._task_id = task_id self._login_username = username self._login_password = password self._spider_name: str = f\"juejin:{self._login_username}\"","task_id self._login_username = username self._login_password = password self._spider_name: str = f\"juejin:{self._login_username}\" self._login_cookies: Optional[str]","phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\"{self._main_url}/phoneNumber\", login_data if email_login is not None:","None: raise ValueError(\"Your login username is illegal!\") if phone_login is not None: login_data.update(phoneNumber=self._login_username)","self._like_blogs_data: List = [] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def","Optional[str] = None self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None self._response_data =","> 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\"获取个人博客数据成功!\") else: logger.error(\"查询个人博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL)","\"blogHref\": entry_data[\"originalUrl\"], \"blogViewers\": entry_data[\"viewsCount\"], \"blogCreateTime\": datetime_str_change_fmt( time_str=entry_data[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ), } self._like_blogs_data.append(blog_data) page_no +=","-> Optional[Tuple[str, Dict]]: \"\"\" 解析用户名 :return: 结果 \"\"\" phone_login = check_is_phone_number(data=self._login_username) email_login =","\"\"\" 解析用户名 :return: 结果 \"\"\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict","logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\"登录失败!\") raise LoginException() else:","+= 1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\"d\"][\"entryList\"] if len(entry_list) > 0: for","datetime_str_change_fmt( time_str=personal_blog[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ) blog_data: Dict = { \"blogId\": personal_blog[\"objectId\"], \"blogTitle\": personal_blog[\"title\"], \"blogHref\":","f\"¤t_uid={self._login_uid}\" self.set_data(spider_name=f\"{self._spider_name}:params\", data=params) # 个人数据 username = self._response_data[\"user\"][\"username\"] description = self._response_data[\"user\"][\"selfDescription\"] avatar_img =","method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if","\"blogId\": personal_blog[\"objectId\"], \"blogTitle\": personal_blog[\"title\"], \"blogHref\": personal_blog[\"originalUrl\"], \"blogViewers\": personal_blog[\"viewsCount\"], \"blogCreateTime\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable","raise ValueError(\"Your login username is illegal!\") if phone_login is not None: login_data.update(phoneNumber=self._login_username) return","= self.make_request( url=login_url, headers=self._common_headers, method=\"POST\", json=login_data, ) if response.content.decode() != \"\": logger.info(\"登录成功!\") self._response_data","= total_count // 20 rest_count = total_count % 20 if rest_count != 0:","} ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data = response.json()","for entry_data in entry_list: if entry_data is None: continue blog_data: Dict = {","email_login is None: raise ValueError(\"Your login username is illegal!\") if phone_login is not","not None: login_data.update(phoneNumber=self._login_username) return f\"{self._main_url}/phoneNumber\", login_data if email_login is not None: login_data.update(email=self._login_username) return","try: login_params = get_result.split(\"&\")[1:-1] self._login_uid = [d for d in login_params if \"uid\"","if params is None: return False test_user_url: str = f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\" test_request_headers: Dict =","= [d for d in login_params if \"token\" in d][ 0 ].replace(\"token=\", \"\")","str = f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\" test_request_headers: Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers )","后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\"获取个人点赞博客成功!\")","self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\"获取个人点赞博客成功!\") # 任务末尾","= self._response_data[\"d\"][\"entrylist\"] if len(entry_list) > 0: for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt(","d][ 0 ].replace(\"uid=\", \"\") self._login_token = [d for d in login_params if \"token\"","[d for d in login_params if \"token\" in d][ 0 ].replace(\"token=\", \"\") self._login_client_id","login_params if \"token\" in d][ 0 ].replace(\"token=\", \"\") self._login_client_id = [ d for","= [] self._like_blogs_data: List = [] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies =","_test_cookies(self, cookies: Optional[str] = None) -> bool: params = self.get_data(spider_name=f\"{self._spider_name}:params\") if params is","\"\": self._response_data = response.json() if self._response_data is not None and self._response_data[\"m\"] == \"ok\":","= self._response_data[\"d\"][\"total\"] total_pages = total_count // 20 rest_count = total_count % 20 if","cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\"登录失败!\") raise LoginException() else: get_result: str =","False test_user_url: str = f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\" test_request_headers: Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url,","\"X-Juejin-Token\": self._login_token, \"X-Juejin-Uid\": self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() !=","blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\"verifyCreatedAt\"] if self._response_data[\"d\"][\"total\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else:","f\"{self._main_url}/email\", login_data return None def parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data()","= self._response_data[\"token\"] self._login_uid = self._response_data[\"userId\"] self._login_client_id = self._response_data[\"clientId\"] # 重要参数持久化 params: str =",") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\"登录失败!\") raise LoginException() else: get_result: str = self.get_data(spider_name=f\"{self._spider_name}:params\")","else: url_params += f\"&{data[0]}={data[1]}\" blogs_url: str = f\"{self._blogs_url}{url_params}\" response = self.make_request(url=blogs_url, headers=self._common_headers) if","0: total_pages += 1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\"d\"][\"entryList\"] if len(entry_list) >","self._like_blogs_data.append(blog_data) page_no += 1 if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no)","= response.json() if ( self._response_data is not None and self._response_data[\"m\"] == \"success\" ):","].replace(\"uid=\", \"\") self._login_token = [d for d in login_params if \"token\" in d][","> 0: for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ) blog_data:","personal_blog[\"originalUrl\"], \"blogViewers\": personal_blog[\"viewsCount\"], \"blogCreateTime\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\"verifyCreatedAt\"] if self._response_data[\"d\"][\"total\"] >","task_id: str, username: str, password: str): self._main_url = \"https://juejin.im/auth/type\" self._blogs_url = \"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\" self._like_blogs_url","if response.content.decode() != \"\": self._response_data = response.json() if ( self._response_data is not None",") logger.info(\"获取个人点赞博客成功!\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\"查询个人点赞博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException()","utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def","TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data )","index, data in enumerate(req_data.items()): if index == 0: url_params += f\"?{data[0]}={data[1]}\" else: url_params","解析用户名 :return: 结果 \"\"\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict =","if response.content.decode() != \"\": self._response_data = response.json() if self._response_data is not None and","{\"password\": self._login_password} if phone_login is None and email_login is None: raise ValueError(\"Your login","self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\"登录失败!\") raise LoginException() else: get_result:","task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str","self._response_data[\"d\"][\"total\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\"获取个人博客数据成功!\") else: logger.error(\"查询个人博客失败!\") self.update_task_status( task_id=self._task_id,","f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\" self._common_headers.update( { \"X-Juejin-Client\": str(self._login_client_id), \"X-Juejin-Src\": \"web\", \"X-Juejin-Token\": self._login_token, \"X-Juejin-Uid\": self._login_uid, } )","self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\"获取个人点赞博客成功!\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\"查询个人点赞博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) )","logger.error(f\"当前掘金账号登录状态: 已退出!\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if test_json_response[\"s\"] == 1: logger.info(f\"当前掘金账号为:","\"blogCreateTime\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\"verifyCreatedAt\"] if self._response_data[\"d\"][\"total\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable)","json=login_data, ) if response.content.decode() != \"\": logger.info(\"登录成功!\") self._response_data = response.json() self._login_cookies = CookieUtils(","+= f\"?{data[0]}={data[1]}\" else: url_params += f\"&{data[0]}={data[1]}\" blogs_url: str = f\"{self._blogs_url}{url_params}\" response = self.make_request(url=blogs_url,","page_no: int = 0): like_blogs_url: str = f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\" self._common_headers.update( { \"X-Juejin-Client\": str(self._login_client_id), \"X-Juejin-Src\":","method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\"登录失败!\") raise LoginException() else: get_result: str = self.get_data(spider_name=f\"{self._spider_name}:params\") if get_result","\"web\", \"X-Juejin-Token\": self._login_token, \"X-Juejin-Uid\": self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode()","if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\"&\")[1:-1] self._login_uid","response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data = response.json() if self._response_data","logger.debug(self._like_blogs_data) logger.debug(f\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\"获取个人点赞博客成功!\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\"查询个人点赞博客失败!\")","self._blogs_data: List = [] self._like_blogs_data: List = [] self._like_blogs_total_page: int = 0 super().__init__()","\"20\", \"order\": \"createdAt\", } if next_params is not None: req_data.update(before=next_params) url_params: str =","self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data = response.json() if self._response_data is not","0: for entry_data in entry_list: if entry_data is None: continue blog_data: Dict =","username: str, password: str): self._main_url = \"https://juejin.im/auth/type\" self._blogs_url = \"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\" self._like_blogs_url = \"https://user-like-wrapper-ms.juejin.im/v1/user\"","List = [] self._like_blogs_data: List = [] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies","self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\"登录失败!\") raise LoginException() else: get_result: str = self.get_data(spider_name=f\"{self._spider_name}:params\") if","time_str=entry_data[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ), } self._like_blogs_data.append(blog_data) page_no += 1 if page_no <= self._like_blogs_total_page: #","0 ].replace(\"uid=\", \"\") self._login_token = [d for d in login_params if \"token\" in","0 ].replace(\"token=\", \"\") self._login_client_id = [ d for d in login_params if \"device_id\"","cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\"登录失败!\") raise","url=login_url, headers=self._common_headers, method=\"POST\", json=login_data, ) if response.content.decode() != \"\": logger.info(\"登录成功!\") self._response_data = response.json()","entry_data[\"objectId\"], \"blogTitle\": entry_data[\"title\"], \"blogHref\": entry_data[\"originalUrl\"], \"blogViewers\": entry_data[\"viewsCount\"], \"blogCreateTime\": datetime_str_change_fmt( time_str=entry_data[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ), }","!= 200 or check_is_json(test_response.content.decode()) is not True ): logger.error(f\"当前掘金账号登录状态: 已退出!\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False","like_blogs_url: str = f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\" self._common_headers.update( { \"X-Juejin-Client\": str(self._login_client_id), \"X-Juejin-Src\": \"web\", \"X-Juejin-Token\": self._login_token, \"X-Juejin-Uid\":","= None self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None self._response_data = None",") else: logger.error(\"登录失败!\") raise LoginException() else: get_result: str = self.get_data(spider_name=f\"{self._spider_name}:params\") if get_result is","Redis 返回数据失败! 错误原因: {err}\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token =","= password self._spider_name: str = f\"juejin:{self._login_username}\" self._login_cookies: Optional[str] = None self._login_token: Optional[str] =","index == 0: url_params += f\"?{data[0]}={data[1]}\" else: url_params += f\"&{data[0]}={data[1]}\" blogs_url: str =","-> bool: params = self.get_data(spider_name=f\"{self._spider_name}:params\") if params is None: return False test_user_url: str","self._login_cookies is None: login_url, login_data = self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\"POST\",","<= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\")","total_count = self._response_data[\"d\"][\"total\"] total_pages = total_count // 20 rest_count = total_count % 20","self._response_data is not None and self._response_data[\"m\"] == \"ok\": next_page_variable = None entry_list =","from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from spiders import BaseSpider,","test_request_headers: Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code","prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ), } self._like_blogs_data.append(blog_data) page_no += 1 if page_no <= self._like_blogs_total_page: # TODO","!= \"\": self._response_data = response.json() if ( self._response_data is not None and self._response_data[\"m\"]","int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \"\"\"","entry_list = self._response_data[\"d\"][\"entrylist\"] if len(entry_list) > 0: for personal_blog in entry_list: blog_create_time =","f\"&device_id={self._login_client_id}\" f\"¤t_uid={self._login_uid}\" self.set_data(spider_name=f\"{self._spider_name}:params\", data=params) # 个人数据 username = self._response_data[\"user\"][\"username\"] description = self._response_data[\"user\"][\"selfDescription\"] avatar_img","is not True ): logger.error(f\"当前掘金账号登录状态: 已退出!\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if","if test_json_response[\"s\"] == 1: logger.info(f\"当前掘金账号为: {self._login_username}, 状态: 已登录\") return True else: logger.error(f\"当前掘金账号登录状态: 已退出!\")","class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str, password: str): self._main_url = \"https://juejin.im/auth/type\"","= self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\"POST\", json=login_data, ) if response.content.decode() !=","params is None: return False test_user_url: str = f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\" test_request_headers: Dict = self.get_default_headers()","1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\"d\"][\"entryList\"] if len(entry_list) > 0: for entry_data","CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class","if response.content.decode() != \"\": logger.info(\"登录成功!\") self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str()","personal_blog[\"objectId\"], \"blogTitle\": personal_blog[\"title\"], \"blogHref\": personal_blog[\"originalUrl\"], \"blogViewers\": personal_blog[\"viewsCount\"], \"blogCreateTime\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable =","\"device_id\": self._login_client_id, \"token\": self._login_token, \"targetUid\": self._login_uid, \"type\": \"post\", \"limit\": \"20\", \"order\": \"createdAt\", }","> 0: for entry_data in entry_list: if entry_data is None: continue blog_data: Dict","= {\"password\": self._login_password} if phone_login is None and email_login is None: raise ValueError(\"Your","is not None: login_data.update(email=self._login_username) return f\"{self._main_url}/email\", login_data return None def parse_data_with_method(self, method: str):","avatar_img, \"followee\": followee, \"follower\": follower, \"likeBlogs\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self,","from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger =","None and email_login is None: raise ValueError(\"Your login username is illegal!\") if phone_login","== BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies","self._main_url = \"https://juejin.im/auth/type\" self._blogs_url = \"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\" self._like_blogs_url = \"https://user-like-wrapper-ms.juejin.im/v1/user\" self._task_id = task_id self._login_username","Dict = { \"blogId\": entry_data[\"objectId\"], \"blogTitle\": entry_data[\"title\"], \"blogHref\": entry_data[\"originalUrl\"], \"blogViewers\": entry_data[\"viewsCount\"], \"blogCreateTime\": datetime_str_change_fmt(","[] self._like_blogs_data: List = [] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name)","self._login_uid = [d for d in login_params if \"uid\" in d][ 0 ].replace(\"uid=\",","entry_data in entry_list: if entry_data is None: continue blog_data: Dict = { \"blogId\":","phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\"password\": self._login_password} if phone_login","self.get_data(spider_name=f\"{self._spider_name}:params\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\"&\")[1:-1]","None self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data: List = [] self._like_blogs_data:","if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method","url_params: str = \"\" for index, data in enumerate(req_data.items()): if index == 0:","ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger","self._login_token = self._response_data[\"token\"] self._login_uid = self._response_data[\"userId\"] self._login_client_id = self._response_data[\"clientId\"] # 重要参数持久化 params: str","= None) -> bool: params = self.get_data(spider_name=f\"{self._spider_name}:params\") if params is None: return False","len(entry_list) > 0: for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", )","test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code != 200 or check_is_json(test_response.content.decode())","self._login_cookies: Optional[str] = None self._login_token: Optional[str] = None self._login_uid: Optional[str] = None self._login_client_id:","\"blogTitle\": personal_blog[\"title\"], \"blogHref\": personal_blog[\"originalUrl\"], \"blogViewers\": personal_blog[\"viewsCount\"], \"blogCreateTime\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\"verifyCreatedAt\"]","login_data return None def parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif","self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is None:","elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is None: login_url, login_data","BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL )","email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\"password\": self._login_password} if phone_login is None and","\"likeBlogs\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data:","else: logger.error(\"登录失败!\") raise LoginException() else: get_result: str = self.get_data(spider_name=f\"{self._spider_name}:params\") if get_result is None:","is None: continue blog_data: Dict = { \"blogId\": entry_data[\"objectId\"], \"blogTitle\": entry_data[\"title\"], \"blogHref\": entry_data[\"originalUrl\"],","personal_blog[\"verifyCreatedAt\"] if self._response_data[\"d\"][\"total\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\"获取个人博客数据成功!\") else: logger.error(\"查询个人博客失败!\")","self._login_uid, \"device_id\": self._login_client_id, \"token\": self._login_token, \"targetUid\": self._login_uid, \"type\": \"post\", \"limit\": \"20\", \"order\": \"createdAt\",","} self._blogs_data.append(blog_data) next_page_variable = personal_blog[\"verifyCreatedAt\"] if self._response_data[\"d\"][\"total\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data)","\"followee\": followee, \"follower\": follower, \"likeBlogs\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params:","= f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\" test_request_headers: Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if","= total_pages entry_list = self._response_data[\"d\"][\"entryList\"] if len(entry_list) > 0: for entry_data in entry_list:","self._login_token, \"targetUid\": self._login_uid, \"type\": \"post\", \"limit\": \"20\", \"order\": \"createdAt\", } if next_params is","= { \"username\": username, \"description\": description, \"avatarImg\": avatar_img, \"followee\": followee, \"follower\": follower, \"likeBlogs\":","prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ) blog_data: Dict = { \"blogId\": personal_blog[\"objectId\"], \"blogTitle\": personal_blog[\"title\"], \"blogHref\": personal_blog[\"originalUrl\"], \"blogViewers\":","= self._response_data[\"user\"][\"selfDescription\"] avatar_img = self._response_data[\"user\"][\"avatarLarge\"] followee = self._response_data[\"user\"][\"followeesCount\"] follower = self._response_data[\"user\"][\"followersCount\"] like_blogs =","( self._response_data is not None and self._response_data[\"m\"] == \"success\" ): logger.info(f\"当前正在获取第{page_no + 1}页的数据!\")","self._blogs_url = \"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\" self._like_blogs_url = \"https://user-like-wrapper-ms.juejin.im/v1/user\" self._task_id = task_id self._login_username = username self._login_password","logger.info(\"登录成功!\") self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies","headers=self._common_headers) if response.content.decode() != \"\": self._response_data = response.json() if self._response_data is not None","self._common_headers.update( { \"X-Juejin-Client\": str(self._login_client_id), \"X-Juejin-Src\": \"web\", \"X-Juejin-Token\": self._login_token, \"X-Juejin-Uid\": self._login_uid, } ) response","get_result: str = self.get_data(spider_name=f\"{self._spider_name}:params\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try:","parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs()","1 if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data)","None self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data:","formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str, password: str):","= self._response_data[\"clientId\"] # 重要参数持久化 params: str = f\"?src=web&uid={self._login_uid}\" f\"&token={self._login_token}\" f\"&device_id={self._login_client_id}\" f\"¤t_uid={self._login_uid}\" self.set_data(spider_name=f\"{self._spider_name}:params\", data=params)","= self._response_data[\"user\"][\"followersCount\"] like_blogs = self._response_data[\"user\"][\"collectedEntriesCount\"] personal_data: Dict = { \"username\": username, \"description\": description,","BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data()","else: # logger.debug(self._like_blogs_data) logger.debug(f\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\"获取个人点赞博客成功!\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish)","返回数据失败! 错误原因: {err}\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\"token\"]","blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ) blog_data: Dict = { \"blogId\": personal_blog[\"objectId\"], \"blogTitle\":","\"src\": \"web\", \"uid\": self._login_uid, \"device_id\": self._login_client_id, \"token\": self._login_token, \"targetUid\": self._login_uid, \"type\": \"post\", \"limit\":","\"X-Juejin-Src\": \"web\", \"X-Juejin-Token\": self._login_token, \"X-Juejin-Uid\": self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if","personal_data: Dict = { \"username\": username, \"description\": description, \"avatarImg\": avatar_img, \"followee\": followee, \"follower\":","entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ) blog_data: Dict = { \"blogId\": personal_blog[\"objectId\"],","int = 0): like_blogs_url: str = f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\" self._common_headers.update( { \"X-Juejin-Client\": str(self._login_client_id), \"X-Juejin-Src\": \"web\",","\"success\" ): logger.info(f\"当前正在获取第{page_no + 1}页的数据!\") if page_no == 0: total_count = self._response_data[\"d\"][\"total\"] total_pages","结果 \"\"\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\"password\": self._login_password}","if phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\"{self._main_url}/phoneNumber\", login_data if email_login is not","typing import Dict, List, Tuple, Optional from utils.logger_utils import LogManager from utils.str_utils import","self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\"查询个人点赞博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies: Optional[str]","= None self._blogs_data: List = [] self._like_blogs_data: List = [] self._like_blogs_total_page: int =","dict = { \"src\": \"web\", \"uid\": self._login_uid, \"device_id\": self._login_client_id, \"token\": self._login_token, \"targetUid\": self._login_uid,","logger.error(\"查询个人博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no: int = 0):","LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address","None: continue blog_data: Dict = { \"blogId\": entry_data[\"objectId\"], \"blogTitle\": entry_data[\"title\"], \"blogHref\": entry_data[\"originalUrl\"], \"blogViewers\":","None: req_data.update(before=next_params) url_params: str = \"\" for index, data in enumerate(req_data.items()): if index","self._response_data[\"d\"][\"total\"] total_pages = total_count // 20 rest_count = total_count % 20 if rest_count","0: total_count = self._response_data[\"d\"][\"total\"] total_pages = total_count // 20 rest_count = total_count %","{ \"blogId\": entry_data[\"objectId\"], \"blogTitle\": entry_data[\"title\"], \"blogHref\": entry_data[\"originalUrl\"], \"blogViewers\": entry_data[\"viewsCount\"], \"blogCreateTime\": datetime_str_change_fmt( time_str=entry_data[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\",","in login_params if \"device_id\" in d ][0].replace(\"device_id=\", \"\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception","from typing import Dict, List, Tuple, Optional from utils.logger_utils import LogManager from utils.str_utils","if self._login_cookies is None: login_url, login_data = self._check_username() response = self.make_request( url=login_url, headers=self._common_headers,","self._blogs_data.append(blog_data) next_page_variable = personal_blog[\"verifyCreatedAt\"] if self._response_data[\"d\"][\"total\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data)","self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\"获取个人博客数据成功!\") else: logger.error(\"查询个人博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no:","logger.info(\"获取个人博客数据成功!\") else: logger.error(\"查询个人博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no: int","as err: logger.error(f\"解析 Redis 返回数据失败! 错误原因: {err}\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): #","in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ) blog_data: Dict = { \"blogId\":","follower = self._response_data[\"user\"][\"followersCount\"] like_blogs = self._response_data[\"user\"][\"collectedEntriesCount\"] personal_data: Dict = { \"username\": username, \"description\":","response.json() if ( self._response_data is not None and self._response_data[\"m\"] == \"success\" ): logger.info(f\"当前正在获取第{page_no","logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username:","\"\": self._response_data = response.json() if ( self._response_data is not None and self._response_data[\"m\"] ==","total_pages entry_list = self._response_data[\"d\"][\"entryList\"] if len(entry_list) > 0: for entry_data in entry_list: if","url_params += f\"?{data[0]}={data[1]}\" else: url_params += f\"&{data[0]}={data[1]}\" blogs_url: str = f\"{self._blogs_url}{url_params}\" response =","login_data if email_login is not None: login_data.update(email=self._login_username) return f\"{self._main_url}/email\", login_data return None def","self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult )","BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL","self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]:","time_str=personal_blog[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ) blog_data: Dict = { \"blogId\": personal_blog[\"objectId\"], \"blogTitle\": personal_blog[\"title\"], \"blogHref\": personal_blog[\"originalUrl\"],","str(self._login_client_id), \"X-Juejin-Src\": \"web\", \"X-Juejin-Token\": self._login_token, \"X-Juejin-Uid\": self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers)","self._response_data[\"d\"][\"entrylist\"] if len(entry_list) > 0: for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\"createdAt\"],","LoginException() else: get_result: str = self.get_data(spider_name=f\"{self._spider_name}:params\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult )","data=self._like_blogs_data ) logger.info(\"获取个人点赞博客成功!\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\"查询个人点赞博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise","else: logger.error(\"查询个人博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no: int =","# 个人数据 username = self._response_data[\"user\"][\"username\"] description = self._response_data[\"user\"][\"selfDescription\"] avatar_img = self._response_data[\"user\"][\"avatarLarge\"] followee =","data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str =","].replace(\"token=\", \"\") self._login_client_id = [ d for d in login_params if \"device_id\" in","datetime_str_change_fmt( time_str=entry_data[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ), } self._like_blogs_data.append(blog_data) page_no += 1 if page_no <= self._like_blogs_total_page:","def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict = { \"src\": \"web\", \"uid\":","= { \"blogId\": entry_data[\"objectId\"], \"blogTitle\": entry_data[\"title\"], \"blogHref\": entry_data[\"originalUrl\"], \"blogViewers\": entry_data[\"viewsCount\"], \"blogCreateTime\": datetime_str_change_fmt( time_str=entry_data[\"createdAt\"],","f\"?{data[0]}={data[1]}\" else: url_params += f\"&{data[0]}={data[1]}\" blogs_url: str = f\"{self._blogs_url}{url_params}\" response = self.make_request(url=blogs_url, headers=self._common_headers)","_parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict = { \"src\": \"web\", \"uid\": self._login_uid,","if len(entry_list) > 0: for entry_data in entry_list: if entry_data is None: continue","phone_login is None and email_login is None: raise ValueError(\"Your login username is illegal!\")","= f\"juejin:{self._login_username}\" self._login_cookies: Optional[str] = None self._login_token: Optional[str] = None self._login_uid: Optional[str] =","Dict = {\"password\": self._login_password} if phone_login is None and email_login is None: raise","\"uid\": self._login_uid, \"device_id\": self._login_client_id, \"token\": self._login_token, \"targetUid\": self._login_uid, \"type\": \"post\", \"limit\": \"20\", \"order\":","page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\"获取到 {len(self._like_blogs_data)}","\"web\", \"uid\": self._login_uid, \"device_id\": self._login_client_id, \"token\": self._login_token, \"targetUid\": self._login_uid, \"type\": \"post\", \"limit\": \"20\",","self._response_data = response.json() if ( self._response_data is not None and self._response_data[\"m\"] == \"success\"","= check_is_email_address(data=self._login_username) login_data: Dict = {\"password\": self._login_password} if phone_login is None and email_login","self._login_username = username self._login_password = password self._spider_name: str = f\"juejin:{self._login_username}\" self._login_cookies: Optional[str] =","\"username\": username, \"description\": description, \"avatarImg\": avatar_img, \"followee\": followee, \"follower\": follower, \"likeBlogs\": like_blogs, }","\"post\", \"limit\": \"20\", \"order\": \"createdAt\", } if next_params is not None: req_data.update(before=next_params) url_params:","login_data.update(email=self._login_username) return f\"{self._main_url}/email\", login_data return None def parse_data_with_method(self, method: str): if method ==","Dict = { \"blogId\": personal_blog[\"objectId\"], \"blogTitle\": personal_blog[\"title\"], \"blogHref\": personal_blog[\"originalUrl\"], \"blogViewers\": personal_blog[\"viewsCount\"], \"blogCreateTime\": blog_create_time,","self._response_data[\"user\"][\"selfDescription\"] avatar_img = self._response_data[\"user\"][\"avatarLarge\"] followee = self._response_data[\"user\"][\"followeesCount\"] follower = self._response_data[\"user\"][\"followersCount\"] like_blogs = self._response_data[\"user\"][\"collectedEntriesCount\"]","\"description\": description, \"avatarImg\": avatar_img, \"followee\": followee, \"follower\": follower, \"likeBlogs\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data)","ValueError(\"Your login username is illegal!\") if phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\"{self._main_url}/phoneNumber\",","= f\"?src=web&uid={self._login_uid}\" f\"&token={self._login_token}\" f\"&device_id={self._login_client_id}\" f\"¤t_uid={self._login_uid}\" self.set_data(spider_name=f\"{self._spider_name}:params\", data=params) # 个人数据 username = self._response_data[\"user\"][\"username\"] description","== \"ok\": next_page_variable = None entry_list = self._response_data[\"d\"][\"entrylist\"] if len(entry_list) > 0: for","True ): logger.error(f\"当前掘金账号登录状态: 已退出!\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if test_json_response[\"s\"] ==","== 1: logger.info(f\"当前掘金账号为: {self._login_username}, 状态: 已登录\") return True else: logger.error(f\"当前掘金账号登录状态: 已退出!\") return False","def _test_cookies(self, cookies: Optional[str] = None) -> bool: params = self.get_data(spider_name=f\"{self._spider_name}:params\") if params","login_data = self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\"POST\", json=login_data, ) if response.content.decode()","== BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish:","logger.debug(f\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\"获取个人点赞博客成功!\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\"查询个人点赞博客失败!\") self.update_task_status(","), } self._like_blogs_data.append(blog_data) page_no += 1 if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据","def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\"token\"] self._login_uid = self._response_data[\"userId\"] self._login_client_id = self._response_data[\"clientId\"]","{len(self._like_blogs_data)} 条个人点赞博客\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\"获取个人点赞博客成功!\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\"查询个人点赞博客失败!\") self.update_task_status( task_id=self._task_id,","test_response.json() if test_json_response[\"s\"] == 1: logger.info(f\"当前掘金账号为: {self._login_username}, 状态: 已登录\") return True else: logger.error(f\"当前掘金账号登录状态:","def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str = f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\" self._common_headers.update( { \"X-Juejin-Client\":","d in login_params if \"token\" in d][ 0 ].replace(\"token=\", \"\") self._login_client_id = [","str = f\"?src=web&uid={self._login_uid}\" f\"&token={self._login_token}\" f\"&device_id={self._login_client_id}\" f\"¤t_uid={self._login_uid}\" self.set_data(spider_name=f\"{self._spider_name}:params\", data=params) # 个人数据 username = self._response_data[\"user\"][\"username\"]","= [ d for d in login_params if \"device_id\" in d ][0].replace(\"device_id=\", \"\")","if len(entry_list) > 0: for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\",","= f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\" self._common_headers.update( { \"X-Juejin-Client\": str(self._login_client_id), \"X-Juejin-Src\": \"web\", \"X-Juejin-Token\": self._login_token, \"X-Juejin-Uid\": self._login_uid, }","self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is None: login_url,","check_is_email_address(data=self._login_username) login_data: Dict = {\"password\": self._login_password} if phone_login is None and email_login is","20 rest_count = total_count % 20 if rest_count != 0: total_pages += 1","data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies: Optional[str] = None) -> bool: params","公共参数 self._login_token = self._response_data[\"token\"] self._login_uid = self._response_data[\"userId\"] self._login_client_id = self._response_data[\"clientId\"] # 重要参数持久化 params:","total_count // 20 rest_count = total_count % 20 if rest_count != 0: total_pages","is not None and self._response_data[\"m\"] == \"ok\": next_page_variable = None entry_list = self._response_data[\"d\"][\"entrylist\"]","time from typing import Dict, List, Tuple, Optional from utils.logger_utils import LogManager from","err: logger.error(f\"解析 Redis 返回数据失败! 错误原因: {err}\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数","= response.json() if self._response_data is not None and self._response_data[\"m\"] == \"ok\": next_page_variable =","self._response_data[\"userId\"] self._login_client_id = self._response_data[\"clientId\"] # 重要参数持久化 params: str = f\"?src=web&uid={self._login_uid}\" f\"&token={self._login_token}\" f\"&device_id={self._login_client_id}\" f\"¤t_uid={self._login_uid}\"","login_data.update(phoneNumber=self._login_username) return f\"{self._main_url}/phoneNumber\", login_data if email_login is not None: login_data.update(email=self._login_username) return f\"{self._main_url}/email\", login_data","List, Tuple, Optional from utils.logger_utils import LogManager from utils.str_utils import check_is_json from config","import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self,","if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\"获取到","logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\"获取个人博客数据成功!\") else: logger.error(\"查询个人博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self,","check_is_json(test_response.content.decode()) is not True ): logger.error(f\"当前掘金账号登录状态: 已退出!\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json()","条个人点赞博客\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\"获取个人点赞博客成功!\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\"查询个人点赞博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL)","= [] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) ->","personal_blog[\"viewsCount\"], \"blogCreateTime\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\"verifyCreatedAt\"] if self._response_data[\"d\"][\"total\"] > 20: time.sleep(0.5)","None) -> bool: params = self.get_data(spider_name=f\"{self._spider_name}:params\") if params is None: return False test_user_url:","raise LoginException() def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str = f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\" self._common_headers.update(","is None: return False test_user_url: str = f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\" test_request_headers: Dict = self.get_default_headers() test_response","None self._response_data = None self._blogs_data: List = [] self._like_blogs_data: List = [] self._like_blogs_total_page:","import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils","Optional from utils.logger_utils import LogManager from utils.str_utils import check_is_json from config import LOG_LEVEL,","== BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is None: login_url, login_data = self._check_username()","url_params += f\"&{data[0]}={data[1]}\" blogs_url: str = f\"{self._blogs_url}{url_params}\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode()","not None and self._response_data[\"m\"] == \"ok\": next_page_variable = None entry_list = self._response_data[\"d\"][\"entrylist\"] if","\"ok\": next_page_variable = None entry_list = self._response_data[\"d\"][\"entrylist\"] if len(entry_list) > 0: for personal_blog","login username is illegal!\") if phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\"{self._main_url}/phoneNumber\", login_data","0): like_blogs_url: str = f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\" self._common_headers.update( { \"X-Juejin-Client\": str(self._login_client_id), \"X-Juejin-Src\": \"web\", \"X-Juejin-Token\": self._login_token,","method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\"token\"] self._login_uid = self._response_data[\"userId\"] self._login_client_id","None: return False test_user_url: str = f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\" test_request_headers: Dict = self.get_default_headers() test_response =","= self.get_data(spider_name=f\"{self._spider_name}:params\") if params is None: return False test_user_url: str = f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\" test_request_headers:","0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \"\"\" 解析用户名 :return:",") else: try: login_params = get_result.split(\"&\")[1:-1] self._login_uid = [d for d in login_params","continue blog_data: Dict = { \"blogId\": entry_data[\"objectId\"], \"blogTitle\": entry_data[\"title\"], \"blogHref\": entry_data[\"originalUrl\"], \"blogViewers\": entry_data[\"viewsCount\"],","任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\"查询个人点赞博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies:","self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\"解析 Redis 返回数据失败! 错误原因: {err}\") self.parse_data_with_method(","self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies )","self._spider_name: str = f\"juejin:{self._login_username}\" self._login_cookies: Optional[str] = None self._login_token: Optional[str] = None self._login_uid:","import time from typing import Dict, List, Tuple, Optional from utils.logger_utils import LogManager","if self._response_data is not None and self._response_data[\"m\"] == \"ok\": next_page_variable = None entry_list","import Dict, List, Tuple, Optional from utils.logger_utils import LogManager from utils.str_utils import check_is_json","self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data: List = [] self._like_blogs_data: List","in d][ 0 ].replace(\"token=\", \"\") self._login_client_id = [ d for d in login_params","self._login_client_id = self._response_data[\"clientId\"] # 重要参数持久化 params: str = f\"?src=web&uid={self._login_uid}\" f\"&token={self._login_token}\" f\"&device_id={self._login_client_id}\" f\"¤t_uid={self._login_uid}\" self.set_data(spider_name=f\"{self._spider_name}:params\",","time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\"获取个人博客数据成功!\") else: logger.error(\"查询个人博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise","self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url:","= self._response_data[\"d\"][\"entryList\"] if len(entry_list) > 0: for entry_data in entry_list: if entry_data is","page_no += 1 if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else:","response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data = response.json() if (","logger.info(f\"当前正在获取第{page_no + 1}页的数据!\") if page_no == 0: total_count = self._response_data[\"d\"][\"total\"] total_pages = total_count","\"\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\"解析 Redis 返回数据失败! 错误原因: {err}\")",") response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data = response.json() if","0: url_params += f\"?{data[0]}={data[1]}\" else: url_params += f\"&{data[0]}={data[1]}\" blogs_url: str = f\"{self._blogs_url}{url_params}\" response","self._response_data[\"user\"][\"username\"] description = self._response_data[\"user\"][\"selfDescription\"] avatar_img = self._response_data[\"user\"][\"avatarLarge\"] followee = self._response_data[\"user\"][\"followeesCount\"] follower = self._response_data[\"user\"][\"followersCount\"]","like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict","JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str, password: str): self._main_url = \"https://juejin.im/auth/type\" self._blogs_url","entry_data[\"originalUrl\"], \"blogViewers\": entry_data[\"viewsCount\"], \"blogCreateTime\": datetime_str_change_fmt( time_str=entry_data[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ), } self._like_blogs_data.append(blog_data) page_no += 1","\"avatarImg\": avatar_img, \"followee\": followee, \"follower\": follower, \"likeBlogs\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def","headers=self._common_headers) if response.content.decode() != \"\": self._response_data = response.json() if ( self._response_data is not","\"token\" in d][ 0 ].replace(\"token=\", \"\") self._login_client_id = [ d for d in","# 重要参数持久化 params: str = f\"?src=web&uid={self._login_uid}\" f\"&token={self._login_token}\" f\"&device_id={self._login_client_id}\" f\"¤t_uid={self._login_uid}\" self.set_data(spider_name=f\"{self._spider_name}:params\", data=params) # 个人数据","self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict = { \"src\":","= response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method(",") class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str, password: str): self._main_url =","LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from spiders","time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\"获取个人点赞博客成功!\") #","\"type\": \"post\", \"limit\": \"20\", \"order\": \"createdAt\", } if next_params is not None: req_data.update(before=next_params)","not None and self._response_data[\"m\"] == \"success\" ): logger.info(f\"当前正在获取第{page_no + 1}页的数据!\") if page_no ==","method=\"POST\", json=login_data, ) if response.content.decode() != \"\": logger.info(\"登录成功!\") self._response_data = response.json() self._login_cookies =","page_no == 0: total_count = self._response_data[\"d\"][\"total\"] total_pages = total_count // 20 rest_count =","is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\"&\")[1:-1] self._login_uid = [d","in d][ 0 ].replace(\"uid=\", \"\") self._login_token = [d for d in login_params if","Dict = { \"username\": username, \"description\": description, \"avatarImg\": avatar_img, \"followee\": followee, \"follower\": follower,","{ \"username\": username, \"description\": description, \"avatarImg\": avatar_img, \"followee\": followee, \"follower\": follower, \"likeBlogs\": like_blogs,","except Exception as err: logger.error(f\"解析 Redis 返回数据失败! 错误原因: {err}\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def","if index == 0: url_params += f\"?{data[0]}={data[1]}\" else: url_params += f\"&{data[0]}={data[1]}\" blogs_url: str","str, password: str): self._main_url = \"https://juejin.im/auth/type\" self._blogs_url = \"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\" self._like_blogs_url = \"https://user-like-wrapper-ms.juejin.im/v1/user\" self._task_id","self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not","): logger.error(f\"当前掘金账号登录状态: 已退出!\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if test_json_response[\"s\"] == 1:","data=params) # 个人数据 username = self._response_data[\"user\"][\"username\"] description = self._response_data[\"user\"][\"selfDescription\"] avatar_img = self._response_data[\"user\"][\"avatarLarge\"] followee","else: logger.error(\"查询个人点赞博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies: Optional[str] =","\"device_id\" in d ][0].replace(\"device_id=\", \"\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\"解析","if \"token\" in d][ 0 ].replace(\"token=\", \"\") self._login_client_id = [ d for d","self._like_blogs_total_page = total_pages entry_list = self._response_data[\"d\"][\"entryList\"] if len(entry_list) > 0: for entry_data in","= self._response_data[\"user\"][\"avatarLarge\"] followee = self._response_data[\"user\"][\"followeesCount\"] follower = self._response_data[\"user\"][\"followersCount\"] like_blogs = self._response_data[\"user\"][\"collectedEntriesCount\"] personal_data: Dict","if entry_data is None: continue blog_data: Dict = { \"blogId\": entry_data[\"objectId\"], \"blogTitle\": entry_data[\"title\"],","\"blogCreateTime\": datetime_str_change_fmt( time_str=entry_data[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ), } self._like_blogs_data.append(blog_data) page_no += 1 if page_no <=","\"\") self._login_client_id = [ d for d in login_params if \"device_id\" in d","} if next_params is not None: req_data.update(before=next_params) url_params: str = \"\" for index,","None self._login_token: Optional[str] = None self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None","_parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str = f\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\" self._common_headers.update( { \"X-Juejin-Client\": str(self._login_client_id),","import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from","None: login_data.update(phoneNumber=self._login_username) return f\"{self._main_url}/phoneNumber\", login_data if email_login is not None: login_data.update(email=self._login_username) return f\"{self._main_url}/email\",","None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\"&\")[1:-1] self._login_uid = [d for","self.get_data(spider_name=f\"{self._spider_name}:params\") if params is None: return False test_user_url: str = f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\" test_request_headers: Dict","self.send_data() def login(self): if self._login_cookies is None: login_url, login_data = self._check_username() response =","cookies: Optional[str] = None) -> bool: params = self.get_data(spider_name=f\"{self._spider_name}:params\") if params is None:","self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data = response.json() if ( self._response_data is","= None self._login_token: Optional[str] = None self._login_uid: Optional[str] = None self._login_client_id: Optional[str] =","\"uid\" in d][ 0 ].replace(\"uid=\", \"\") self._login_token = [d for d in login_params","d][ 0 ].replace(\"token=\", \"\") self._login_client_id = [ d for d in login_params if","method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs()","+= 1 if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: #","in d ][0].replace(\"device_id=\", \"\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\"解析 Redis","from utils.exception_utils import LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils","logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict = {","f\"juejin:{self._login_username}\" self._login_cookies: Optional[str] = None self._login_token: Optional[str] = None self._login_uid: Optional[str] = None","\"order\": \"createdAt\", } if next_params is not None: req_data.update(before=next_params) url_params: str = \"\"","data in enumerate(req_data.items()): if index == 0: url_params += f\"?{data[0]}={data[1]}\" else: url_params +=","len(entry_list) > 0: for entry_data in entry_list: if entry_data is None: continue blog_data:","f\"&token={self._login_token}\" f\"&device_id={self._login_client_id}\" f\"¤t_uid={self._login_uid}\" self.set_data(spider_name=f\"{self._spider_name}:params\", data=params) # 个人数据 username = self._response_data[\"user\"][\"username\"] description = self._response_data[\"user\"][\"selfDescription\"]","in enumerate(req_data.items()): if index == 0: url_params += f\"?{data[0]}={data[1]}\" else: url_params += f\"&{data[0]}={data[1]}\"",") def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\"token\"] self._login_uid = self._response_data[\"userId\"] self._login_client_id =",") except Exception as err: logger.error(f\"解析 Redis 返回数据失败! 错误原因: {err}\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult )","import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils","# 公共参数 self._login_token = self._response_data[\"token\"] self._login_uid = self._response_data[\"userId\"] self._login_client_id = self._response_data[\"clientId\"] # 重要参数持久化","!= \"\": self._response_data = response.json() if self._response_data is not None and self._response_data[\"m\"] ==","d in login_params if \"uid\" in d][ 0 ].replace(\"uid=\", \"\") self._login_token = [d","][0].replace(\"device_id=\", \"\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\"解析 Redis 返回数据失败! 错误原因:","utils.logger_utils import LogManager from utils.str_utils import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from","bool: params = self.get_data(spider_name=f\"{self._spider_name}:params\") if params is None: return False test_user_url: str =","total_pages += 1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\"d\"][\"entryList\"] if len(entry_list) > 0:","return False test_user_url: str = f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\" test_request_headers: Dict = self.get_default_headers() test_response = self.make_request(","response.content.decode() != \"\": self._response_data = response.json() if ( self._response_data is not None and","= get_result.split(\"&\")[1:-1] self._login_uid = [d for d in login_params if \"uid\" in d][","{ \"X-Juejin-Client\": str(self._login_client_id), \"X-Juejin-Src\": \"web\", \"X-Juejin-Token\": self._login_token, \"X-Juejin-Uid\": self._login_uid, } ) response =","{ \"src\": \"web\", \"uid\": self._login_uid, \"device_id\": self._login_client_id, \"token\": self._login_token, \"targetUid\": self._login_uid, \"type\": \"post\",","is None: login_url, login_data = self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\"POST\", json=login_data,","_parse_login_data(self): # 公共参数 self._login_token = self._response_data[\"token\"] self._login_uid = self._response_data[\"userId\"] self._login_client_id = self._response_data[\"clientId\"] #","in login_params if \"uid\" in d][ 0 ].replace(\"uid=\", \"\") self._login_token = [d for","self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict = { \"src\": \"web\",","username, \"description\": description, \"avatarImg\": avatar_img, \"followee\": followee, \"follower\": follower, \"likeBlogs\": like_blogs, } logger.debug(personal_data)","from utils.logger_utils import LogManager from utils.str_utils import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL","def __init__(self, task_id: str, username: str, password: str): self._main_url = \"https://juejin.im/auth/type\" self._blogs_url =","= self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code != 200","personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ) blog_data: Dict = {","d for d in login_params if \"device_id\" in d ][0].replace(\"device_id=\", \"\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs","datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from","password: str): self._main_url = \"https://juejin.im/auth/type\" self._blogs_url = \"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\" self._like_blogs_url = \"https://user-like-wrapper-ms.juejin.im/v1/user\" self._task_id =","self._login_token, \"X-Juejin-Uid\": self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \"\":","method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\"&\")[1:-1] self._login_uid = [d for d in",":return: 结果 \"\"\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\"password\":","self._login_uid = self._response_data[\"userId\"] self._login_client_id = self._response_data[\"clientId\"] # 重要参数持久化 params: str = f\"?src=web&uid={self._login_uid}\" f\"&token={self._login_token}\"","_check_username(self) -> Optional[Tuple[str, Dict]]: \"\"\" 解析用户名 :return: 结果 \"\"\" phone_login = check_is_phone_number(data=self._login_username) email_login","\"follower\": follower, \"likeBlogs\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] =","not True ): logger.error(f\"当前掘金账号登录状态: 已退出!\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if test_json_response[\"s\"]","from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException,","else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\"获取个人博客数据成功!\") else: logger.error(\"查询个人博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def","self._response_data = None self._blogs_data: List = [] self._like_blogs_data: List = [] self._like_blogs_total_page: int","== \"success\" ): logger.info(f\"当前正在获取第{page_no + 1}页的数据!\") if page_no == 0: total_count = self._response_data[\"d\"][\"total\"]","Dict]]: \"\"\" 解析用户名 :return: 结果 \"\"\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data:","// 20 rest_count = total_count % 20 if rest_count != 0: total_pages +=","blog_data: Dict = { \"blogId\": entry_data[\"objectId\"], \"blogTitle\": entry_data[\"title\"], \"blogHref\": entry_data[\"originalUrl\"], \"blogViewers\": entry_data[\"viewsCount\"], \"blogCreateTime\":","= \"https://juejin.im/auth/type\" self._blogs_url = \"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\" self._like_blogs_url = \"https://user-like-wrapper-ms.juejin.im/v1/user\" self._task_id = task_id self._login_username =","Optional[str] = None self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data: List =","None entry_list = self._response_data[\"d\"][\"entrylist\"] if len(entry_list) > 0: for personal_blog in entry_list: blog_create_time","super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \"\"\" 解析用户名 :return: 结果","response = self.make_request( url=login_url, headers=self._common_headers, method=\"POST\", json=login_data, ) if response.content.decode() != \"\": logger.info(\"登录成功!\")","= self._response_data[\"user\"][\"followeesCount\"] follower = self._response_data[\"user\"][\"followersCount\"] like_blogs = self._response_data[\"user\"][\"collectedEntriesCount\"] personal_data: Dict = { \"username\":","= [d for d in login_params if \"uid\" in d][ 0 ].replace(\"uid=\", \"\")","import LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number,","followee, \"follower\": follower, \"likeBlogs\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str]","self._response_data[\"m\"] == \"success\" ): logger.info(f\"当前正在获取第{page_no + 1}页的数据!\") if page_no == 0: total_count =","description, \"avatarImg\": avatar_img, \"followee\": followee, \"follower\": follower, \"likeBlogs\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs)","next_params: Optional[str] = None): req_data: dict = { \"src\": \"web\", \"uid\": self._login_uid, \"device_id\":","BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is","!= \"\": logger.info(\"登录成功!\") self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies(","if \"uid\" in d][ 0 ].replace(\"uid=\", \"\") self._login_token = [d for d in","params: str = f\"?src=web&uid={self._login_uid}\" f\"&token={self._login_token}\" f\"&device_id={self._login_client_id}\" f\"¤t_uid={self._login_uid}\" self.set_data(spider_name=f\"{self._spider_name}:params\", data=params) # 个人数据 username =","str = \"\" for index, data in enumerate(req_data.items()): if index == 0: url_params","logger.error(\"登录失败!\") raise LoginException() else: get_result: str = self.get_data(spider_name=f\"{self._spider_name}:params\") if get_result is None: self.parse_data_with_method(","entry_data[\"viewsCount\"], \"blogCreateTime\": datetime_str_change_fmt( time_str=entry_data[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ), } self._like_blogs_data.append(blog_data) page_no += 1 if page_no","= \"\" for index, data in enumerate(req_data.items()): if index == 0: url_params +=","d ][0].replace(\"device_id=\", \"\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\"解析 Redis 返回数据失败!","self._login_token = [d for d in login_params if \"token\" in d][ 0 ].replace(\"token=\",","and self._response_data[\"m\"] == \"ok\": next_page_variable = None entry_list = self._response_data[\"d\"][\"entrylist\"] if len(entry_list) >","self._login_token: Optional[str] = None self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None self._response_data","self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if test_json_response[\"s\"] == 1: logger.info(f\"当前掘金账号为: {self._login_username}, 状态:","if page_no == 0: total_count = self._response_data[\"d\"][\"total\"] total_pages = total_count // 20 rest_count","\"\") self._login_token = [d for d in login_params if \"token\" in d][ 0","__init__(self, task_id: str, username: str, password: str): self._main_url = \"https://juejin.im/auth/type\" self._blogs_url = \"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\"","str = self.get_data(spider_name=f\"{self._spider_name}:params\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params","like_blogs = self._response_data[\"user\"][\"collectedEntriesCount\"] personal_data: Dict = { \"username\": username, \"description\": description, \"avatarImg\": avatar_img,","Dict, List, Tuple, Optional from utils.logger_utils import LogManager from utils.str_utils import check_is_json from","= self.get_data(spider_name=f\"{self._spider_name}:params\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params =","self._login_uid, \"type\": \"post\", \"limit\": \"20\", \"order\": \"createdAt\", } if next_params is not None:","= test_response.json() if test_json_response[\"s\"] == 1: logger.info(f\"当前掘金账号为: {self._login_username}, 状态: 已登录\") return True else:","if next_params is not None: req_data.update(before=next_params) url_params: str = \"\" for index, data","logger.error(f\"解析 Redis 返回数据失败! 错误原因: {err}\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token","entry_list = self._response_data[\"d\"][\"entryList\"] if len(entry_list) > 0: for entry_data in entry_list: if entry_data","\"targetUid\": self._login_uid, \"type\": \"post\", \"limit\": \"20\", \"order\": \"createdAt\", } if next_params is not","f\"?src=web&uid={self._login_uid}\" f\"&token={self._login_token}\" f\"&device_id={self._login_client_id}\" f\"¤t_uid={self._login_uid}\" self.set_data(spider_name=f\"{self._spider_name}:params\", data=params) # 个人数据 username = self._response_data[\"user\"][\"username\"] description =","check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\"password\": self._login_password} if phone_login is None","self._response_data[\"user\"][\"followersCount\"] like_blogs = self._response_data[\"user\"][\"collectedEntriesCount\"] personal_data: Dict = { \"username\": username, \"description\": description, \"avatarImg\":","= self._response_data[\"user\"][\"collectedEntriesCount\"] personal_data: Dict = { \"username\": username, \"description\": description, \"avatarImg\": avatar_img, \"followee\":","login(self): if self._login_cookies is None: login_url, login_data = self._check_username() response = self.make_request( url=login_url,","test_user_url: str = f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\" test_request_headers: Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers","def parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs:","elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self):","method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\"解析 Redis 返回数据失败! 错误原因: {err}\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult","= None): req_data: dict = { \"src\": \"web\", \"uid\": self._login_uid, \"device_id\": self._login_client_id, \"token\":","Tuple, Optional from utils.logger_utils import LogManager from utils.str_utils import check_is_json from config import","BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is None: login_url, login_data = self._check_username() response","username self._login_password = password self._spider_name: str = f\"juejin:{self._login_username}\" self._login_cookies: Optional[str] = None self._login_token:","self._response_data[\"user\"][\"followeesCount\"] follower = self._response_data[\"user\"][\"followersCount\"] like_blogs = self._response_data[\"user\"][\"collectedEntriesCount\"] personal_data: Dict = { \"username\": username,","test_json_response = test_response.json() if test_json_response[\"s\"] == 1: logger.info(f\"当前掘金账号为: {self._login_username}, 状态: 已登录\") return True","self._response_data[\"token\"] self._login_uid = self._response_data[\"userId\"] self._login_client_id = self._response_data[\"clientId\"] # 重要参数持久化 params: str = f\"?src=web&uid={self._login_uid}\"","test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not True ): logger.error(f\"当前掘金账号登录状态: 已退出!\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return","= f\"{self._blogs_url}{url_params}\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data = response.json()","response.json() if self._response_data is not None and self._response_data[\"m\"] == \"ok\": next_page_variable = None","str = f\"{self._blogs_url}{url_params}\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data =","self._response_data[\"user\"][\"collectedEntriesCount\"] personal_data: Dict = { \"username\": username, \"description\": description, \"avatarImg\": avatar_img, \"followee\": followee,","is None and email_login is None: raise ValueError(\"Your login username is illegal!\") if","spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers(","task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies: Optional[str] = None) -> bool:","LogManager from utils.str_utils import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import","return f\"{self._main_url}/phoneNumber\", login_data if email_login is not None: login_data.update(email=self._login_username) return f\"{self._main_url}/email\", login_data return","0: for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ) blog_data: Dict","\"X-Juejin-Client\": str(self._login_client_id), \"X-Juejin-Src\": \"web\", \"X-Juejin-Token\": self._login_token, \"X-Juejin-Uid\": self._login_uid, } ) response = self.make_request(url=like_blogs_url,","raise LoginException() else: get_result: str = self.get_data(spider_name=f\"{self._spider_name}:params\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult","self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \"\"\" 解析用户名 :return: 结果 \"\"\" phone_login =","= self._response_data[\"userId\"] self._login_client_id = self._response_data[\"clientId\"] # 重要参数持久化 params: str = f\"?src=web&uid={self._login_uid}\" f\"&token={self._login_token}\" f\"&device_id={self._login_client_id}\"","= total_count % 20 if rest_count != 0: total_pages += 1 self._like_blogs_total_page =","blogs_url: str = f\"{self._blogs_url}{url_params}\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data","not None: login_data.update(email=self._login_username) return f\"{self._main_url}/email\", login_data return None def parse_data_with_method(self, method: str): if","% 20 if rest_count != 0: total_pages += 1 self._like_blogs_total_page = total_pages entry_list","next_page_variable = None entry_list = self._response_data[\"d\"][\"entrylist\"] if len(entry_list) > 0: for personal_blog in","None and self._response_data[\"m\"] == \"success\" ): logger.info(f\"当前正在获取第{page_no + 1}页的数据!\") if page_no == 0:","is not None and self._response_data[\"m\"] == \"success\" ): logger.info(f\"当前正在获取第{page_no + 1}页的数据!\") if page_no","self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\"获取个人博客数据成功!\") else: logger.error(\"查询个人博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException()","self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies: Optional[str] = None) ->","{err}\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\"token\"] self._login_uid =","= self._response_data[\"user\"][\"username\"] description = self._response_data[\"user\"][\"selfDescription\"] avatar_img = self._response_data[\"user\"][\"avatarLarge\"] followee = self._response_data[\"user\"][\"followeesCount\"] follower =","if ( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not True ): logger.error(f\"当前掘金账号登录状态: 已退出!\")","for d in login_params if \"token\" in d][ 0 ].replace(\"token=\", \"\") self._login_client_id =","rest_count = total_count % 20 if rest_count != 0: total_pages += 1 self._like_blogs_total_page","= self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \"\": self._response_data = response.json() if self._response_data is","avatar_img = self._response_data[\"user\"][\"avatarLarge\"] followee = self._response_data[\"user\"][\"followeesCount\"] follower = self._response_data[\"user\"][\"followersCount\"] like_blogs = self._response_data[\"user\"][\"collectedEntriesCount\"] personal_data:","if ( self._response_data is not None and self._response_data[\"m\"] == \"success\" ): logger.info(f\"当前正在获取第{page_no +","= None self._response_data = None self._blogs_data: List = [] self._like_blogs_data: List = []","PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from spiders import","total_pages = total_count // 20 rest_count = total_count % 20 if rest_count !=","self._login_password = password self._spider_name: str = f\"juejin:{self._login_username}\" self._login_cookies: Optional[str] = None self._login_token: Optional[str]","Optional[Tuple[str, Dict]]: \"\"\" 解析用户名 :return: 结果 \"\"\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username)","self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \"\"\" 解析用户名 :return: 结果 \"\"\"","not None: req_data.update(before=next_params) url_params: str = \"\" for index, data in enumerate(req_data.items()): if","\"https://user-like-wrapper-ms.juejin.im/v1/user\" self._task_id = task_id self._login_username = username self._login_password = password self._spider_name: str =","): logger.info(f\"当前正在获取第{page_no + 1}页的数据!\") if page_no == 0: total_count = self._response_data[\"d\"][\"total\"] total_pages =","\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\" self._like_blogs_url = \"https://user-like-wrapper-ms.juejin.im/v1/user\" self._task_id = task_id self._login_username = username self._login_password = password","for d in login_params if \"device_id\" in d ][0].replace(\"device_id=\", \"\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs )","= self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is","self._like_blogs_url = \"https://user-like-wrapper-ms.juejin.im/v1/user\" self._task_id = task_id self._login_username = username self._login_password = password self._spider_name:","None def parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method ==","and self._response_data[\"m\"] == \"success\" ): logger.info(f\"当前正在获取第{page_no + 1}页的数据!\") if page_no == 0: total_count","20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\"获取个人博客数据成功!\") else: logger.error(\"查询个人博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) )","raise ParseDataException() def _test_cookies(self, cookies: Optional[str] = None) -> bool: params = self.get_data(spider_name=f\"{self._spider_name}:params\")","next_params is not None: req_data.update(before=next_params) url_params: str = \"\" for index, data in","config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException","enumerate(req_data.items()): if index == 0: url_params += f\"?{data[0]}={data[1]}\" else: url_params += f\"&{data[0]}={data[1]}\" blogs_url:","is not None: login_data.update(phoneNumber=self._login_username) return f\"{self._main_url}/phoneNumber\", login_data if email_login is not None: login_data.update(email=self._login_username)","check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import","None: login_data.update(email=self._login_username) return f\"{self._main_url}/email\", login_data return None def parse_data_with_method(self, method: str): if method","description = self._response_data[\"user\"][\"selfDescription\"] avatar_img = self._response_data[\"user\"][\"avatarLarge\"] followee = self._response_data[\"user\"][\"followeesCount\"] follower = self._response_data[\"user\"][\"followersCount\"] like_blogs","check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id:","for index, data in enumerate(req_data.items()): if index == 0: url_params += f\"?{data[0]}={data[1]}\" else:","self._response_data[\"clientId\"] # 重要参数持久化 params: str = f\"?src=web&uid={self._login_uid}\" f\"&token={self._login_token}\" f\"&device_id={self._login_client_id}\" f\"¤t_uid={self._login_uid}\" self.set_data(spider_name=f\"{self._spider_name}:params\", data=params) #","if phone_login is None and email_login is None: raise ValueError(\"Your login username is","get_result.split(\"&\")[1:-1] self._login_uid = [d for d in login_params if \"uid\" in d][ 0","= { \"blogId\": personal_blog[\"objectId\"], \"blogTitle\": personal_blog[\"title\"], \"blogHref\": personal_blog[\"originalUrl\"], \"blogViewers\": personal_blog[\"viewsCount\"], \"blogCreateTime\": blog_create_time, }","None and self._response_data[\"m\"] == \"ok\": next_page_variable = None entry_list = self._response_data[\"d\"][\"entrylist\"] if len(entry_list)","str, username: str, password: str): self._main_url = \"https://juejin.im/auth/type\" self._blogs_url = \"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\" self._like_blogs_url =",") blog_data: Dict = { \"blogId\": personal_blog[\"objectId\"], \"blogTitle\": personal_blog[\"title\"], \"blogHref\": personal_blog[\"originalUrl\"], \"blogViewers\": personal_blog[\"viewsCount\"],","from utils.str_utils import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt","= task_id self._login_username = username self._login_password = password self._spider_name: str = f\"juejin:{self._login_username}\" self._login_cookies:","self._response_data[\"user\"][\"avatarLarge\"] followee = self._response_data[\"user\"][\"followeesCount\"] follower = self._response_data[\"user\"][\"followersCount\"] like_blogs = self._response_data[\"user\"][\"collectedEntriesCount\"] personal_data: Dict =","illegal!\") if phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\"{self._main_url}/phoneNumber\", login_data if email_login is","username = self._response_data[\"user\"][\"username\"] description = self._response_data[\"user\"][\"selfDescription\"] avatar_img = self._response_data[\"user\"][\"avatarLarge\"] followee = self._response_data[\"user\"][\"followeesCount\"] follower","self._login_client_id, \"token\": self._login_token, \"targetUid\": self._login_uid, \"type\": \"post\", \"limit\": \"20\", \"order\": \"createdAt\", } if","method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is None: login_url, login_data =","None: login_url, login_data = self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\"POST\", json=login_data, )","} self._like_blogs_data.append(blog_data) page_no += 1 if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5)","== 0: total_count = self._response_data[\"d\"][\"total\"] total_pages = total_count // 20 rest_count = total_count","[] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str,","None self._blogs_data: List = [] self._like_blogs_data: List = [] self._like_blogs_total_page: int = 0","if \"device_id\" in d ][0].replace(\"device_id=\", \"\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err:","is illegal!\") if phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\"{self._main_url}/phoneNumber\", login_data if email_login","Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code !=","\"createdAt\", } if next_params is not None: req_data.update(before=next_params) url_params: str = \"\" for","f\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\" test_request_headers: Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if (","None): req_data: dict = { \"src\": \"web\", \"uid\": self._login_uid, \"device_id\": self._login_client_id, \"token\": self._login_token,","entry_data[\"title\"], \"blogHref\": entry_data[\"originalUrl\"], \"blogViewers\": entry_data[\"viewsCount\"], \"blogCreateTime\": datetime_str_change_fmt( time_str=entry_data[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ), } self._like_blogs_data.append(blog_data) page_no","rest_count != 0: total_pages += 1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\"d\"][\"entryList\"] if","or check_is_json(test_response.content.decode()) is not True ): logger.error(f\"当前掘金账号登录状态: 已退出!\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response =","get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\"&\")[1:-1] self._login_uid =","= None entry_list = self._response_data[\"d\"][\"entrylist\"] if len(entry_list) > 0: for personal_blog in entry_list:","\"blogViewers\": entry_data[\"viewsCount\"], \"blogCreateTime\": datetime_str_change_fmt( time_str=entry_data[\"createdAt\"], prev_fmt=\"%Y-%m-%dT%H:%M:%S.%fZ\", ), } self._like_blogs_data.append(blog_data) page_no += 1 if","and email_login is None: raise ValueError(\"Your login username is illegal!\") if phone_login is","login_url, login_data = self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\"POST\", json=login_data, ) if","self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\"&\")[1:-1] self._login_uid = [d for d","= username self._login_password = password self._spider_name: str = f\"juejin:{self._login_username}\" self._login_cookies: Optional[str] = None","str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif","self.set_data(spider_name=f\"{self._spider_name}:params\", data=params) # 个人数据 username = self._response_data[\"user\"][\"username\"] description = self._response_data[\"user\"][\"selfDescription\"] avatar_img = self._response_data[\"user\"][\"avatarLarge\"]","log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str, password: str): self._main_url","+= f\"&{data[0]}={data[1]}\" blogs_url: str = f\"{self._blogs_url}{url_params}\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() !=","\"\" for index, data in enumerate(req_data.items()): if index == 0: url_params += f\"?{data[0]}={data[1]}\"","req_data: dict = { \"src\": \"web\", \"uid\": self._login_uid, \"device_id\": self._login_client_id, \"token\": self._login_token, \"targetUid\":","response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult","str = f\"juejin:{self._login_username}\" self._login_cookies: Optional[str] = None self._login_token: Optional[str] = None self._login_uid: Optional[str]","self.make_request( url=login_url, headers=self._common_headers, method=\"POST\", json=login_data, ) if response.content.decode() != \"\": logger.info(\"登录成功!\") self._response_data =","login_params = get_result.split(\"&\")[1:-1] self._login_uid = [d for d in login_params if \"uid\" in","req_data.update(before=next_params) url_params: str = \"\" for index, data in enumerate(req_data.items()): if index ==","utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType,","in entry_list: if entry_data is None: continue blog_data: Dict = { \"blogId\": entry_data[\"objectId\"],","login_data: Dict = {\"password\": self._login_password} if phone_login is None and email_login is None:","1}页的数据!\") if page_no == 0: total_count = self._response_data[\"d\"][\"total\"] total_pages = total_count // 20","entry_data is None: continue blog_data: Dict = { \"blogId\": entry_data[\"objectId\"], \"blogTitle\": entry_data[\"title\"], \"blogHref\":","# 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\"查询个人点赞博客失败!\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self,","personal_blog[\"title\"], \"blogHref\": personal_blog[\"originalUrl\"], \"blogViewers\": personal_blog[\"viewsCount\"], \"blogCreateTime\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\"verifyCreatedAt\"] if",") if response.content.decode() != \"\": logger.info(\"登录成功!\") self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items()","# TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data","Exception as err: logger.error(f\"解析 Redis 返回数据失败! 错误原因: {err}\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self):","False test_json_response = test_response.json() if test_json_response[\"s\"] == 1: logger.info(f\"当前掘金账号为: {self._login_username}, 状态: 已登录\") return","= personal_blog[\"verifyCreatedAt\"] if self._response_data[\"d\"][\"total\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\"获取个人博客数据成功!\") else:","for d in login_params if \"uid\" in d][ 0 ].replace(\"uid=\", \"\") self._login_token ="],"string":"[\n \"self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data: List\",\n \"login_params if \\\"uid\\\" in d][ 0 ].replace(\\\"uid=\\\", \\\"\\\") self._login_token = [d for d\",\n \"next_page_variable = personal_blog[\\\"verifyCreatedAt\\\"] if self._response_data[\\\"d\\\"][\\\"total\\\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\\\"获取个人博客数据成功!\\\")\",\n \"错误原因: {err}\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\\\"token\\\"] self._login_uid\",\n \"!= 0: total_pages += 1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\\\"d\\\"][\\\"entryList\\\"] if len(entry_list)\",\n \"def _check_username(self) -> Optional[Tuple[str, Dict]]: \\\"\\\"\\\" 解析用户名 :return: 结果 \\\"\\\"\\\" phone_login = check_is_phone_number(data=self._login_username)\",\n \"test_json_response[\\\"s\\\"] == 1: logger.info(f\\\"当前掘金账号为: {self._login_username}, 状态: 已登录\\\") return True else: logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") return\",\n \"self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\\\"token\\\"] self._login_uid = self._response_data[\\\"userId\\\"]\",\n \"params = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if params is None: return False test_user_url: str = f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\"\",\n \"= check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\\\"password\\\": self._login_password} if phone_login is\",\n \"重要参数持久化 params: str = f\\\"?src=web&uid={self._login_uid}\\\" f\\\"&token={self._login_token}\\\" f\\\"&device_id={self._login_client_id}\\\" f\\\"¤t_uid={self._login_uid}\\\" self.set_data(spider_name=f\\\"{self._spider_name}:params\\\", data=params) # 个人数据 username\",\n \"username is illegal!\\\") if phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\\\"{self._main_url}/phoneNumber\\\", login_data if\",\n \"200 or check_is_json(test_response.content.decode()) is not True ): logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response\",\n \"followee = self._response_data[\\\"user\\\"][\\\"followeesCount\\\"] follower = self._response_data[\\\"user\\\"][\\\"followersCount\\\"] like_blogs = self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"] personal_data: Dict = {\",\n \"login_params if \\\"device_id\\\" in d ][0].replace(\\\"device_id=\\\", \\\"\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as\",\n \"CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\\\"登录失败!\\\")\",\n \"\\\"blogViewers\\\": personal_blog[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\\\"verifyCreatedAt\\\"] if self._response_data[\\\"d\\\"][\\\"total\\\"] > 20:\",\n \"= { \\\"src\\\": \\\"web\\\", \\\"uid\\\": self._login_uid, \\\"device_id\\\": self._login_client_id, \\\"token\\\": self._login_token, \\\"targetUid\\\": self._login_uid, \\\"type\\\":\",\n \") raise ParseDataException() def _test_cookies(self, cookies: Optional[str] = None) -> bool: params =\",\n \"url=test_user_url, headers=test_request_headers ) if ( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not True\",\n \"List = [] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self)\",\n \"import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5,\",\n \"f\\\"&{data[0]}={data[1]}\\\" blogs_url: str = f\\\"{self._blogs_url}{url_params}\\\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\":\",\n \"self._response_data is not None and self._response_data[\\\"m\\\"] == \\\"success\\\" ): logger.info(f\\\"当前正在获取第{page_no + 1}页的数据!\\\") if\",\n \"f\\\"{self._blogs_url}{url_params}\\\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data = response.json() if\",\n \"spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\\\"登录失败!\\\") raise LoginException() else: get_result: str\",\n \"[ d for d in login_params if \\\"device_id\\\" in d ][0].replace(\\\"device_id=\\\", \\\"\\\") self.parse_data_with_method(\",\n \"utils.exception_utils import LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import\",\n \"\\\"blogTitle\\\": entry_data[\\\"title\\\"], \\\"blogHref\\\": entry_data[\\\"originalUrl\\\"], \\\"blogViewers\\\": entry_data[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": datetime_str_change_fmt( time_str=entry_data[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ), } self._like_blogs_data.append(blog_data)\",\n \"= \\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\" self._like_blogs_url = \\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\" self._task_id = task_id self._login_username = username self._login_password =\",\n \"in login_params if \\\"token\\\" in d][ 0 ].replace(\\\"token=\\\", \\\"\\\") self._login_client_id = [ d\",\n \"\\\"token\\\": self._login_token, \\\"targetUid\\\": self._login_uid, \\\"type\\\": \\\"post\\\", \\\"limit\\\": \\\"20\\\", \\\"order\\\": \\\"createdAt\\\", } if next_params\",\n \"response.content.decode() != \\\"\\\": self._response_data = response.json() if self._response_data is not None and self._response_data[\\\"m\\\"]\",\n \"self._response_data = response.json() if self._response_data is not None and self._response_data[\\\"m\\\"] == \\\"ok\\\": next_page_variable\",\n \"20 if rest_count != 0: total_pages += 1 self._like_blogs_total_page = total_pages entry_list =\",\n \"= LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str,\",\n \"LoginException() def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str = f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\" self._common_headers.update( {\",\n \"entry_list: if entry_data is None: continue blog_data: Dict = { \\\"blogId\\\": entry_data[\\\"objectId\\\"], \\\"blogTitle\\\":\",\n \"return False test_json_response = test_response.json() if test_json_response[\\\"s\\\"] == 1: logger.info(f\\\"当前掘金账号为: {self._login_username}, 状态: 已登录\\\")\",\n \"if email_login is not None: login_data.update(email=self._login_username) return f\\\"{self._main_url}/email\\\", login_data return None def parse_data_with_method(self,\",\n \"self._login_client_id = [ d for d in login_params if \\\"device_id\\\" in d ][0].replace(\\\"device_id=\\\",\",\n \"for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ) blog_data: Dict =\",\n \"\\\"blogHref\\\": personal_blog[\\\"originalUrl\\\"], \\\"blogViewers\\\": personal_blog[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\\\"verifyCreatedAt\\\"] if self._response_data[\\\"d\\\"][\\\"total\\\"]\",\n \"if self._response_data[\\\"d\\\"][\\\"total\\\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\\\"获取个人博客数据成功!\\\") else: logger.error(\\\"查询个人博客失败!\\\") self.update_task_status(\",\n \"str = f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\" self._common_headers.update( { \\\"X-Juejin-Client\\\": str(self._login_client_id), \\\"X-Juejin-Src\\\": \\\"web\\\", \\\"X-Juejin-Token\\\": self._login_token, \\\"X-Juejin-Uid\\\": self._login_uid,\",\n \"个人数据 username = self._response_data[\\\"user\\\"][\\\"username\\\"] description = self._response_data[\\\"user\\\"][\\\"selfDescription\\\"] avatar_img = self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"] followee = self._response_data[\\\"user\\\"][\\\"followeesCount\\\"]\",\n \"logger.info(\\\"获取个人点赞博客成功!\\\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\\\"查询个人点赞博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def\",\n \"# logger.debug(self._like_blogs_data) logger.debug(f\\\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\\\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\\\"获取个人点赞博客成功!\\\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else:\",\n \"= datetime_str_change_fmt( time_str=personal_blog[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ) blog_data: Dict = { \\\"blogId\\\": personal_blog[\\\"objectId\\\"], \\\"blogTitle\\\": personal_blog[\\\"title\\\"],\",\n \"ParseDataException() def _test_cookies(self, cookies: Optional[str] = None) -> bool: params = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if\",\n \"total_count % 20 if rest_count != 0: total_pages += 1 self._like_blogs_total_page = total_pages\",\n \"\\\"\\\"\\\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\\\"password\\\": self._login_password} if\",\n \"str): self._main_url = \\\"https://juejin.im/auth/type\\\" self._blogs_url = \\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\" self._like_blogs_url = \\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\" self._task_id = task_id\",\n \"method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method ==\",\n \").to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\\\"登录失败!\\\") raise LoginException()\",\n \"Optional[str] = None) -> bool: params = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if params is None: return\",\n \"import LogManager from utils.str_utils import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils\",\n \"else: try: login_params = get_result.split(\\\"&\\\")[1:-1] self._login_uid = [d for d in login_params if\",\n \"headers=test_request_headers ) if ( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not True ):\",\n \"== 0: url_params += f\\\"?{data[0]}={data[1]}\\\" else: url_params += f\\\"&{data[0]}={data[1]}\\\" blogs_url: str = f\\\"{self._blogs_url}{url_params}\\\"\",\n \"d in login_params if \\\"device_id\\\" in d ][0].replace(\\\"device_id=\\\", \\\"\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except\",\n \"else: get_result: str = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else:\",\n \"( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not True ): logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") self._async_task.remove_async_scheduler(job_id=self._spider_name)\",\n \"self._response_data[\\\"m\\\"] == \\\"ok\\\": next_page_variable = None entry_list = self._response_data[\\\"d\\\"][\\\"entrylist\\\"] if len(entry_list) > 0:\",\n \"return None def parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method\",\n \"self._response_data[\\\"d\\\"][\\\"entryList\\\"] if len(entry_list) > 0: for entry_data in entry_list: if entry_data is None:\",\n \"= \\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\" self._task_id = task_id self._login_username = username self._login_password = password self._spider_name: str\",\n \"check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id: str,\",\n \"{ \\\"blogId\\\": personal_blog[\\\"objectId\\\"], \\\"blogTitle\\\": personal_blog[\\\"title\\\"], \\\"blogHref\\\": personal_blog[\\\"originalUrl\\\"], \\\"blogViewers\\\": personal_blog[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": blog_create_time, } self._blogs_data.append(blog_data)\",\n \"[d for d in login_params if \\\"uid\\\" in d][ 0 ].replace(\\\"uid=\\\", \\\"\\\") self._login_token\",\n \"= 0): like_blogs_url: str = f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\" self._common_headers.update( { \\\"X-Juejin-Client\\\": str(self._login_client_id), \\\"X-Juejin-Src\\\": \\\"web\\\", \\\"X-Juejin-Token\\\":\",\n \"is not None: req_data.update(before=next_params) url_params: str = \\\"\\\" for index, data in enumerate(req_data.items()):\",\n \"is None: raise ValueError(\\\"Your login username is illegal!\\\") if phone_login is not None:\",\n \"response.content.decode() != \\\"\\\": logger.info(\\\"登录成功!\\\") self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies)\",\n \"self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\\\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\\\") self.data_model.set_personal_like_blogs_data(\",\n \"if rest_count != 0: total_pages += 1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\\\"d\\\"][\\\"entryList\\\"]\",\n \"Optional[str] = None): req_data: dict = { \\\"src\\\": \\\"web\\\", \\\"uid\\\": self._login_uid, \\\"device_id\\\": self._login_client_id,\",\n \"\\\"limit\\\": \\\"20\\\", \\\"order\\\": \\\"createdAt\\\", } if next_params is not None: req_data.update(before=next_params) url_params: str\",\n \"follower, \\\"likeBlogs\\\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None):\",\n \"return f\\\"{self._main_url}/email\\\", login_data return None def parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult:\",\n \"def login(self): if self._login_cookies is None: login_url, login_data = self._check_username() response = self.make_request(\",\n \"self._login_password} if phone_login is None and email_login is None: raise ValueError(\\\"Your login username\",\n \"self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code != 200 or\",\n \"self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\\\"POST\\\", json=login_data, ) if response.content.decode() != \\\"\\\":\",\n \"from utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider):\",\n \"= self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \\\"\\\"\\\" 解析用户名 :return: 结果 \\\"\\\"\\\" phone_login\",\n \"} logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict =\",\n \"= 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \\\"\\\"\\\" 解析用户名\",\n \"\\\"\\\": logger.info(\\\"登录成功!\\\") self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name,\",\n \"= self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data = response.json() if ( self._response_data\",\n \"+ 1}页的数据!\\\") if page_no == 0: total_count = self._response_data[\\\"d\\\"][\\\"total\\\"] total_pages = total_count //\",\n \"= None self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data: List = []\",\n \"\\\"blogId\\\": entry_data[\\\"objectId\\\"], \\\"blogTitle\\\": entry_data[\\\"title\\\"], \\\"blogHref\\\": entry_data[\\\"originalUrl\\\"], \\\"blogViewers\\\": entry_data[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": datetime_str_change_fmt( time_str=entry_data[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ),\",\n \"Optional[str] = None self._response_data = None self._blogs_data: List = [] self._like_blogs_data: List =\",\n \"utils.str_utils import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from\",\n \"LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str, password:\",\n \"f\\\"{self._main_url}/phoneNumber\\\", login_data if email_login is not None: login_data.update(email=self._login_username) return f\\\"{self._main_url}/email\\\", login_data return None\",\n \"已退出!\\\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if test_json_response[\\\"s\\\"] == 1: logger.info(f\\\"当前掘金账号为: {self._login_username},\",\n \"headers=self._common_headers, method=\\\"POST\\\", json=login_data, ) if response.content.decode() != \\\"\\\": logger.info(\\\"登录成功!\\\") self._response_data = response.json() self._login_cookies\",\n \"\\\"X-Juejin-Uid\\\": self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data\",\n \"Optional[str] = None self._login_token: Optional[str] = None self._login_uid: Optional[str] = None self._login_client_id: Optional[str]\",\n \"password self._spider_name: str = f\\\"juejin:{self._login_username}\\\" self._login_cookies: Optional[str] = None self._login_token: Optional[str] = None\",\n \"self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def\",\n \"logger.error(\\\"查询个人点赞博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies: Optional[str] = None)\",\n \") raise LoginException() def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str = f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\"\",\n \"\\\"https://juejin.im/auth/type\\\" self._blogs_url = \\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\" self._like_blogs_url = \\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\" self._task_id = task_id self._login_username = username\",\n \"= CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else:\",\n \") if ( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not True ): logger.error(f\\\"当前掘金账号登录状态:\",\n \"blog_data: Dict = { \\\"blogId\\\": personal_blog[\\\"objectId\\\"], \\\"blogTitle\\\": personal_blog[\\\"title\\\"], \\\"blogHref\\\": personal_blog[\\\"originalUrl\\\"], \\\"blogViewers\\\": personal_blog[\\\"viewsCount\\\"], \\\"blogCreateTime\\\":\",\n \"email_login is not None: login_data.update(email=self._login_username) return f\\\"{self._main_url}/email\\\", login_data return None def parse_data_with_method(self, method:\",\n \"self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data =\",\n \"self._task_id = task_id self._login_username = username self._login_password = password self._spider_name: str = f\\\"juejin:{self._login_username}\\\"\",\n \"task_id self._login_username = username self._login_password = password self._spider_name: str = f\\\"juejin:{self._login_username}\\\" self._login_cookies: Optional[str]\",\n \"phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\\\"{self._main_url}/phoneNumber\\\", login_data if email_login is not None:\",\n \"None: raise ValueError(\\\"Your login username is illegal!\\\") if phone_login is not None: login_data.update(phoneNumber=self._login_username)\",\n \"self._like_blogs_data: List = [] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def\",\n \"Optional[str] = None self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None self._response_data =\",\n \"> 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\\\"获取个人博客数据成功!\\\") else: logger.error(\\\"查询个人博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL)\",\n \"\\\"blogHref\\\": entry_data[\\\"originalUrl\\\"], \\\"blogViewers\\\": entry_data[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": datetime_str_change_fmt( time_str=entry_data[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ), } self._like_blogs_data.append(blog_data) page_no +=\",\n \"-> Optional[Tuple[str, Dict]]: \\\"\\\"\\\" 解析用户名 :return: 结果 \\\"\\\"\\\" phone_login = check_is_phone_number(data=self._login_username) email_login =\",\n \"\\\"\\\"\\\" 解析用户名 :return: 结果 \\\"\\\"\\\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict\",\n \"logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\\\"登录失败!\\\") raise LoginException() else:\",\n \"+= 1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\\\"d\\\"][\\\"entryList\\\"] if len(entry_list) > 0: for\",\n \"datetime_str_change_fmt( time_str=personal_blog[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ) blog_data: Dict = { \\\"blogId\\\": personal_blog[\\\"objectId\\\"], \\\"blogTitle\\\": personal_blog[\\\"title\\\"], \\\"blogHref\\\":\",\n \"f\\\"¤t_uid={self._login_uid}\\\" self.set_data(spider_name=f\\\"{self._spider_name}:params\\\", data=params) # 个人数据 username = self._response_data[\\\"user\\\"][\\\"username\\\"] description = self._response_data[\\\"user\\\"][\\\"selfDescription\\\"] avatar_img =\",\n \"method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if\",\n \"\\\"blogId\\\": personal_blog[\\\"objectId\\\"], \\\"blogTitle\\\": personal_blog[\\\"title\\\"], \\\"blogHref\\\": personal_blog[\\\"originalUrl\\\"], \\\"blogViewers\\\": personal_blog[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable\",\n \"raise ValueError(\\\"Your login username is illegal!\\\") if phone_login is not None: login_data.update(phoneNumber=self._login_username) return\",\n \"= self.make_request( url=login_url, headers=self._common_headers, method=\\\"POST\\\", json=login_data, ) if response.content.decode() != \\\"\\\": logger.info(\\\"登录成功!\\\") self._response_data\",\n \"= total_count // 20 rest_count = total_count % 20 if rest_count != 0:\",\n \"} ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data = response.json()\",\n \"for entry_data in entry_list: if entry_data is None: continue blog_data: Dict = {\",\n \"email_login is None: raise ValueError(\\\"Your login username is illegal!\\\") if phone_login is not\",\n \"not None: login_data.update(phoneNumber=self._login_username) return f\\\"{self._main_url}/phoneNumber\\\", login_data if email_login is not None: login_data.update(email=self._login_username) return\",\n \"try: login_params = get_result.split(\\\"&\\\")[1:-1] self._login_uid = [d for d in login_params if \\\"uid\\\"\",\n \"if params is None: return False test_user_url: str = f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\" test_request_headers: Dict =\",\n \"= [d for d in login_params if \\\"token\\\" in d][ 0 ].replace(\\\"token=\\\", \\\"\\\")\",\n \"str = f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\" test_request_headers: Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers )\",\n \"后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\\\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\\\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\\\"获取个人点赞博客成功!\\\")\",\n \"self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\\\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\\\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\\\"获取个人点赞博客成功!\\\") # 任务末尾\",\n \"= self._response_data[\\\"d\\\"][\\\"entrylist\\\"] if len(entry_list) > 0: for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt(\",\n \"d][ 0 ].replace(\\\"uid=\\\", \\\"\\\") self._login_token = [d for d in login_params if \\\"token\\\"\",\n \"[d for d in login_params if \\\"token\\\" in d][ 0 ].replace(\\\"token=\\\", \\\"\\\") self._login_client_id\",\n \"login_params if \\\"token\\\" in d][ 0 ].replace(\\\"token=\\\", \\\"\\\") self._login_client_id = [ d for\",\n \"= [] self._like_blogs_data: List = [] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies =\",\n \"_test_cookies(self, cookies: Optional[str] = None) -> bool: params = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if params is\",\n \"\\\"\\\": self._response_data = response.json() if self._response_data is not None and self._response_data[\\\"m\\\"] == \\\"ok\\\":\",\n \"= self._response_data[\\\"d\\\"][\\\"total\\\"] total_pages = total_count // 20 rest_count = total_count % 20 if\",\n \"cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\\\"登录失败!\\\") raise LoginException() else: get_result: str =\",\n \"False test_user_url: str = f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\" test_request_headers: Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url,\",\n \"\\\"X-Juejin-Token\\\": self._login_token, \\\"X-Juejin-Uid\\\": self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() !=\",\n \"blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\\\"verifyCreatedAt\\\"] if self._response_data[\\\"d\\\"][\\\"total\\\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else:\",\n \"f\\\"{self._main_url}/email\\\", login_data return None def parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data()\",\n \"= self._response_data[\\\"token\\\"] self._login_uid = self._response_data[\\\"userId\\\"] self._login_client_id = self._response_data[\\\"clientId\\\"] # 重要参数持久化 params: str =\",\n \") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\\\"登录失败!\\\") raise LoginException() else: get_result: str = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\")\",\n \"else: url_params += f\\\"&{data[0]}={data[1]}\\\" blogs_url: str = f\\\"{self._blogs_url}{url_params}\\\" response = self.make_request(url=blogs_url, headers=self._common_headers) if\",\n \"0: total_pages += 1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\\\"d\\\"][\\\"entryList\\\"] if len(entry_list) >\",\n \"self._like_blogs_data.append(blog_data) page_no += 1 if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no)\",\n \"= response.json() if ( self._response_data is not None and self._response_data[\\\"m\\\"] == \\\"success\\\" ):\",\n \"].replace(\\\"uid=\\\", \\\"\\\") self._login_token = [d for d in login_params if \\\"token\\\" in d][\",\n \"> 0: for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ) blog_data:\",\n \"personal_blog[\\\"originalUrl\\\"], \\\"blogViewers\\\": personal_blog[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\\\"verifyCreatedAt\\\"] if self._response_data[\\\"d\\\"][\\\"total\\\"] >\",\n \"task_id: str, username: str, password: str): self._main_url = \\\"https://juejin.im/auth/type\\\" self._blogs_url = \\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\" self._like_blogs_url\",\n \"if response.content.decode() != \\\"\\\": self._response_data = response.json() if ( self._response_data is not None\",\n \") logger.info(\\\"获取个人点赞博客成功!\\\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\\\"查询个人点赞博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException()\",\n \"utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def\",\n \"TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\\\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\\\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data )\",\n \"index, data in enumerate(req_data.items()): if index == 0: url_params += f\\\"?{data[0]}={data[1]}\\\" else: url_params\",\n \"解析用户名 :return: 结果 \\\"\\\"\\\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict =\",\n \"if response.content.decode() != \\\"\\\": self._response_data = response.json() if self._response_data is not None and\",\n \"{\\\"password\\\": self._login_password} if phone_login is None and email_login is None: raise ValueError(\\\"Your login\",\n \"self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\\\"登录失败!\\\") raise LoginException() else: get_result:\",\n \"task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str\",\n \"self._response_data[\\\"d\\\"][\\\"total\\\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\\\"获取个人博客数据成功!\\\") else: logger.error(\\\"查询个人博客失败!\\\") self.update_task_status( task_id=self._task_id,\",\n \"f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\" self._common_headers.update( { \\\"X-Juejin-Client\\\": str(self._login_client_id), \\\"X-Juejin-Src\\\": \\\"web\\\", \\\"X-Juejin-Token\\\": self._login_token, \\\"X-Juejin-Uid\\\": self._login_uid, } )\",\n \"self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\\\"获取个人点赞博客成功!\\\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\\\"查询个人点赞博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) )\",\n \"logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if test_json_response[\\\"s\\\"] == 1: logger.info(f\\\"当前掘金账号为:\",\n \"\\\"blogCreateTime\\\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\\\"verifyCreatedAt\\\"] if self._response_data[\\\"d\\\"][\\\"total\\\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable)\",\n \"json=login_data, ) if response.content.decode() != \\\"\\\": logger.info(\\\"登录成功!\\\") self._response_data = response.json() self._login_cookies = CookieUtils(\",\n \"+= f\\\"?{data[0]}={data[1]}\\\" else: url_params += f\\\"&{data[0]}={data[1]}\\\" blogs_url: str = f\\\"{self._blogs_url}{url_params}\\\" response = self.make_request(url=blogs_url,\",\n \"page_no: int = 0): like_blogs_url: str = f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\" self._common_headers.update( { \\\"X-Juejin-Client\\\": str(self._login_client_id), \\\"X-Juejin-Src\\\":\",\n \"method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\\\"登录失败!\\\") raise LoginException() else: get_result: str = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if get_result\",\n \"\\\"web\\\", \\\"X-Juejin-Token\\\": self._login_token, \\\"X-Juejin-Uid\\\": self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode()\",\n \"if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\\\"&\\\")[1:-1] self._login_uid\",\n \"response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data = response.json() if self._response_data\",\n \"logger.debug(self._like_blogs_data) logger.debug(f\\\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\\\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\\\"获取个人点赞博客成功!\\\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\\\"查询个人点赞博客失败!\\\")\",\n \"self._blogs_data: List = [] self._like_blogs_data: List = [] self._like_blogs_total_page: int = 0 super().__init__()\",\n \"\\\"20\\\", \\\"order\\\": \\\"createdAt\\\", } if next_params is not None: req_data.update(before=next_params) url_params: str =\",\n \"self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data = response.json() if self._response_data is not\",\n \"0: for entry_data in entry_list: if entry_data is None: continue blog_data: Dict =\",\n \"username: str, password: str): self._main_url = \\\"https://juejin.im/auth/type\\\" self._blogs_url = \\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\" self._like_blogs_url = \\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\"\",\n \"List = [] self._like_blogs_data: List = [] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies\",\n \"self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\\\"登录失败!\\\") raise LoginException() else: get_result: str = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if\",\n \"time_str=entry_data[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ), } self._like_blogs_data.append(blog_data) page_no += 1 if page_no <= self._like_blogs_total_page: #\",\n \"0 ].replace(\\\"uid=\\\", \\\"\\\") self._login_token = [d for d in login_params if \\\"token\\\" in\",\n \"0 ].replace(\\\"token=\\\", \\\"\\\") self._login_client_id = [ d for d in login_params if \\\"device_id\\\"\",\n \"cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: logger.error(\\\"登录失败!\\\") raise\",\n \"url=login_url, headers=self._common_headers, method=\\\"POST\\\", json=login_data, ) if response.content.decode() != \\\"\\\": logger.info(\\\"登录成功!\\\") self._response_data = response.json()\",\n \"entry_data[\\\"objectId\\\"], \\\"blogTitle\\\": entry_data[\\\"title\\\"], \\\"blogHref\\\": entry_data[\\\"originalUrl\\\"], \\\"blogViewers\\\": entry_data[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": datetime_str_change_fmt( time_str=entry_data[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ), }\",\n \"!= 200 or check_is_json(test_response.content.decode()) is not True ): logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False\",\n \"like_blogs_url: str = f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\" self._common_headers.update( { \\\"X-Juejin-Client\\\": str(self._login_client_id), \\\"X-Juejin-Src\\\": \\\"web\\\", \\\"X-Juejin-Token\\\": self._login_token, \\\"X-Juejin-Uid\\\":\",\n \"= None self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None self._response_data = None\",\n \") else: logger.error(\\\"登录失败!\\\") raise LoginException() else: get_result: str = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if get_result is\",\n \"Redis 返回数据失败! 错误原因: {err}\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token =\",\n \"= password self._spider_name: str = f\\\"juejin:{self._login_username}\\\" self._login_cookies: Optional[str] = None self._login_token: Optional[str] =\",\n \"index == 0: url_params += f\\\"?{data[0]}={data[1]}\\\" else: url_params += f\\\"&{data[0]}={data[1]}\\\" blogs_url: str =\",\n \"-> bool: params = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if params is None: return False test_user_url: str\",\n \"self._login_cookies is None: login_url, login_data = self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\\\"POST\\\",\",\n \"<= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\\\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\\\")\",\n \"total_count = self._response_data[\\\"d\\\"][\\\"total\\\"] total_pages = total_count // 20 rest_count = total_count % 20\",\n \"self._response_data is not None and self._response_data[\\\"m\\\"] == \\\"ok\\\": next_page_variable = None entry_list =\",\n \"from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from spiders import BaseSpider,\",\n \"test_request_headers: Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code\",\n \"prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ), } self._like_blogs_data.append(blog_data) page_no += 1 if page_no <= self._like_blogs_total_page: # TODO\",\n \"!= \\\"\\\": self._response_data = response.json() if ( self._response_data is not None and self._response_data[\\\"m\\\"]\",\n \"int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \\\"\\\"\\\"\",\n \"entry_list = self._response_data[\\\"d\\\"][\\\"entrylist\\\"] if len(entry_list) > 0: for personal_blog in entry_list: blog_create_time =\",\n \"f\\\"&device_id={self._login_client_id}\\\" f\\\"¤t_uid={self._login_uid}\\\" self.set_data(spider_name=f\\\"{self._spider_name}:params\\\", data=params) # 个人数据 username = self._response_data[\\\"user\\\"][\\\"username\\\"] description = self._response_data[\\\"user\\\"][\\\"selfDescription\\\"] avatar_img\",\n \"is not True ): logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if\",\n \"if test_json_response[\\\"s\\\"] == 1: logger.info(f\\\"当前掘金账号为: {self._login_username}, 状态: 已登录\\\") return True else: logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\")\",\n \"class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str, password: str): self._main_url = \\\"https://juejin.im/auth/type\\\"\",\n \"= self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\\\"POST\\\", json=login_data, ) if response.content.decode() !=\",\n \"params is None: return False test_user_url: str = f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\" test_request_headers: Dict = self.get_default_headers()\",\n \"1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\\\"d\\\"][\\\"entryList\\\"] if len(entry_list) > 0: for entry_data\",\n \"CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class\",\n \"if response.content.decode() != \\\"\\\": logger.info(\\\"登录成功!\\\") self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str()\",\n \"personal_blog[\\\"objectId\\\"], \\\"blogTitle\\\": personal_blog[\\\"title\\\"], \\\"blogHref\\\": personal_blog[\\\"originalUrl\\\"], \\\"blogViewers\\\": personal_blog[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable =\",\n \"\\\"device_id\\\": self._login_client_id, \\\"token\\\": self._login_token, \\\"targetUid\\\": self._login_uid, \\\"type\\\": \\\"post\\\", \\\"limit\\\": \\\"20\\\", \\\"order\\\": \\\"createdAt\\\", }\",\n \"> 0: for entry_data in entry_list: if entry_data is None: continue blog_data: Dict\",\n \"= {\\\"password\\\": self._login_password} if phone_login is None and email_login is None: raise ValueError(\\\"Your\",\n \"is not None: login_data.update(email=self._login_username) return f\\\"{self._main_url}/email\\\", login_data return None def parse_data_with_method(self, method: str):\",\n \"avatar_img, \\\"followee\\\": followee, \\\"follower\\\": follower, \\\"likeBlogs\\\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self,\",\n \"from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger =\",\n \"None and email_login is None: raise ValueError(\\\"Your login username is illegal!\\\") if phone_login\",\n \"== BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies\",\n \"self._main_url = \\\"https://juejin.im/auth/type\\\" self._blogs_url = \\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\" self._like_blogs_url = \\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\" self._task_id = task_id self._login_username\",\n \"Dict = { \\\"blogId\\\": entry_data[\\\"objectId\\\"], \\\"blogTitle\\\": entry_data[\\\"title\\\"], \\\"blogHref\\\": entry_data[\\\"originalUrl\\\"], \\\"blogViewers\\\": entry_data[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": datetime_str_change_fmt(\",\n \"[] self._like_blogs_data: List = [] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name)\",\n \"self._login_uid = [d for d in login_params if \\\"uid\\\" in d][ 0 ].replace(\\\"uid=\\\",\",\n \"entry_data in entry_list: if entry_data is None: continue blog_data: Dict = { \\\"blogId\\\":\",\n \"phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\\\"password\\\": self._login_password} if phone_login\",\n \"self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\\\"&\\\")[1:-1]\",\n \"None self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data: List = [] self._like_blogs_data:\",\n \"if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method\",\n \"url_params: str = \\\"\\\" for index, data in enumerate(req_data.items()): if index == 0:\",\n \"ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger\",\n \"self._login_token = self._response_data[\\\"token\\\"] self._login_uid = self._response_data[\\\"userId\\\"] self._login_client_id = self._response_data[\\\"clientId\\\"] # 重要参数持久化 params: str\",\n \"= None) -> bool: params = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if params is None: return False\",\n \"len(entry_list) > 0: for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", )\",\n \"test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code != 200 or check_is_json(test_response.content.decode())\",\n \"self._login_cookies: Optional[str] = None self._login_token: Optional[str] = None self._login_uid: Optional[str] = None self._login_client_id:\",\n \"\\\"blogTitle\\\": personal_blog[\\\"title\\\"], \\\"blogHref\\\": personal_blog[\\\"originalUrl\\\"], \\\"blogViewers\\\": personal_blog[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\\\"verifyCreatedAt\\\"]\",\n \"login_data return None def parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif\",\n \"self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is None:\",\n \"elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is None: login_url, login_data\",\n \"BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL )\",\n \"email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\\\"password\\\": self._login_password} if phone_login is None and\",\n \"\\\"likeBlogs\\\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data:\",\n \"else: logger.error(\\\"登录失败!\\\") raise LoginException() else: get_result: str = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if get_result is None:\",\n \"is None: continue blog_data: Dict = { \\\"blogId\\\": entry_data[\\\"objectId\\\"], \\\"blogTitle\\\": entry_data[\\\"title\\\"], \\\"blogHref\\\": entry_data[\\\"originalUrl\\\"],\",\n \"personal_blog[\\\"verifyCreatedAt\\\"] if self._response_data[\\\"d\\\"][\\\"total\\\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\\\"获取个人博客数据成功!\\\") else: logger.error(\\\"查询个人博客失败!\\\")\",\n \"self._login_uid, \\\"device_id\\\": self._login_client_id, \\\"token\\\": self._login_token, \\\"targetUid\\\": self._login_uid, \\\"type\\\": \\\"post\\\", \\\"limit\\\": \\\"20\\\", \\\"order\\\": \\\"createdAt\\\",\",\n \"} self._blogs_data.append(blog_data) next_page_variable = personal_blog[\\\"verifyCreatedAt\\\"] if self._response_data[\\\"d\\\"][\\\"total\\\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data)\",\n \"\\\"followee\\\": followee, \\\"follower\\\": follower, \\\"likeBlogs\\\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params:\",\n \"= f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\" test_request_headers: Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if\",\n \"= total_pages entry_list = self._response_data[\\\"d\\\"][\\\"entryList\\\"] if len(entry_list) > 0: for entry_data in entry_list:\",\n \"self._login_token, \\\"targetUid\\\": self._login_uid, \\\"type\\\": \\\"post\\\", \\\"limit\\\": \\\"20\\\", \\\"order\\\": \\\"createdAt\\\", } if next_params is\",\n \"= { \\\"username\\\": username, \\\"description\\\": description, \\\"avatarImg\\\": avatar_img, \\\"followee\\\": followee, \\\"follower\\\": follower, \\\"likeBlogs\\\":\",\n \"prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ) blog_data: Dict = { \\\"blogId\\\": personal_blog[\\\"objectId\\\"], \\\"blogTitle\\\": personal_blog[\\\"title\\\"], \\\"blogHref\\\": personal_blog[\\\"originalUrl\\\"], \\\"blogViewers\\\":\",\n \"= self._response_data[\\\"user\\\"][\\\"selfDescription\\\"] avatar_img = self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"] followee = self._response_data[\\\"user\\\"][\\\"followeesCount\\\"] follower = self._response_data[\\\"user\\\"][\\\"followersCount\\\"] like_blogs =\",\n \"( self._response_data is not None and self._response_data[\\\"m\\\"] == \\\"success\\\" ): logger.info(f\\\"当前正在获取第{page_no + 1}页的数据!\\\")\",\n \"self._blogs_url = \\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\" self._like_blogs_url = \\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\" self._task_id = task_id self._login_username = username self._login_password\",\n \"logger.info(\\\"登录成功!\\\") self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies\",\n \"headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data = response.json() if self._response_data is not None\",\n \"self._common_headers.update( { \\\"X-Juejin-Client\\\": str(self._login_client_id), \\\"X-Juejin-Src\\\": \\\"web\\\", \\\"X-Juejin-Token\\\": self._login_token, \\\"X-Juejin-Uid\\\": self._login_uid, } ) response\",\n \"get_result: str = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try:\",\n \"parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs()\",\n \"1 if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data)\",\n \"None self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data:\",\n \"formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str, password: str):\",\n \"= self._response_data[\\\"clientId\\\"] # 重要参数持久化 params: str = f\\\"?src=web&uid={self._login_uid}\\\" f\\\"&token={self._login_token}\\\" f\\\"&device_id={self._login_client_id}\\\" f\\\"¤t_uid={self._login_uid}\\\" self.set_data(spider_name=f\\\"{self._spider_name}:params\\\", data=params)\",\n \"= self._response_data[\\\"user\\\"][\\\"followersCount\\\"] like_blogs = self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"] personal_data: Dict = { \\\"username\\\": username, \\\"description\\\": description,\",\n \"BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data()\",\n \"else: # logger.debug(self._like_blogs_data) logger.debug(f\\\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\\\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\\\"获取个人点赞博客成功!\\\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish)\",\n \"返回数据失败! 错误原因: {err}\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\\\"token\\\"]\",\n \"blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ) blog_data: Dict = { \\\"blogId\\\": personal_blog[\\\"objectId\\\"], \\\"blogTitle\\\":\",\n \"\\\"src\\\": \\\"web\\\", \\\"uid\\\": self._login_uid, \\\"device_id\\\": self._login_client_id, \\\"token\\\": self._login_token, \\\"targetUid\\\": self._login_uid, \\\"type\\\": \\\"post\\\", \\\"limit\\\":\",\n \"\\\"X-Juejin-Src\\\": \\\"web\\\", \\\"X-Juejin-Token\\\": self._login_token, \\\"X-Juejin-Uid\\\": self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if\",\n \"personal_data: Dict = { \\\"username\\\": username, \\\"description\\\": description, \\\"avatarImg\\\": avatar_img, \\\"followee\\\": followee, \\\"follower\\\":\",\n \"entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ) blog_data: Dict = { \\\"blogId\\\": personal_blog[\\\"objectId\\\"],\",\n \"int = 0): like_blogs_url: str = f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\" self._common_headers.update( { \\\"X-Juejin-Client\\\": str(self._login_client_id), \\\"X-Juejin-Src\\\": \\\"web\\\",\",\n \"\\\"success\\\" ): logger.info(f\\\"当前正在获取第{page_no + 1}页的数据!\\\") if page_no == 0: total_count = self._response_data[\\\"d\\\"][\\\"total\\\"] total_pages\",\n \"结果 \\\"\\\"\\\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\\\"password\\\": self._login_password}\",\n \"if phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\\\"{self._main_url}/phoneNumber\\\", login_data if email_login is not\",\n \"typing import Dict, List, Tuple, Optional from utils.logger_utils import LogManager from utils.str_utils import\",\n \"self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\\\"查询个人点赞博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies: Optional[str]\",\n \"= None self._blogs_data: List = [] self._like_blogs_data: List = [] self._like_blogs_total_page: int =\",\n \"dict = { \\\"src\\\": \\\"web\\\", \\\"uid\\\": self._login_uid, \\\"device_id\\\": self._login_client_id, \\\"token\\\": self._login_token, \\\"targetUid\\\": self._login_uid,\",\n \"logger.error(\\\"查询个人博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no: int = 0):\",\n \"LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address\",\n \"None: continue blog_data: Dict = { \\\"blogId\\\": entry_data[\\\"objectId\\\"], \\\"blogTitle\\\": entry_data[\\\"title\\\"], \\\"blogHref\\\": entry_data[\\\"originalUrl\\\"], \\\"blogViewers\\\":\",\n \"None: req_data.update(before=next_params) url_params: str = \\\"\\\" for index, data in enumerate(req_data.items()): if index\",\n \"self._response_data[\\\"d\\\"][\\\"total\\\"] total_pages = total_count // 20 rest_count = total_count % 20 if rest_count\",\n \"0: total_count = self._response_data[\\\"d\\\"][\\\"total\\\"] total_pages = total_count // 20 rest_count = total_count %\",\n \"{ \\\"blogId\\\": entry_data[\\\"objectId\\\"], \\\"blogTitle\\\": entry_data[\\\"title\\\"], \\\"blogHref\\\": entry_data[\\\"originalUrl\\\"], \\\"blogViewers\\\": entry_data[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": datetime_str_change_fmt( time_str=entry_data[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\",\",\n \"in login_params if \\\"device_id\\\" in d ][0].replace(\\\"device_id=\\\", \\\"\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception\",\n \"from typing import Dict, List, Tuple, Optional from utils.logger_utils import LogManager from utils.str_utils\",\n \"if self._login_cookies is None: login_url, login_data = self._check_username() response = self.make_request( url=login_url, headers=self._common_headers,\",\n \"self._blogs_data.append(blog_data) next_page_variable = personal_blog[\\\"verifyCreatedAt\\\"] if self._response_data[\\\"d\\\"][\\\"total\\\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data)\",\n \"self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\\\"获取个人博客数据成功!\\\") else: logger.error(\\\"查询个人博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no:\",\n \"logger.info(\\\"获取个人博客数据成功!\\\") else: logger.error(\\\"查询个人博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no: int\",\n \"as err: logger.error(f\\\"解析 Redis 返回数据失败! 错误原因: {err}\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): #\",\n \"in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ) blog_data: Dict = { \\\"blogId\\\":\",\n \"follower = self._response_data[\\\"user\\\"][\\\"followersCount\\\"] like_blogs = self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"] personal_data: Dict = { \\\"username\\\": username, \\\"description\\\":\",\n \"response.json() if ( self._response_data is not None and self._response_data[\\\"m\\\"] == \\\"success\\\" ): logger.info(f\\\"当前正在获取第{page_no\",\n \"logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username:\",\n \"\\\"\\\": self._response_data = response.json() if ( self._response_data is not None and self._response_data[\\\"m\\\"] ==\",\n \"total_pages entry_list = self._response_data[\\\"d\\\"][\\\"entryList\\\"] if len(entry_list) > 0: for entry_data in entry_list: if\",\n \"url_params += f\\\"?{data[0]}={data[1]}\\\" else: url_params += f\\\"&{data[0]}={data[1]}\\\" blogs_url: str = f\\\"{self._blogs_url}{url_params}\\\" response =\",\n \"login_data if email_login is not None: login_data.update(email=self._login_username) return f\\\"{self._main_url}/email\\\", login_data return None def\",\n \"self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult )\",\n \"BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL\",\n \"self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]:\",\n \"time_str=personal_blog[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ) blog_data: Dict = { \\\"blogId\\\": personal_blog[\\\"objectId\\\"], \\\"blogTitle\\\": personal_blog[\\\"title\\\"], \\\"blogHref\\\": personal_blog[\\\"originalUrl\\\"],\",\n \"str(self._login_client_id), \\\"X-Juejin-Src\\\": \\\"web\\\", \\\"X-Juejin-Token\\\": self._login_token, \\\"X-Juejin-Uid\\\": self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers)\",\n \"self._response_data[\\\"d\\\"][\\\"entrylist\\\"] if len(entry_list) > 0: for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\\\"createdAt\\\"],\",\n \"LoginException() else: get_result: str = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult )\",\n \"data=self._like_blogs_data ) logger.info(\\\"获取个人点赞博客成功!\\\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\\\"查询个人点赞博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise\",\n \"else: logger.error(\\\"查询个人博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no: int =\",\n \"# 个人数据 username = self._response_data[\\\"user\\\"][\\\"username\\\"] description = self._response_data[\\\"user\\\"][\\\"selfDescription\\\"] avatar_img = self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"] followee =\",\n \"data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str =\",\n \"].replace(\\\"token=\\\", \\\"\\\") self._login_client_id = [ d for d in login_params if \\\"device_id\\\" in\",\n \"datetime_str_change_fmt( time_str=entry_data[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ), } self._like_blogs_data.append(blog_data) page_no += 1 if page_no <= self._like_blogs_total_page:\",\n \"def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict = { \\\"src\\\": \\\"web\\\", \\\"uid\\\":\",\n \"= { \\\"blogId\\\": entry_data[\\\"objectId\\\"], \\\"blogTitle\\\": entry_data[\\\"title\\\"], \\\"blogHref\\\": entry_data[\\\"originalUrl\\\"], \\\"blogViewers\\\": entry_data[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": datetime_str_change_fmt( time_str=entry_data[\\\"createdAt\\\"],\",\n \"f\\\"?{data[0]}={data[1]}\\\" else: url_params += f\\\"&{data[0]}={data[1]}\\\" blogs_url: str = f\\\"{self._blogs_url}{url_params}\\\" response = self.make_request(url=blogs_url, headers=self._common_headers)\",\n \"_parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict = { \\\"src\\\": \\\"web\\\", \\\"uid\\\": self._login_uid,\",\n \"if len(entry_list) > 0: for entry_data in entry_list: if entry_data is None: continue\",\n \"phone_login is None and email_login is None: raise ValueError(\\\"Your login username is illegal!\\\")\",\n \"= f\\\"juejin:{self._login_username}\\\" self._login_cookies: Optional[str] = None self._login_token: Optional[str] = None self._login_uid: Optional[str] =\",\n \"Dict = {\\\"password\\\": self._login_password} if phone_login is None and email_login is None: raise\",\n \"\\\"uid\\\": self._login_uid, \\\"device_id\\\": self._login_client_id, \\\"token\\\": self._login_token, \\\"targetUid\\\": self._login_uid, \\\"type\\\": \\\"post\\\", \\\"limit\\\": \\\"20\\\", \\\"order\\\":\",\n \"page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\\\"获取到 {len(self._like_blogs_data)}\",\n \"\\\"web\\\", \\\"uid\\\": self._login_uid, \\\"device_id\\\": self._login_client_id, \\\"token\\\": self._login_token, \\\"targetUid\\\": self._login_uid, \\\"type\\\": \\\"post\\\", \\\"limit\\\": \\\"20\\\",\",\n \"self._response_data = response.json() if ( self._response_data is not None and self._response_data[\\\"m\\\"] == \\\"success\\\"\",\n \"= check_is_email_address(data=self._login_username) login_data: Dict = {\\\"password\\\": self._login_password} if phone_login is None and email_login\",\n \"self._login_username = username self._login_password = password self._spider_name: str = f\\\"juejin:{self._login_username}\\\" self._login_cookies: Optional[str] =\",\n \"\\\"username\\\": username, \\\"description\\\": description, \\\"avatarImg\\\": avatar_img, \\\"followee\\\": followee, \\\"follower\\\": follower, \\\"likeBlogs\\\": like_blogs, }\",\n \"\\\"post\\\", \\\"limit\\\": \\\"20\\\", \\\"order\\\": \\\"createdAt\\\", } if next_params is not None: req_data.update(before=next_params) url_params:\",\n \"login_data.update(email=self._login_username) return f\\\"{self._main_url}/email\\\", login_data return None def parse_data_with_method(self, method: str): if method ==\",\n \"Dict = { \\\"blogId\\\": personal_blog[\\\"objectId\\\"], \\\"blogTitle\\\": personal_blog[\\\"title\\\"], \\\"blogHref\\\": personal_blog[\\\"originalUrl\\\"], \\\"blogViewers\\\": personal_blog[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": blog_create_time,\",\n \"self._response_data[\\\"user\\\"][\\\"selfDescription\\\"] avatar_img = self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"] followee = self._response_data[\\\"user\\\"][\\\"followeesCount\\\"] follower = self._response_data[\\\"user\\\"][\\\"followersCount\\\"] like_blogs = self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"]\",\n \"\\\"description\\\": description, \\\"avatarImg\\\": avatar_img, \\\"followee\\\": followee, \\\"follower\\\": follower, \\\"likeBlogs\\\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data)\",\n \"ValueError(\\\"Your login username is illegal!\\\") if phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\\\"{self._main_url}/phoneNumber\\\",\",\n \"= f\\\"?src=web&uid={self._login_uid}\\\" f\\\"&token={self._login_token}\\\" f\\\"&device_id={self._login_client_id}\\\" f\\\"¤t_uid={self._login_uid}\\\" self.set_data(spider_name=f\\\"{self._spider_name}:params\\\", data=params) # 个人数据 username = self._response_data[\\\"user\\\"][\\\"username\\\"] description\",\n \"== \\\"ok\\\": next_page_variable = None entry_list = self._response_data[\\\"d\\\"][\\\"entrylist\\\"] if len(entry_list) > 0: for\",\n \"True ): logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if test_json_response[\\\"s\\\"] ==\",\n \"== 1: logger.info(f\\\"当前掘金账号为: {self._login_username}, 状态: 已登录\\\") return True else: logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") return False\",\n \"def _test_cookies(self, cookies: Optional[str] = None) -> bool: params = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if params\",\n \"login_data = self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\\\"POST\\\", json=login_data, ) if response.content.decode()\",\n \"== BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish:\",\n \"logger.debug(f\\\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\\\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\\\"获取个人点赞博客成功!\\\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\\\"查询个人点赞博客失败!\\\") self.update_task_status(\",\n \"), } self._like_blogs_data.append(blog_data) page_no += 1 if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据\",\n \"def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\\\"token\\\"] self._login_uid = self._response_data[\\\"userId\\\"] self._login_client_id = self._response_data[\\\"clientId\\\"]\",\n \"{len(self._like_blogs_data)} 条个人点赞博客\\\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\\\"获取个人点赞博客成功!\\\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\\\"查询个人点赞博客失败!\\\") self.update_task_status( task_id=self._task_id,\",\n \"test_response.json() if test_json_response[\\\"s\\\"] == 1: logger.info(f\\\"当前掘金账号为: {self._login_username}, 状态: 已登录\\\") return True else: logger.error(f\\\"当前掘金账号登录状态:\",\n \"def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str = f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\" self._common_headers.update( { \\\"X-Juejin-Client\\\":\",\n \"d in login_params if \\\"token\\\" in d][ 0 ].replace(\\\"token=\\\", \\\"\\\") self._login_client_id = [\",\n \"str = f\\\"?src=web&uid={self._login_uid}\\\" f\\\"&token={self._login_token}\\\" f\\\"&device_id={self._login_client_id}\\\" f\\\"¤t_uid={self._login_uid}\\\" self.set_data(spider_name=f\\\"{self._spider_name}:params\\\", data=params) # 个人数据 username = self._response_data[\\\"user\\\"][\\\"username\\\"]\",\n \"= [ d for d in login_params if \\\"device_id\\\" in d ][0].replace(\\\"device_id=\\\", \\\"\\\")\",\n \"if len(entry_list) > 0: for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\",\",\n \"= f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\" self._common_headers.update( { \\\"X-Juejin-Client\\\": str(self._login_client_id), \\\"X-Juejin-Src\\\": \\\"web\\\", \\\"X-Juejin-Token\\\": self._login_token, \\\"X-Juejin-Uid\\\": self._login_uid, }\",\n \"self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is None: login_url,\",\n \"check_is_email_address(data=self._login_username) login_data: Dict = {\\\"password\\\": self._login_password} if phone_login is None and email_login is\",\n \"20 rest_count = total_count % 20 if rest_count != 0: total_pages += 1\",\n \"data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies: Optional[str] = None) -> bool: params\",\n \"公共参数 self._login_token = self._response_data[\\\"token\\\"] self._login_uid = self._response_data[\\\"userId\\\"] self._login_client_id = self._response_data[\\\"clientId\\\"] # 重要参数持久化 params:\",\n \"total_count // 20 rest_count = total_count % 20 if rest_count != 0: total_pages\",\n \"is not None and self._response_data[\\\"m\\\"] == \\\"ok\\\": next_page_variable = None entry_list = self._response_data[\\\"d\\\"][\\\"entrylist\\\"]\",\n \"time from typing import Dict, List, Tuple, Optional from utils.logger_utils import LogManager from\",\n \"err: logger.error(f\\\"解析 Redis 返回数据失败! 错误原因: {err}\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数\",\n \"= response.json() if self._response_data is not None and self._response_data[\\\"m\\\"] == \\\"ok\\\": next_page_variable =\",\n \"self._response_data[\\\"userId\\\"] self._login_client_id = self._response_data[\\\"clientId\\\"] # 重要参数持久化 params: str = f\\\"?src=web&uid={self._login_uid}\\\" f\\\"&token={self._login_token}\\\" f\\\"&device_id={self._login_client_id}\\\" f\\\"¤t_uid={self._login_uid}\\\"\",\n \"login_data.update(phoneNumber=self._login_username) return f\\\"{self._main_url}/phoneNumber\\\", login_data if email_login is not None: login_data.update(email=self._login_username) return f\\\"{self._main_url}/email\\\", login_data\",\n \"List, Tuple, Optional from utils.logger_utils import LogManager from utils.str_utils import check_is_json from config\",\n \"import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self,\",\n \"if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\\\"获取到\",\n \"logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\\\"获取个人博客数据成功!\\\") else: logger.error(\\\"查询个人博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self,\",\n \"check_is_json(test_response.content.decode()) is not True ): logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json()\",\n \"条个人点赞博客\\\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\\\"获取个人点赞博客成功!\\\") # 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\\\"查询个人点赞博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL)\",\n \"= [] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) ->\",\n \"personal_blog[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\\\"verifyCreatedAt\\\"] if self._response_data[\\\"d\\\"][\\\"total\\\"] > 20: time.sleep(0.5)\",\n \"None) -> bool: params = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if params is None: return False test_user_url:\",\n \"raise LoginException() def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str = f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\" self._common_headers.update(\",\n \"is None: return False test_user_url: str = f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\" test_request_headers: Dict = self.get_default_headers() test_response\",\n \"None self._response_data = None self._blogs_data: List = [] self._like_blogs_data: List = [] self._like_blogs_total_page:\",\n \"import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils\",\n \"Optional from utils.logger_utils import LogManager from utils.str_utils import check_is_json from config import LOG_LEVEL,\",\n \"== BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is None: login_url, login_data = self._check_username()\",\n \"url_params += f\\\"&{data[0]}={data[1]}\\\" blogs_url: str = f\\\"{self._blogs_url}{url_params}\\\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode()\",\n \"not None and self._response_data[\\\"m\\\"] == \\\"ok\\\": next_page_variable = None entry_list = self._response_data[\\\"d\\\"][\\\"entrylist\\\"] if\",\n \"\\\"ok\\\": next_page_variable = None entry_list = self._response_data[\\\"d\\\"][\\\"entrylist\\\"] if len(entry_list) > 0: for personal_blog\",\n \"login username is illegal!\\\") if phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\\\"{self._main_url}/phoneNumber\\\", login_data\",\n \"0): like_blogs_url: str = f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\" self._common_headers.update( { \\\"X-Juejin-Client\\\": str(self._login_client_id), \\\"X-Juejin-Src\\\": \\\"web\\\", \\\"X-Juejin-Token\\\": self._login_token,\",\n \"method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\\\"token\\\"] self._login_uid = self._response_data[\\\"userId\\\"] self._login_client_id\",\n \"None: return False test_user_url: str = f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\" test_request_headers: Dict = self.get_default_headers() test_response =\",\n \"= self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if params is None: return False test_user_url: str = f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\" test_request_headers:\",\n \"0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \\\"\\\"\\\" 解析用户名 :return:\",\n \") else: try: login_params = get_result.split(\\\"&\\\")[1:-1] self._login_uid = [d for d in login_params\",\n \"continue blog_data: Dict = { \\\"blogId\\\": entry_data[\\\"objectId\\\"], \\\"blogTitle\\\": entry_data[\\\"title\\\"], \\\"blogHref\\\": entry_data[\\\"originalUrl\\\"], \\\"blogViewers\\\": entry_data[\\\"viewsCount\\\"],\",\n \"任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\\\"查询个人点赞博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies:\",\n \"self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\\\"解析 Redis 返回数据失败! 错误原因: {err}\\\") self.parse_data_with_method(\",\n \"self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies )\",\n \"self._spider_name: str = f\\\"juejin:{self._login_username}\\\" self._login_cookies: Optional[str] = None self._login_token: Optional[str] = None self._login_uid:\",\n \"import time from typing import Dict, List, Tuple, Optional from utils.logger_utils import LogManager\",\n \"if self._response_data is not None and self._response_data[\\\"m\\\"] == \\\"ok\\\": next_page_variable = None entry_list\",\n \"import Dict, List, Tuple, Optional from utils.logger_utils import LogManager from utils.str_utils import check_is_json\",\n \"self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data: List = [] self._like_blogs_data: List\",\n \"in d][ 0 ].replace(\\\"token=\\\", \\\"\\\") self._login_client_id = [ d for d in login_params\",\n \"self._login_client_id = self._response_data[\\\"clientId\\\"] # 重要参数持久化 params: str = f\\\"?src=web&uid={self._login_uid}\\\" f\\\"&token={self._login_token}\\\" f\\\"&device_id={self._login_client_id}\\\" f\\\"¤t_uid={self._login_uid}\\\" self.set_data(spider_name=f\\\"{self._spider_name}:params\\\",\",\n \"time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\\\"获取个人博客数据成功!\\\") else: logger.error(\\\"查询个人博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise\",\n \"self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def _parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url:\",\n \"= self._response_data[\\\"d\\\"][\\\"entryList\\\"] if len(entry_list) > 0: for entry_data in entry_list: if entry_data is\",\n \"page_no += 1 if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else:\",\n \"response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data = response.json() if (\",\n \"logger.info(f\\\"当前正在获取第{page_no + 1}页的数据!\\\") if page_no == 0: total_count = self._response_data[\\\"d\\\"][\\\"total\\\"] total_pages = total_count\",\n \"\\\"\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\\\"解析 Redis 返回数据失败! 错误原因: {err}\\\")\",\n \") response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data = response.json() if\",\n \"0: url_params += f\\\"?{data[0]}={data[1]}\\\" else: url_params += f\\\"&{data[0]}={data[1]}\\\" blogs_url: str = f\\\"{self._blogs_url}{url_params}\\\" response\",\n \"self._response_data[\\\"user\\\"][\\\"username\\\"] description = self._response_data[\\\"user\\\"][\\\"selfDescription\\\"] avatar_img = self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"] followee = self._response_data[\\\"user\\\"][\\\"followeesCount\\\"] follower = self._response_data[\\\"user\\\"][\\\"followersCount\\\"]\",\n \"like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict\",\n \"JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str, password: str): self._main_url = \\\"https://juejin.im/auth/type\\\" self._blogs_url\",\n \"entry_data[\\\"originalUrl\\\"], \\\"blogViewers\\\": entry_data[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": datetime_str_change_fmt( time_str=entry_data[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ), } self._like_blogs_data.append(blog_data) page_no += 1\",\n \"\\\"avatarImg\\\": avatar_img, \\\"followee\\\": followee, \\\"follower\\\": follower, \\\"likeBlogs\\\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def\",\n \"headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data = response.json() if ( self._response_data is not\",\n \"\\\"token\\\" in d][ 0 ].replace(\\\"token=\\\", \\\"\\\") self._login_client_id = [ d for d in\",\n \"# 重要参数持久化 params: str = f\\\"?src=web&uid={self._login_uid}\\\" f\\\"&token={self._login_token}\\\" f\\\"&device_id={self._login_client_id}\\\" f\\\"¤t_uid={self._login_uid}\\\" self.set_data(spider_name=f\\\"{self._spider_name}:params\\\", data=params) # 个人数据\",\n \"self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict = { \\\"src\\\":\",\n \"= response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method(\",\n \") class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str, password: str): self._main_url =\",\n \"LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from spiders\",\n \"time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\\\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\\\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data ) logger.info(\\\"获取个人点赞博客成功!\\\") #\",\n \"\\\"type\\\": \\\"post\\\", \\\"limit\\\": \\\"20\\\", \\\"order\\\": \\\"createdAt\\\", } if next_params is not None: req_data.update(before=next_params)\",\n \"not None and self._response_data[\\\"m\\\"] == \\\"success\\\" ): logger.info(f\\\"当前正在获取第{page_no + 1}页的数据!\\\") if page_no ==\",\n \"method=\\\"POST\\\", json=login_data, ) if response.content.decode() != \\\"\\\": logger.info(\\\"登录成功!\\\") self._response_data = response.json() self._login_cookies =\",\n \"page_no == 0: total_count = self._response_data[\\\"d\\\"][\\\"total\\\"] total_pages = total_count // 20 rest_count =\",\n \"is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\\\"&\\\")[1:-1] self._login_uid = [d\",\n \"in d][ 0 ].replace(\\\"uid=\\\", \\\"\\\") self._login_token = [d for d in login_params if\",\n \"Dict = { \\\"username\\\": username, \\\"description\\\": description, \\\"avatarImg\\\": avatar_img, \\\"followee\\\": followee, \\\"follower\\\": follower,\",\n \"{ \\\"username\\\": username, \\\"description\\\": description, \\\"avatarImg\\\": avatar_img, \\\"followee\\\": followee, \\\"follower\\\": follower, \\\"likeBlogs\\\": like_blogs,\",\n \"except Exception as err: logger.error(f\\\"解析 Redis 返回数据失败! 错误原因: {err}\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def\",\n \"if index == 0: url_params += f\\\"?{data[0]}={data[1]}\\\" else: url_params += f\\\"&{data[0]}={data[1]}\\\" blogs_url: str\",\n \"str, password: str): self._main_url = \\\"https://juejin.im/auth/type\\\" self._blogs_url = \\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\" self._like_blogs_url = \\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\" self._task_id\",\n \"self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not\",\n \"): logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if test_json_response[\\\"s\\\"] == 1:\",\n \"data=params) # 个人数据 username = self._response_data[\\\"user\\\"][\\\"username\\\"] description = self._response_data[\\\"user\\\"][\\\"selfDescription\\\"] avatar_img = self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"] followee\",\n \"else: logger.error(\\\"查询个人点赞博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies: Optional[str] =\",\n \"\\\"device_id\\\" in d ][0].replace(\\\"device_id=\\\", \\\"\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\\\"解析\",\n \"if \\\"token\\\" in d][ 0 ].replace(\\\"token=\\\", \\\"\\\") self._login_client_id = [ d for d\",\n \"self._like_blogs_total_page = total_pages entry_list = self._response_data[\\\"d\\\"][\\\"entryList\\\"] if len(entry_list) > 0: for entry_data in\",\n \"= self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"] followee = self._response_data[\\\"user\\\"][\\\"followeesCount\\\"] follower = self._response_data[\\\"user\\\"][\\\"followersCount\\\"] like_blogs = self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"] personal_data: Dict\",\n \"if entry_data is None: continue blog_data: Dict = { \\\"blogId\\\": entry_data[\\\"objectId\\\"], \\\"blogTitle\\\": entry_data[\\\"title\\\"],\",\n \"\\\"blogCreateTime\\\": datetime_str_change_fmt( time_str=entry_data[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ), } self._like_blogs_data.append(blog_data) page_no += 1 if page_no <=\",\n \"\\\"\\\") self._login_client_id = [ d for d in login_params if \\\"device_id\\\" in d\",\n \"} if next_params is not None: req_data.update(before=next_params) url_params: str = \\\"\\\" for index,\",\n \"None self._login_token: Optional[str] = None self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None\",\n \"_parse_personal_like_blogs(self, page_no: int = 0): like_blogs_url: str = f\\\"{self._like_blogs_url}/{self._login_uid}/like/entry?page={page_no}&pageSize=20\\\" self._common_headers.update( { \\\"X-Juejin-Client\\\": str(self._login_client_id),\",\n \"import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from\",\n \"None: login_data.update(phoneNumber=self._login_username) return f\\\"{self._main_url}/phoneNumber\\\", login_data if email_login is not None: login_data.update(email=self._login_username) return f\\\"{self._main_url}/email\\\",\",\n \"None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\\\"&\\\")[1:-1] self._login_uid = [d for\",\n \"self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if params is None: return False test_user_url: str = f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\" test_request_headers: Dict\",\n \"self.send_data() def login(self): if self._login_cookies is None: login_url, login_data = self._check_username() response =\",\n \"cookies: Optional[str] = None) -> bool: params = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if params is None:\",\n \"self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data = response.json() if ( self._response_data is\",\n \"= None self._login_token: Optional[str] = None self._login_uid: Optional[str] = None self._login_client_id: Optional[str] =\",\n \"\\\"uid\\\" in d][ 0 ].replace(\\\"uid=\\\", \\\"\\\") self._login_token = [d for d in login_params\",\n \"d][ 0 ].replace(\\\"token=\\\", \\\"\\\") self._login_client_id = [ d for d in login_params if\",\n \"method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs()\",\n \"+= 1 if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: #\",\n \"in d ][0].replace(\\\"device_id=\\\", \\\"\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\\\"解析 Redis\",\n \"from utils.exception_utils import LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils\",\n \"logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict = {\",\n \"f\\\"juejin:{self._login_username}\\\" self._login_cookies: Optional[str] = None self._login_token: Optional[str] = None self._login_uid: Optional[str] = None\",\n \"\\\"order\\\": \\\"createdAt\\\", } if next_params is not None: req_data.update(before=next_params) url_params: str = \\\"\\\"\",\n \"data in enumerate(req_data.items()): if index == 0: url_params += f\\\"?{data[0]}={data[1]}\\\" else: url_params +=\",\n \"len(entry_list) > 0: for entry_data in entry_list: if entry_data is None: continue blog_data:\",\n \"f\\\"&token={self._login_token}\\\" f\\\"&device_id={self._login_client_id}\\\" f\\\"¤t_uid={self._login_uid}\\\" self.set_data(spider_name=f\\\"{self._spider_name}:params\\\", data=params) # 个人数据 username = self._response_data[\\\"user\\\"][\\\"username\\\"] description = self._response_data[\\\"user\\\"][\\\"selfDescription\\\"]\",\n \"in enumerate(req_data.items()): if index == 0: url_params += f\\\"?{data[0]}={data[1]}\\\" else: url_params += f\\\"&{data[0]}={data[1]}\\\"\",\n \") def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\\\"token\\\"] self._login_uid = self._response_data[\\\"userId\\\"] self._login_client_id =\",\n \") except Exception as err: logger.error(f\\\"解析 Redis 返回数据失败! 错误原因: {err}\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult )\",\n \"import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils\",\n \"# 公共参数 self._login_token = self._response_data[\\\"token\\\"] self._login_uid = self._response_data[\\\"userId\\\"] self._login_client_id = self._response_data[\\\"clientId\\\"] # 重要参数持久化\",\n \"!= \\\"\\\": self._response_data = response.json() if self._response_data is not None and self._response_data[\\\"m\\\"] ==\",\n \"d in login_params if \\\"uid\\\" in d][ 0 ].replace(\\\"uid=\\\", \\\"\\\") self._login_token = [d\",\n \"][0].replace(\\\"device_id=\\\", \\\"\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\\\"解析 Redis 返回数据失败! 错误原因:\",\n \"utils.logger_utils import LogManager from utils.str_utils import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from\",\n \"bool: params = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if params is None: return False test_user_url: str =\",\n \"total_pages += 1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\\\"d\\\"][\\\"entryList\\\"] if len(entry_list) > 0:\",\n \"return False test_user_url: str = f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\" test_request_headers: Dict = self.get_default_headers() test_response = self.make_request(\",\n \"response.content.decode() != \\\"\\\": self._response_data = response.json() if ( self._response_data is not None and\",\n \"= get_result.split(\\\"&\\\")[1:-1] self._login_uid = [d for d in login_params if \\\"uid\\\" in d][\",\n \"{ \\\"X-Juejin-Client\\\": str(self._login_client_id), \\\"X-Juejin-Src\\\": \\\"web\\\", \\\"X-Juejin-Token\\\": self._login_token, \\\"X-Juejin-Uid\\\": self._login_uid, } ) response =\",\n \"{ \\\"src\\\": \\\"web\\\", \\\"uid\\\": self._login_uid, \\\"device_id\\\": self._login_client_id, \\\"token\\\": self._login_token, \\\"targetUid\\\": self._login_uid, \\\"type\\\": \\\"post\\\",\",\n \"is None: login_url, login_data = self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\\\"POST\\\", json=login_data,\",\n \"_parse_login_data(self): # 公共参数 self._login_token = self._response_data[\\\"token\\\"] self._login_uid = self._response_data[\\\"userId\\\"] self._login_client_id = self._response_data[\\\"clientId\\\"] #\",\n \"in login_params if \\\"uid\\\" in d][ 0 ].replace(\\\"uid=\\\", \\\"\\\") self._login_token = [d for\",\n \"self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] = None): req_data: dict = { \\\"src\\\": \\\"web\\\",\",\n \"username, \\\"description\\\": description, \\\"avatarImg\\\": avatar_img, \\\"followee\\\": followee, \\\"follower\\\": follower, \\\"likeBlogs\\\": like_blogs, } logger.debug(personal_data)\",\n \"from utils.logger_utils import LogManager from utils.str_utils import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL\",\n \"def __init__(self, task_id: str, username: str, password: str): self._main_url = \\\"https://juejin.im/auth/type\\\" self._blogs_url =\",\n \"= self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code != 200\",\n \"personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ) blog_data: Dict = {\",\n \"d for d in login_params if \\\"device_id\\\" in d ][0].replace(\\\"device_id=\\\", \\\"\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs\",\n \"datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from\",\n \"password: str): self._main_url = \\\"https://juejin.im/auth/type\\\" self._blogs_url = \\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\" self._like_blogs_url = \\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\" self._task_id =\",\n \"self._login_token, \\\"X-Juejin-Uid\\\": self._login_uid, } ) response = self.make_request(url=like_blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\":\",\n \"method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\\\"&\\\")[1:-1] self._login_uid = [d for d in\",\n \":return: 结果 \\\"\\\"\\\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\\\"password\\\":\",\n \"self._login_uid = self._response_data[\\\"userId\\\"] self._login_client_id = self._response_data[\\\"clientId\\\"] # 重要参数持久化 params: str = f\\\"?src=web&uid={self._login_uid}\\\" f\\\"&token={self._login_token}\\\"\",\n \"_check_username(self) -> Optional[Tuple[str, Dict]]: \\\"\\\"\\\" 解析用户名 :return: 结果 \\\"\\\"\\\" phone_login = check_is_phone_number(data=self._login_username) email_login\",\n \"\\\"follower\\\": follower, \\\"likeBlogs\\\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str] =\",\n \"not True ): logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if test_json_response[\\\"s\\\"]\",\n \"from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException,\",\n \"else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\\\"获取个人博客数据成功!\\\") else: logger.error(\\\"查询个人博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException() def\",\n \"self._response_data = None self._blogs_data: List = [] self._like_blogs_data: List = [] self._like_blogs_total_page: int\",\n \"== \\\"success\\\" ): logger.info(f\\\"当前正在获取第{page_no + 1}页的数据!\\\") if page_no == 0: total_count = self._response_data[\\\"d\\\"][\\\"total\\\"]\",\n \"Dict]]: \\\"\\\"\\\" 解析用户名 :return: 结果 \\\"\\\"\\\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data:\",\n \"// 20 rest_count = total_count % 20 if rest_count != 0: total_pages +=\",\n \"blog_data: Dict = { \\\"blogId\\\": entry_data[\\\"objectId\\\"], \\\"blogTitle\\\": entry_data[\\\"title\\\"], \\\"blogHref\\\": entry_data[\\\"originalUrl\\\"], \\\"blogViewers\\\": entry_data[\\\"viewsCount\\\"], \\\"blogCreateTime\\\":\",\n \"= \\\"https://juejin.im/auth/type\\\" self._blogs_url = \\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\" self._like_blogs_url = \\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\" self._task_id = task_id self._login_username =\",\n \"Optional[str] = None self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data: List =\",\n \"None entry_list = self._response_data[\\\"d\\\"][\\\"entrylist\\\"] if len(entry_list) > 0: for personal_blog in entry_list: blog_create_time\",\n \"super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \\\"\\\"\\\" 解析用户名 :return: 结果\",\n \"response = self.make_request( url=login_url, headers=self._common_headers, method=\\\"POST\\\", json=login_data, ) if response.content.decode() != \\\"\\\": logger.info(\\\"登录成功!\\\")\",\n \"= self._response_data[\\\"user\\\"][\\\"followeesCount\\\"] follower = self._response_data[\\\"user\\\"][\\\"followersCount\\\"] like_blogs = self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"] personal_data: Dict = { \\\"username\\\":\",\n \"= [d for d in login_params if \\\"uid\\\" in d][ 0 ].replace(\\\"uid=\\\", \\\"\\\")\",\n \"import LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number,\",\n \"followee, \\\"follower\\\": follower, \\\"likeBlogs\\\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs) def _parse_personal_blogs(self, next_params: Optional[str]\",\n \"self._response_data[\\\"m\\\"] == \\\"success\\\" ): logger.info(f\\\"当前正在获取第{page_no + 1}页的数据!\\\") if page_no == 0: total_count =\",\n \"description, \\\"avatarImg\\\": avatar_img, \\\"followee\\\": followee, \\\"follower\\\": follower, \\\"likeBlogs\\\": like_blogs, } logger.debug(personal_data) self.data_model.set_personal_data(data=personal_data) self.parse_data_with_method(method=BaseSpiderParseMethodType.PersonalBlogs)\",\n \"next_params: Optional[str] = None): req_data: dict = { \\\"src\\\": \\\"web\\\", \\\"uid\\\": self._login_uid, \\\"device_id\\\":\",\n \"BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is\",\n \"!= \\\"\\\": logger.info(\\\"登录成功!\\\") self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies(\",\n \"if \\\"uid\\\" in d][ 0 ].replace(\\\"uid=\\\", \\\"\\\") self._login_token = [d for d in\",\n \"params: str = f\\\"?src=web&uid={self._login_uid}\\\" f\\\"&token={self._login_token}\\\" f\\\"&device_id={self._login_client_id}\\\" f\\\"¤t_uid={self._login_uid}\\\" self.set_data(spider_name=f\\\"{self._spider_name}:params\\\", data=params) # 个人数据 username =\",\n \"str = \\\"\\\" for index, data in enumerate(req_data.items()): if index == 0: url_params\",\n \"logger.error(\\\"登录失败!\\\") raise LoginException() else: get_result: str = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if get_result is None: self.parse_data_with_method(\",\n \"entry_data[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": datetime_str_change_fmt( time_str=entry_data[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ), } self._like_blogs_data.append(blog_data) page_no += 1 if page_no\",\n \"= \\\"\\\" for index, data in enumerate(req_data.items()): if index == 0: url_params +=\",\n \"d ][0].replace(\\\"device_id=\\\", \\\"\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\\\"解析 Redis 返回数据失败!\",\n \"self._login_token = [d for d in login_params if \\\"token\\\" in d][ 0 ].replace(\\\"token=\\\",\",\n \"and self._response_data[\\\"m\\\"] == \\\"ok\\\": next_page_variable = None entry_list = self._response_data[\\\"d\\\"][\\\"entrylist\\\"] if len(entry_list) >\",\n \"self._login_token: Optional[str] = None self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None self._response_data\",\n \"self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response = test_response.json() if test_json_response[\\\"s\\\"] == 1: logger.info(f\\\"当前掘金账号为: {self._login_username}, 状态:\",\n \"if page_no == 0: total_count = self._response_data[\\\"d\\\"][\\\"total\\\"] total_pages = total_count // 20 rest_count\",\n \"\\\"\\\") self._login_token = [d for d in login_params if \\\"token\\\" in d][ 0\",\n \"__init__(self, task_id: str, username: str, password: str): self._main_url = \\\"https://juejin.im/auth/type\\\" self._blogs_url = \\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\"\",\n \"str = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params\",\n \"like_blogs = self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"] personal_data: Dict = { \\\"username\\\": username, \\\"description\\\": description, \\\"avatarImg\\\": avatar_img,\",\n \"Dict, List, Tuple, Optional from utils.logger_utils import LogManager from utils.str_utils import check_is_json from\",\n \"= self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params =\",\n \"self._login_uid, \\\"type\\\": \\\"post\\\", \\\"limit\\\": \\\"20\\\", \\\"order\\\": \\\"createdAt\\\", } if next_params is not None:\",\n \"= test_response.json() if test_json_response[\\\"s\\\"] == 1: logger.info(f\\\"当前掘金账号为: {self._login_username}, 状态: 已登录\\\") return True else:\",\n \"if next_params is not None: req_data.update(before=next_params) url_params: str = \\\"\\\" for index, data\",\n \"logger.error(f\\\"解析 Redis 返回数据失败! 错误原因: {err}\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token\",\n \"entry_list = self._response_data[\\\"d\\\"][\\\"entryList\\\"] if len(entry_list) > 0: for entry_data in entry_list: if entry_data\",\n \"\\\"targetUid\\\": self._login_uid, \\\"type\\\": \\\"post\\\", \\\"limit\\\": \\\"20\\\", \\\"order\\\": \\\"createdAt\\\", } if next_params is not\",\n \"f\\\"?src=web&uid={self._login_uid}\\\" f\\\"&token={self._login_token}\\\" f\\\"&device_id={self._login_client_id}\\\" f\\\"¤t_uid={self._login_uid}\\\" self.set_data(spider_name=f\\\"{self._spider_name}:params\\\", data=params) # 个人数据 username = self._response_data[\\\"user\\\"][\\\"username\\\"] description =\",\n \"check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username) login_data: Dict = {\\\"password\\\": self._login_password} if phone_login is None\",\n \"self._response_data[\\\"user\\\"][\\\"followersCount\\\"] like_blogs = self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"] personal_data: Dict = { \\\"username\\\": username, \\\"description\\\": description, \\\"avatarImg\\\":\",\n \"= self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"] personal_data: Dict = { \\\"username\\\": username, \\\"description\\\": description, \\\"avatarImg\\\": avatar_img, \\\"followee\\\":\",\n \"login(self): if self._login_cookies is None: login_url, login_data = self._check_username() response = self.make_request( url=login_url,\",\n \"test_user_url: str = f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\" test_request_headers: Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers\",\n \"def parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs:\",\n \"elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self):\",\n \"method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err: logger.error(f\\\"解析 Redis 返回数据失败! 错误原因: {err}\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult\",\n \"= None): req_data: dict = { \\\"src\\\": \\\"web\\\", \\\"uid\\\": self._login_uid, \\\"device_id\\\": self._login_client_id, \\\"token\\\":\",\n \"Tuple, Optional from utils.logger_utils import LogManager from utils.str_utils import check_is_json from config import\",\n \"BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is None: login_url, login_data = self._check_username() response\",\n \"username self._login_password = password self._spider_name: str = f\\\"juejin:{self._login_username}\\\" self._login_cookies: Optional[str] = None self._login_token:\",\n \"self._response_data[\\\"user\\\"][\\\"followeesCount\\\"] follower = self._response_data[\\\"user\\\"][\\\"followersCount\\\"] like_blogs = self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"] personal_data: Dict = { \\\"username\\\": username,\",\n \"test_json_response = test_response.json() if test_json_response[\\\"s\\\"] == 1: logger.info(f\\\"当前掘金账号为: {self._login_username}, 状态: 已登录\\\") return True\",\n \"self._response_data[\\\"token\\\"] self._login_uid = self._response_data[\\\"userId\\\"] self._login_client_id = self._response_data[\\\"clientId\\\"] # 重要参数持久化 params: str = f\\\"?src=web&uid={self._login_uid}\\\"\",\n \"test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not True ): logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return\",\n \"= f\\\"{self._blogs_url}{url_params}\\\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data = response.json()\",\n \"response.json() if self._response_data is not None and self._response_data[\\\"m\\\"] == \\\"ok\\\": next_page_variable = None\",\n \"str = f\\\"{self._blogs_url}{url_params}\\\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data =\",\n \"self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"] personal_data: Dict = { \\\"username\\\": username, \\\"description\\\": description, \\\"avatarImg\\\": avatar_img, \\\"followee\\\": followee,\",\n \"is None and email_login is None: raise ValueError(\\\"Your login username is illegal!\\\") if\",\n \"spiders import BaseSpider, BaseSpiderParseMethodType, CookieUtils from utils.str_utils import check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers(\",\n \"task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies: Optional[str] = None) -> bool:\",\n \"LogManager from utils.str_utils import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import\",\n \"return f\\\"{self._main_url}/phoneNumber\\\", login_data if email_login is not None: login_data.update(email=self._login_username) return f\\\"{self._main_url}/email\\\", login_data return\",\n \"0: for personal_blog in entry_list: blog_create_time = datetime_str_change_fmt( time_str=personal_blog[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ) blog_data: Dict\",\n \"\\\"X-Juejin-Client\\\": str(self._login_client_id), \\\"X-Juejin-Src\\\": \\\"web\\\", \\\"X-Juejin-Token\\\": self._login_token, \\\"X-Juejin-Uid\\\": self._login_uid, } ) response = self.make_request(url=like_blogs_url,\",\n \"raise LoginException() else: get_result: str = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\") if get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult\",\n \"self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \\\"\\\"\\\" 解析用户名 :return: 结果 \\\"\\\"\\\" phone_login =\",\n \"= self._response_data[\\\"userId\\\"] self._login_client_id = self._response_data[\\\"clientId\\\"] # 重要参数持久化 params: str = f\\\"?src=web&uid={self._login_uid}\\\" f\\\"&token={self._login_token}\\\" f\\\"&device_id={self._login_client_id}\\\"\",\n \"= total_count % 20 if rest_count != 0: total_pages += 1 self._like_blogs_total_page =\",\n \"blogs_url: str = f\\\"{self._blogs_url}{url_params}\\\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data\",\n \"not None: login_data.update(email=self._login_username) return f\\\"{self._main_url}/email\\\", login_data return None def parse_data_with_method(self, method: str): if\",\n \"% 20 if rest_count != 0: total_pages += 1 self._like_blogs_total_page = total_pages entry_list\",\n \"next_page_variable = None entry_list = self._response_data[\\\"d\\\"][\\\"entrylist\\\"] if len(entry_list) > 0: for personal_blog in\",\n \"None and self._response_data[\\\"m\\\"] == \\\"success\\\" ): logger.info(f\\\"当前正在获取第{page_no + 1}页的数据!\\\") if page_no == 0:\",\n \"is not None and self._response_data[\\\"m\\\"] == \\\"success\\\" ): logger.info(f\\\"当前正在获取第{page_no + 1}页的数据!\\\") if page_no\",\n \"self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\\\"获取个人博客数据成功!\\\") else: logger.error(\\\"查询个人博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise LoginException()\",\n \"self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self, cookies: Optional[str] = None) ->\",\n \"{err}\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self): # 公共参数 self._login_token = self._response_data[\\\"token\\\"] self._login_uid =\",\n \"= self._response_data[\\\"user\\\"][\\\"username\\\"] description = self._response_data[\\\"user\\\"][\\\"selfDescription\\\"] avatar_img = self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"] followee = self._response_data[\\\"user\\\"][\\\"followeesCount\\\"] follower =\",\n \"if ( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is not True ): logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\")\",\n \"for d in login_params if \\\"token\\\" in d][ 0 ].replace(\\\"token=\\\", \\\"\\\") self._login_client_id =\",\n \"rest_count = total_count % 20 if rest_count != 0: total_pages += 1 self._like_blogs_total_page\",\n \"= self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() != \\\"\\\": self._response_data = response.json() if self._response_data is\",\n \"avatar_img = self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"] followee = self._response_data[\\\"user\\\"][\\\"followeesCount\\\"] follower = self._response_data[\\\"user\\\"][\\\"followersCount\\\"] like_blogs = self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"] personal_data:\",\n \"if ( self._response_data is not None and self._response_data[\\\"m\\\"] == \\\"success\\\" ): logger.info(f\\\"当前正在获取第{page_no +\",\n \"= None self._response_data = None self._blogs_data: List = [] self._like_blogs_data: List = []\",\n \"PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from spiders import\",\n \"total_pages = total_count // 20 rest_count = total_count % 20 if rest_count !=\",\n \"self._login_password = password self._spider_name: str = f\\\"juejin:{self._login_username}\\\" self._login_cookies: Optional[str] = None self._login_token: Optional[str]\",\n \"Optional[Tuple[str, Dict]]: \\\"\\\"\\\" 解析用户名 :return: 结果 \\\"\\\"\\\" phone_login = check_is_phone_number(data=self._login_username) email_login = check_is_email_address(data=self._login_username)\",\n \"self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str, Dict]]: \\\"\\\"\\\" 解析用户名 :return: 结果 \\\"\\\"\\\"\",\n \"not None: req_data.update(before=next_params) url_params: str = \\\"\\\" for index, data in enumerate(req_data.items()): if\",\n \"\\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\" self._task_id = task_id self._login_username = username self._login_password = password self._spider_name: str =\",\n \"): logger.info(f\\\"当前正在获取第{page_no + 1}页的数据!\\\") if page_no == 0: total_count = self._response_data[\\\"d\\\"][\\\"total\\\"] total_pages =\",\n \"\\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\" self._like_blogs_url = \\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\" self._task_id = task_id self._login_username = username self._login_password = password\",\n \"for d in login_params if \\\"device_id\\\" in d ][0].replace(\\\"device_id=\\\", \\\"\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs )\",\n \"= self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code != 200 or check_is_json(test_response.content.decode()) is\",\n \"self._like_blogs_url = \\\"https://user-like-wrapper-ms.juejin.im/v1/user\\\" self._task_id = task_id self._login_username = username self._login_password = password self._spider_name:\",\n \"None def parse_data_with_method(self, method: str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method ==\",\n \"and self._response_data[\\\"m\\\"] == \\\"success\\\" ): logger.info(f\\\"当前正在获取第{page_no + 1}页的数据!\\\") if page_no == 0: total_count\",\n \"20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\\\"获取个人博客数据成功!\\\") else: logger.error(\\\"查询个人博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) )\",\n \"raise ParseDataException() def _test_cookies(self, cookies: Optional[str] = None) -> bool: params = self.get_data(spider_name=f\\\"{self._spider_name}:params\\\")\",\n \"next_params is not None: req_data.update(before=next_params) url_params: str = \\\"\\\" for index, data in\",\n \"config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException\",\n \"enumerate(req_data.items()): if index == 0: url_params += f\\\"?{data[0]}={data[1]}\\\" else: url_params += f\\\"&{data[0]}={data[1]}\\\" blogs_url:\",\n \"is not None: login_data.update(phoneNumber=self._login_username) return f\\\"{self._main_url}/phoneNumber\\\", login_data if email_login is not None: login_data.update(email=self._login_username)\",\n \"check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt from utils.exception_utils import\",\n \"None: login_data.update(email=self._login_username) return f\\\"{self._main_url}/email\\\", login_data return None def parse_data_with_method(self, method: str): if method\",\n \"description = self._response_data[\\\"user\\\"][\\\"selfDescription\\\"] avatar_img = self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"] followee = self._response_data[\\\"user\\\"][\\\"followeesCount\\\"] follower = self._response_data[\\\"user\\\"][\\\"followersCount\\\"] like_blogs\",\n \"check_is_phone_number, check_is_email_address logger = LogManager(__name__).get_logger_and_add_handlers( formatter_template=5, log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id:\",\n \"for index, data in enumerate(req_data.items()): if index == 0: url_params += f\\\"?{data[0]}={data[1]}\\\" else:\",\n \"self._response_data[\\\"clientId\\\"] # 重要参数持久化 params: str = f\\\"?src=web&uid={self._login_uid}\\\" f\\\"&token={self._login_token}\\\" f\\\"&device_id={self._login_client_id}\\\" f\\\"¤t_uid={self._login_uid}\\\" self.set_data(spider_name=f\\\"{self._spider_name}:params\\\", data=params) #\",\n \"if phone_login is None and email_login is None: raise ValueError(\\\"Your login username is\",\n \"get_result.split(\\\"&\\\")[1:-1] self._login_uid = [d for d in login_params if \\\"uid\\\" in d][ 0\",\n \"= { \\\"blogId\\\": personal_blog[\\\"objectId\\\"], \\\"blogTitle\\\": personal_blog[\\\"title\\\"], \\\"blogHref\\\": personal_blog[\\\"originalUrl\\\"], \\\"blogViewers\\\": personal_blog[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": blog_create_time, }\",\n \"None and self._response_data[\\\"m\\\"] == \\\"ok\\\": next_page_variable = None entry_list = self._response_data[\\\"d\\\"][\\\"entrylist\\\"] if len(entry_list)\",\n \"str, username: str, password: str): self._main_url = \\\"https://juejin.im/auth/type\\\" self._blogs_url = \\\"https://timeline-merger-ms.juejin.im/v1/get_entry_by_self\\\" self._like_blogs_url =\",\n \") blog_data: Dict = { \\\"blogId\\\": personal_blog[\\\"objectId\\\"], \\\"blogTitle\\\": personal_blog[\\\"title\\\"], \\\"blogHref\\\": personal_blog[\\\"originalUrl\\\"], \\\"blogViewers\\\": personal_blog[\\\"viewsCount\\\"],\",\n \"from utils.str_utils import check_is_json from config import LOG_LEVEL, PROCESS_STATUS_FAIL from utils.time_utils import datetime_str_change_fmt\",\n \"= task_id self._login_username = username self._login_password = password self._spider_name: str = f\\\"juejin:{self._login_username}\\\" self._login_cookies:\",\n \"self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"] followee = self._response_data[\\\"user\\\"][\\\"followeesCount\\\"] follower = self._response_data[\\\"user\\\"][\\\"followersCount\\\"] like_blogs = self._response_data[\\\"user\\\"][\\\"collectedEntriesCount\\\"] personal_data: Dict =\",\n \"illegal!\\\") if phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\\\"{self._main_url}/phoneNumber\\\", login_data if email_login is\",\n \"username = self._response_data[\\\"user\\\"][\\\"username\\\"] description = self._response_data[\\\"user\\\"][\\\"selfDescription\\\"] avatar_img = self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"] followee = self._response_data[\\\"user\\\"][\\\"followeesCount\\\"] follower\",\n \"self._login_client_id, \\\"token\\\": self._login_token, \\\"targetUid\\\": self._login_uid, \\\"type\\\": \\\"post\\\", \\\"limit\\\": \\\"20\\\", \\\"order\\\": \\\"createdAt\\\", } if\",\n \"method == BaseSpiderParseMethodType.Finish: self.send_data() def login(self): if self._login_cookies is None: login_url, login_data =\",\n \"None: login_url, login_data = self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\\\"POST\\\", json=login_data, )\",\n \"} self._like_blogs_data.append(blog_data) page_no += 1 if page_no <= self._like_blogs_total_page: # TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5)\",\n \"== 0: total_count = self._response_data[\\\"d\\\"][\\\"total\\\"] total_pages = total_count // 20 rest_count = total_count\",\n \"[] self._like_blogs_total_page: int = 0 super().__init__() self._login_cookies = self.get_cookies(spider_name=self._spider_name) def _check_username(self) -> Optional[Tuple[str,\",\n \"None self._blogs_data: List = [] self._like_blogs_data: List = [] self._like_blogs_total_page: int = 0\",\n \"if \\\"device_id\\\" in d ][0].replace(\\\"device_id=\\\", \\\"\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.PersonalBlogs ) except Exception as err:\",\n \"is illegal!\\\") if phone_login is not None: login_data.update(phoneNumber=self._login_username) return f\\\"{self._main_url}/phoneNumber\\\", login_data if email_login\",\n \"Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if ( test_response.status_code !=\",\n \"\\\"createdAt\\\", } if next_params is not None: req_data.update(before=next_params) url_params: str = \\\"\\\" for\",\n \"f\\\"https://user-storage-api-ms.juejin.im/v1/getUserInfo{params}\\\" test_request_headers: Dict = self.get_default_headers() test_response = self.make_request( url=test_user_url, headers=test_request_headers ) if (\",\n \"None): req_data: dict = { \\\"src\\\": \\\"web\\\", \\\"uid\\\": self._login_uid, \\\"device_id\\\": self._login_client_id, \\\"token\\\": self._login_token,\",\n \"entry_data[\\\"title\\\"], \\\"blogHref\\\": entry_data[\\\"originalUrl\\\"], \\\"blogViewers\\\": entry_data[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": datetime_str_change_fmt( time_str=entry_data[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ), } self._like_blogs_data.append(blog_data) page_no\",\n \"rest_count != 0: total_pages += 1 self._like_blogs_total_page = total_pages entry_list = self._response_data[\\\"d\\\"][\\\"entryList\\\"] if\",\n \"or check_is_json(test_response.content.decode()) is not True ): logger.error(f\\\"当前掘金账号登录状态: 已退出!\\\") self._async_task.remove_async_scheduler(job_id=self._spider_name) return False test_json_response =\",\n \"get_result is None: self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\\\"&\\\")[1:-1] self._login_uid =\",\n \"= None entry_list = self._response_data[\\\"d\\\"][\\\"entrylist\\\"] if len(entry_list) > 0: for personal_blog in entry_list:\",\n \"\\\"blogViewers\\\": entry_data[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": datetime_str_change_fmt( time_str=entry_data[\\\"createdAt\\\"], prev_fmt=\\\"%Y-%m-%dT%H:%M:%S.%fZ\\\", ), } self._like_blogs_data.append(blog_data) page_no += 1 if\",\n \"and email_login is None: raise ValueError(\\\"Your login username is illegal!\\\") if phone_login is\",\n \"login_url, login_data = self._check_username() response = self.make_request( url=login_url, headers=self._common_headers, method=\\\"POST\\\", json=login_data, ) if\",\n \"self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) else: try: login_params = get_result.split(\\\"&\\\")[1:-1] self._login_uid = [d for d\",\n \"= username self._login_password = password self._spider_name: str = f\\\"juejin:{self._login_username}\\\" self._login_cookies: Optional[str] = None\",\n \"str): if method == BaseSpiderParseMethodType.LoginResult: self._parse_login_data() elif method == BaseSpiderParseMethodType.PersonalBlogs: self._parse_personal_blogs() self._parse_personal_like_blogs() elif\",\n \"self.set_data(spider_name=f\\\"{self._spider_name}:params\\\", data=params) # 个人数据 username = self._response_data[\\\"user\\\"][\\\"username\\\"] description = self._response_data[\\\"user\\\"][\\\"selfDescription\\\"] avatar_img = self._response_data[\\\"user\\\"][\\\"avatarLarge\\\"]\",\n \"log_level_int=LOG_LEVEL ) class JuejinSpider(BaseSpider): def __init__(self, task_id: str, username: str, password: str): self._main_url\",\n \"+= f\\\"&{data[0]}={data[1]}\\\" blogs_url: str = f\\\"{self._blogs_url}{url_params}\\\" response = self.make_request(url=blogs_url, headers=self._common_headers) if response.content.decode() !=\",\n \"\\\"\\\" for index, data in enumerate(req_data.items()): if index == 0: url_params += f\\\"?{data[0]}={data[1]}\\\"\",\n \"req_data: dict = { \\\"src\\\": \\\"web\\\", \\\"uid\\\": self._login_uid, \\\"device_id\\\": self._login_client_id, \\\"token\\\": self._login_token, \\\"targetUid\\\":\",\n \"response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items() ).to_str() logger.debug(self._login_cookies) self.set_cookies( spider_name=self._spider_name, cookies=self._login_cookies ) self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult\",\n \"str = f\\\"juejin:{self._login_username}\\\" self._login_cookies: Optional[str] = None self._login_token: Optional[str] = None self._login_uid: Optional[str]\",\n \"self.make_request( url=login_url, headers=self._common_headers, method=\\\"POST\\\", json=login_data, ) if response.content.decode() != \\\"\\\": logger.info(\\\"登录成功!\\\") self._response_data =\",\n \"login_params = get_result.split(\\\"&\\\")[1:-1] self._login_uid = [d for d in login_params if \\\"uid\\\" in\",\n \"req_data.update(before=next_params) url_params: str = \\\"\\\" for index, data in enumerate(req_data.items()): if index ==\",\n \"utils.time_utils import datetime_str_change_fmt from utils.exception_utils import LoginException, ParseDataException from spiders import BaseSpider, BaseSpiderParseMethodType,\",\n \"in entry_list: if entry_data is None: continue blog_data: Dict = { \\\"blogId\\\": entry_data[\\\"objectId\\\"],\",\n \"login_data: Dict = {\\\"password\\\": self._login_password} if phone_login is None and email_login is None:\",\n \"1}页的数据!\\\") if page_no == 0: total_count = self._response_data[\\\"d\\\"][\\\"total\\\"] total_pages = total_count // 20\",\n \"entry_data is None: continue blog_data: Dict = { \\\"blogId\\\": entry_data[\\\"objectId\\\"], \\\"blogTitle\\\": entry_data[\\\"title\\\"], \\\"blogHref\\\":\",\n \"# 任务末尾 self.parse_data_with_method(method=BaseSpiderParseMethodType.Finish) else: logger.error(\\\"查询个人点赞博客失败!\\\") self.update_task_status( task_id=self._task_id, data=str(PROCESS_STATUS_FAIL) ) raise ParseDataException() def _test_cookies(self,\",\n \"personal_blog[\\\"title\\\"], \\\"blogHref\\\": personal_blog[\\\"originalUrl\\\"], \\\"blogViewers\\\": personal_blog[\\\"viewsCount\\\"], \\\"blogCreateTime\\\": blog_create_time, } self._blogs_data.append(blog_data) next_page_variable = personal_blog[\\\"verifyCreatedAt\\\"] if\",\n \") if response.content.decode() != \\\"\\\": logger.info(\\\"登录成功!\\\") self._response_data = response.json() self._login_cookies = CookieUtils( cookie_list=response.cookies.items()\",\n \"# TODO 后面考虑多线程进行任务拆分，并发获取数据 time.sleep(0.5) self._parse_personal_like_blogs(page_no=page_no) else: # logger.debug(self._like_blogs_data) logger.debug(f\\\"获取到 {len(self._like_blogs_data)} 条个人点赞博客\\\") self.data_model.set_personal_like_blogs_data( data=self._like_blogs_data\",\n \"Exception as err: logger.error(f\\\"解析 Redis 返回数据失败! 错误原因: {err}\\\") self.parse_data_with_method( method=BaseSpiderParseMethodType.LoginResult ) def _parse_login_data(self):\",\n \"False test_json_response = test_response.json() if test_json_response[\\\"s\\\"] == 1: logger.info(f\\\"当前掘金账号为: {self._login_username}, 状态: 已登录\\\") return\",\n \"= personal_blog[\\\"verifyCreatedAt\\\"] if self._response_data[\\\"d\\\"][\\\"total\\\"] > 20: time.sleep(0.5) self._parse_personal_blogs(next_params=next_page_variable) else: logger.debug(self._blogs_data) self.data_model.set_personal_blogs_data(data=self._blogs_data) logger.info(\\\"获取个人博客数据成功!\\\") else:\",\n \"for d in login_params if \\\"uid\\\" in d][ 0 ].replace(\\\"uid=\\\", \\\"\\\") self._login_token =\"\n]","isConversational":false}}},{"rowIdx":1485,"cells":{"ngram":{"kind":"list like","value":["36, 40, 44, 48, 52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48,","52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else:","ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in","44, 48, 52, 56,60, 64]) else: channel_optional.append( [4, 8, 12, 16, 20, 24,","# channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32])) channel_list.append(32) elif 13","channel_optional.append([12, 16]) elif 7 < i <= 14: channel_optional.append([4, 8, 12, 16, 20,","RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set","16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 60, 64])","[4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52,","trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import","36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list) net2","import paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert,","elif 14 < i <= 21: channel_optional.append( [4, 8, 12, 16, 20, 24,","channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif 7 < i <= 13: #","12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 60,","from paddle.vision.datasets import Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay,","56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) distill_config =","# channel_optional.append([20, 24, 28, 32]) elif 14 < i <= 21: channel_optional.append( [4,","# channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif 7 < i <= 13:","14 < i <= 21: channel_optional.append( [4, 8, 12, 16, 20, 24, 28,","5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD","MultiStepDecay, LinearWarmup import random from resnet20 import * import paddle # supernet trainning","channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16]) elif 7 < i <= 14:","else: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32, 36, 40,","= ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in range(0, 23): if","channel_list = [] for i in range(1, 21): if 0 < i <=","32]) # channel_optional.append([20, 24, 28, 32]) elif 14 < i <= 21: channel_optional.append(","CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms =","40, 44, 48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model","i <= 14: channel_optional.append([4, 8, 12, 16, 20, 24, 28, 32]) # channel_optional.append([20,","WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865,","= './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY),","RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)])","channel_optional.append([20, 24, 28, 32]) elif 14 < i <= 21: channel_optional.append( [4, 8,","paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list = [] for","= 5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409]","Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR","in range(0, 23): if i <= 7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12,","import Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils","< i <= 19: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28,","from paddle.vision.transforms import ( ToTensor, RandomHorizontalFlip, RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop,",") from paddle.vision.datasets import Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay,","= supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net)","ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train',","from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20 import * import","48, 52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12, 16, 20,","12, 16, 20, 24, 28, 32])) channel_list.append(32) elif 13 < i <= 19:","CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20 import * import paddle # supernet","transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints', save_freq=100, shuffle=True,","基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import OFA,","< i <= 13: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28,","28, 32]) elif 14 < i <= 21: channel_optional.append( [4, 8, 12, 16,","mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints', save_freq=100,","MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE","parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(),","= Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE,","channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in range(0, 23): if i <=","supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH","52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24,","48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net)","= OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1","0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4),","7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16]) elif 7 < i <=","import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20 import * import paddle #","28, 32]) # channel_optional.append([20, 24, 28, 32]) elif 14 < i <= 21:","paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9","8, 12, 16, 20, 24, 28, 32]) # channel_optional.append([20, 24, 28, 32]) elif","[0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum(","i in range(0, 23): if i <= 7: channel_optional.append([4, 8, 12, 16]) #","OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list = [] for i in","= DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel')","ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in range(0, 23): if i","= paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM =","sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model =","4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52,","range(1, 21): if 0 < i <= 7: # channel_list.append(random.choice([ 4, 8, 12,","channel_optional = [] for i in range(0, 23): if i <= 7: channel_optional.append([4,","= [] for i in range(0, 23): if i <= 7: channel_optional.append([4, 8,","60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2)","= 0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942,","import ( ToTensor, RandomHorizontalFlip, RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation","LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN","4, 8, 12, 16])) channel_list.append(16) elif 7 < i <= 13: # channel_list.append(random.choice([","RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set =","i <= 7: # channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif 7 <","20, 24, 28, 32])) channel_list.append(32) elif 13 < i <= 19: # channel_list.append(random.choice([","23): if i <= 7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16]) elif","[] for i in range(0, 23): if i <= 7: channel_optional.append([4, 8, 12,","= 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN =","# https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig,","transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set,","Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100 from","LinearWarmup import random from resnet20 import * import paddle # supernet trainning 基于paddleslim模型压缩包","40, 44, 48, 52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52,","callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints', save_freq=100, shuffle=True, num_workers=4, verbose=1, callbacks=callbacks, )","DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model","if 0 < i <= 7: # channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16)","19: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32, 36, 40,","[] for i in range(1, 21): if 0 < i <= 7: #","<= 19: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32, 36,","128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE =","48, 52, 56,60, 64]) else: channel_optional.append( [4, 8, 12, 16, 20, 24, 28,","48, 52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64])","import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list = [] for i","56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net =","8, 12, 16]) # channel_optional.append([12, 16]) elif 7 < i <= 14: channel_optional.append([4,","56,60, 64]) else: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36,","0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071,","# supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from","net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in range(0, 23): if i <= 7:","32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list)","RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(),","7 < i <= 14: channel_optional.append([4, 8, 12, 16, 20, 24, 28, 32])","12, 16])) channel_list.append(16) elif 7 < i <= 13: # channel_list.append(random.choice([ 4, 8,","32])) channel_list.append(32) elif 13 < i <= 19: # channel_list.append(random.choice([ 4, 8, 12,","<= 7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16]) elif 7 < i","momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)),","channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48,","Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random","RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE,","= 300 LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE =","range(0, 23): if i <= 7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16])","paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5)))","16]) elif 7 < i <= 14: channel_optional.append([4, 8, 12, 16, 20, 24,","Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr","Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms)","test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH,","24, 28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) else: #","0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR,","56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28,","[LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints', save_freq=100, shuffle=True, num_workers=4, verbose=1, callbacks=callbacks,","ToTensor, RandomHorizontalFlip, RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from","in range(1, 21): if 0 < i <= 7: # channel_list.append(random.choice([ 4, 8,","16])) channel_list.append(16) elif 7 < i <= 13: # channel_list.append(random.choice([ 4, 8, 12,","64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model,","from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list = []","32, 36, 40, 44, 48, 52, 56, 60, 64]) # channel_optional.append([36, 40, 44,","BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958]","= 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE","paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN,","52, 56,60, 64]) else: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32,","CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks =","64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config","52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) distill_config","24, 28, 32])) channel_list.append(32) elif 13 < i <= 19: # channel_list.append(random.choice([ 4,","44, 48, 52, 56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list) net2 = ResNet20(100,","# channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config =","8, 12, 16, 20, 24, 28, 32])) channel_list.append(32) elif 13 < i <=","# channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44,","model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM","16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64)","52, 56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams'))","train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(),","Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit(","< i <= 14: channel_optional.append([4, 8, 12, 16, 20, 24, 28, 32]) #","i <= 19: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32,","# channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else: channel_optional.append( [4, 8, 12,","RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100 from paddle.io import DataLoader from","elif 13 < i <= 19: # channel_list.append(random.choice([ 4, 8, 12, 16, 20,","from paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from","import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20 import","supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa","2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32,","44, 48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model =","HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100 from paddle.io","channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in range(0,","64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else: channel_optional.append( [4, 8,","300 LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128","<= 13: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32])) channel_list.append(32)","'./data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(),","= [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000,","[0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0.,","resnet20 import * import paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from","52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net","padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN,","14: channel_optional.append([4, 8, 12, 16, 20, 24, 28, 32]) # channel_optional.append([20, 24, 28,","channel_list.append(16) elif 7 < i <= 13: # channel_list.append(random.choice([ 4, 8, 12, 16,","= Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms","ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100 from paddle.io import DataLoader","20, 24, 28, 32]) # channel_optional.append([20, 24, 28, 32]) elif 14 < i","RandomHorizontalFlip, RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets","44, 48, 52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12, 16,","< i <= 7: # channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif 7","i <= 21: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36,","16]) # channel_optional.append([12, 16]) elif 7 < i <= 14: channel_optional.append([4, 8, 12,","< i <= 21: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32,","* import paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import","DistillConfig from paddleslim.nas.ofa.utils import utils channel_list = [] for i in range(1, 21):","28, 32])) channel_list.append(32) elif 13 < i <= 19: # channel_list.append(random.choice([ 4, 8,","else: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44,","from resnet20 import * import paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star","40, 44, 48, 52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12,","7 < i <= 13: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24,","64])) channel_list.append(64) net = ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional =","44, 48, 52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60,","24, 28, 32]) elif 14 < i <= 21: channel_optional.append( [4, 8, 12,","21): if 0 < i <= 7: # channel_list.append(random.choice([ 4, 8, 12, 16]))","16, 20, 24, 28, 32])) channel_list.append(32) elif 13 < i <= 19: #","random from resnet20 import * import paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim","0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup(","60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else: channel_optional.append( [4,","28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([","if i <= 7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16]) elif 7","sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH =","net = ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for","( ToTensor, RandomHorizontalFlip, RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation )","CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH),","elif 7 < i <= 13: # channel_list.append(random.choice([ 4, 8, 12, 16, 20,","Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints',","paddle.vision.transforms import ( ToTensor, RandomHorizontalFlip, RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize,","12, 16]) # channel_optional.append([12, 16]) elif 7 < i <= 14: channel_optional.append([4, 8,","paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20","for i in range(0, 23): if i <= 7: channel_optional.append([4, 8, 12, 16])","<= 14: channel_optional.append([4, 8, 12, 16, 20, 24, 28, 32]) # channel_optional.append([20, 24,","24, 28, 32, 36, 40, 44, 48, 52, 56, 60, 64]) # channel_optional.append([36,","MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD =","21: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44,","paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import","channel_optional.append([4, 8, 12, 16, 20, 24, 28, 32]) # channel_optional.append([20, 24, 28, 32])","MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([","distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY =","ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY = 5e-4","channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48,","for i in range(1, 21): if 0 < i <= 7: # channel_list.append(random.choice([","Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks","13 < i <= 19: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24,","BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100 from paddle.io import","0 < i <= 7: # channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif","from paddleslim.nas.ofa.utils import utils channel_list = [] for i in range(1, 21): if","40, 44, 48, 52, 56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list) net2 =","https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig","= Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')]","mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set,","32]) elif 14 < i <= 21: channel_optional.append( [4, 8, 12, 16, 20,","distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config)","= Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300","20, 24, 28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) net","channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else: channel_optional.append( [4, 8, 12, 16,","elif 7 < i <= 14: channel_optional.append([4, 8, 12, 16, 20, 24, 28,","CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set","RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list = [] for i in range(1,","OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY","utils channel_list = [] for i in range(1, 21): if 0 < i","= [] for i in range(1, 21): if 0 < i <= 7:","欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from","56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else: channel_optional.append(","net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in range(0, 23):","channel_list.append(64) net = ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = []","8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56,","ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR =","import Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import","= Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test',","8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56,60,","4, 8, 12, 16, 20, 24, 28, 32])) channel_list.append(32) elif 13 < i","32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4,","RandomRotation ) from paddle.vision.datasets import Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr import","channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32, 36,","0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR),","7: # channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif 7 < i <=","Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms =","]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set =","import * import paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super","supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list =","channel_list.append(32) elif 13 < i <= 19: # channel_list.append(random.choice([ 4, 8, 12, 16,","= ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i","import utils channel_list = [] for i in range(1, 21): if 0 <","learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms","from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils","paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet","13: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32])) channel_list.append(32) elif","= [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare(","5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD),","<= 21: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36, 40,","channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional)","16, 20, 24, 28, 32]) # channel_optional.append([20, 24, 28, 32]) elif 14 <","transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ])","RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import","channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32])) channel_list.append(32) elif 13 <","24, 28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) net =","val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE,","36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8,","0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM,","DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20 import *","Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list","28, 32, 36, 40, 44, 48, 52, 56, 60, 64]) # channel_optional.append([36, 40,","import random from resnet20 import * import paddle # supernet trainning 基于paddleslim模型压缩包 #","weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15),","28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) net = ResNet20(100,","48, 52, 56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list) net2 = ResNet20(100, channel_list)","20, 24, 28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) else:","i in range(1, 21): if 0 < i <= 7: # channel_list.append(random.choice([ 4,","LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)),","64]) else: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36, 40,","paddle.vision.datasets import Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup","CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(),","64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32,","56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional","24, 28, 32]) # channel_optional.append([20, 24, 28, 32]) elif 14 < i <=","12, 16, 20, 24, 28, 32]) # channel_optional.append([20, 24, 28, 32]) elif 14","12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56,60, 64]))","i <= 7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16]) elif 7 <","model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1,","= [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints', save_freq=100, shuffle=True, num_workers=4, verbose=1,","callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints', save_freq=100, shuffle=True, num_workers=4,","# channel_optional.append([12, 16]) elif 7 < i <= 14: channel_optional.append([4, 8, 12, 16,","SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100","i <= 13: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32]))","DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(),","paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20 import * import paddle","Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms)","<= 7: # channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif 7 < i","0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918,","8, 12, 16])) channel_list.append(16) elif 7 < i <= 13: # channel_list.append(random.choice([ 4,","40, 44, 48, 52, 56,60, 64]) else: channel_optional.append( [4, 8, 12, 16, 20,","CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz'","20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 60, 64]) #","paddleslim.nas.ofa.utils import utils channel_list = [] for i in range(1, 21): if 0"],"string":"[\n \"36, 40, 44, 48, 52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48,\",\n \"52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else:\",\n \"ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in\",\n \"44, 48, 52, 56,60, 64]) else: channel_optional.append( [4, 8, 12, 16, 20, 24,\",\n \"# channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32])) channel_list.append(32) elif 13\",\n \"channel_optional.append([12, 16]) elif 7 < i <= 14: channel_optional.append([4, 8, 12, 16, 20,\",\n \"RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set\",\n \"16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 60, 64])\",\n \"[4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52,\",\n \"trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import\",\n \"36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list) net2\",\n \"import paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert,\",\n \"elif 14 < i <= 21: channel_optional.append( [4, 8, 12, 16, 20, 24,\",\n \"channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif 7 < i <= 13: #\",\n \"12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 60,\",\n \"from paddle.vision.datasets import Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay,\",\n \"56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) distill_config =\",\n \"# channel_optional.append([20, 24, 28, 32]) elif 14 < i <= 21: channel_optional.append( [4,\",\n \"# channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif 7 < i <= 13:\",\n \"14 < i <= 21: channel_optional.append( [4, 8, 12, 16, 20, 24, 28,\",\n \"5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD\",\n \"MultiStepDecay, LinearWarmup import random from resnet20 import * import paddle # supernet trainning\",\n \"channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16]) elif 7 < i <= 14:\",\n \"else: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32, 36, 40,\",\n \"= ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in range(0, 23): if\",\n \"channel_list = [] for i in range(1, 21): if 0 < i <=\",\n \"32]) # channel_optional.append([20, 24, 28, 32]) elif 14 < i <= 21: channel_optional.append(\",\n \"CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms =\",\n \"40, 44, 48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model\",\n \"i <= 14: channel_optional.append([4, 8, 12, 16, 20, 24, 28, 32]) # channel_optional.append([20,\",\n \"WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865,\",\n \"= './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY),\",\n \"RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)])\",\n \"channel_optional.append([20, 24, 28, 32]) elif 14 < i <= 21: channel_optional.append( [4, 8,\",\n \"paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list = [] for\",\n \"= 5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409]\",\n \"Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR\",\n \"in range(0, 23): if i <= 7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12,\",\n \"import Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils\",\n \"< i <= 19: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28,\",\n \"from paddle.vision.transforms import ( ToTensor, RandomHorizontalFlip, RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop,\",\n \") from paddle.vision.datasets import Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay,\",\n \"= supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net)\",\n \"ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train',\",\n \"from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20 import * import\",\n \"48, 52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12, 16, 20,\",\n \"12, 16, 20, 24, 28, 32])) channel_list.append(32) elif 13 < i <= 19:\",\n \"CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20 import * import paddle # supernet\",\n \"transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints', save_freq=100, shuffle=True,\",\n \"基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import OFA,\",\n \"< i <= 13: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28,\",\n \"28, 32]) elif 14 < i <= 21: channel_optional.append( [4, 8, 12, 16,\",\n \"mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints', save_freq=100,\",\n \"MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE\",\n \"parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(),\",\n \"= Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE,\",\n \"channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in range(0, 23): if i <=\",\n \"supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH\",\n \"52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24,\",\n \"48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net)\",\n \"= OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1\",\n \"0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4),\",\n \"7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16]) elif 7 < i <=\",\n \"import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20 import * import paddle #\",\n \"28, 32]) # channel_optional.append([20, 24, 28, 32]) elif 14 < i <= 21:\",\n \"paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9\",\n \"8, 12, 16, 20, 24, 28, 32]) # channel_optional.append([20, 24, 28, 32]) elif\",\n \"[0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum(\",\n \"i in range(0, 23): if i <= 7: channel_optional.append([4, 8, 12, 16]) #\",\n \"OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list = [] for i in\",\n \"= DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel')\",\n \"ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in range(0, 23): if i\",\n \"= paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM =\",\n \"sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model =\",\n \"4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52,\",\n \"range(1, 21): if 0 < i <= 7: # channel_list.append(random.choice([ 4, 8, 12,\",\n \"channel_optional = [] for i in range(0, 23): if i <= 7: channel_optional.append([4,\",\n \"= [] for i in range(0, 23): if i <= 7: channel_optional.append([4, 8,\",\n \"60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2)\",\n \"= 0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942,\",\n \"import ( ToTensor, RandomHorizontalFlip, RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation\",\n \"LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN\",\n \"4, 8, 12, 16])) channel_list.append(16) elif 7 < i <= 13: # channel_list.append(random.choice([\",\n \"RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set =\",\n \"i <= 7: # channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif 7 <\",\n \"20, 24, 28, 32])) channel_list.append(32) elif 13 < i <= 19: # channel_list.append(random.choice([\",\n \"23): if i <= 7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16]) elif\",\n \"[] for i in range(0, 23): if i <= 7: channel_optional.append([4, 8, 12,\",\n \"= 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN =\",\n \"# https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig,\",\n \"transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set,\",\n \"Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100 from\",\n \"LinearWarmup import random from resnet20 import * import paddle # supernet trainning 基于paddleslim模型压缩包\",\n \"40, 44, 48, 52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52,\",\n \"callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints', save_freq=100, shuffle=True, num_workers=4, verbose=1, callbacks=callbacks, )\",\n \"DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model\",\n \"if 0 < i <= 7: # channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16)\",\n \"19: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32, 36, 40,\",\n \"[] for i in range(1, 21): if 0 < i <= 7: #\",\n \"<= 19: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32, 36,\",\n \"128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE =\",\n \"48, 52, 56,60, 64]) else: channel_optional.append( [4, 8, 12, 16, 20, 24, 28,\",\n \"48, 52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64])\",\n \"import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list = [] for i\",\n \"56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net =\",\n \"8, 12, 16]) # channel_optional.append([12, 16]) elif 7 < i <= 14: channel_optional.append([4,\",\n \"56,60, 64]) else: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36,\",\n \"0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071,\",\n \"# supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from\",\n \"net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in range(0, 23): if i <= 7:\",\n \"32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list)\",\n \"RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(),\",\n \"7 < i <= 14: channel_optional.append([4, 8, 12, 16, 20, 24, 28, 32])\",\n \"12, 16])) channel_list.append(16) elif 7 < i <= 13: # channel_list.append(random.choice([ 4, 8,\",\n \"32])) channel_list.append(32) elif 13 < i <= 19: # channel_list.append(random.choice([ 4, 8, 12,\",\n \"<= 7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16]) elif 7 < i\",\n \"momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)),\",\n \"channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48,\",\n \"Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random\",\n \"RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE,\",\n \"= 300 LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE =\",\n \"range(0, 23): if i <= 7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16])\",\n \"paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5)))\",\n \"16]) elif 7 < i <= 14: channel_optional.append([4, 8, 12, 16, 20, 24,\",\n \"Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr\",\n \"Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms)\",\n \"test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH,\",\n \"24, 28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) else: #\",\n \"0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR,\",\n \"56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28,\",\n \"[LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints', save_freq=100, shuffle=True, num_workers=4, verbose=1, callbacks=callbacks,\",\n \"ToTensor, RandomHorizontalFlip, RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from\",\n \"in range(1, 21): if 0 < i <= 7: # channel_list.append(random.choice([ 4, 8,\",\n \"16])) channel_list.append(16) elif 7 < i <= 13: # channel_list.append(random.choice([ 4, 8, 12,\",\n \"64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model,\",\n \"from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list = []\",\n \"32, 36, 40, 44, 48, 52, 56, 60, 64]) # channel_optional.append([36, 40, 44,\",\n \"BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958]\",\n \"= 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE\",\n \"paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN,\",\n \"52, 56,60, 64]) else: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32,\",\n \"CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks =\",\n \"64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config\",\n \"52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) distill_config\",\n \"24, 28, 32])) channel_list.append(32) elif 13 < i <= 19: # channel_list.append(random.choice([ 4,\",\n \"44, 48, 52, 56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list) net2 = ResNet20(100,\",\n \"# channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config =\",\n \"8, 12, 16, 20, 24, 28, 32])) channel_list.append(32) elif 13 < i <=\",\n \"# channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44,\",\n \"model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM\",\n \"16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64)\",\n \"52, 56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams'))\",\n \"train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(),\",\n \"Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit(\",\n \"< i <= 14: channel_optional.append([4, 8, 12, 16, 20, 24, 28, 32]) #\",\n \"i <= 19: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32,\",\n \"# channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else: channel_optional.append( [4, 8, 12,\",\n \"RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100 from paddle.io import DataLoader from\",\n \"elif 13 < i <= 19: # channel_list.append(random.choice([ 4, 8, 12, 16, 20,\",\n \"from paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from\",\n \"import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20 import\",\n \"supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa\",\n \"2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32,\",\n \"44, 48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model =\",\n \"HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100 from paddle.io\",\n \"channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in range(0,\",\n \"64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else: channel_optional.append( [4, 8,\",\n \"300 LR = 0.1 WEIGHT_DECAY = 5e-4 MOMENTUM = 0.9 BATCH_SIZE = 128\",\n \"<= 13: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32])) channel_list.append(32)\",\n \"'./data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(),\",\n \"= [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000,\",\n \"[0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0.,\",\n \"resnet20 import * import paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from\",\n \"52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net\",\n \"padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN,\",\n \"14: channel_optional.append([4, 8, 12, 16, 20, 24, 28, 32]) # channel_optional.append([20, 24, 28,\",\n \"channel_list.append(16) elif 7 < i <= 13: # channel_list.append(random.choice([ 4, 8, 12, 16,\",\n \"= Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms\",\n \"ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100 from paddle.io import DataLoader\",\n \"20, 24, 28, 32]) # channel_optional.append([20, 24, 28, 32]) elif 14 < i\",\n \"RandomHorizontalFlip, RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets\",\n \"44, 48, 52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12, 16,\",\n \"< i <= 7: # channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif 7\",\n \"i <= 21: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36,\",\n \"16]) # channel_optional.append([12, 16]) elif 7 < i <= 14: channel_optional.append([4, 8, 12,\",\n \"< i <= 21: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32,\",\n \"* import paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import\",\n \"DistillConfig from paddleslim.nas.ofa.utils import utils channel_list = [] for i in range(1, 21):\",\n \"28, 32])) channel_list.append(32) elif 13 < i <= 19: # channel_list.append(random.choice([ 4, 8,\",\n \"else: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44,\",\n \"from resnet20 import * import paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star\",\n \"40, 44, 48, 52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12,\",\n \"7 < i <= 13: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24,\",\n \"64])) channel_list.append(64) net = ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional =\",\n \"44, 48, 52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60,\",\n \"24, 28, 32]) elif 14 < i <= 21: channel_optional.append( [4, 8, 12,\",\n \"21): if 0 < i <= 7: # channel_list.append(random.choice([ 4, 8, 12, 16]))\",\n \"16, 20, 24, 28, 32])) channel_list.append(32) elif 13 < i <= 19: #\",\n \"random from resnet20 import * import paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim\",\n \"0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup(\",\n \"60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else: channel_optional.append( [4,\",\n \"28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([\",\n \"if i <= 7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16]) elif 7\",\n \"sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH =\",\n \"net = ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for\",\n \"( ToTensor, RandomHorizontalFlip, RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation )\",\n \"CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH),\",\n \"elif 7 < i <= 13: # channel_list.append(random.choice([ 4, 8, 12, 16, 20,\",\n \"Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints',\",\n \"paddle.vision.transforms import ( ToTensor, RandomHorizontalFlip, RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize,\",\n \"12, 16]) # channel_optional.append([12, 16]) elif 7 < i <= 14: channel_optional.append([4, 8,\",\n \"paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20\",\n \"for i in range(0, 23): if i <= 7: channel_optional.append([4, 8, 12, 16])\",\n \"<= 14: channel_optional.append([4, 8, 12, 16, 20, 24, 28, 32]) # channel_optional.append([20, 24,\",\n \"24, 28, 32, 36, 40, 44, 48, 52, 56, 60, 64]) # channel_optional.append([36,\",\n \"MOMENTUM = 0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD =\",\n \"21: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44,\",\n \"paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import\",\n \"channel_optional.append([4, 8, 12, 16, 20, 24, 28, 32]) # channel_optional.append([20, 24, 28, 32])\",\n \"MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([\",\n \"distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY =\",\n \"ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY = 5e-4\",\n \"channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48,\",\n \"for i in range(1, 21): if 0 < i <= 7: # channel_list.append(random.choice([\",\n \"Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks\",\n \"13 < i <= 19: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24,\",\n \"BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100 from paddle.io import\",\n \"0 < i <= 7: # channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif\",\n \"from paddleslim.nas.ofa.utils import utils channel_list = [] for i in range(1, 21): if\",\n \"40, 44, 48, 52, 56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list) net2 =\",\n \"https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig\",\n \"= Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')]\",\n \"mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms) callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set,\",\n \"32]) elif 14 < i <= 21: channel_optional.append( [4, 8, 12, 16, 20,\",\n \"distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional) sp_model = Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config)\",\n \"= Convert(sp_net_config).convert(net) ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300\",\n \"20, 24, 28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) net\",\n \"channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else: channel_optional.append( [4, 8, 12, 16,\",\n \"elif 7 < i <= 14: channel_optional.append([4, 8, 12, 16, 20, 24, 28,\",\n \"CIFAR_STD), ]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set\",\n \"RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list = [] for i in range(1,\",\n \"OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR = 0.1 WEIGHT_DECAY\",\n \"utils channel_list = [] for i in range(1, 21): if 0 < i\",\n \"= [] for i in range(1, 21): if 0 < i <= 7:\",\n \"欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from\",\n \"56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else: channel_optional.append(\",\n \"net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i in range(0, 23):\",\n \"channel_list.append(64) net = ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = []\",\n \"8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56,\",\n \"ofa_net = OFA(sp_model, distill_config=distill_config) ofa_net.set_task('channel') model = paddle.Model(ofa_net) MAX_EPOCH = 300 LR =\",\n \"import Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import\",\n \"= Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test',\",\n \"8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56,60,\",\n \"4, 8, 12, 16, 20, 24, 28, 32])) channel_list.append(32) elif 13 < i\",\n \"32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4,\",\n \"RandomRotation ) from paddle.vision.datasets import Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr import\",\n \"channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32, 36,\",\n \"0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR),\",\n \"7: # channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif 7 < i <=\",\n \"Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ]) val_transforms =\",\n \"]) val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set =\",\n \"import * import paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super\",\n \"supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list =\",\n \"channel_list.append(32) elif 13 < i <= 19: # channel_list.append(random.choice([ 4, 8, 12, 16,\",\n \"= ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional = [] for i\",\n \"import utils channel_list = [] for i in range(1, 21): if 0 <\",\n \"learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms\",\n \"from paddleslim.nas.ofa.convert_super import Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils\",\n \"paddle # supernet trainning 基于paddleslim模型压缩包 # https://github.com/PaddlePaddle/PaddleSlim 欢迎大家多多star from paddleslim.nas.ofa.convert_super import Convert, supernet\",\n \"13: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32])) channel_list.append(32) elif\",\n \"= [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare(\",\n \"5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD),\",\n \"<= 21: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36, 40,\",\n \"channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) distill_config = DistillConfig(teacher_model=net2) sp_net_config = supernet(channel=channel_optional)\",\n \"16, 20, 24, 28, 32]) # channel_optional.append([20, 24, 28, 32]) elif 14 <\",\n \"transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD), ])\",\n \"RandomResizedCrop, SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import\",\n \"channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32])) channel_list.append(32) elif 13 <\",\n \"24, 28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) net =\",\n \"val_transforms = Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE,\",\n \"36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8,\",\n \"0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM,\",\n \"DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20 import *\",\n \"Convert, supernet from paddleslim.nas.ofa import OFA, RunConfig, DistillConfig from paddleslim.nas.ofa.utils import utils channel_list\",\n \"28, 32, 36, 40, 44, 48, 52, 56, 60, 64]) # channel_optional.append([36, 40,\",\n \"import random from resnet20 import * import paddle # supernet trainning 基于paddleslim模型压缩包 #\",\n \"weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15),\",\n \"28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) net = ResNet20(100,\",\n \"48, 52, 56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list) net2 = ResNet20(100, channel_list)\",\n \"20, 24, 28, 32, 36, 40, 44, 48, 52, 56,60, 64])) channel_list.append(64) else:\",\n \"i in range(1, 21): if 0 < i <= 7: # channel_list.append(random.choice([ 4,\",\n \"LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)),\",\n \"64]) else: channel_optional.append( [4, 8, 12, 16, 20, 24, 28, 32, 36, 40,\",\n \"paddle.vision.datasets import Cifar100 from paddle.io import DataLoader from paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup\",\n \"CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1, 5))) transforms = Compose([ RandomCrop(32, padding=4), RandomApply(BrightnessTransform(0.1)), RandomApply(ContrastTransform(0.1)), RandomHorizontalFlip(), RandomRotation(15), ToArray(),\",\n \"64])) channel_list.append(64) else: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32,\",\n \"56,60, 64])) channel_list.append(64) net = ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_optional\",\n \"24, 28, 32]) # channel_optional.append([20, 24, 28, 32]) elif 14 < i <=\",\n \"12, 16, 20, 24, 28, 32]) # channel_optional.append([20, 24, 28, 32]) elif 14\",\n \"12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56,60, 64]))\",\n \"i <= 7: channel_optional.append([4, 8, 12, 16]) # channel_optional.append([12, 16]) elif 7 <\",\n \"model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(), weight_decay=WEIGHT_DECAY), CrossEntropyLoss(), paddle.metric.Accuracy(topk=(1,\",\n \"= [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints', save_freq=100, shuffle=True, num_workers=4, verbose=1,\",\n \"callbacks = [LRSchedulerM(), callbacks.VisualDL('vis_logs/ofa_resnet20')] model.fit( train_set, test_set, epochs=MAX_EPOCH, batch_size=BATCH_SIZE, save_dir='checkpoints', save_freq=100, shuffle=True, num_workers=4,\",\n \"# channel_optional.append([12, 16]) elif 7 < i <= 14: channel_optional.append([4, 8, 12, 16,\",\n \"SaturationTransform, Compose, HueTransform, BrightnessTransform, ContrastTransform, RandomCrop, Normalize, RandomRotation ) from paddle.vision.datasets import Cifar100\",\n \"i <= 13: # channel_list.append(random.choice([ 4, 8, 12, 16, 20, 24, 28, 32]))\",\n \"DATA_FILE = './data/data76994/cifar-100-python.tar.gz' model.prepare( paddle.optimizer.Momentum( learning_rate=LinearWarmup( CosineAnnealingDecay(LR, MAX_EPOCH), 2000, 0., LR), momentum=MOMENTUM, parameters=model.parameters(),\",\n \"paddle.optimizer.lr import CosineAnnealingDecay, MultiStepDecay, LinearWarmup import random from resnet20 import * import paddle\",\n \"Compose([ToArray(), Normalize(CIFAR_MEAN, CIFAR_STD)]) train_set = Cifar100(DATA_FILE, mode='train', transform=transforms) test_set = Cifar100(DATA_FILE, mode='test', transform=val_transforms)\",\n \"<= 7: # channel_list.append(random.choice([ 4, 8, 12, 16])) channel_list.append(16) elif 7 < i\",\n \"0.9 BATCH_SIZE = 128 CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918,\",\n \"8, 12, 16])) channel_list.append(16) elif 7 < i <= 13: # channel_list.append(random.choice([ 4,\",\n \"40, 44, 48, 52, 56,60, 64]) else: channel_optional.append( [4, 8, 12, 16, 20,\",\n \"CIFAR_MEAN = [0.5071, 0.4865, 0.4409] CIFAR_STD = [0.1942, 0.1918, 0.1958] DATA_FILE = './data/data76994/cifar-100-python.tar.gz'\",\n \"20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 60, 64]) #\",\n \"paddleslim.nas.ofa.utils import utils channel_list = [] for i in range(1, 21): if 0\"\n]","isConversational":false}}},{"rowIdx":1486,"cells":{"ngram":{"kind":"list like","value":["AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,","a Pastebin link. \"\"\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\", aliases=[\"e\"], invoke_without_command=True)","@classmethod def format_tagscript(cls, tag: SlashTag, limit: int = 60) -> str: title =","slashtagset_rmeval(self, ctx: commands.Context): \"\"\"Remove the slash eval command.\"\"\" if not self.eval_command: return await","color=0xC9C9C9, title=\"SlashTags Settings\", description=\"\\n\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\"appid\") async def slashtagset_appid(self, ctx: commands.Context,","Edit a slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on","to make this argument optional, all following arguments must also be optional.*\", pred,","async def slashtag_list(self, ctx: commands.Context): \"\"\"View stored slash tags.\"\"\" tags = self.guild_tag_cache[ctx.guild.id] if","tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name, tagscript,","@slashtag_global.command(\"pastebin\", aliases=[\"++\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link:","loaded = \"loaded\" if target_state else \"unloaded\" return await ctx.send(f\"The SlashTag interaction testing","not self.eval_command: return await ctx.send(\"The eval command hasn't been registered.\") try: await self.http.remove_slash_command(self.eval_command)","TagScriptConverter, ): \"\"\" Add a user command tag with TagScript. [Slash tag usage","this software and associated documentation files (the \"Software\"), to deal in the Software","OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE","commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\"restore\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx,","Load or unload the SlashTag interaction development test cog. \"\"\" target_state = (","self.config.guild(guild).tags.clear() await ctx.send(\"Tags deleted.\") @commands.is_owner() @slashtag.group(\"global\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass",") except asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding additional arguments.\") break if","the Software without restriction, including without limitation the rights to use, copy, modify,","the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies","ctx.send(\"Timed out, not deleting slash tags.\") if not pred.result: return await ctx.send(\"Ok, not","without restriction, including without limitation the rights to use, copy, modify, merge, publish,","\"\"\" Add a slash tag with a Pastebin link. \"\"\" await self.create_slash_tag(ctx, tag_name,","name and value \" \"weren't seperated by a `:`.\", delete_after=15, ) continue if","name=\"eval\", description=\"SlashTags debugging eval command. Only bot owners can use this.\", options=[ SlashOption(name=\"body\",","Union import discord from redbot.core import commands from redbot.core.utils.chat_formatting import box, humanize_list, inline,","choice names and values you would like to add as choices to \"","Tag Stats\", color=await ctx.embed_color()) embeds = [] for usage_data in chunks(counter.most_common(), 10): usage_chart","async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None): \"\"\" Load or unload","import logging import re import types from collections import Counter from copy import","\"\"\" app_id = id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\"Application","target_state: loaded = \"Loaded\" self.add_test_cog() else: loaded = \"Unloaded\" self.remove_test_cog() await ctx.send(f\"{loaded} the","slash tag's TagScript.\"\"\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\"name\") async def slashtag_edit_name( self, ctx:",") -> List[SlashOption]: added_required = False for i in range(1, 11): try: option","TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER","exceeded the 100 character limit.\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\":\", 1)) choices.append(choice)","def _sub(match: re.Match) -> str: if match.group(1): return \"[p]slashtag global\" repl = \"global","tag's name.\"\"\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\"description\") async def slashtag_edit_description( self, ctx: commands.Context, tag:","await ctx.send(\"Query timed out, not adding additional arguments.\") break if pred.result is False:","registered.\") @commands.check(dev_check) @slashtagset.command(\"rmeval\") async def slashtagset_rmeval(self, ctx: commands.Context): \"\"\"Remove the slash eval command.\"\"\"","@slashtag.command(\"clear\", hidden=True) async def slashtag_clear(self, ctx: commands.Context): \"\"\"Clear all slash tags for this","sublicense, and/or sell copies of the Software, and to permit persons to whom","no global slash tags.\" ) return await ctx.send(message) counter = Counter({tag.name: tag.uses for","is not None else not await self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded","logging import re import types from collections import Counter from copy import copy","`{choice_text}` to a choice as its name and value \" \"weren't seperated by","See this slash tag usage stats. **Example:** `[p]slashtag usage` \"\"\" await self.show_slash_tag_usage(ctx, ctx.guild)","@slashtag_global.command(\"remove\", aliases=[\"delete\", \"-\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await","tag usage stats. **Example:** `[p]slashtag usage` \"\"\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"restore\", hidden=True)","commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\"list\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context):","( true_or_false if true_or_false is not None else not await self.config.testing_enabled() ) if","notice and this permission notice shall be included in all copies or substantial","self.send_and_query_response(ctx, query) choices = [] for choice_text in response.split(\"|\"): if \":\" not in","tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"message\")","if option_type.lower() == \"choices\": choices = await self.get_choices(ctx) option_type = \"STRING\" else: choices","async def view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global: bool, ):","for more information on slash tag arguments. \"\"\" await tag.edit_options(ctx) @slashtag_edit.command(\"argument\", aliases=[\"option\"]) async","command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name,","self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None await ctx.send(\"`/eval` has been","See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag arguments. \"\"\" await","from redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate from ..abc import MixinMeta from","return \"[p]slashtag global\" repl = \"global \" name = match.group(0) repl += name","tags on this server.\") await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context,","32 characters and can only contain characters \" \"that are alphanumeric or '_'","async def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx,","except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None await ctx.send(\"`/eval` has been deleted.\")","slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Delete a slash tag.\"\"\" await ctx.send(await tag.delete())","If you don't know what this means, you don't need to worry about","False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"message\") async def","( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType","ctx, \"Would you like to add another argument? (Y/n)\", pred ) except asyncio.TimeoutError:","ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\"description\") @copy_doc(slashtag_edit_description)","async def get_option( self, ctx: commands.Context, *, added_required: bool = False ) ->","slashtag_usage(self, ctx: commands.Context): \"\"\" See this slash tag usage stats. **Example:** `[p]slashtag usage`","slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \"\"\" Add a","body to evaluate.\", required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id","this server.\"\"\" await tag.send_info(ctx) @slashtag.command(\"raw\") async def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter):","@copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ):","tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"user\") async def slashtag_user( self, ctx: commands.Context, tag_name:","from collections import Counter from copy import copy from typing import Dict, List,","This only applies to legacy bots. If you don't know what this means,","ctx.send(f\"The SlashTag interaction testing cog is already {loaded}.\") await self.config.testing_enabled.set(target_state) if target_state: loaded","original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__","MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \"Is this argument required? (Y/n)\\n*Keep in mind that if","@slashtag.command(\"info\") async def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \"\"\"Get info about a","self.eval_command = None await ctx.send(\"`/eval` has been deleted.\") @slashtagset.command(\"testing\") async def slashtagset_testing(self, ctx:","raw content.\"\"\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit: int = 60)","@slashtag_global.command(\"usage\", aliases=[\"stats\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\"restore\", hidden=True) @copy_doc(slashtag_restore)","this server? (Y/n)\", pred ) except asyncio.TimeoutError: return await ctx.send(\"Timed out, not deleting","@slashtag_global.command(\"list\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if not tags:","discord from redbot.core import commands from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from","delete_after=15) break options.append(option) if i == 10: break pred = MessagePredicate.yes_or_no(ctx) try: await","await ctx.send(f\"Reached max choices ({CHOICE_LIMIT}).\") break return choices async def get_option( self, ctx:","(Y/n)\\n*Keep in mind that if you choose to make this argument optional, all","commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a slash tag with","copy from typing import Dict, List, Union import discord from redbot.core import commands","\"\"\"Get info about a slash tag that is stored on this server.\"\"\" await","to deal in the Software without restriction, including without limitation the rights to","deleted.\") @slashtagset.command(\"testing\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None): \"\"\" Load","*, is_global: bool, ): description = [ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda","response = await self.send_and_query_response(ctx, query) choices = [] for choice_text in response.split(\"|\"): if","ctx: commands.Context, tag: GuildTagConverter, argument: str ): \"\"\"Edit a single slash tag's argument","await self.send_and_query_response( ctx, \"Would you like to add arguments to this tag? (Y/n)\",","list of choice names and values you would like to add as choices","\"\"\"Delete a slash tag.\"\"\" await ctx.send(await tag.delete()) @slashtag.command(\"info\") async def slashtag_info(self, ctx: commands.Context,","None: pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message = await self.bot.wait_for(\"message\",","slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None): \"\"\" Load or unload the SlashTag","global\" repl = \"global \" name = match.group(0) repl += name if name.istitle():","Software without restriction, including without limitation the rights to use, copy, modify, merge,","async def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\"list\") @copy_doc(slashtag_list) async","ctx), ) except asyncio.TimeoutError: return await ctx.send(\"Tag addition timed out.\") else: description =","tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"user\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx:","def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \"\"\" Add","on this server? (Y/n)\", pred ) except asyncio.TimeoutError: return await ctx.send(\"Timed out, not","@commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"add\", aliases=[\"create\", \"+\"]) async def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *,","def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\"slashset\"]) async def slashtagset(self, ctx:","self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"message\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context,","commands.Context, tag: GuildTagConverter): \"\"\" Edit a slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html)","if name.istitle(): repl = repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden:","if true_or_false is not None else not await self.config.testing_enabled() ) if target_state is","def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await","slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add","async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\"argument\", aliases=[\"option\"]) @copy_doc(slashtag_edit_argument) async","choice_text in response.split(\"|\"): if \":\" not in choice_text: await ctx.send( f\"Failed to parse","OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. \"\"\" import asyncio import","= \"global \" name = match.group(0) repl += name if name.istitle(): repl =","valid_option_types])}\", \"(select `string` if you don't understand)\", ] option_type = await self.send_and_query_response( ctx,","match.group(0) repl += name if name.istitle(): repl = repl.title() return repl def copy_doc(original:","is stored on this server.\"\"\" await tag.send_info(ctx) @slashtag.command(\"raw\") async def slashtag_raw(self, ctx: commands.Context,","name.istitle(): repl = repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command,","\"\" if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would","range(1, 11): try: option = await self.get_option(ctx, added_required=added_required) if not option.required: added_required =","icon_url=ctx.me.avatar_url) else: slash_tags = \"slash tags\" e.set_author(name=\"Stored Slash Tags\", icon_url=ctx.guild.icon_url) embeds = []","async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \"\"\" Edit a slash tag's arguments.","global slash tags.\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\"usage\", aliases=[\"stats\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self,","tag with a Pastebin link. \"\"\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\",","@slashtag.command(\"restore\", hidden=True) async def slashtag_restore(self, ctx: commands.Context): \"\"\"Restore all slash tags from the","= MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \"\\n\".join(name_desc), name_pred) match = name_pred.result name, description =","a slash tag's raw content.\"\"\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit:","from copy import copy from typing import Dict, List, Union import discord from","ctx: commands.Context): \"\"\"Manage SlashTags settings.\"\"\" @slashtagset.command(\"settings\") async def slashtagset_settings(self, ctx: commands.Context): \"\"\"View SlashTags","f\"Test cog loaded: {testing_enabled}\", ] embed = discord.Embed( color=0xC9C9C9, title=\"SlashTags Settings\", description=\"\\n\".join(description) )","commands.Context, id: int = None): \"\"\" Manually set the application ID for [botname]","slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *, description: str ): \"\"\"Edit a slash","description = [ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t: t.name) ] description","async def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *, description: str ): \"\"\"Edit","TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\"tagscript\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context,","tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a slash tag.\"\"\" await ctx.send(await tag.edit_tagscript(tagscript))","await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None):","ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ): \"\"\"Edit a slash tag's name.\"\"\"","tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\"argument\", aliases=[\"option\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context,","tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"pastebin\", aliases=[\"++\"]) async def slashtag_pastebin( self, ctx:","else self.global_tag_cache if not tags: message = ( \"This server has no slash","MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you like to add another argument? (Y/n)\",","@slashtag_global.command(\"raw\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\"list\")","free of charge, to any person obtaining a copy of this software and","and this permission notice shall be included in all copies or substantial portions","get_option( self, ctx: commands.Context, *, added_required: bool = False ) -> SlashOption: name_desc","tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a slash tag with TagScript.","ctx.send(\"`/eval` has been deleted.\") @slashtagset.command(\"testing\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool =","already {loaded}.\") await self.config.testing_enabled.set(target_state) if target_state: loaded = \"Loaded\" self.add_test_cog() else: loaded =","don't know what this means, you don't need to worry about it. \"\"\"","rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of","await ctx.send(await tag.delete()) @slashtag.command(\"info\") async def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \"\"\"Get","..http import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus","self, ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\"description\")","already registered.\") slasheval = ApplicationCommand( self, name=\"eval\", description=\"SlashTags debugging eval command. Only bot","was automatically made optional as the previous one was optional.\", delete_after=15, ) required","\"+\"]) async def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ):","headers=(\"Tag\", \"Uses\")), \"prolog\") embed = e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds,","except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def","EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES","added_required = True except asyncio.TimeoutError: await ctx.send(\"Adding this argument timed out.\", delete_after=15) break","\"\"\"Clear all slash tags for this server.\"\"\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response(","use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use TagScript blocks. \"\"\"","\"What should the tag description to be? (maximum 100 characters)\", pred=MessagePredicate.length_less(101, ctx), )","id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\"Application ID set to","`member:A member of this server.`\\n\", \"*Slash argument names may not exceed 32 characters","name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"message\") async def slashtag_message( self, ctx:","query = ( \"Send the list of choice names and values you would","DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\"list\") async def slashtag_list(self, ctx: commands.Context): \"\"\"View stored slash","notice shall be included in all copies or substantial portions of the Software.","= ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag","slashtag_list(self, ctx: commands.Context): \"\"\"View stored slash tags.\"\"\" tags = self.guild_tag_cache[ctx.guild.id] if not tags:","..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu as button_menu from","commands.Context): tags = self.global_tag_cache if not tags: return await ctx.send(\"There are no global","tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True,","tag.edit_description(description)) @slashtag_global_edit.command(\"arguments\", aliases=[\"options\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx)","stored on this server.\"\"\" await tag.send_info(ctx) @slashtag.command(\"raw\") async def slashtag_raw(self, ctx: commands.Context, *,","*, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\"pastebin\",","optional.*\", pred, ) required = pred.result else: await ctx.send( \"This argument was automatically","{slash_tags}\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\"list\") async def",") except asyncio.TimeoutError: return await ctx.send(\"Tag addition timed out.\") else: description = \"\"","tags, is_global=True) @slashtag_global.command(\"usage\", aliases=[\"stats\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\"restore\",","command {command!r} on guild {ctx.guild!r}\") # exc info unneeded since error handler should","import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\") CHOICE_RE = re.compile(r\".{1,100}:.{1,100}\") CHOICE_LIMIT = 25","ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION","argument name be and description be?\", \"The argument name and description should be","await ctx.send(embed=embed) @slashtagset.command(\"appid\") async def slashtagset_appid(self, ctx: commands.Context, id: int = None): \"\"\"","and description be?\", \"The argument name and description should be split by a","..abc import MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter,","commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\"tagscript\") @copy_doc(slashtag_edit_tagscript) async","`:`, and each choice \" \"should be seperated by `|`. Example:\\n`dog:Doggo|cat:Catto`\" ) response","try again: <https://discordapp.com/oauth2/authorize\" f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\" ) return await ctx.send(text) except Exception: log.error(\"Failed to create","if target_state else \"unloaded\" return await ctx.send(f\"The SlashTag interaction testing cog is already","\"prolog\") embed = e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\"usage\",","): description = [ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t: t.name) ]","CHOICE_LIMIT: await ctx.send(f\"Reached max choices ({CHOICE_LIMIT}).\") break return choices async def get_option( self,","bool = None): \"\"\" Load or unload the SlashTag interaction development test cog.","in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\"Tag\", \"Uses\")), \"prolog\") embed = e.copy() embed.description","choose to make this argument optional, all following arguments must also be optional.*\",","a slash tag's description.\"\"\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\"arguments\", aliases=[\"options\"]) async def slashtag_edit_arguments(self, ctx:","for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\"Tags","tags\" e.set_author(name=\"Global Slash Tags\", icon_url=ctx.me.avatar_url) else: slash_tags = \"slash tags\" e.set_author(name=\"Stored Slash Tags\",","@slashtag_global_edit.command(\"tagscript\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter","TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a user command tag with","OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,","not adding additional arguments.\") break if pred.result is False: break return options async","it differs from the bot user ID. This only applies to legacy bots.","\"\"\"Get a slash tag's raw content.\"\"\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag,","publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons","tag.edit_description(description)) @slashtag_edit.command(\"arguments\", aliases=[\"options\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \"\"\" Edit a","MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Are you sure you want to delete all","def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Get a slash tag's raw content.\"\"\"","await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await","type=command_type, ) try: await command.register() except discord.Forbidden as error: log.error( \"Failed to create","ctx: commands.Context): \"\"\"Restore all slash tags from the database.\"\"\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner()","tagscript: TagScriptConverter, ): \"\"\" Add a user command tag with TagScript. [Slash tag","def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await","THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. \"\"\" import","and values should be seperated by `:`, and each choice \" \"should be","1): embed = e.copy() embed.description = page embed.set_footer(text=f\"{index}/{len(pages)} | {len(tags)} {slash_tags}\") embeds.append(embed) #","tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"user\") async def slashtag_user( self, ctx: commands.Context,","ctx.send(\"Ok, not deleting slash tags.\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for","{eval_command}\", f\"Test cog loaded: {testing_enabled}\", ] embed = discord.Embed( color=0xC9C9C9, title=\"SlashTags Settings\", description=\"\\n\".join(description)","list(pagify(description)) for index, page in enumerate(pages, 1): embed = e.copy() embed.description = page","def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx,","slash_tags = \"slash tags\" e.set_author(name=\"Stored Slash Tags\", icon_url=ctx.guild.icon_url) embeds = [] pages =","TagScriptConverter ): \"\"\"Edit a slash tag.\"\"\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\"tagscript\") async def slashtag_edit_tagscript(","\"What should the argument name be and description be?\", \"The argument name and","SlashTags settings.\"\"\" eval_command = f\"✅ (**{self.eval_command}**)\" if self.eval_command else \"❎\" testing_enabled = \"✅\"","slash tags for this server.\"\"\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Are","embeds = [] pages = list(pagify(description)) for index, page in enumerate(pages, 1): embed","dev_check TAG_RE = re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\") CHOICE_RE = re.compile(r\".{1,100}:.{1,100}\") CHOICE_LIMIT = 25 log = logging.getLogger(\"red.phenom4n4n.slashtags.commands\")","`{id}`.\") @commands.check(dev_check) @slashtagset.command(\"addeval\") async def slashtagset_addeval(self, ctx: commands.Context): \"\"\"Add a slash eval command","def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *, description: str ): await ctx.send(await","SlashOption, SlashTag from ..testing.button_menus import menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks,","option_type = SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \"Is","embeds) @slashtag.command(\"list\") async def slashtag_list(self, ctx: commands.Context): \"\"\"View stored slash tags.\"\"\" tags =","isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__ = doc return overriden return decorator","): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"user\") @copy_doc(slashtag_user) async","\"loaded\" if target_state else \"unloaded\" return await ctx.send(f\"The SlashTag interaction testing cog is","= e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\"usage\", aliases=[\"stats\"]) async","ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Delete a slash tag.\"\"\" await ctx.send(await tag.delete()) @slashtag.command(\"info\")","tag.initialize()) async def get_options( self, ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required","SOFTWARE. \"\"\" import asyncio import logging import re import types from collections import","if target_state: loaded = \"Loaded\" self.add_test_cog() else: loaded = \"Unloaded\" self.remove_test_cog() await ctx.send(f\"{loaded}","= original.help if isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden,","self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not tags: message = ( \"This server","\"unloaded\" return await ctx.send(f\"The SlashTag interaction testing cog is already {loaded}.\") await self.config.testing_enabled.set(target_state)","await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) async def slashtag_edit( self,","argument was automatically made optional as the previous one was optional.\", delete_after=15, )","self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\"Application ID set to `{id}`.\") @commands.check(dev_check)","@commands.is_owner() @slashtag.group(\"global\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\"add\") @copy_doc(slashtag_add) async def","slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\"restore\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context):","message = await self.bot.wait_for(\"message\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask)","\"The argument name and description should be split by a `:`.\", \"Example: `member:A","( \"This server has no slash tags.\" if guild else \"There are no","ctx), ) if option_type.lower() == \"choices\": choices = await self.get_choices(ctx) option_type = \"STRING\"","above copyright notice and this permission notice shall be included in all copies","registered.\") slasheval = ApplicationCommand( self, name=\"eval\", description=\"SlashTags debugging eval command. Only bot owners","commands.Context): \"\"\"Remove the slash eval command.\"\"\" if not self.eval_command: return await ctx.send(\"The eval","choice_text: await ctx.send( f\"Failed to parse `{choice_text}` to a choice as its name","f\"{title}{discord.utils.escape_markdown(tagscript)}\" async def view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global: bool,","self.send_and_query_response( ctx, \"Are you sure you want to delete all slash tags on","tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\"list\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags =","await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]:","await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\"tagscript\") async def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *,","documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag arguments. \"\"\" await tag.edit_options(ctx) @slashtag_edit.command(\"argument\",","f\"`{tag.type.get_prefix()}{tag.name}` - \" limit -= len(title) tagscript = tag.tagscript if len(tagscript) > limit","than or equal to 100 characters.*\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx,","await self.send_and_query_response(ctx, query) choices = [] for choice_text in response.split(\"|\"): if \":\" not","slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ): \"\"\"Edit a slash","FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS","copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original, commands.Command)","ctx.guild) @commands.is_owner() @slashtag.command(\"restore\", hidden=True) async def slashtag_restore(self, ctx: commands.Context): \"\"\"Restore all slash tags","ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name,","ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a slash tag's TagScript.\"\"\"","commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\"slashset\"]) async def slashtagset(self, ctx: commands.Context): \"\"\"Manage SlashTags","is True: await self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options,","@slashtag_edit.command(\"arguments\", aliases=[\"options\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \"\"\" Edit a slash","else: if pred.result is True: await self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name,","Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\"st\"]) async def slashtag(self, ctx: commands.Context): \"\"\" Slash Tag management with","info unneeded since error handler should print it, however info on the command","Tags\", icon_url=ctx.me.avatar_url) else: slash_tags = \"slash tags\" e.set_author(name=\"Stored Slash Tags\", icon_url=ctx.guild.icon_url) embeds =","def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query = ( \"Send the list of","arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag arguments. \"\"\"","automatically made optional as the previous one was optional.\", delete_after=15, ) required =","await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"remove\", aliases=[\"delete\", \"-\"]) async def slashtag_remove(self, ctx: commands.Context, *,","embeds = [] for usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\"Tag\", \"Uses\")),","in mind that if you choose to make this argument optional, all following","be split by a `:`.\", \"Example: `member:A member of this server.`\\n\", \"*Slash argument","commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\"description\") @copy_doc(slashtag_edit_description) async","await ctx.send(\"Timed out, not deleting slash tags.\") if not pred.result: return await ctx.send(\"Ok,","furnished to do so, subject to the following conditions: The above copyright notice","usage_chart = box(tabulate(usage_data, headers=(\"Tag\", \"Uses\")), \"prolog\") embed = e.copy() embed.description = usage_chart embeds.append(embed)","tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True)","== \"choices\": choices = await self.get_choices(ctx) option_type = \"STRING\" else: choices = []","permit persons to whom the Software is furnished to do so, subject to","ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION,","menu from redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate from ..abc import MixinMeta","= list(pagify(description)) for index, page in enumerate(pages, 1): embed = e.copy() embed.description =","copies of the Software, and to permit persons to whom the Software is","a `:`.\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await ctx.send( f\"Failed to parse","aliases=[\"stats\"]) async def slashtag_usage(self, ctx: commands.Context): \"\"\" See this slash tag usage stats.","\"\"\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"restore\", hidden=True) async def slashtag_restore(self, ctx: commands.Context): \"\"\"Restore","command_type=ApplicationCommandType.USER ) @slashtag_global.command(\"pastebin\", aliases=[\"++\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False),","\"\"\"Add a slash eval command for debugging.\"\"\" if self.eval_command: return await ctx.send(\"An eval","await ctx.send(f\"The SlashTag interaction testing cog is already {loaded}.\") await self.config.testing_enabled.set(target_state) if target_state:","= False ) -> SlashOption: name_desc = [ \"What should the argument name","tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag arguments.","ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"user\") @copy_doc(slashtag_user) async def slashtag_global_user( self,","await self.send_and_query_response(ctx, \"\\n\".join(name_desc), name_pred) match = name_pred.result name, description = match.group(1), match.group(2) valid_option_types","a single slash tag's argument by name.\"\"\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"remove\", aliases=[\"delete\",","= TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__ = doc","if not name.startswith(\"SUB\") ] valid_option_types.append(\"choices\") option_query = [ \"What should the argument type","await ctx.send(\"There are no slash tags on this server.\") await self.view_slash_tags(ctx, tags, is_global=False)","SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu as","class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\"st\"]) async def slashtag(self, ctx: commands.Context): \"\"\" Slash Tag management","this argument optional, all following arguments must also be optional.*\", pred, ) required","= box(tabulate(usage_data, headers=(\"Tag\", \"Uses\")), \"prolog\") embed = e.copy() embed.description = usage_chart embeds.append(embed) await","@slashtag_global.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *,","await ctx.send(\"The eval command hasn't been registered.\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass","is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"user\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context, tag_name:","@slashtag.command(\"pastebin\", aliases=[\"++\"]) async def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter,","check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE )","page embed.set_footer(text=f\"{index}/{len(pages)} | {len(tags)} {slash_tags}\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx,","argument name and description should be split by a `:`.\", \"Example: `member:A member","pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message = await self.bot.wait_for(\"message\", check=pred,","await ctx.send( \"This argument was automatically made optional as the previous one was","if pred.result is False: break return options async def send_and_query_response( self, ctx: commands.Context,","tags for this server.\"\"\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Are you","def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a","slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\"raw\") @copy_doc(slashtag_raw) async def","if isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__ = doc return overriden return","match.group(2) valid_option_types = [ name.lower() for name in SlashOptionType.__members__.keys() if not name.startswith(\"SUB\") ]","e.set_author(name=\"Global Slash Tags\", icon_url=ctx.me.avatar_url) else: slash_tags = \"slash tags\" e.set_author(name=\"Stored Slash Tags\", icon_url=ctx.guild.icon_url)","CHOICE_LIMIT = 25 log = logging.getLogger(\"red.phenom4n4n.slashtags.commands\") def _sub(match: re.Match) -> str: if match.group(1):","@copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\"raw\")","await self.send_and_query_response( ctx, \"Are you sure you want to delete all slash tags","to use TagScript blocks. \"\"\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"add\", aliases=[\"create\", \"+\"]) async def slashtag_add( self,","def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None): \"\"\" Load or unload the","as error: log.error( \"Failed to create command {command!r} on guild {ctx.guild!r}\", exc_info=error )","be seperated by `|`. Example:\\n`dog:Doggo|cat:Catto`\" ) response = await self.send_and_query_response(ctx, query) choices =","loaded: {testing_enabled}\", ] embed = discord.Embed( color=0xC9C9C9, title=\"SlashTags Settings\", description=\"\\n\".join(description) ) await ctx.send(embed=embed)","= [] for choice_text in response.split(\"|\"): if \":\" not in choice_text: await ctx.send(","bot owners can use this.\", options=[ SlashOption(name=\"body\", description=\"Code body to evaluate.\", required=True) ],","slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\"remove\",","mind that if you choose to make this argument optional, all following arguments","= 25 log = logging.getLogger(\"red.phenom4n4n.slashtags.commands\") def _sub(match: re.Match) -> str: if match.group(1): return","ID for [botname] slash commands if it differs from the bot user ID.","async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\"add\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx:","is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"user\") async def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False,","*, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) @copy_doc(slashtag_edit)","if self.testing_enabled else \"❎\" description = [ f\"Application ID: **{self.application_id}**\", f\"Eval command: {eval_command}\",","of this software and associated documentation files (the \"Software\"), to deal in the","tag? (Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding arguments.\")","@copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if not tags: return","enumerate(pages, 1): embed = e.copy() embed.description = page embed.set_footer(text=f\"{index}/{len(pages)} | {len(tags)} {slash_tags}\") embeds.append(embed)","repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if","all following arguments must also be optional.*\", pred, ) required = pred.result else:","await ctx.send( f\"Failed to parse `{choice_text}` to a choice as its name and","text = ( \"Looks like I don't have permission to add Slash Commands","can use this.\", options=[ SlashOption(name=\"body\", description=\"Code body to evaluate.\", required=True) ], ) await","sell copies of the Software, and to permit persons to whom the Software","\"\"\" Add a user command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\"","SlashOptionType.__members__.keys() if not name.startswith(\"SUB\") ] valid_option_types.append(\"choices\") option_query = [ \"What should the argument","self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): \"\"\"Edit a single slash tag's","tagscript, is_global=False) async def create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript: str, *,","] description = \"\\n\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \"global","@commands.is_owner() @slashtag.command(\"restore\", hidden=True) async def slashtag_restore(self, ctx: commands.Context): \"\"\"Restore all slash tags from","def get_options( self, ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required = False","await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self,","TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"message\") @copy_doc(slashtag_message)","types: {humanize_list([inline(n) for n in valid_option_types])}\", \"(select `string` if you don't understand)\", ]","get_options( self, ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required = False for","choices = [] option_type = SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx) await","List[SlashOption] ) -> List[SlashOption]: added_required = False for i in range(1, 11): try:","tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\"tagscript\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx:","self.send_and_query_response( ctx, \"What should the tag description to be? (maximum 100 characters)\", pred=MessagePredicate.length_less(101,","description.\"\"\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\"arguments\", aliases=[\"options\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter):","else \"❎\" testing_enabled = \"✅\" if self.testing_enabled else \"❎\" description = [ f\"Application","a slash tag's name.\"\"\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\"description\") async def slashtag_edit_description( self, ctx:","tag: GuildTagConverter): \"\"\"Delete a slash tag.\"\"\" await ctx.send(await tag.delete()) @slashtag.command(\"info\") async def slashtag_info(self,","a slash tag with a Pastebin link. \"\"\" await self.create_slash_tag(ctx, tag_name, link, is_global=False)","Slash Tags\", icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description)) for index, page in","check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content","command {command!r} on guild {ctx.guild!r}\", exc_info=error ) text = ( \"Looks like I","import types from collections import Counter from copy import copy from typing import","await ctx.send(\"Tag addition timed out.\") else: description = \"\" if command_type == ApplicationCommandType.CHAT_INPUT:","t: t.name) ] description = \"\\n\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags","true_or_false is not None else not await self.config.testing_enabled() ) if target_state is self.testing_enabled:","self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"user\") async def slashtag_user( self,","name: TagName(check_global=False) ): \"\"\"Edit a slash tag's name.\"\"\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\"description\") async","= await self.get_choices(ctx) option_type = \"STRING\" else: choices = [] option_type = SlashOptionType[option_type.upper()]","ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a slash tag.\"\"\" await","if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you","of the Software, and to permit persons to whom the Software is furnished",") except asyncio.TimeoutError: return await ctx.send(\"Timed out, not deleting slash tags.\") if not","bot user ID. This only applies to legacy bots. If you don't know","async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await","doc else: overriden.__doc__ = doc return overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\"st\"])","tag.send_raw_tagscript(ctx) @slashtag_global.command(\"list\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if not","is None: pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message = await","`string` if you don't understand)\", ] option_type = await self.send_and_query_response( ctx, \"\\n\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types,","adding additional arguments.\") break if pred.result is False: break return options async def","like to add arguments to this tag? (Y/n)\", pred ) except asyncio.TimeoutError: await","copyright notice and this permission notice shall be included in all copies or","usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"user\")","tags from the database.\"\"\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"clear\", hidden=True) async def slashtag_clear(self,","if self.eval_command: return await ctx.send(\"An eval command is already registered.\") slasheval = ApplicationCommand(","`:`.\", \"Example: `member:A member of this server.`\\n\", \"*Slash argument names may not exceed","TAG_RE = re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\") CHOICE_RE = re.compile(r\".{1,100}:.{1,100}\") CHOICE_LIMIT = 25 log = logging.getLogger(\"red.phenom4n4n.slashtags.commands\") def","database.\"\"\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"clear\", hidden=True) async def slashtag_clear(self, ctx: commands.Context): \"\"\"Clear","aliases=[\"++\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter,","str: if match.group(1): return \"[p]slashtag global\" repl = \"global \" name = match.group(0)","def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \"\"\" Edit a slash tag's arguments. See","set the application ID for [botname] slash commands if it differs from the","name.\"\"\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\"description\") async def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter,","async def slashtag_usage(self, ctx: commands.Context): \"\"\" See this slash tag usage stats. **Example:**","True except asyncio.TimeoutError: await ctx.send(\"Adding this argument timed out.\", delete_after=15) break options.append(option) if","about it. \"\"\" app_id = id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id","use TagScript blocks. \"\"\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"add\", aliases=[\"create\", \"+\"]) async def slashtag_add( self, ctx:","log = logging.getLogger(\"red.phenom4n4n.slashtags.commands\") def _sub(match: re.Match) -> str: if match.group(1): return \"[p]slashtag global\"","@slashtag_edit.command(\"description\") async def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *, description: str ):","List[ApplicationOptionChoice]: query = ( \"Send the list of choice names and values you","tabulate import tabulate from ..abc import MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter,","THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR","check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a message command tag with TagScript.","TagConverter, TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand,","await command.register() except discord.Forbidden as error: log.error( \"Failed to create command {command!r} on","since error handler should print it, however info on the command options is","the tag description to be? (maximum 100 characters)\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError:","n in valid_option_types])}\", \"(select `string` if you don't understand)\", ] option_type = await","global slash tags.\" ) return await ctx.send(message) counter = Counter({tag.name: tag.uses for tag","f\"✅ (**{self.eval_command}**)\" if self.eval_command else \"❎\" testing_enabled = \"✅\" if self.testing_enabled else \"❎\"","[This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use TagScript blocks. \"\"\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"add\",","SlashTag interaction testing cog is already {loaded}.\") await self.config.testing_enabled.set(target_state) if target_state: loaded =","not CHOICE_RE.match(choice_text): await ctx.send( f\"Failed to parse `{choice_text}` to a choice as \"","ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\"slashset\"]) async def slashtagset(self, ctx: commands.Context): \"\"\"Manage","async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id] if","{humanize_list([inline(n) for n in valid_option_types])}\", \"(select `string` if you don't understand)\", ] option_type","required = pred.result else: await ctx.send( \"This argument was automatically made optional as","option.required: added_required = True except asyncio.TimeoutError: await ctx.send(\"Adding this argument timed out.\", delete_after=15)","format_tagscript(cls, tag: SlashTag, limit: int = 60) -> str: title = f\"`{tag.type.get_prefix()}{tag.name}` -","import asyncio import logging import re import types from collections import Counter from","GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\"argument\", aliases=[\"option\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context, tag:","None, *, timeout: int = 60, ) -> str: if pred is None:","@slashtag.command(\"list\") async def slashtag_list(self, ctx: commands.Context): \"\"\"View stored slash tags.\"\"\" tags = self.guild_tag_cache[ctx.guild.id]","choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"message\") async def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False),","await tag.send_info(ctx) @slashtag.command(\"raw\") async def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Get a","tag_name: str, tagscript: str, *, is_global: bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT,","slash commands if it differs from the bot user ID. This only applies","cog. \"\"\" target_state = ( true_or_false if true_or_false is not None else not","ctx.send(f\"Reached max choices ({CHOICE_LIMIT}).\") break return choices async def get_option( self, ctx: commands.Context,","ctx.send(await tag.delete()) @slashtag_global.command(\"raw\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await","Manually set the application ID for [botname] slash commands if it differs from","`[p]slashtag usage` \"\"\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"restore\", hidden=True) async def slashtag_restore(self, ctx:","= ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id = None if is_global else","= None if is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description =","or '-'.\", \"The argument description must be less than or equal to 100",") text = ( \"Looks like I don't have permission to add Slash","tag.edit_name(name)) @slashtag_global_edit.command(\"description\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *, description:","distribute, sublicense, and/or sell copies of the Software, and to permit persons to","out, not adding additional arguments.\") break if pred.result is False: break return options","software and associated documentation files (the \"Software\"), to deal in the Software without","key=lambda t: t.name) ] description = \"\\n\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global:","SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"message\") async def slashtag_message( self,","async def get_options( self, ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required =","= discord.Embed(title=\"Slash Tag Stats\", color=await ctx.embed_color()) embeds = [] for usage_data in chunks(counter.most_common(),","= False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id =","tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a message command tag","await self.show_slash_tag_usage(ctx) @slashtag_global.command(\"restore\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None)","name_pred.result name, description = match.group(1), match.group(2) valid_option_types = [ name.lower() for name in","TagScript blocks. \"\"\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"add\", aliases=[\"create\", \"+\"]) async def slashtag_add( self, ctx: commands.Context,","shall be included in all copies or substantial portions of the Software. THE","slash tag's description.\"\"\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\"arguments\", aliases=[\"options\"]) async def slashtag_edit_arguments(self, ctx: commands.Context,","commands.Context): \"\"\"View SlashTags settings.\"\"\" eval_command = f\"✅ (**{self.eval_command}**)\" if self.eval_command else \"❎\" testing_enabled","i in range(1, 11): try: option = await self.get_option(ctx, added_required=added_required) if not option.required:","ctx, \"Is this argument required? (Y/n)\\n*Keep in mind that if you choose to","): options: List[SlashOption] = [] guild_id = None if is_global else ctx.guild.id if","following arguments must also be optional.*\", pred, ) required = pred.result else: await","): \"\"\"Edit a slash tag's TagScript.\"\"\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\"name\") async def","NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,","str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\"remove\", aliases=[\"delete\", \"-\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx:","this invite link and try again: <https://discordapp.com/oauth2/authorize\" f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\" ) return await ctx.send(text) except",") except asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding arguments.\") else: if pred.result",") @slashtag_global.command(\"pastebin\", aliases=[\"++\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *,","not tags: message = ( \"This server has no slash tags.\" if guild","this means, you don't need to worry about it. \"\"\" app_id = id","ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a user","await ctx.send(await tag.delete()) @slashtag_global.command(\"raw\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter):","its name and value \" \"weren't seperated by a `:`.\", delete_after=15, ) continue","await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\"arguments\", aliases=[\"options\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \"\"\"","ctx: commands.Context): \"\"\"Remove the slash eval command.\"\"\" if not self.eval_command: return await ctx.send(\"The","app_id = id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\"Application ID","from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu as button_menu","link. \"\"\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) async def","e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\"usage\", aliases=[\"stats\"]) async def","async def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \"\"\"","= await self.send_and_query_response( ctx, \"\\n\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \"choices\": choices","and each choice \" \"should be seperated by `|`. Example:\\n`dog:Doggo|cat:Catto`\" ) response =","commands.Context): pass @slashtag_global.command(\"add\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *,","..testing.button_menus import menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE =","want to delete all slash tags on this server? (Y/n)\", pred ) except","is hereby granted, free of charge, to any person obtaining a copy of","except asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding arguments.\") else: if pred.result is","aliases=[\"delete\", \"-\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await","await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"pastebin\", aliases=[\"++\"]) async def","timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async","you like to add arguments to this tag? (Y/n)\", pred ) except asyncio.TimeoutError:","*, tagscript: TagScriptConverter ): \"\"\"Edit a slash tag.\"\"\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\"tagscript\") async","import menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\")","\"What should the argument type be?\", f\"Valid option types: {humanize_list([inline(n) for n in","-= len(title) tagscript = tag.tagscript if len(tagscript) > limit - 3: tagscript =","match.group(1), match.group(2) valid_option_types = [ name.lower() for name in SlashOptionType.__members__.keys() if not name.startswith(\"SUB\")","timed out, not adding additional arguments.\") break if pred.result is False: break return","ID set to `{id}`.\") @commands.check(dev_check) @slashtagset.command(\"addeval\") async def slashtagset_addeval(self, ctx: commands.Context): \"\"\"Add a","\"\\n\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \"choices\": choices = await self.get_choices(ctx) option_type","== 10: break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you like","[]) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await","import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu as button_menu from ..utils","def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument)","tags: return await ctx.send(\"There are no global slash tags.\") await self.view_slash_tags(ctx, tags, is_global=True)","error: log.error( \"Failed to create command {command!r} on guild {ctx.guild!r}\", exc_info=error ) text","OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS","discord.Forbidden as error: log.error( \"Failed to create command {command!r} on guild {ctx.guild!r}\", exc_info=error","log.error( \"Failed to create command {command!r} on guild {ctx.guild!r}\", exc_info=error ) text =","pass @slashtag_global.command(\"add\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript:","(maximum 100 characters)\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await ctx.send(\"Tag addition timed","): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\"pastebin\", aliases=[\"++\"]) @copy_doc(slashtag_pastebin) async","self, ctx: commands.Context, *, added_required: bool = False ) -> SlashOption: name_desc =",") -> SlashOption: name_desc = [ \"What should the argument name be and","await ctx.send(\"Tags deleted.\") @commands.is_owner() @slashtag.group(\"global\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\"add\")","eval command. Only bot owners can use this.\", options=[ SlashOption(name=\"body\", description=\"Code body to","embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\"list\") async def slashtag_list(self, ctx: commands.Context): \"\"\"View stored","repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc =","from the database.\"\"\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"clear\", hidden=True) async def slashtag_clear(self, ctx:","humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from","TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER","slash tag arguments. \"\"\" await tag.edit_options(ctx) @slashtag_edit.command(\"argument\", aliases=[\"option\"]) async def slashtag_edit_argument( self, ctx:","commands.Context, query: str, pred: MessagePredicate = None, *, timeout: int = 60, )","repl += name if name.istitle(): repl = repl.title() return repl def copy_doc(original: Union[commands.Command,","if not pred.result: return await ctx.send(\"Ok, not deleting slash tags.\") guild: discord.Guild =","types from collections import Counter from copy import copy from typing import Dict,","command options is needed raise tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command,","= None, *, timeout: int = 60, ) -> str: if pred is","the SlashTag interaction development test cog. \"\"\" target_state = ( true_or_false if true_or_false","= discord.Embed( color=0xC9C9C9, title=\"SlashTags Settings\", description=\"\\n\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\"appid\") async def slashtagset_appid(self,","SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. \"\"\" import asyncio","ctx: commands.Context, query: str, pred: MessagePredicate = None, *, timeout: int = 60,","menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\"list\") async def slashtag_list(self, ctx: commands.Context): \"\"\"View","you would like to add as choices to \" \"the tag. Choice names","= \"loaded\" if target_state else \"unloaded\" return await ctx.send(f\"The SlashTag interaction testing cog","delete all slash tags on this server? (Y/n)\", pred ) except asyncio.TimeoutError: return","ctx: commands.Context): \"\"\"Clear all slash tags for this server.\"\"\" pred = MessagePredicate.yes_or_no(ctx) try:","ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True)","embed = discord.Embed( color=0xC9C9C9, title=\"SlashTags Settings\", description=\"\\n\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\"appid\") async def","optional.\", delete_after=15, ) required = False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices,","THE USE OR OTHER DEALINGS IN THE SOFTWARE. \"\"\" import asyncio import logging","eval command.\"\"\" if not self.eval_command: return await ctx.send(\"The eval command hasn't been registered.\")","\"\"\" await tag.edit_options(ctx) @slashtag_edit.command(\"argument\", aliases=[\"option\"]) async def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter,","GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType from","self.get_option(ctx, added_required=added_required) if not option.required: added_required = True except asyncio.TimeoutError: await ctx.send(\"Adding this","self.eval_command = slasheval.id await ctx.send(\"`/eval` has been registered.\") @commands.check(dev_check) @slashtagset.command(\"rmeval\") async def slashtagset_rmeval(self,","be?\", \"The argument name and description should be split by a `:`.\", \"Example:","cog loaded: {testing_enabled}\", ] embed = discord.Embed( color=0xC9C9C9, title=\"SlashTags Settings\", description=\"\\n\".join(description) ) await","hasn't been registered.\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command =","tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\"pastebin\", aliases=[\"++\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context,","copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\"Tags deleted.\") @commands.is_owner() @slashtag.group(\"global\")","interaction testing cog is already {loaded}.\") await self.config.testing_enabled.set(target_state) if target_state: loaded = \"Loaded\"","cog is already {loaded}.\") await self.config.testing_enabled.set(target_state) if target_state: loaded = \"Loaded\" self.add_test_cog() else:","merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit","= MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you like to add another argument?","commands.Context, tag_name: str, tagscript: str, *, is_global: bool = False, command_type: ApplicationCommandType =","@slashtag_global_edit.command(\"name\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True),","List[SlashOption] = [] guild_id = None if is_global else ctx.guild.id if command_type ==","another argument? (Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding","description be?\", \"The argument name and description should be split by a `:`.\",","commands.Context): \"\"\"Manage SlashTags settings.\"\"\" @slashtagset.command(\"settings\") async def slashtagset_settings(self, ctx: commands.Context): \"\"\"View SlashTags settings.\"\"\"","tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \"\"\" Add a slash tag with a","= [ \"What should the argument type be?\", f\"Valid option types: {humanize_list([inline(n) for","= await self.bot.wait_for(\"message\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await","\"\"\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"add\", aliases=[\"create\", \"+\"]) async def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False),","tag's raw content.\"\"\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit: int =","should the argument type be?\", f\"Valid option types: {humanize_list([inline(n) for n in valid_option_types])}\",","await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag( self, ctx: commands.Context, tag_name: str,","PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def","character limit.\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\":\", 1)) choices.append(choice) if len(choices) >=","( \"Looks like I don't have permission to add Slash Commands here. Reinvite","ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT","= ( \"Send the list of choice names and values you would like","\"\"\" target_state = ( true_or_false if true_or_false is not None else not await","async def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if not tags: return await","tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"message\") @copy_doc(slashtag_message) async def","WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT","LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF","from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from","tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a slash tag's TagScript.\"\"\" await self.slashtag_edit(ctx,","slash tags\" e.set_author(name=\"Global Slash Tags\", icon_url=ctx.me.avatar_url) else: slash_tags = \"slash tags\" e.set_author(name=\"Stored Slash","inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from tabulate","= f\"`{tag.type.get_prefix()}{tag.name}` - \" limit -= len(title) tagscript = tag.tagscript if len(tagscript) >","import box, humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import","argument by name.\"\"\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"remove\", aliases=[\"delete\", \"-\"]) async def slashtag_remove(self,","= tagscript[:limit] + \"...\" tagscript = tagscript.replace(\"\\n\", \" \") return f\"{title}{discord.utils.escape_markdown(tagscript)}\" async def","tagscript: TagScriptConverter, ): \"\"\" Add a slash tag with TagScript. [Slash tag usage","if len(choices) >= CHOICE_LIMIT: await ctx.send(f\"Reached max choices ({CHOICE_LIMIT}).\") break return choices async","redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate from","TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE","*, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\"tagscript\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self,","you choose to make this argument optional, all following arguments must also be","Dict, List, Union import discord from redbot.core import commands from redbot.core.utils.chat_formatting import box,","only contain characters \" \"that are alphanumeric or '_' or '-'.\", \"The argument","charge, to any person obtaining a copy of this software and associated documentation","def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original,","False ) -> SlashOption: name_desc = [ \"What should the argument name be","KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,","commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript,","-> List[ApplicationOptionChoice]: query = ( \"Send the list of choice names and values","ApplicationCommand( self, name=\"eval\", description=\"SlashTags debugging eval command. Only bot owners can use this.\",","like to add another argument? (Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed","options async def send_and_query_response( self, ctx: commands.Context, query: str, pred: MessagePredicate = None,","= 60, ) -> str: if pred is None: pred = MessagePredicate.same_context(ctx) ask","self.get_choices(ctx) option_type = \"STRING\" else: choices = [] option_type = SlashOptionType[option_type.upper()] if not","in SlashOptionType.__members__.keys() if not name.startswith(\"SUB\") ] valid_option_types.append(\"choices\") option_query = [ \"What should the","<reponame>Myst1c-a/phen-cogs<filename>slashtags/mixins/commands.py<gh_stars>0 \"\"\" MIT License Copyright (c) 2020-present phenom4n4n Permission is hereby granted, free","ctx.send(\"There are no slash tags on this server.\") await self.view_slash_tags(ctx, tags, is_global=False) async","@commands.group(aliases=[\"slashset\"]) async def slashtagset(self, ctx: commands.Context): \"\"\"Manage SlashTags settings.\"\"\" @slashtagset.command(\"settings\") async def slashtagset_settings(self,","message command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx,","persons to whom the Software is furnished to do so, subject to the","ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\"restore\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await","IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY","view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global: bool, ): description =","await ctx.send(f\"Application ID set to `{id}`.\") @commands.check(dev_check) @slashtagset.command(\"addeval\") async def slashtagset_addeval(self, ctx: commands.Context):","\"\"\" Add a message command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\"","deleting slash tags.\") if not pred.result: return await ctx.send(\"Ok, not deleting slash tags.\")","argument: str ): \"\"\"Edit a single slash tag's argument by name.\"\"\" await tag.edit_single_option(ctx,","NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND","slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\"list\") @copy_doc(slashtag_list) async def slashtag_global_list(self,","usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\"usage\", aliases=[\"stats\"]) async def slashtag_usage(self, ctx: commands.Context):","tags\" e.set_author(name=\"Stored Slash Tags\", icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description)) for index,","settings.\"\"\" eval_command = f\"✅ (**{self.eval_command}**)\" if self.eval_command else \"❎\" testing_enabled = \"✅\" if","TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def","GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a slash tag.\"\"\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\"tagscript\")","IN THE SOFTWARE. \"\"\" import asyncio import logging import re import types from","in sorted(tags.values(), key=lambda t: t.name) ] description = \"\\n\".join(description) e = discord.Embed(color=await ctx.embed_color())","commands.Context): \"\"\"Add a slash eval command for debugging.\"\"\" if self.eval_command: return await ctx.send(\"An","await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\"description\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter,","= re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\") CHOICE_RE = re.compile(r\".{1,100}:.{1,100}\") CHOICE_LIMIT = 25 log = logging.getLogger(\"red.phenom4n4n.slashtags.commands\") def _sub(match:","tag's description.\"\"\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\"arguments\", aliases=[\"options\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag:","logging.getLogger(\"red.phenom4n4n.slashtags.commands\") def _sub(match: re.Match) -> str: if match.group(1): return \"[p]slashtag global\" repl =","ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu as button_menu from ..utils import","to whom the Software is furnished to do so, subject to the following","60, ) -> str: if pred is None: pred = MessagePredicate.same_context(ctx) ask =","if not tags: message = ( \"This server has no slash tags.\" if","and can only contain characters \" \"that are alphanumeric or '_' or '-'.\",","Slash Tags\", icon_url=ctx.me.avatar_url) else: slash_tags = \"slash tags\" e.set_author(name=\"Stored Slash Tags\", icon_url=ctx.guild.icon_url) embeds","usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag( self, ctx:","applies to legacy bots. If you don't know what this means, you don't","to add arguments to this tag? (Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query","if is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response(","in the Software without restriction, including without limitation the rights to use, copy,","OTHER DEALINGS IN THE SOFTWARE. \"\"\" import asyncio import logging import re import","description=\"SlashTags debugging eval command. Only bot owners can use this.\", options=[ SlashOption(name=\"body\", description=\"Code","self, ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required = False for i","set to `{id}`.\") @commands.check(dev_check) @slashtagset.command(\"addeval\") async def slashtagset_addeval(self, ctx: commands.Context): \"\"\"Add a slash","TagName(check_global=False), *, link: PastebinConverter, ): \"\"\" Add a slash tag with a Pastebin",") try: await command.register() except discord.Forbidden as error: log.error( \"Failed to create command","return f\"{title}{discord.utils.escape_markdown(tagscript)}\" async def view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global:","management with TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how","\"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"pastebin\", aliases=[\"++\"]) async","match = name_pred.result name, description = match.group(1), match.group(2) valid_option_types = [ name.lower() for","bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id","try: option = await self.get_option(ctx, added_required=added_required) if not option.required: added_required = True except",") @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"pastebin\", aliases=[\"++\"]) async def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *,","ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required = False for i in","return message.content async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query = ( \"Send","if not tags: return await ctx.send(\"There are no global slash tags.\") await self.view_slash_tags(ctx,","eval command hasn't been registered.\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear()","Exception: log.error(\"Failed to create command {command!r} on guild {ctx.guild!r}\") # exc info unneeded","= [ f\"Application ID: **{self.application_id}**\", f\"Eval command: {eval_command}\", f\"Test cog loaded: {testing_enabled}\", ]","self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx:","self.send_and_query_response( ctx, \"Would you like to add another argument? (Y/n)\", pred ) except","10): usage_chart = box(tabulate(usage_data, headers=(\"Tag\", \"Uses\")), \"prolog\") embed = e.copy() embed.description = usage_chart","pred.result: return await ctx.send(\"Ok, not deleting slash tags.\") guild: discord.Guild = ctx.guild await","tag in tags.copy().values()}) e = discord.Embed(title=\"Slash Tag Stats\", color=await ctx.embed_color()) embeds = []","\"slash tags\" e.set_author(name=\"Stored Slash Tags\", icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description)) for","ctx: commands.Context, tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\"remove\", aliases=[\"delete\", \"-\"])","made optional as the previous one was optional.\", delete_after=15, ) required = False","tag.send_info(ctx) @slashtag.command(\"raw\") async def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Get a slash","async def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): \"\"\"Edit a","await ctx.send(\"`/eval` has been deleted.\") @slashtagset.command(\"testing\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool","= None): tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not tags: message","async def slashtagset_settings(self, ctx: commands.Context): \"\"\"View SlashTags settings.\"\"\" eval_command = f\"✅ (**{self.eval_command}**)\" if","option_type = await self.send_and_query_response( ctx, \"\\n\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \"choices\":","value exceeded the 100 character limit.\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\":\", 1))","description = \"\" if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response(","except asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding additional arguments.\") break if pred.result","def slashtag_restore(self, ctx: commands.Context): \"\"\"Restore all slash tags from the database.\"\"\" await self.restore_tags(ctx,","try: description = await self.send_and_query_response( ctx, \"What should the tag description to be?","): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\"arguments\", aliases=[\"options\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag:","as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\") CHOICE_RE =","@slashtag_global_edit.command(\"description\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *, description: str","don't have permission to add Slash Commands here. Reinvite me \" \"with this","async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query = ( \"Send the list","choice as \" \"its name or value exceeded the 100 character limit.\", delete_after=15,","timed out.\") else: description = \"\" if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx)","name.\"\"\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"remove\", aliases=[\"delete\", \"-\"]) async def slashtag_remove(self, ctx: commands.Context,","str ): \"\"\"Edit a single slash tag's argument by name.\"\"\" await tag.edit_single_option(ctx, argument)","associated documentation files (the \"Software\"), to deal in the Software without restriction, including","return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help","\"\"\" Manually set the application ID for [botname] slash commands if it differs","async def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \"\"\"","BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE","self, ctx: commands.Context, tag: GlobalTagConverter, *, description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\"arguments\",","you don't understand)\", ] option_type = await self.send_and_query_response( ctx, \"\\n\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), )","# await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\"list\") async def slashtag_list(self, ctx:","\" name = match.group(0) repl += name if name.istitle(): repl = repl.title() return","names and values should be seperated by `:`, and each choice \" \"should","legacy bots. If you don't know what this means, you don't need to","understand)\", ] option_type = await self.send_and_query_response( ctx, \"\\n\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower()","slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a","None) @commands.is_owner() @commands.group(aliases=[\"slashset\"]) async def slashtagset(self, ctx: commands.Context): \"\"\"Manage SlashTags settings.\"\"\" @slashtagset.command(\"settings\") async","raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def get_choices(self, ctx: commands.Context) ->","type be?\", f\"Valid option types: {humanize_list([inline(n) for n in valid_option_types])}\", \"(select `string` if","> limit - 3: tagscript = tagscript[:limit] + \"...\" tagscript = tagscript.replace(\"\\n\", \"","self.global_tag_cache if not tags: message = ( \"This server has no slash tags.\"","ID. This only applies to legacy bots. If you don't know what this","if match.group(1): return \"[p]slashtag global\" repl = \"global \" name = match.group(0) repl","obtaining a copy of this software and associated documentation files (the \"Software\"), to","GlobalTagConverter, *, description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\"arguments\", aliases=[\"options\"]) @copy_doc(slashtag_edit_arguments) async def","ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\"name\")","break return choices async def get_option( self, ctx: commands.Context, *, added_required: bool =","isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override =","if not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \"Is this argument required?","Reinvite me \" \"with this invite link and try again: <https://discordapp.com/oauth2/authorize\" f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\" )","= [] guild_id = None if is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT:","= [] pages = list(pagify(description)) for index, page in enumerate(pages, 1): embed =","\"\"\"Edit a slash tag's TagScript.\"\"\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\"name\") async def slashtag_edit_name(","to create command {command!r} on guild {ctx.guild!r}\") # exc info unneeded since error","exc_info=error ) text = ( \"Looks like I don't have permission to add","guild_id = None if is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description","\"the tag. Choice names and values should be seperated by `:`, and each","slashtagset_appid(self, ctx: commands.Context, id: int = None): \"\"\" Manually set the application ID","MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \"choices\": choices = await self.get_choices(ctx) option_type =","if isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override","including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense,","import re import types from collections import Counter from copy import copy from","sure you want to delete all slash tags on this server? (Y/n)\", pred","description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\"arguments\", aliases=[\"options\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx:","names and values you would like to add as choices to \" \"the","to a choice as \" \"its name or value exceeded the 100 character","or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT","by a `:`.\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await ctx.send( f\"Failed to","@copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\"slashset\"]) async def","TagName(check_global=False) ): \"\"\"Edit a slash tag's name.\"\"\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\"description\") async def","f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\" ) return await ctx.send(text) except Exception: log.error(\"Failed to create command {command!r} on","): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\"tagscript\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag:","seperated by `|`. Example:\\n`dog:Doggo|cat:Catto`\" ) response = await self.send_and_query_response(ctx, query) choices = []","3: tagscript = tagscript[:limit] + \"...\" tagscript = tagscript.replace(\"\\n\", \" \") return f\"{title}{discord.utils.escape_markdown(tagscript)}\"","ctx.send(await tag.initialize()) async def get_options( self, ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]:","{ctx.guild!r}\", exc_info=error ) text = ( \"Looks like I don't have permission to","commands.Context) -> List[ApplicationOptionChoice]: query = ( \"Send the list of choice names and","ctx: commands.Context, tag: GuildTagConverter): \"\"\" Edit a slash tag's arguments. See [this documentation","command_type == ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx, \"What should the tag","re.Match) -> str: if match.group(1): return \"[p]slashtag global\" repl = \"global \" name","a slash eval command for debugging.\"\"\" if self.eval_command: return await ctx.send(\"An eval command","choices = await self.get_choices(ctx) option_type = \"STRING\" else: choices = [] option_type =","*, tagscript: TagScriptConverter, ): \"\"\" Add a user command tag with TagScript. [Slash","await ctx.send(query) try: message = await self.bot.wait_for(\"message\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask)","self.delete_quietly(message) return message.content async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query = (","False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id = None","ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\") CHOICE_RE = re.compile(r\".{1,100}:.{1,100}\") CHOICE_LIMIT = 25 log","names may not exceed 32 characters and can only contain characters \" \"that","try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None await ctx.send(\"`/eval`","False: break return options async def send_and_query_response( self, ctx: commands.Context, query: str, pred:","added_required = False for i in range(1, 11): try: option = await self.get_option(ctx,","choices = [] for choice_text in response.split(\"|\"): if \":\" not in choice_text: await",") @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"user\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False),","self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\"remove\", aliases=[\"delete\",","Add a message command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await","COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN","description=\"\\n\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\"appid\") async def slashtagset_appid(self, ctx: commands.Context, id: int =","and values you would like to add as choices to \" \"the tag.","from ..abc import MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName,","link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context, tag:","ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE","await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit: int = 60) -> str:","redbot.core import commands from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from redbot.core.utils.menus import","ctx: commands.Context, tag: GuildTagConverter, *, description: str ): \"\"\"Edit a slash tag's description.\"\"\"","ctx: commands.Context): \"\"\" See this slash tag usage stats. **Example:** `[p]slashtag usage` \"\"\"","\" \"weren't seperated by a `:`.\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await","= \"STRING\" else: choices = [] option_type = SlashOptionType[option_type.upper()] if not added_required: pred","\"\"\" See this slash tag usage stats. **Example:** `[p]slashtag usage` \"\"\" await self.show_slash_tag_usage(ctx,","permission to add Slash Commands here. Reinvite me \" \"with this invite link","await tag.send_raw_tagscript(ctx) @slashtag_global.command(\"list\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if","(Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding arguments.\") else:","means, you don't need to worry about it. \"\"\" app_id = id or","\"...\" tagscript = tagscript.replace(\"\\n\", \" \") return f\"{title}{discord.utils.escape_markdown(tagscript)}\" async def view_slash_tags( self, ctx:","a choice as its name and value \" \"weren't seperated by a `:`.\",","icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description)) for index, page in enumerate(pages, 1):","guild else \"There are no global slash tags.\" ) return await ctx.send(message) counter","def view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global: bool, ): description","tag: GuildTagConverter, *, name: TagName(check_global=False) ): \"\"\"Edit a slash tag's name.\"\"\" await ctx.send(await","@copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ):","debugging eval command. Only bot owners can use this.\", options=[ SlashOption(name=\"body\", description=\"Code body","slasheval.id await ctx.send(\"`/eval` has been registered.\") @commands.check(dev_check) @slashtagset.command(\"rmeval\") async def slashtagset_rmeval(self, ctx: commands.Context):","None if is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description = await","raise tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize())","\"\"\" MIT License Copyright (c) 2020-present phenom4n4n Permission is hereby granted, free of","slash tag's raw content.\"\"\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit: int","from tabulate import tabulate from ..abc import MixinMeta from ..converters import ( GlobalTagConverter,","required? (Y/n)\\n*Keep in mind that if you choose to make this argument optional,","= id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\"Application ID set","if command_type == ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx, \"What should the","def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\"raw\") @copy_doc(slashtag_raw) async","def slashtagset_appid(self, ctx: commands.Context, id: int = None): \"\"\" Manually set the application","the following conditions: The above copyright notice and this permission notice shall be","@copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ):","it. \"\"\" app_id = id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await","[] option_type = SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx,","settings.\"\"\" @slashtagset.command(\"settings\") async def slashtagset_settings(self, ctx: commands.Context): \"\"\"View SlashTags settings.\"\"\" eval_command = f\"✅","= True except asyncio.TimeoutError: await ctx.send(\"Adding this argument timed out.\", delete_after=15) break options.append(option)","asyncio.TimeoutError: return await ctx.send(\"Timed out, not deleting slash tags.\") if not pred.result: return","valid_option_types = [ name.lower() for name in SlashOptionType.__members__.keys() if not name.startswith(\"SUB\") ] valid_option_types.append(\"choices\")","\"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"user\") async def","*, tag: TagConverter): \"\"\"Get info about a slash tag that is stored on","await tag.edit_options(ctx) @slashtag_global_edit.command(\"argument\", aliases=[\"option\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter,","GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\"list\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache","\"❎\" testing_enabled = \"✅\" if self.testing_enabled else \"❎\" description = [ f\"Application ID:","Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub,","name_pred) match = name_pred.result name, description = match.group(1), match.group(2) valid_option_types = [ name.lower()","commands.Context): \"\"\"Restore all slash tags from the database.\"\"\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"clear\",","values should be seperated by `:`, and each choice \" \"should be seperated","slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *, description: str ): await ctx.send(await tag.edit_description(description))","tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\"Tags deleted.\") @commands.is_owner() @slashtag.group(\"global\") @copy_doc(slashtag) async def slashtag_global(self,","await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"restore\", hidden=True) async def slashtag_restore(self, ctx: commands.Context): \"\"\"Restore all","name_desc = [ \"What should the argument name be and description be?\", \"The","return overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\"st\"]) async def slashtag(self, ctx: commands.Context):","optional as the previous one was optional.\", delete_after=15, ) required = False return","str, *, is_global: bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption]","CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.","to parse `{choice_text}` to a choice as its name and value \" \"weren't","(Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding additional arguments.\")","included in all copies or substantial portions of the Software. THE SOFTWARE IS","await self.get_option(ctx, added_required=added_required) if not option.required: added_required = True except asyncio.TimeoutError: await ctx.send(\"Adding","@commands.group(aliases=[\"st\"]) async def slashtag(self, ctx: commands.Context): \"\"\" Slash Tag management with TagScript. These","*, tagscript: TagScriptConverter, ): \"\"\" Add a slash tag with TagScript. [Slash tag","GuildTagConverter, argument: str ): \"\"\"Edit a single slash tag's argument by name.\"\"\" await","for tag in tags.copy().values()}) e = discord.Embed(title=\"Slash Tag Stats\", color=await ctx.embed_color()) embeds =","ctx, \"What should the tag description to be? (maximum 100 characters)\", pred=MessagePredicate.length_less(101, ctx),","= slasheval.id await ctx.send(\"`/eval` has been registered.\") @commands.check(dev_check) @slashtagset.command(\"rmeval\") async def slashtagset_rmeval(self, ctx:","test cog. \"\"\" target_state = ( true_or_false if true_or_false is not None else","(**{self.eval_command}**)\" if self.eval_command else \"❎\" testing_enabled = \"✅\" if self.testing_enabled else \"❎\" description","return await ctx.send(\"Ok, not deleting slash tags.\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id,","Slash Tag management with TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation","use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,","ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a slash tag","content.\"\"\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit: int = 60) ->","limit: int = 60) -> str: title = f\"`{tag.type.get_prefix()}{tag.name}` - \" limit -=","\"This server has no slash tags.\" if guild else \"There are no global","async def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Delete a slash tag.\"\"\" await","aliases=[\"option\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ):","ctx.send(embed=embed) @slashtagset.command(\"appid\") async def slashtagset_appid(self, ctx: commands.Context, id: int = None): \"\"\" Manually","await ctx.send(\"Adding this argument timed out.\", delete_after=15) break options.append(option) if i == 10:","redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates","optional, all following arguments must also be optional.*\", pred, ) required = pred.result","name be and description be?\", \"The argument name and description should be split","NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR","[Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag(","Dict[int, SlashTag], *, is_global: bool, ): description = [ self.format_tagscript(tag) for tag in","commands.Context): \"\"\" See this slash tag usage stats. **Example:** `[p]slashtag usage` \"\"\" await","'-'.\", \"The argument description must be less than or equal to 100 characters.*\",","name or value exceeded the 100 character limit.\", delete_after=15, ) continue choice =","async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\"slashset\"]) async def slashtagset(self,","embeds, DEFAULT_CONTROLS) @slashtag.command(\"usage\", aliases=[\"stats\"]) async def slashtag_usage(self, ctx: commands.Context): \"\"\" See this slash","await self.send_and_query_response( ctx, \"Is this argument required? (Y/n)\\n*Keep in mind that if you","description: str ): \"\"\"Edit a slash tag's description.\"\"\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\"arguments\", aliases=[\"options\"])","def slashtagset(self, ctx: commands.Context): \"\"\"Manage SlashTags settings.\"\"\" @slashtagset.command(\"settings\") async def slashtagset_settings(self, ctx: commands.Context):","the argument type be?\", f\"Valid option types: {humanize_list([inline(n) for n in valid_option_types])}\", \"(select","in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\"Tags deleted.\") @commands.is_owner()","asyncio.TimeoutError: await ctx.send(\"Adding this argument timed out.\", delete_after=15) break options.append(option) if i ==","License Copyright (c) 2020-present phenom4n4n Permission is hereby granted, free of charge, to",") @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"message\") async def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *,","for n in valid_option_types])}\", \"(select `string` if you don't understand)\", ] option_type =","\"Software\"), to deal in the Software without restriction, including without limitation the rights",") return await ctx.send(text) except Exception: log.error(\"Failed to create command {command!r} on guild","deal in the Software without restriction, including without limitation the rights to use,","= [ name.lower() for name in SlashOptionType.__members__.keys() if not name.startswith(\"SUB\") ] valid_option_types.append(\"choices\") option_query","tag: GuildTagConverter): \"\"\" Edit a slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for","\"\"\"Edit a slash tag.\"\"\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\"tagscript\") async def slashtag_edit_tagscript( self, ctx:","ApplicationOptionChoice(*choice_text.split(\":\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\"Reached max choices ({CHOICE_LIMIT}).\") break","to `{id}`.\") @commands.check(dev_check) @slashtagset.command(\"addeval\") async def slashtagset_addeval(self, ctx: commands.Context): \"\"\"Add a slash eval","choice as its name and value \" \"weren't seperated by a `:`.\", delete_after=15,",") await ctx.send(await tag.initialize()) async def get_options( self, ctx: commands.Context, options: List[SlashOption] )","AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE","if self.eval_command else \"❎\" testing_enabled = \"✅\" if self.testing_enabled else \"❎\" description =","discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \"global slash tags\" e.set_author(name=\"Global Slash Tags\", icon_url=ctx.me.avatar_url)","embed.description = page embed.set_footer(text=f\"{index}/{len(pages)} | {len(tags)} {slash_tags}\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS)","\"that are alphanumeric or '_' or '-'.\", \"The argument description must be less","command: {eval_command}\", f\"Test cog loaded: {testing_enabled}\", ] embed = discord.Embed( color=0xC9C9C9, title=\"SlashTags Settings\",","TagScriptConverter, ): \"\"\" Add a slash tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html)","= \"\" if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx,","not deleting slash tags.\") if not pred.result: return await ctx.send(\"Ok, not deleting slash","guild {ctx.guild!r}\", exc_info=error ) text = ( \"Looks like I don't have permission","query: str, pred: MessagePredicate = None, *, timeout: int = 60, ) ->","await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\"name\") async def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter,","def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original, commands.Command) else original.__doc__ doc","self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\"There are no slash tags on this","@commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"message\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *,","] option_type = await self.send_and_query_response( ctx, \"\\n\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() ==","await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None await ctx.send(\"`/eval` has","CHOICE_RE = re.compile(r\".{1,100}:.{1,100}\") CHOICE_LIMIT = 25 log = logging.getLogger(\"red.phenom4n4n.slashtags.commands\") def _sub(match: re.Match) ->","overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\"st\"]) async def slashtag(self, ctx: commands.Context): \"\"\"","name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try: await command.register() except discord.Forbidden as error:","TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\"description\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context,","tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"user\")","is_global=False) async def create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript: str, *, is_global:",") return await ctx.send(message) counter = Counter({tag.name: tag.uses for tag in tags.copy().values()}) e","tag.edit_options(ctx) @slashtag_global_edit.command(\"argument\", aliases=[\"option\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument:","bots. If you don't know what this means, you don't need to worry","repl = \"global \" name = match.group(0) repl += name if name.istitle(): repl","@commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"message\") async def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript:","less than or equal to 100 characters.*\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await","to add Slash Commands here. Reinvite me \" \"with this invite link and","that if you choose to make this argument optional, all following arguments must","pred.result else: await ctx.send( \"This argument was automatically made optional as the previous","aliases=[\"delete\", \"-\"]) async def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Delete a slash","so, subject to the following conditions: The above copyright notice and this permission","100 characters)\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await ctx.send(\"Tag addition timed out.\")","tag.uses for tag in tags.copy().values()}) e = discord.Embed(title=\"Slash Tag Stats\", color=await ctx.embed_color()) embeds","added_required: bool = False ) -> SlashOption: name_desc = [ \"What should the","\" \") return f\"{title}{discord.utils.escape_markdown(tagscript)}\" async def view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag],","ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\"tagscript\") @copy_doc(slashtag_edit_tagscript)","\"\"\"Restore all slash tags from the database.\"\"\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"clear\", hidden=True)","await ctx.send(\"An eval command is already registered.\") slasheval = ApplicationCommand( self, name=\"eval\", description=\"SlashTags","import Counter from copy import copy from typing import Dict, List, Union import","each choice \" \"should be seperated by `|`. Example:\\n`dog:Doggo|cat:Catto`\" ) response = await","] embed = discord.Embed( color=0xC9C9C9, title=\"SlashTags Settings\", description=\"\\n\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\"appid\") async","Counter from copy import copy from typing import Dict, List, Union import discord","slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\"slashset\"]) async def slashtagset(self, ctx: commands.Context):","characters)\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await ctx.send(\"Tag addition timed out.\") else:","commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\"edit\",","if you choose to make this argument optional, all following arguments must also","ctx: commands.Context, *, added_required: bool = False ) -> SlashOption: name_desc = [","= pred.result else: await ctx.send( \"This argument was automatically made optional as the","has no slash tags.\" if guild else \"There are no global slash tags.\"","try: await self.send_and_query_response( ctx, \"Are you sure you want to delete all slash","if you don't understand)\", ] option_type = await self.send_and_query_response( ctx, \"\\n\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx),","@slashtag_edit.command(\"tagscript\") async def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ):","@copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *, description: str ):","async def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await","from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http","no global slash tags.\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\"usage\", aliases=[\"stats\"]) @copy_doc(slashtag_usage) async def","usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"pastebin\",","on guild {ctx.guild!r}\") # exc info unneeded since error handler should print it,","to 100 characters.*\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \"\\n\".join(name_desc), name_pred) match","is self.testing_enabled: loaded = \"loaded\" if target_state else \"unloaded\" return await ctx.send(f\"The SlashTag","slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a slash","f\"Application ID: **{self.application_id}**\", f\"Eval command: {eval_command}\", f\"Test cog loaded: {testing_enabled}\", ] embed =","discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None await ctx.send(\"`/eval` has been deleted.\") @slashtagset.command(\"testing\")","ctx.send(\"Tags deleted.\") @commands.is_owner() @slashtag.group(\"global\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\"add\") @copy_doc(slashtag_add)","menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\"usage\", aliases=[\"stats\"]) async def slashtag_usage(self, ctx: commands.Context): \"\"\" See this","to parse `{choice_text}` to a choice as \" \"its name or value exceeded","\"Are you sure you want to delete all slash tags on this server?","self.global_tag_cache if not tags: return await ctx.send(\"There are no global slash tags.\") await","not pred.result: return await ctx.send(\"Ok, not deleting slash tags.\") guild: discord.Guild = ctx.guild","may not exceed 32 characters and can only contain characters \" \"that are","arguments to this tag? (Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed out,","conditions: The above copyright notice and this permission notice shall be included in","THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO","tag.delete()) @slashtag_global.command(\"raw\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx)","*, tagscript: TagScriptConverter, ): \"\"\" Add a message command tag with TagScript. [Slash","option_type.lower() == \"choices\": choices = await self.get_choices(ctx) option_type = \"STRING\" else: choices =","async def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \"\"\"Get info about a slash","tagscript: TagScriptConverter ): \"\"\"Edit a slash tag's TagScript.\"\"\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\"name\")","is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx,","None await ctx.send(\"`/eval` has been deleted.\") @slashtagset.command(\"testing\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false:","pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding additional arguments.\") break","ctx.send(\"There are no global slash tags.\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\"usage\", aliases=[\"stats\"]) @copy_doc(slashtag_usage)","[] guild_id = None if is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try:","should be seperated by `:`, and each choice \" \"should be seperated by","ctx: commands.Context): tags = self.global_tag_cache if not tags: return await ctx.send(\"There are no","name in SlashOptionType.__members__.keys() if not name.startswith(\"SUB\") ] valid_option_types.append(\"choices\") option_query = [ \"What should","alphanumeric or '_' or '-'.\", \"The argument description must be less than or","slash tags.\") if not pred.result: return await ctx.send(\"Ok, not deleting slash tags.\") guild:","ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\"tagscript\") async def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript:","\"\\n\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \"global slash tags\" e.set_author(name=\"Global","slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name,","*, added_required: bool = False ) -> SlashOption: name_desc = [ \"What should","return await ctx.send(f\"The SlashTag interaction testing cog is already {loaded}.\") await self.config.testing_enabled.set(target_state) if","FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR","not tags: return await ctx.send(\"There are no global slash tags.\") await self.view_slash_tags(ctx, tags,","for name in SlashOptionType.__members__.keys() if not name.startswith(\"SUB\") ] valid_option_types.append(\"choices\") option_query = [ \"What","@slashtag_edit.command(\"argument\", aliases=[\"option\"]) async def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ):","tagscript=tagscript) @slashtag_global_edit.command(\"name\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *, name:","if \":\" not in choice_text: await ctx.send( f\"Failed to parse `{choice_text}` to a","slashtag_clear(self, ctx: commands.Context): \"\"\"Clear all slash tags for this server.\"\"\" pred = MessagePredicate.yes_or_no(ctx)","def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\"restore\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx:","slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\"argument\", aliases=[\"option\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument(","e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \"global slash tags\" e.set_author(name=\"Global Slash","delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\":\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await","e.set_author(name=\"Stored Slash Tags\", icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description)) for index, page","ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\"pastebin\", aliases=[\"++\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self,","commands.Context, tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\"remove\", aliases=[\"delete\", \"-\"]) @copy_doc(slashtag_remove)","unneeded since error handler should print it, however info on the command options","str ): \"\"\"Edit a slash tag's description.\"\"\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\"arguments\", aliases=[\"options\"]) async","): \"\"\"Edit a slash tag.\"\"\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\"tagscript\") async def slashtag_edit_tagscript( self,","True: await self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type,","pass await self.config.eval_command.clear() self.eval_command = None await ctx.send(\"`/eval` has been deleted.\") @slashtagset.command(\"testing\") async","\"with this invite link and try again: <https://discordapp.com/oauth2/authorize\" f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\" ) return await ctx.send(text)","a user command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag(","GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\"remove\", aliases=[\"delete\", \"-\"]) @copy_doc(slashtag_remove) async def","or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\"Application ID set to `{id}`.\")","if pred.result is True: await self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name, description=description,","slash tags from the database.\"\"\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"clear\", hidden=True) async def","embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\"list\") async def slashtag_list(self,","= ( \"This server has no slash tags.\" if guild else \"There are","id: int = None): \"\"\" Manually set the application ID for [botname] slash","choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\"Reached max choices ({CHOICE_LIMIT}).\") break return choices","tags.\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\"usage\", aliases=[\"stats\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context):","else: choices = [] option_type = SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx)","\"\"\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag( self, ctx: commands.Context, tag_name:","): \"\"\"Edit a slash tag's name.\"\"\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\"description\") async def slashtag_edit_description(",") continue if not CHOICE_RE.match(choice_text): await ctx.send( f\"Failed to parse `{choice_text}` to a","slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \"\"\" Edit a slash tag's arguments. See [this","aliases=[\"e\"], invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter","in enumerate(pages, 1): embed = e.copy() embed.description = page embed.set_footer(text=f\"{index}/{len(pages)} | {len(tags)} {slash_tags}\")","testing cog is already {loaded}.\") await self.config.testing_enabled.set(target_state) if target_state: loaded = \"Loaded\" self.add_test_cog()","..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http import","= None): \"\"\" Manually set the application ID for [botname] slash commands if","LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.","stored slash tags.\"\"\" tags = self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\"There are","{loaded}.\") await self.config.testing_enabled.set(target_state) if target_state: loaded = \"Loaded\" self.add_test_cog() else: loaded = \"Unloaded\"","SlashTag, limit: int = 60) -> str: title = f\"`{tag.type.get_prefix()}{tag.name}` - \" limit","slash_tags = \"global slash tags\" e.set_author(name=\"Global Slash Tags\", icon_url=ctx.me.avatar_url) else: slash_tags = \"slash","*, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\"list\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags","else \"There are no global slash tags.\" ) return await ctx.send(message) counter =","*, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True)","PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT","ctx: commands.Context): \"\"\"View stored slash tags.\"\"\" tags = self.guild_tag_cache[ctx.guild.id] if not tags: return","tags.\") if not pred.result: return await ctx.send(\"Ok, not deleting slash tags.\") guild: discord.Guild","\"Uses\")), \"prolog\") embed = e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS)","ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\"tagscript\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *,","TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use TagScript blocks. \"\"\" @commands.mod_or_permissions(manage_guild=True)","the Software is furnished to do so, subject to the following conditions: The","argument? (Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding additional","tagscript: str, *, is_global: bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options:","if pred is None: pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message","IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING","DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate from ..abc import","color=await ctx.embed_color()) embeds = [] for usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data,","return await ctx.send(text) except Exception: log.error(\"Failed to create command {command!r} on guild {ctx.guild!r}\")","has been deleted.\") @slashtagset.command(\"testing\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None):","A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT","60) -> str: title = f\"`{tag.type.get_prefix()}{tag.name}` - \" limit -= len(title) tagscript =","decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original, commands.Command) else original.__doc__ doc =","title = f\"`{tag.type.get_prefix()}{tag.name}` - \" limit -= len(title) tagscript = tag.tagscript if len(tagscript)","async def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await","tabulate from ..abc import MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter,","GuildTagConverter): \"\"\" Edit a slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more","command.register() except discord.Forbidden as error: log.error( \"Failed to create command {command!r} on guild","commands if it differs from the bot user ID. This only applies to","ctx: commands.Context, true_or_false: bool = None): \"\"\" Load or unload the SlashTag interaction","page in enumerate(pages, 1): embed = e.copy() embed.description = page embed.set_footer(text=f\"{index}/{len(pages)} | {len(tags)}","GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\"name\") @copy_doc(slashtag_edit_name) async def","by name.\"\"\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"remove\", aliases=[\"delete\", \"-\"]) async def slashtag_remove(self, ctx:","ctx.send(text) except Exception: log.error(\"Failed to create command {command!r} on guild {ctx.guild!r}\") # exc","characters.*\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \"\\n\".join(name_desc), name_pred) match = name_pred.result","self.eval_command: return await ctx.send(\"The eval command hasn't been registered.\") try: await self.http.remove_slash_command(self.eval_command) except","[] for usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\"Tag\", \"Uses\")), \"prolog\") embed","re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\") CHOICE_RE = re.compile(r\".{1,100}:.{1,100}\") CHOICE_LIMIT = 25 log = logging.getLogger(\"red.phenom4n4n.slashtags.commands\") def _sub(match: re.Match)","tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\"Tags deleted.\")","def slashtagset_settings(self, ctx: commands.Context): \"\"\"View SlashTags settings.\"\"\" eval_command = f\"✅ (**{self.eval_command}**)\" if self.eval_command","@slashtag.command(\"user\") async def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter,","MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message = await self.bot.wait_for(\"message\", check=pred, timeout=timeout) except","): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"message\") @copy_doc(slashtag_message) async def slashtag_global_message( self,","async def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await","len(choices) >= CHOICE_LIMIT: await ctx.send(f\"Reached max choices ({CHOICE_LIMIT}).\") break return choices async def","OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR","make this argument optional, all following arguments must also be optional.*\", pred, )","to the following conditions: The above copyright notice and this permission notice shall","aliases=[\"options\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\"argument\", aliases=[\"option\"])","tag.\"\"\" await ctx.send(await tag.delete()) @slashtag.command(\"info\") async def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter):","= await self.get_option(ctx, added_required=added_required) if not option.required: added_required = True except asyncio.TimeoutError: await","Software, and to permit persons to whom the Software is furnished to do","Add a user command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await","slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(","= \"slash tags\" e.set_author(name=\"Stored Slash Tags\", icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description))","try: await self.send_and_query_response( ctx, \"Would you like to add arguments to this tag?","break if pred.result is False: break return options async def send_and_query_response( self, ctx:","@slashtag_global.command(\"add\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter,","@slashtag_global.command(\"restore\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\"slashset\"])","\"choices\": choices = await self.get_choices(ctx) option_type = \"STRING\" else: choices = [] option_type","is_global=True) @slashtag_global.command(\"usage\", aliases=[\"stats\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\"restore\", hidden=True)","ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\"description\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *,","commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a slash tag.\"\"\" await ctx.send(await","ctx.send(\"Query timed out, not adding additional arguments.\") break if pred.result is False: break","*, tagscript: TagScriptConverter ): \"\"\"Edit a slash tag's TagScript.\"\"\" await self.slashtag_edit(ctx, tag, tagscript=tagscript)","@copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\"restore\", hidden=True) @copy_doc(slashtag_restore) async def",") await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\"`/eval` has been registered.\")","\":\" not in choice_text: await ctx.send( f\"Failed to parse `{choice_text}` to a choice","is already {loaded}.\") await self.config.testing_enabled.set(target_state) if target_state: loaded = \"Loaded\" self.add_test_cog() else: loaded","await self.config.eval_command.clear() self.eval_command = None await ctx.send(\"`/eval` has been deleted.\") @slashtagset.command(\"testing\") async def","These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use TagScript","MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE","self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def get_choices(self, ctx: commands.Context)","'_' or '-'.\", \"The argument description must be less than or equal to","IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED","commands.Context): \"\"\"Clear all slash tags for this server.\"\"\" pred = MessagePredicate.yes_or_no(ctx) try: await","tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit: int = 60) -> str: title","await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"user\") @copy_doc(slashtag_user) async def","and value \" \"weren't seperated by a `:`.\", delete_after=15, ) continue if not","\" \"should be seperated by `|`. Example:\\n`dog:Doggo|cat:Catto`\" ) response = await self.send_and_query_response(ctx, query)","link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) @copy_doc(slashtag_edit) async","ctx.send( f\"Failed to parse `{choice_text}` to a choice as its name and value","check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a user command tag with TagScript.","server has no slash tags.\" if guild else \"There are no global slash","self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript,","i == 10: break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you","self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\"name\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter,","self.testing_enabled: loaded = \"loaded\" if target_state else \"unloaded\" return await ctx.send(f\"The SlashTag interaction","server.\"\"\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Are you sure you want","return await ctx.send(\"Timed out, not deleting slash tags.\") if not pred.result: return await","aliases=[\"stats\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\"restore\", hidden=True) @copy_doc(slashtag_restore) async","in tags.copy().values()}) e = discord.Embed(title=\"Slash Tag Stats\", color=await ctx.embed_color()) embeds = [] for","self.eval_command: return await ctx.send(\"An eval command is already registered.\") slasheval = ApplicationCommand( self,","embed = e.copy() embed.description = page embed.set_footer(text=f\"{index}/{len(pages)} | {len(tags)} {slash_tags}\") embeds.append(embed) # await","options) command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try: await","not exceed 32 characters and can only contain characters \" \"that are alphanumeric","= app_id await ctx.send(f\"Application ID set to `{id}`.\") @commands.check(dev_check) @slashtagset.command(\"addeval\") async def slashtagset_addeval(self,","CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR","been registered.\") @commands.check(dev_check) @slashtagset.command(\"rmeval\") async def slashtagset_rmeval(self, ctx: commands.Context): \"\"\"Remove the slash eval","added_required=added_required) if not option.required: added_required = True except asyncio.TimeoutError: await ctx.send(\"Adding this argument","again: <https://discordapp.com/oauth2/authorize\" f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\" ) return await ctx.send(text) except Exception: log.error(\"Failed to create command","a choice as \" \"its name or value exceeded the 100 character limit.\",","person obtaining a copy of this software and associated documentation files (the \"Software\"),","async def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Get a slash tag's raw","if is_global: slash_tags = \"global slash tags\" e.set_author(name=\"Global Slash Tags\", icon_url=ctx.me.avatar_url) else: slash_tags","await self.bot.wait_for(\"message\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message)","self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded = \"loaded\" if target_state else \"unloaded\"","repl = repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]):","button_menu(ctx, embeds) @slashtag.command(\"list\") async def slashtag_list(self, ctx: commands.Context): \"\"\"View stored slash tags.\"\"\" tags","commands.Context, *, tag: TagConverter): \"\"\"Get info about a slash tag that is stored","await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\"pastebin\", aliases=[\"++\"]) @copy_doc(slashtag_pastebin) async def","server.\") await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild =","tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\"description\") @copy_doc(slashtag_edit_description) async def","not None else not await self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded =","is_global: bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = []","= await self.send_and_query_response(ctx, query) choices = [] for choice_text in response.split(\"|\"): if \":\"","usage` \"\"\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"restore\", hidden=True) async def slashtag_restore(self, ctx: commands.Context):","only applies to legacy bots. If you don't know what this means, you","asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def get_choices(self,","@slashtagset.command(\"settings\") async def slashtagset_settings(self, ctx: commands.Context): \"\"\"View SlashTags settings.\"\"\" eval_command = f\"✅ (**{self.eval_command}**)\"","in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED","TagConverter): \"\"\"Get info about a slash tag that is stored on this server.\"\"\"","tag, tagscript=tagscript) @slashtag_edit.command(\"name\") async def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *, name:","for this server.\"\"\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Are you sure","command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"pastebin\", aliases=[\"++\"]) async def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False),","a slash tag that is stored on this server.\"\"\" await tag.send_info(ctx) @slashtag.command(\"raw\") async","name = match.group(0) repl += name if name.istitle(): repl = repl.title() return repl","modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to","def slashtag_clear(self, ctx: commands.Context): \"\"\"Clear all slash tags for this server.\"\"\" pred =","commands.Context, *, tag: GuildTagConverter): \"\"\"Get a slash tag's raw content.\"\"\" await tag.send_raw_tagscript(ctx) @classmethod","out.\", delete_after=15) break options.append(option) if i == 10: break pred = MessagePredicate.yes_or_no(ctx) try:","commands.Context, *, added_required: bool = False ) -> SlashOption: name_desc = [ \"What","also be optional.*\", pred, ) required = pred.result else: await ctx.send( \"This argument","pred.result is False: break return options async def send_and_query_response( self, ctx: commands.Context, query:","response.split(\"|\"): if \":\" not in choice_text: await ctx.send( f\"Failed to parse `{choice_text}` to","be?\", f\"Valid option types: {humanize_list([inline(n) for n in valid_option_types])}\", \"(select `string` if you","aliases=[\"++\"]) async def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ):","str, tagscript: str, *, is_global: bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ):","as choices to \" \"the tag. Choice names and values should be seperated","break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you like to add","to be? (maximum 100 characters)\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await ctx.send(\"Tag","description = await self.send_and_query_response( ctx, \"What should the tag description to be? (maximum","was optional.\", delete_after=15, ) required = False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required,","pred.result is True: await self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id,","): \"\"\" Add a user command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html)","slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \"\"\"Get info about a slash tag that","100 characters.*\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \"\\n\".join(name_desc), name_pred) match =","and description should be split by a `:`.\", \"Example: `member:A member of this","seperated by a `:`.\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await ctx.send( f\"Failed","slash tags.\"\"\" tags = self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\"There are no","match.group(1): return \"[p]slashtag global\" repl = \"global \" name = match.group(0) repl +=","on the command options is needed raise tag = SlashTag( self, tagscript, guild_id=guild_id,","self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\"Application ID set to `{id}`.\") @commands.check(dev_check) @slashtagset.command(\"addeval\") async","is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"pastebin\", aliases=[\"++\"]) async def slashtag_pastebin( self, ctx: commands.Context, tag_name:","option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"message\") async def slashtag_message( self, ctx: commands.Context, tag_name:","this server.\") await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild","continue choice = ApplicationOptionChoice(*choice_text.split(\":\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\"Reached max","site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use TagScript blocks. \"\"\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"add\", aliases=[\"create\",","commands.Command): overriden._help_override = doc else: overriden.__doc__ = doc return overriden return decorator class","sorted(tags.values(), key=lambda t: t.name) ] description = \"\\n\".join(description) e = discord.Embed(color=await ctx.embed_color()) if","description to be? (maximum 100 characters)\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await","is already registered.\") slasheval = ApplicationCommand( self, name=\"eval\", description=\"SlashTags debugging eval command. Only","async def slashtag_clear(self, ctx: commands.Context): \"\"\"Clear all slash tags for this server.\"\"\" pred","\"❎\" description = [ f\"Application ID: **{self.application_id}**\", f\"Eval command: {eval_command}\", f\"Test cog loaded:","\"\"\"Edit a single slash tag's argument by name.\"\"\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"remove\",","GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a slash tag's TagScript.\"\"\" await self.slashtag_edit(ctx, tag,","exceed 32 characters and can only contain characters \" \"that are alphanumeric or","return options async def send_and_query_response( self, ctx: commands.Context, query: str, pred: MessagePredicate =","\"(select `string` if you don't understand)\", ] option_type = await self.send_and_query_response( ctx, \"\\n\".join(option_query),","-> str: title = f\"`{tag.type.get_prefix()}{tag.name}` - \" limit -= len(title) tagscript = tag.tagscript","self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\"name\") async def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *,","slash tags on this server? (Y/n)\", pred ) except asyncio.TimeoutError: return await ctx.send(\"Timed","t.name) ] description = \"\\n\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags =","create command {command!r} on guild {ctx.guild!r}\") # exc info unneeded since error handler","TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a message command tag with","tags.\" if guild else \"There are no global slash tags.\" ) return await","GuildTagConverter): \"\"\"Get a slash tag's raw content.\"\"\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag:","self, name=\"eval\", description=\"SlashTags debugging eval command. Only bot owners can use this.\", options=[","return await ctx.send(\"Tag addition timed out.\") else: description = \"\" if command_type ==","Add a slash tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag(ctx,","of choice names and values you would like to add as choices to","by `:`, and each choice \" \"should be seperated by `|`. Example:\\n`dog:Doggo|cat:Catto`\" )","ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu","invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter","): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit(","else: overriden.__doc__ = doc return overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\"st\"]) async","is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\"pastebin\", aliases=[\"++\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name:","worry about it. \"\"\" app_id = id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id =","_sub(match: re.Match) -> str: if match.group(1): return \"[p]slashtag global\" repl = \"global \"","\"\"\"Remove the slash eval command.\"\"\" if not self.eval_command: return await ctx.send(\"The eval command","None): \"\"\" Load or unload the SlashTag interaction development test cog. \"\"\" target_state","def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \"\"\"Get info about a slash tag","tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"message\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context, tag_name:","server.\"\"\" await tag.send_info(ctx) @slashtag.command(\"raw\") async def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Get","name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \"\\n\".join(name_desc), name_pred) match = name_pred.result name, description","tag.tagscript if len(tagscript) > limit - 3: tagscript = tagscript[:limit] + \"...\" tagscript","to any person obtaining a copy of this software and associated documentation files","..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\") CHOICE_RE = re.compile(r\".{1,100}:.{1,100}\") CHOICE_LIMIT =","value \" \"weren't seperated by a `:`.\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text):","= match.group(0) repl += name if name.istitle(): repl = repl.title() return repl def","@copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\"list\") @copy_doc(slashtag_list)","on this server.\"\"\" await tag.send_info(ctx) @slashtag.command(\"raw\") async def slashtag_raw(self, ctx: commands.Context, *, tag:","in range(1, 11): try: option = await self.get_option(ctx, added_required=added_required) if not option.required: added_required","contain characters \" \"that are alphanumeric or '_' or '-'.\", \"The argument description","link and try again: <https://discordapp.com/oauth2/authorize\" f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\" ) return await ctx.send(text) except Exception: log.error(\"Failed","THE SOFTWARE. \"\"\" import asyncio import logging import re import types from collections","ctx.send(await tag.delete()) @slashtag.command(\"info\") async def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \"\"\"Get info","await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"clear\", hidden=True) async def slashtag_clear(self, ctx: commands.Context): \"\"\"Clear all","self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link,","int = None): \"\"\" Manually set the application ID for [botname] slash commands","ctx.send(f\"Application ID set to `{id}`.\") @commands.check(dev_check) @slashtagset.command(\"addeval\") async def slashtagset_addeval(self, ctx: commands.Context): \"\"\"Add","are no global slash tags.\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\"usage\", aliases=[\"stats\"]) @copy_doc(slashtag_usage) async","the slash eval command.\"\"\" if not self.eval_command: return await ctx.send(\"The eval command hasn't","ctx.send(\"Query timed out, not adding arguments.\") else: if pred.result is True: await self.get_options(ctx,","= self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\"There are no slash tags on","[] pages = list(pagify(description)) for index, page in enumerate(pages, 1): embed = e.copy()","*, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\"raw\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context,","a copy of this software and associated documentation files (the \"Software\"), to deal","Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS","OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN","check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER )","commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\"raw\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx:","= MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Are you sure you want to delete","WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF","types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original, commands.Command) else original.__doc__","def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\"argument\", aliases=[\"option\"]) @copy_doc(slashtag_edit_argument) async def","= doc return overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\"st\"]) async def slashtag(self,","tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\"pastebin\", aliases=[\"++\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx:","@slashtag_global.command(\"message\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript:","are no global slash tags.\" ) return await ctx.send(message) counter = Counter({tag.name: tag.uses","slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag,","and to permit persons to whom the Software is furnished to do so,","tags: return await ctx.send(\"There are no slash tags on this server.\") await self.view_slash_tags(ctx,","pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \"Is this argument required? (Y/n)\\n*Keep in mind","have permission to add Slash Commands here. Reinvite me \" \"with this invite","commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \"\"\" Add a slash tag with","break options.append(option) if i == 10: break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response(","return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\"st\"]) async def slashtag(self, ctx: commands.Context): \"\"\" Slash","self.send_and_query_response( ctx, \"Would you like to add arguments to this tag? (Y/n)\", pred","from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate","- \" limit -= len(title) tagscript = tag.tagscript if len(tagscript) > limit -","embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\"usage\", aliases=[\"stats\"]) async def slashtag_usage(self,","command is already registered.\") slasheval = ApplicationCommand( self, name=\"eval\", description=\"SlashTags debugging eval command.","tags = self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\"There are no slash tags","commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use TagScript blocks.","ctx.send( \"This argument was automatically made optional as the previous one was optional.\",","SlashOption: name_desc = [ \"What should the argument name be and description be?\",","commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a message command",") -> str: if pred is None: pred = MessagePredicate.same_context(ctx) ask = await","add arguments to this tag? (Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed","argument timed out.\", delete_after=15) break options.append(option) if i == 10: break pred =","values you would like to add as choices to \" \"the tag. Choice","@commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"remove\", aliases=[\"delete\", \"-\"]) async def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Delete","out.\") else: description = \"\" if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try:","if len(tagscript) > limit - 3: tagscript = tagscript[:limit] + \"...\" tagscript =","pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding arguments.\") else: if","choices ({CHOICE_LIMIT}).\") break return choices async def get_option( self, ctx: commands.Context, *, added_required:","title=\"SlashTags Settings\", description=\"\\n\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\"appid\") async def slashtagset_appid(self, ctx: commands.Context, id:","from ..testing.button_menus import menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE","@slashtag.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript:","): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\"description\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context, tag:","is_global=True) @slashtag_global.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter,","a `:`.\", \"Example: `member:A member of this server.`\\n\", \"*Slash argument names may not","= SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async def","= ( \"Looks like I don't have permission to add Slash Commands here.","GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\"tagscript\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript(","TagScriptConverter, ): \"\"\" Add a message command tag with TagScript. [Slash tag usage","copy of this software and associated documentation files (the \"Software\"), to deal in","page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag arguments. \"\"\" await tag.edit_options(ctx) @slashtag_edit.command(\"argument\", aliases=[\"option\"])","SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \"Is this argument","tag arguments. \"\"\" await tag.edit_options(ctx) @slashtag_edit.command(\"argument\", aliases=[\"option\"]) async def slashtag_edit_argument( self, ctx: commands.Context,","documentation on how to use TagScript blocks. \"\"\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"add\", aliases=[\"create\", \"+\"]) async","-> SlashOption: name_desc = [ \"What should the argument name be and description","async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await","int = 60, ) -> str: if pred is None: pred = MessagePredicate.same_context(ctx)","-> str: if match.group(1): return \"[p]slashtag global\" repl = \"global \" name =","out, not deleting slash tags.\") if not pred.result: return await ctx.send(\"Ok, not deleting","return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"message\") async def slashtag_message(","tag, tagscript=tagscript) @slashtag_global_edit.command(\"name\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *,","if not tags: return await ctx.send(\"There are no slash tags on this server.\")","[ \"What should the argument name be and description be?\", \"The argument name","MessagePredicate = None, *, timeout: int = 60, ) -> str: if pred","unload the SlashTag interaction development test cog. \"\"\" target_state = ( true_or_false if","GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\"description\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description(","for index, page in enumerate(pages, 1): embed = e.copy() embed.description = page embed.set_footer(text=f\"{index}/{len(pages)}","OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR","\"Loaded\" self.add_test_cog() else: loaded = \"Unloaded\" self.remove_test_cog() await ctx.send(f\"{loaded} the SlashTag interaction testing","self, ctx: commands.Context, tag_name: str, tagscript: str, *, is_global: bool = False, command_type:","ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\"list\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx:","overriden.__doc__ = doc return overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\"st\"]) async def","choices async def get_option( self, ctx: commands.Context, *, added_required: bool = False )","or '_' or '-'.\", \"The argument description must be less than or equal","invite link and try again: <https://discordapp.com/oauth2/authorize\" f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\" ) return await ctx.send(text) except Exception:","ctx: commands.Context, guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache","PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType from ..objects import","async def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ):","tag.\"\"\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\"tagscript\") async def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter,","SlashTags settings.\"\"\" @slashtagset.command(\"settings\") async def slashtagset_settings(self, ctx: commands.Context): \"\"\"View SlashTags settings.\"\"\" eval_command =","else: description = \"\" if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await","you don't know what this means, you don't need to worry about it.","and try again: <https://discordapp.com/oauth2/authorize\" f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\" ) return await ctx.send(text) except Exception: log.error(\"Failed to","= self.global_tag_cache if not tags: return await ctx.send(\"There are no global slash tags.\")","on how to use TagScript blocks. \"\"\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"add\", aliases=[\"create\", \"+\"]) async def","message.content async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query = ( \"Send the",") if option_type.lower() == \"choices\": choices = await self.get_choices(ctx) option_type = \"STRING\" else:","been registered.\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None","not adding arguments.\") else: if pred.result is True: await self.get_options(ctx, options) command =","to add as choices to \" \"the tag. Choice names and values should","all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS","SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR","ctx, \"Are you sure you want to delete all slash tags on this","exc info unneeded since error handler should print it, however info on the","return choices async def get_option( self, ctx: commands.Context, *, added_required: bool = False","ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True)","import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import","this argument timed out.\", delete_after=15) break options.append(option) if i == 10: break pred","send_and_query_response( self, ctx: commands.Context, query: str, pred: MessagePredicate = None, *, timeout: int","slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\"add\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context, tag_name:","must also be optional.*\", pred, ) required = pred.result else: await ctx.send( \"This","pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Are you sure you want to","pred ) except asyncio.TimeoutError: return await ctx.send(\"Timed out, not deleting slash tags.\") if","argument description must be less than or equal to 100 characters.*\", ] name_pred","discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del","asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding arguments.\") else: if pred.result is True:","options=options, type=command_type, ) try: await command.register() except discord.Forbidden as error: log.error( \"Failed to","with a Pastebin link. \"\"\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\", aliases=[\"e\"],","testing_enabled = \"✅\" if self.testing_enabled else \"❎\" description = [ f\"Application ID: **{self.application_id}**\",","to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the","be and description be?\", \"The argument name and description should be split by","await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"user\") async def slashtag_user(","argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\"remove\", aliases=[\"delete\", \"-\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self,","): \"\"\" Add a slash tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\"","arguments.\") break if pred.result is False: break return options async def send_and_query_response( self,","all slash tags from the database.\"\"\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"clear\", hidden=True) async","tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async def get_options( self, ctx:","-> List[SlashOption]: added_required = False for i in range(1, 11): try: option =","OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL","10: break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you like to","] valid_option_types.append(\"choices\") option_query = [ \"What should the argument type be?\", f\"Valid option","[ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t: t.name) ] description = \"\\n\".join(description)","slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name,","def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx,","else \"unloaded\" return await ctx.send(f\"The SlashTag interaction testing cog is already {loaded}.\") await","I don't have permission to add Slash Commands here. Reinvite me \" \"with","GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType from ..objects","description = match.group(1), match.group(2) valid_option_types = [ name.lower() for name in SlashOptionType.__members__.keys() if","\"\"\" Slash Tag management with TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has","**Example:** `[p]slashtag usage` \"\"\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"restore\", hidden=True) async def slashtag_restore(self,","ctx: commands.Context, *, tag: TagConverter): \"\"\"Get info about a slash tag that is","ctx.send( f\"Failed to parse `{choice_text}` to a choice as \" \"its name or","self.send_and_query_response(ctx, \"\\n\".join(name_desc), name_pred) match = name_pred.result name, description = match.group(1), match.group(2) valid_option_types =","WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE","slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add","commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a user command","self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a","PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS","button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\") CHOICE_RE = re.compile(r\".{1,100}:.{1,100}\")","TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\"name\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx:",") from ..http import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag","await ctx.send(\"Query timed out, not adding arguments.\") else: if pred.result is True: await","self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\"Tags deleted.\") @commands.is_owner() @slashtag.group(\"global\") @copy_doc(slashtag) async def slashtag_global(self, ctx:","this server.\"\"\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Are you sure you","tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\"raw\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *,","tags.\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache()","loaded = \"Loaded\" self.add_test_cog() else: loaded = \"Unloaded\" self.remove_test_cog() await ctx.send(f\"{loaded} the SlashTag","await ctx.send(\"Ok, not deleting slash tags.\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, [])","self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"pastebin\", aliases=[\"++\"]) async def slashtag_pastebin(","\"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT","tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async","continue if not CHOICE_RE.match(choice_text): await ctx.send( f\"Failed to parse `{choice_text}` to a choice","*, description: str ): \"\"\"Edit a slash tag's description.\"\"\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\"arguments\",","**{self.application_id}**\", f\"Eval command: {eval_command}\", f\"Test cog loaded: {testing_enabled}\", ] embed = discord.Embed( color=0xC9C9C9,","11): try: option = await self.get_option(ctx, added_required=added_required) if not option.required: added_required = True","commands.Context, true_or_false: bool = None): \"\"\" Load or unload the SlashTag interaction development","\"\"\"Edit a slash tag's name.\"\"\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\"description\") async def slashtag_edit_description( self,","option_type = \"STRING\" else: choices = [] option_type = SlashOptionType[option_type.upper()] if not added_required:","any person obtaining a copy of this software and associated documentation files (the","differs from the bot user ID. This only applies to legacy bots. If","\" \"with this invite link and try again: <https://discordapp.com/oauth2/authorize\" f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\" ) return await","slashtag(self, ctx: commands.Context): \"\"\" Slash Tag management with TagScript. These commands use TagScriptEngine.","tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\"Tags deleted.\") @commands.is_owner() @slashtag.group(\"global\") @copy_doc(slashtag) async","async def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *, description: str ): await","slashtagset(self, ctx: commands.Context): \"\"\"Manage SlashTags settings.\"\"\" @slashtagset.command(\"settings\") async def slashtagset_settings(self, ctx: commands.Context): \"\"\"View","typing import Dict, List, Union import discord from redbot.core import commands from redbot.core.utils.chat_formatting","what this means, you don't need to worry about it. \"\"\" app_id =","slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name))","await tag.edit_options(ctx) @slashtag_edit.command(\"argument\", aliases=[\"option\"]) async def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument:","bool, ): description = [ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t: t.name)","slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(","asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding additional arguments.\") break if pred.result is","THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER","ctx.send(\"The eval command hasn't been registered.\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await","tags: Dict[int, SlashTag], *, is_global: bool, ): description = [ self.format_tagscript(tag) for tag","the Software, and to permit persons to whom the Software is furnished to","name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\"description\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx:","tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True)","def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\"","link: PastebinConverter, ): \"\"\" Add a slash tag with a Pastebin link. \"\"\"","slash tags.\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\"usage\", aliases=[\"stats\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx:","@commands.check(dev_check) @slashtagset.command(\"rmeval\") async def slashtagset_rmeval(self, ctx: commands.Context): \"\"\"Remove the slash eval command.\"\"\" if","types.FunctionType]): doc = original.help if isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc)","description should be split by a `:`.\", \"Example: `member:A member of this server.`\\n\",",") await ctx.send(embed=embed) @slashtagset.command(\"appid\") async def slashtagset_appid(self, ctx: commands.Context, id: int = None):","box, humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate","on this server.\") await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild:","copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\",","[ \"What should the argument type be?\", f\"Valid option types: {humanize_list([inline(n) for n","import tabulate from ..abc import MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter,","self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a slash","async def create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript: str, *, is_global: bool","SlashTag interaction development test cog. \"\"\" target_state = ( true_or_false if true_or_false is","def send_and_query_response( self, ctx: commands.Context, query: str, pred: MessagePredicate = None, *, timeout:","self.send_and_query_response( ctx, \"Is this argument required? (Y/n)\\n*Keep in mind that if you choose","GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\"raw\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *, tag:","decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\"st\"]) async def slashtag(self, ctx: commands.Context): \"\"\" Slash Tag","phenom4n4n Permission is hereby granted, free of charge, to any person obtaining a","= \"Loaded\" self.add_test_cog() else: loaded = \"Unloaded\" self.remove_test_cog() await ctx.send(f\"{loaded} the SlashTag interaction","TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption,","ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id = None if is_global else ctx.guild.id","ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx, \"What should","tagscript: TagScriptConverter, ): \"\"\" Add a message command tag with TagScript. [Slash tag","slash tag with a Pastebin link. \"\"\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True)","TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"message\") @copy_doc(slashtag_message) async def slashtag_global_message(","await self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded = \"loaded\" if target_state else","timeout: int = 60, ) -> str: if pred is None: pred =","\"\"\"Manage SlashTags settings.\"\"\" @slashtagset.command(\"settings\") async def slashtagset_settings(self, ctx: commands.Context): \"\"\"View SlashTags settings.\"\"\" eval_command","aliases=[\"create\", \"+\"]) async def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter,","counter = Counter({tag.name: tag.uses for tag in tags.copy().values()}) e = discord.Embed(title=\"Slash Tag Stats\",","command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try: await command.register()","stats. **Example:** `[p]slashtag usage` \"\"\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"restore\", hidden=True) async def","discord.Embed( color=0xC9C9C9, title=\"SlashTags Settings\", description=\"\\n\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\"appid\") async def slashtagset_appid(self, ctx:","ctx) await self.send_and_query_response(ctx, \"\\n\".join(name_desc), name_pred) match = name_pred.result name, description = match.group(1), match.group(2)","`:`.\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await ctx.send( f\"Failed to parse `{choice_text}`","\"\"\" Load or unload the SlashTag interaction development test cog. \"\"\" target_state =","await self.send_and_query_response( ctx, \"Would you like to add another argument? (Y/n)\", pred )","commands.Context, guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if","self.send_and_query_response( ctx, \"\\n\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \"choices\": choices = await","25 log = logging.getLogger(\"red.phenom4n4n.slashtags.commands\") def _sub(match: re.Match) -> str: if match.group(1): return \"[p]slashtag","self.eval_command else \"❎\" testing_enabled = \"✅\" if self.testing_enabled else \"❎\" description = [","async def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ):","for [botname] slash commands if it differs from the bot user ID. This","{command!r} on guild {ctx.guild!r}\", exc_info=error ) text = ( \"Looks like I don't","choice \" \"should be seperated by `|`. Example:\\n`dog:Doggo|cat:Catto`\" ) response = await self.send_and_query_response(ctx,","do so, subject to the following conditions: The above copyright notice and this","MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \"\\n\".join(name_desc), name_pred) match = name_pred.result name, description = match.group(1),","additional arguments.\") break if pred.result is False: break return options async def send_and_query_response(","development test cog. \"\"\" target_state = ( true_or_false if true_or_false is not None","split by a `:`.\", \"Example: `member:A member of this server.`\\n\", \"*Slash argument names","print it, however info on the command options is needed raise tag =","= Counter({tag.name: tag.uses for tag in tags.copy().values()}) e = discord.Embed(title=\"Slash Tag Stats\", color=await","tagscript: TagScriptConverter ): \"\"\"Edit a slash tag.\"\"\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\"tagscript\") async def","application ID for [botname] slash commands if it differs from the bot user","is furnished to do so, subject to the following conditions: The above copyright","option_query = [ \"What should the argument type be?\", f\"Valid option types: {humanize_list([inline(n)","def slashtag_usage(self, ctx: commands.Context): \"\"\" See this slash tag usage stats. **Example:** `[p]slashtag","needed raise tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await","for choice_text in response.split(\"|\"): if \":\" not in choice_text: await ctx.send( f\"Failed to","*, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"message\") @copy_doc(slashtag_message) async","tags = self.global_tag_cache if not tags: return await ctx.send(\"There are no global slash","ctx, \"\\n\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \"choices\": choices = await self.get_choices(ctx)","except asyncio.TimeoutError: return await ctx.send(\"Timed out, not deleting slash tags.\") if not pred.result:","guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag( self, ctx: commands.Context,","return await ctx.send(\"There are no slash tags on this server.\") await self.view_slash_tags(ctx, tags,","this tag? (Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed out, not adding","Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original, commands.Command) else","FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR","TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE","await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\"`/eval` has been registered.\") @commands.check(dev_check) @slashtagset.command(\"rmeval\") async","INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR","import commands from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS,","USE OR OTHER DEALINGS IN THE SOFTWARE. \"\"\" import asyncio import logging import","await self.send_and_query_response( ctx, \"\\n\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \"choices\": choices =","Tags\", icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description)) for index, page in enumerate(pages,","await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\"description\") async def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *,","(Y/n)\", pred ) except asyncio.TimeoutError: return await ctx.send(\"Timed out, not deleting slash tags.\")","DEALINGS IN THE SOFTWARE. \"\"\" import asyncio import logging import re import types","self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try: await command.register() except discord.Forbidden as","tag: GuildTagConverter): \"\"\"Get a slash tag's raw content.\"\"\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls,","def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a",") required = False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True)","[ name.lower() for name in SlashOptionType.__members__.keys() if not name.startswith(\"SUB\") ] valid_option_types.append(\"choices\") option_query =","tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\"Tags deleted.\") @commands.is_owner() @slashtag.group(\"global\") @copy_doc(slashtag)","(the \"Software\"), to deal in the Software without restriction, including without limitation the","= ( true_or_false if true_or_false is not None else not await self.config.testing_enabled() )","has been registered.\") @commands.check(dev_check) @slashtagset.command(\"rmeval\") async def slashtagset_rmeval(self, ctx: commands.Context): \"\"\"Remove the slash","self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\"pastebin\", aliases=[\"++\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin(","argument required? (Y/n)\\n*Keep in mind that if you choose to make this argument","to permit persons to whom the Software is furnished to do so, subject","to a choice as its name and value \" \"weren't seperated by a","tags.\" ) return await ctx.send(message) counter = Counter({tag.name: tag.uses for tag in tags.copy().values()})","command.\"\"\" if not self.eval_command: return await ctx.send(\"The eval command hasn't been registered.\") try:","async def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit","choices to \" \"the tag. Choice names and values should be seperated by","slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag","commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True)","more information on slash tag arguments. \"\"\" await tag.edit_options(ctx) @slashtag_edit.command(\"argument\", aliases=[\"option\"]) async def","description=\"Code body to evaluate.\", required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command =","ctx.send(\"`/eval` has been registered.\") @commands.check(dev_check) @slashtagset.command(\"rmeval\") async def slashtagset_rmeval(self, ctx: commands.Context): \"\"\"Remove the","be seperated by `:`, and each choice \" \"should be seperated by `|`.","self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try:","create command {command!r} on guild {ctx.guild!r}\", exc_info=error ) text = ( \"Looks like","tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\"edit\", aliases=[\"e\"],","slash eval command.\"\"\" if not self.eval_command: return await ctx.send(\"The eval command hasn't been","{len(tags)} {slash_tags}\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\"list\") async","to worry about it. \"\"\" app_id = id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id","Slash Commands here. Reinvite me \" \"with this invite link and try again:","@slashtagset.command(\"rmeval\") async def slashtagset_rmeval(self, ctx: commands.Context): \"\"\"Remove the slash eval command.\"\"\" if not","OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER","Permission is hereby granted, free of charge, to any person obtaining a copy","use this.\", options=[ SlashOption(name=\"body\", description=\"Code body to evaluate.\", required=True) ], ) await slasheval.register()","return await ctx.send(\"An eval command is already registered.\") slasheval = ApplicationCommand( self, name=\"eval\",","how to use TagScript blocks. \"\"\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"add\", aliases=[\"create\", \"+\"]) async def slashtag_add(","be included in all copies or substantial portions of the Software. THE SOFTWARE","*, timeout: int = 60, ) -> str: if pred is None: pred","ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx, \"What should the tag description to","await self.get_choices(ctx) option_type = \"STRING\" else: choices = [] option_type = SlashOptionType[option_type.upper()] if","whom the Software is furnished to do so, subject to the following conditions:","previous one was optional.\", delete_after=15, ) required = False return SlashOption( name=name.lower(), description=description,","tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag( self,","user command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx,","break return options async def send_and_query_response( self, ctx: commands.Context, query: str, pred: MessagePredicate","self, ctx: commands.Context, tag: GuildTagConverter, *, description: str ): \"\"\"Edit a slash tag's","tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"message\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True,","ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\"description\") async def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *, description:","blocks. \"\"\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"add\", aliases=[\"create\", \"+\"]) async def slashtag_add( self, ctx: commands.Context, tag_name:","this slash tag usage stats. **Example:** `[p]slashtag usage` \"\"\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner()","target_state else \"unloaded\" return await ctx.send(f\"The SlashTag interaction testing cog is already {loaded}.\")","argument optional, all following arguments must also be optional.*\", pred, ) required =","tags: message = ( \"This server has no slash tags.\" if guild else","pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you like to add another","\"Would you like to add another argument? (Y/n)\", pred ) except asyncio.TimeoutError: await","of this server.`\\n\", \"*Slash argument names may not exceed 32 characters and can","\"Is this argument required? (Y/n)\\n*Keep in mind that if you choose to make","as \" \"its name or value exceeded the 100 character limit.\", delete_after=15, )","argument names may not exceed 32 characters and can only contain characters \"","import MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, )","List[SlashOption]: added_required = False for i in range(1, 11): try: option = await","hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\"slashset\"]) async","command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"user\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True,","self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async def get_options( self,","not tags: return await ctx.send(\"There are no slash tags on this server.\") await","slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript))","DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,","ID: **{self.application_id}**\", f\"Eval command: {eval_command}\", f\"Test cog loaded: {testing_enabled}\", ] embed = discord.Embed(","= ApplicationOptionChoice(*choice_text.split(\":\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\"Reached max choices ({CHOICE_LIMIT}).\")","of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY","not option.required: added_required = True except asyncio.TimeoutError: await ctx.send(\"Adding this argument timed out.\",","this server.`\\n\", \"*Slash argument names may not exceed 32 characters and can only","= [] for usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\"Tag\", \"Uses\")), \"prolog\")","or value exceeded the 100 character limit.\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\":\",","server? (Y/n)\", pred ) except asyncio.TimeoutError: return await ctx.send(\"Timed out, not deleting slash","menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\") CHOICE_RE","self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\"tagscript\")","await tag.edit_single_option(ctx, argument) @slashtag_global.command(\"remove\", aliases=[\"delete\", \"-\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *,","async def send_and_query_response( self, ctx: commands.Context, query: str, pred: MessagePredicate = None, *,","TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__ = doc return","str: if pred is None: pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query) try:","GuildTagConverter, *, name: TagName(check_global=False) ): \"\"\"Edit a slash tag's name.\"\"\" await ctx.send(await tag.edit_name(name))","tag.delete()) @slashtag.command(\"info\") async def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \"\"\"Get info about","tag: TagConverter): \"\"\"Get info about a slash tag that is stored on this","added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \"Is this argument required? (Y/n)\\n*Keep in","tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context,","ctx.send(\"Tag addition timed out.\") else: description = \"\" if command_type == ApplicationCommandType.CHAT_INPUT: pred","MIT License Copyright (c) 2020-present phenom4n4n Permission is hereby granted, free of charge,","\"Would you like to add arguments to this tag? (Y/n)\", pred ) except","= re.compile(r\".{1,100}:.{1,100}\") CHOICE_LIMIT = 25 log = logging.getLogger(\"red.phenom4n4n.slashtags.commands\") def _sub(match: re.Match) -> str:","else: slash_tags = \"slash tags\" e.set_author(name=\"Stored Slash Tags\", icon_url=ctx.guild.icon_url) embeds = [] pages","to \" \"the tag. Choice names and values should be seperated by `:`,","async def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit","aliases=[\"e\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript:","this argument required? (Y/n)\\n*Keep in mind that if you choose to make this","\" \"that are alphanumeric or '_' or '-'.\", \"The argument description must be","import discord from redbot.core import commands from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify","should the argument name be and description be?\", \"The argument name and description","guild_id=guild_id, options=options, type=command_type, ) try: await command.register() except discord.Forbidden as error: log.error( \"Failed","await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"message\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx:","= \"✅\" if self.testing_enabled else \"❎\" description = [ f\"Application ID: **{self.application_id}**\", f\"Eval","<https://discordapp.com/oauth2/authorize\" f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\" ) return await ctx.send(text) except Exception: log.error(\"Failed to create command {command!r}","in choice_text: await ctx.send( f\"Failed to parse `{choice_text}` to a choice as its","\"Send the list of choice names and values you would like to add","slash tags.\" ) return await ctx.send(message) counter = Counter({tag.name: tag.uses for tag in","[Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE )","({CHOICE_LIMIT}).\") break return choices async def get_option( self, ctx: commands.Context, *, added_required: bool","can only contain characters \" \"that are alphanumeric or '_' or '-'.\", \"The","\"There are no global slash tags.\" ) return await ctx.send(message) counter = Counter({tag.name:","await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\"slashset\"]) async def slashtagset(self, ctx: commands.Context): \"\"\"Manage SlashTags settings.\"\"\"","the bot user ID. This only applies to legacy bots. If you don't","has documentation on how to use TagScript blocks. \"\"\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"add\", aliases=[\"create\", \"+\"])","@slashtag_global.command(\"user\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript:","self.testing_enabled else \"❎\" description = [ f\"Application ID: **{self.application_id}**\", f\"Eval command: {eval_command}\", f\"Test","and associated documentation files (the \"Software\"), to deal in the Software without restriction,","= e.copy() embed.description = page embed.set_footer(text=f\"{index}/{len(pages)} | {len(tags)} {slash_tags}\") embeds.append(embed) # await menu(ctx,","without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or","import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice,","def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await","[ f\"Application ID: **{self.application_id}**\", f\"Eval command: {eval_command}\", f\"Test cog loaded: {testing_enabled}\", ] embed","OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER","except discord.Forbidden as error: log.error( \"Failed to create command {command!r} on guild {ctx.guild!r}\",","copy import copy from typing import Dict, List, Union import discord from redbot.core","CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE","await ctx.send(await tag.initialize()) async def get_options( self, ctx: commands.Context, options: List[SlashOption] ) ->","handler should print it, however info on the command options is needed raise","TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use","commands.Context): \"\"\" Slash Tag management with TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html)","if not option.required: added_required = True except asyncio.TimeoutError: await ctx.send(\"Adding this argument timed","\"should be seperated by `|`. Example:\\n`dog:Doggo|cat:Catto`\" ) response = await self.send_and_query_response(ctx, query) choices","GuildTagConverter, *, description: str ): \"\"\"Edit a slash tag's description.\"\"\" await ctx.send(await tag.edit_description(description))","info on the command options is needed raise tag = SlashTag( self, tagscript,","command hasn't been registered.\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command","from typing import Dict, List, Union import discord from redbot.core import commands from","tags.\"\"\" tags = self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\"There are no slash","from ..http import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from","self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx,","tag_name, link, is_global=True) @slashtag_global.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context,","all slash tags for this server.\"\"\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx,","await ctx.send(\"`/eval` has been registered.\") @commands.check(dev_check) @slashtagset.command(\"rmeval\") async def slashtagset_rmeval(self, ctx: commands.Context): \"\"\"Remove","tagscript = tagscript.replace(\"\\n\", \" \") return f\"{title}{discord.utils.escape_markdown(tagscript)}\" async def view_slash_tags( self, ctx: commands.Context,","re import types from collections import Counter from copy import copy from typing","SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async def get_options(","@commands.is_owner() @slashtag.command(\"clear\", hidden=True) async def slashtag_clear(self, ctx: commands.Context): \"\"\"Clear all slash tags for","ctx: commands.Context): pass @slashtag_global.command(\"add\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True),","commands.Context): \"\"\"View stored slash tags.\"\"\" tags = self.guild_tag_cache[ctx.guild.id] if not tags: return await","import copy from typing import Dict, List, Union import discord from redbot.core import","in response.split(\"|\"): if \":\" not in choice_text: await ctx.send( f\"Failed to parse `{choice_text}`","@copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter,","as the previous one was optional.\", delete_after=15, ) required = False return SlashOption(","Example:\\n`dog:Doggo|cat:Catto`\" ) response = await self.send_and_query_response(ctx, query) choices = [] for choice_text in","slash tag.\"\"\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\"tagscript\") async def slashtag_edit_tagscript( self, ctx: commands.Context, tag:","log.error(\"Failed to create command {command!r} on guild {ctx.guild!r}\") # exc info unneeded since","need to worry about it. \"\"\" app_id = id or self.bot.user.id await self.config.application_id.set(app_id)","tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\"remove\", aliases=[\"delete\", \"-\"]) @copy_doc(slashtag_remove) async","return await ctx.send(\"There are no global slash tags.\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\"usage\",","you like to add another argument? (Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query","@copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): await","tagscript = tagscript[:limit] + \"...\" tagscript = tagscript.replace(\"\\n\", \" \") return f\"{title}{discord.utils.escape_markdown(tagscript)}\" async","tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a user command tag","Stats\", color=await ctx.embed_color()) embeds = [] for usage_data in chunks(counter.most_common(), 10): usage_chart =","a slash tag.\"\"\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\"tagscript\") async def slashtag_edit_tagscript( self, ctx: commands.Context,","\"its name or value exceeded the 100 character limit.\", delete_after=15, ) continue choice","): \"\"\"Edit a single slash tag's argument by name.\"\"\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True)","slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a slash","Add a slash tag with a Pastebin link. \"\"\" await self.create_slash_tag(ctx, tag_name, link,","delete_after=15, ) required = False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, )","self, ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ): \"\"\"Edit a slash tag's","self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a slash tag's","SlashTag], *, is_global: bool, ): description = [ self.format_tagscript(tag) for tag in sorted(tags.values(),","option = await self.get_option(ctx, added_required=added_required) if not option.required: added_required = True except asyncio.TimeoutError:","await self.config.testing_enabled.set(target_state) if target_state: loaded = \"Loaded\" self.add_test_cog() else: loaded = \"Unloaded\" self.remove_test_cog()","= ApplicationCommand( self, name=\"eval\", description=\"SlashTags debugging eval command. Only bot owners can use","def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ): \"\"\"Edit a","bool = False ) -> SlashOption: name_desc = [ \"What should the argument","PastebinConverter, ): \"\"\" Add a slash tag with a Pastebin link. \"\"\" await","{command!r} on guild {ctx.guild!r}\") # exc info unneeded since error handler should print","author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async def get_options( self, ctx: commands.Context, options:","ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \"\"\" Add a slash tag","index, page in enumerate(pages, 1): embed = e.copy() embed.description = page embed.set_footer(text=f\"{index}/{len(pages)} |","chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\"Tag\", \"Uses\")), \"prolog\") embed = e.copy() embed.description =","adding arguments.\") else: if pred.result is True: await self.get_options(ctx, options) command = ApplicationCommand(","a slash tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag(ctx, tag_name,","slash tag's argument by name.\"\"\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"remove\", aliases=[\"delete\", \"-\"]) async","e = discord.Embed(title=\"Slash Tag Stats\", color=await ctx.embed_color()) embeds = [] for usage_data in","@slashtag.command(\"remove\", aliases=[\"delete\", \"-\"]) async def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Delete a","for debugging.\"\"\" if self.eval_command: return await ctx.send(\"An eval command is already registered.\") slasheval","== ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you like to","OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING","tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False)","embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\"usage\", aliases=[\"stats\"]) async def slashtag_usage(self, ctx: commands.Context): \"\"\"","tag's TagScript.\"\"\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\"name\") async def slashtag_edit_name( self, ctx: commands.Context,","async def slashtagset(self, ctx: commands.Context): \"\"\"Manage SlashTags settings.\"\"\" @slashtagset.command(\"settings\") async def slashtagset_settings(self, ctx:","be? (maximum 100 characters)\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await ctx.send(\"Tag addition","options: List[SlashOption] ) -> List[SlashOption]: added_required = False for i in range(1, 11):","seperated by `:`, and each choice \" \"should be seperated by `|`. Example:\\n`dog:Doggo|cat:Catto`\"","slashtag_restore(self, ctx: commands.Context): \"\"\"Restore all slash tags from the database.\"\"\" await self.restore_tags(ctx, ctx.guild)","| {len(tags)} {slash_tags}\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\"list\")","def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\"list\") @copy_doc(slashtag_list) async def","@copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ):","ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try: await command.register() except discord.Forbidden","= ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try: await command.register() except","*, tag: GuildTagConverter): \"\"\"Delete a slash tag.\"\"\" await ctx.send(await tag.delete()) @slashtag.command(\"info\") async def","would like to add as choices to \" \"the tag. Choice names and","\"[p]slashtag global\" repl = \"global \" name = match.group(0) repl += name if","ctx: commands.Context): \"\"\"Add a slash eval command for debugging.\"\"\" if self.eval_command: return await","to this tag? (Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed out, not","def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): \"\"\"Edit a single","you don't need to worry about it. \"\"\" app_id = id or self.bot.user.id","None): tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not tags: message =","description = \"\\n\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \"global slash","False for i in range(1, 11): try: option = await self.get_option(ctx, added_required=added_required) if","slash tag's name.\"\"\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\"description\") async def slashtag_edit_description( self, ctx: commands.Context,","deleted.\") @commands.is_owner() @slashtag.group(\"global\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\"add\") @copy_doc(slashtag_add) async","registered.\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None await","this permission notice shall be included in all copies or substantial portions of","valid_option_types.append(\"choices\") option_query = [ \"What should the argument type be?\", f\"Valid option types:","SlashOption(name=\"body\", description=\"Code body to evaluate.\", required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command","ctx: commands.Context): \"\"\" Slash Tag management with TagScript. These commands use TagScriptEngine. [This","doc = original.help if isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc) if","not await self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded = \"loaded\" if target_state","f\"Valid option types: {humanize_list([inline(n) for n in valid_option_types])}\", \"(select `string` if you don't","server.`\\n\", \"*Slash argument names may not exceed 32 characters and can only contain","del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\"Tags deleted.\") @commands.is_owner() @slashtag.group(\"global\") @copy_doc(slashtag) async def","slash tag usage stats. **Example:** `[p]slashtag usage` \"\"\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"restore\",","IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A","self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query","be less than or equal to 100 characters.*\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx)","@slashtag.command(\"usage\", aliases=[\"stats\"]) async def slashtag_usage(self, ctx: commands.Context): \"\"\" See this slash tag usage","guild else self.global_tag_cache if not tags: message = ( \"This server has no","ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id = None if is_global","however info on the command options is needed raise tag = SlashTag( self,","guild {ctx.guild!r}\") # exc info unneeded since error handler should print it, however","option types: {humanize_list([inline(n) for n in valid_option_types])}\", \"(select `string` if you don't understand)\",","TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\"pastebin\", aliases=[\"++\"]) @copy_doc(slashtag_pastebin)","by `|`. Example:\\n`dog:Doggo|cat:Catto`\" ) response = await self.send_and_query_response(ctx, query) choices = [] for","on guild {ctx.guild!r}\", exc_info=error ) text = ( \"Looks like I don't have","commands.Context, tag: GuildTagConverter, *, description: str ): \"\"\"Edit a slash tag's description.\"\"\" await","don't understand)\", ] option_type = await self.send_and_query_response( ctx, \"\\n\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if","= await ctx.send(query) try: message = await self.bot.wait_for(\"message\", check=pred, timeout=timeout) except asyncio.TimeoutError: await","from redbot.core import commands from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from redbot.core.utils.menus","def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if not tags: return await ctx.send(\"There","*, link: PastebinConverter, ): \"\"\" Add a slash tag with a Pastebin link.","*, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\"name\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name(","tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\"tagscript\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript:","\"-\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete())","should be split by a `:`.\", \"Example: `member:A member of this server.`\\n\", \"*Slash","BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION","async def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ):","self.show_slash_tag_usage(ctx) @slashtag_global.command(\"restore\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner()","self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\"`/eval` has been registered.\") @commands.check(dev_check) @slashtagset.command(\"rmeval\") async def","slasheval = ApplicationCommand( self, name=\"eval\", description=\"SlashTags debugging eval command. Only bot owners can","else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx, \"What","arguments.\") else: if pred.result is True: await self.get_options(ctx, options) command = ApplicationCommand( self,","query) choices = [] for choice_text in response.split(\"|\"): if \":\" not in choice_text:","no slash tags on this server.\") await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self,","Software is furnished to do so, subject to the following conditions: The above","\"\"\" Edit a slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information","tag.edit_options(ctx) @slashtag_edit.command(\"argument\", aliases=[\"option\"]) async def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str","= f\"✅ (**{self.eval_command}**)\" if self.eval_command else \"❎\" testing_enabled = \"✅\" if self.testing_enabled else","= False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"message\") async","[botname] slash commands if it differs from the bot user ID. This only","return await ctx.send(\"The eval command hasn't been registered.\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException:","\"\"\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) async def slashtag_edit(","command for debugging.\"\"\" if self.eval_command: return await ctx.send(\"An eval command is already registered.\")","await self.delete_quietly(message) return message.content async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query =","usage stats. **Example:** `[p]slashtag usage` \"\"\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"restore\", hidden=True) async","ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"user\") async def slashtag_user( self, ctx:","else \"❎\" description = [ f\"Application ID: **{self.application_id}**\", f\"Eval command: {eval_command}\", f\"Test cog","except Exception: log.error(\"Failed to create command {command!r} on guild {ctx.guild!r}\") # exc info","def slashtag(self, ctx: commands.Context): \"\"\" Slash Tag management with TagScript. These commands use","for i in range(1, 11): try: option = await self.get_option(ctx, added_required=added_required) if not","ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global: bool, ): description = [ self.format_tagscript(tag)","try: message = await self.bot.wait_for(\"message\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await","tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\"name\") @copy_doc(slashtag_edit_name) async","\"\"\" import asyncio import logging import re import types from collections import Counter","str, pred: MessagePredicate = None, *, timeout: int = 60, ) -> str:","characters \" \"that are alphanumeric or '_' or '-'.\", \"The argument description must","): \"\"\"Edit a slash tag's description.\"\"\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\"arguments\", aliases=[\"options\"]) async def","except asyncio.TimeoutError: await ctx.send(\"Adding this argument timed out.\", delete_after=15) break options.append(option) if i","documentation files (the \"Software\"), to deal in the Software without restriction, including without","name if name.istitle(): repl = repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def","files (the \"Software\"), to deal in the Software without restriction, including without limitation","know what this means, you don't need to worry about it. \"\"\" app_id","self.config.testing_enabled.set(target_state) if target_state: loaded = \"Loaded\" self.add_test_cog() else: loaded = \"Unloaded\" self.remove_test_cog() await","or equal to 100 characters.*\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \"\\n\".join(name_desc),","not deleting slash tags.\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag","create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript: str, *, is_global: bool = False,","to do so, subject to the following conditions: The above copyright notice and","slash tags on this server.\") await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx:","Tag management with TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on","if i == 10: break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would","limit.\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\":\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT:","[this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag arguments. \"\"\" await tag.edit_options(ctx)","target_state = ( true_or_false if true_or_false is not None else not await self.config.testing_enabled()","tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not tags: message = (","*, description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\"arguments\", aliases=[\"options\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self,","pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await ctx.send(\"Tag addition timed out.\") else: description","await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\"Application ID set to `{id}`.\") @commands.check(dev_check) @slashtagset.command(\"addeval\")","add Slash Commands here. Reinvite me \" \"with this invite link and try","the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND,","await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\"usage\", aliases=[\"stats\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await","@slashtag.command(\"raw\") async def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Get a slash tag's","AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN","import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate from ..abc","tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"remove\", aliases=[\"delete\", \"-\"]) async def slashtag_remove(self, ctx: commands.Context, *, tag:","@commands.guild_only() @commands.group(aliases=[\"st\"]) async def slashtag(self, ctx: commands.Context): \"\"\" Slash Tag management with TagScript.","\"This argument was automatically made optional as the previous one was optional.\", delete_after=15,","def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \"\"\" Add","max choices ({CHOICE_LIMIT}).\") break return choices async def get_option( self, ctx: commands.Context, *,","try: await command.register() except discord.Forbidden as error: log.error( \"Failed to create command {command!r}","slash tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag(ctx, tag_name, tagscript,","deleting slash tags.\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in","= MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you like to add arguments to","evaluate.\", required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\"`/eval`","a slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash","slash tag that is stored on this server.\"\"\" await tag.send_info(ctx) @slashtag.command(\"raw\") async def","\"*Slash argument names may not exceed 32 characters and can only contain characters","await button_menu(ctx, embeds) @slashtag.command(\"list\") async def slashtag_list(self, ctx: commands.Context): \"\"\"View stored slash tags.\"\"\"","should print it, however info on the command options is needed raise tag","100 character limit.\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\":\", 1)) choices.append(choice) if len(choices)","def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Delete a slash tag.\"\"\" await ctx.send(await","is needed raise tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await","self, ctx: commands.Context, query: str, pred: MessagePredicate = None, *, timeout: int =","int = 60) -> str: title = f\"`{tag.type.get_prefix()}{tag.name}` - \" limit -= len(title)","def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await","box(tabulate(usage_data, headers=(\"Tag\", \"Uses\")), \"prolog\") embed = e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx,","description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"message\") async def slashtag_message( self, ctx: commands.Context,","not name.startswith(\"SUB\") ] valid_option_types.append(\"choices\") option_query = [ \"What should the argument type be?\",","1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\"Reached max choices ({CHOICE_LIMIT}).\") break return","slash tag.\"\"\" await ctx.send(await tag.delete()) @slashtag.command(\"info\") async def slashtag_info(self, ctx: commands.Context, *, tag:","ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\"arguments\", aliases=[\"options\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await","def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *, description: str ): \"\"\"Edit a","\"STRING\" else: choices = [] option_type = SlashOptionType[option_type.upper()] if not added_required: pred =","@slashtag.command(\"message\") async def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter,","the command options is needed raise tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id,","guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"user\") async","no slash tags.\" if guild else \"There are no global slash tags.\" )","command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id = None if","= [ \"What should the argument name be and description be?\", \"The argument","arguments must also be optional.*\", pred, ) required = pred.result else: await ctx.send(","error handler should print it, however info on the command options is needed","None else not await self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded = \"loaded\"","@commands.check(dev_check) @slashtagset.command(\"addeval\") async def slashtagset_addeval(self, ctx: commands.Context): \"\"\"Add a slash eval command for","] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \"\\n\".join(name_desc), name_pred) match = name_pred.result name,","@commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"user\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *,","tagscript[:limit] + \"...\" tagscript = tagscript.replace(\"\\n\", \" \") return f\"{title}{discord.utils.escape_markdown(tagscript)}\" async def view_slash_tags(","required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"message\") async def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False,","= discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \"global slash tags\" e.set_author(name=\"Global Slash Tags\",","ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"pastebin\", aliases=[\"++\"]) async def slashtag_pastebin( self,","to add another argument? (Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed out,","self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript:","all slash tags on this server? (Y/n)\", pred ) except asyncio.TimeoutError: return await","TagName(check_global=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a slash tag with TagScript. [Slash","like I don't have permission to add Slash Commands here. Reinvite me \"","the database.\"\"\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"clear\", hidden=True) async def slashtag_clear(self, ctx: commands.Context):","await ctx.send(\"There are no global slash tags.\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\"usage\", aliases=[\"stats\"])","self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript)","SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,","tag: SlashTag, limit: int = 60) -> str: title = f\"`{tag.type.get_prefix()}{tag.name}` - \"","get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query = ( \"Send the list of choice","ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Get a slash tag's raw content.\"\"\" await tag.send_raw_tagscript(ctx)","slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): \"\"\"Edit a single slash","are no slash tags on this server.\") await self.view_slash_tags(ctx, tags, is_global=False) async def","commands.Context, tag: GuildTagConverter, argument: str ): \"\"\"Edit a single slash tag's argument by","ask = await ctx.send(query) try: message = await self.bot.wait_for(\"message\", check=pred, timeout=timeout) except asyncio.TimeoutError:","TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE","with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async","ctx.send(\"An eval command is already registered.\") slasheval = ApplicationCommand( self, name=\"eval\", description=\"SlashTags debugging","LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT","ctx: commands.Context, tag: GlobalTagConverter, *, description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\"arguments\", aliases=[\"options\"])","substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY","self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\"usage\", aliases=[\"stats\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx)","self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) async def slashtag_edit( self, ctx:","tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\"tagscript\") @copy_doc(slashtag_edit_tagscript) async def","Copyright (c) 2020-present phenom4n4n Permission is hereby granted, free of charge, to any","(c) 2020-present phenom4n4n Permission is hereby granted, free of charge, to any person","are alphanumeric or '_' or '-'.\", \"The argument description must be less than","self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t: t.name) ] description = \"\\n\".join(description) e","try: await self.send_and_query_response( ctx, \"Would you like to add another argument? (Y/n)\", pred","single slash tag's argument by name.\"\"\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"remove\", aliases=[\"delete\", \"-\"])","slashtagset_settings(self, ctx: commands.Context): \"\"\"View SlashTags settings.\"\"\" eval_command = f\"✅ (**{self.eval_command}**)\" if self.eval_command else","TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN","tagscript = tag.tagscript if len(tagscript) > limit - 3: tagscript = tagscript[:limit] +","self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"user\") @copy_doc(slashtag_user) async def slashtag_global_user(","as its name and value \" \"weren't seperated by a `:`.\", delete_after=15, )","): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\"name\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context,","commands from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu","the previous one was optional.\", delete_after=15, ) required = False return SlashOption( name=name.lower(),","import MessagePredicate from tabulate import tabulate from ..abc import MixinMeta from ..converters import","async def slashtagset_appid(self, ctx: commands.Context, id: int = None): \"\"\" Manually set the","ctx.embed_color()) if is_global: slash_tags = \"global slash tags\" e.set_author(name=\"Global Slash Tags\", icon_url=ctx.me.avatar_url) else:","tag_name, tagscript, is_global=False) async def create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript: str,","TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"user\") @copy_doc(slashtag_user)","await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\"tagscript\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter,","IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR","= None): \"\"\" Load or unload the SlashTag interaction development test cog. \"\"\"","slash tags.\" if guild else \"There are no global slash tags.\" ) return","self, ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global: bool, ): description = [","*, name: TagName(check_global=False) ): \"\"\"Edit a slash tag's name.\"\"\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\"description\")","*, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\"description\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self,","\"global \" name = match.group(0) repl += name if name.istitle(): repl = repl.title()","or unload the SlashTag interaction development test cog. \"\"\" target_state = ( true_or_false","add another argument? (Y/n)\", pred ) except asyncio.TimeoutError: await ctx.send(\"Query timed out, not","description=description, guild_id=guild_id, options=options, type=command_type, ) try: await command.register() except discord.Forbidden as error: log.error(","self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a slash tag.\"\"\"","invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ):","TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\"edit\", aliases=[\"e\"], invoke_without_command=True)","slash eval command for debugging.\"\"\" if self.eval_command: return await ctx.send(\"An eval command is","return await ctx.send(message) counter = Counter({tag.name: tag.uses for tag in tags.copy().values()}) e =","equal to 100 characters.*\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \"\\n\".join(name_desc), name_pred)","tag.edit_single_option(ctx, argument) @slashtag_global.command(\"remove\", aliases=[\"delete\", \"-\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *, tag:","redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate from ..abc import MixinMeta from ..converters","is_global: bool, ): description = [ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t:","slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\"`/eval` has been registered.\") @commands.check(dev_check) @slashtagset.command(\"rmeval\")","me \" \"with this invite link and try again: <https://discordapp.com/oauth2/authorize\" f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\" ) return","don't need to worry about it. \"\"\" app_id = id or self.bot.user.id await","aliases=[\"options\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \"\"\" Edit a slash tag's","timed out, not adding arguments.\") else: if pred.result is True: await self.get_options(ctx, options)","except asyncio.TimeoutError: return await ctx.send(\"Tag addition timed out.\") else: description = \"\" if","it, however info on the command options is needed raise tag = SlashTag(","ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear()","str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\"arguments\", aliases=[\"options\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context,","guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache()","MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from","@copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\"argument\", aliases=[\"option\"]) @copy_doc(slashtag_edit_argument)","async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\"restore\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self,","here. Reinvite me \" \"with this invite link and try again: <https://discordapp.com/oauth2/authorize\" f\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\"","parse `{choice_text}` to a choice as its name and value \" \"weren't seperated","the 100 character limit.\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\":\", 1)) choices.append(choice) if","tag that is stored on this server.\"\"\" await tag.send_info(ctx) @slashtag.command(\"raw\") async def slashtag_raw(self,","ctx, \"Would you like to add arguments to this tag? (Y/n)\", pred )","== ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx, \"What should the tag description","from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\") CHOICE_RE = re.compile(r\".{1,100}:.{1,100}\") CHOICE_LIMIT","if not self.eval_command: return await ctx.send(\"The eval command hasn't been registered.\") try: await","OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES","ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\" Add a message","that is stored on this server.\"\"\" await tag.send_info(ctx) @slashtag.command(\"raw\") async def slashtag_raw(self, ctx:","aliases=[\"option\"]) async def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): \"\"\"Edit","user ID. This only applies to legacy bots. If you don't know what","original.help if isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command):","Choice names and values should be seperated by `:`, and each choice \"","\" \"its name or value exceeded the 100 character limit.\", delete_after=15, ) continue","eval command is already registered.\") slasheval = ApplicationCommand( self, name=\"eval\", description=\"SlashTags debugging eval","[Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER )","= name_pred.result name, description = match.group(1), match.group(2) valid_option_types = [ name.lower() for name","is_global: slash_tags = \"global slash tags\" e.set_author(name=\"Global Slash Tags\", icon_url=ctx.me.avatar_url) else: slash_tags =","tag in sorted(tags.values(), key=lambda t: t.name) ] description = \"\\n\".join(description) e = discord.Embed(color=await","self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"restore\", hidden=True) async def slashtag_restore(self, ctx: commands.Context): \"\"\"Restore all slash","interaction development test cog. \"\"\" target_state = ( true_or_false if true_or_false is not","if target_state is self.testing_enabled: loaded = \"loaded\" if target_state else \"unloaded\" return await","for usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\"Tag\", \"Uses\")), \"prolog\") embed =","information on slash tag arguments. \"\"\" await tag.edit_options(ctx) @slashtag_edit.command(\"argument\", aliases=[\"option\"]) async def slashtag_edit_argument(","GuildTagConverter): \"\"\"Delete a slash tag.\"\"\" await ctx.send(await tag.delete()) @slashtag.command(\"info\") async def slashtag_info(self, ctx:","to delete all slash tags on this server? (Y/n)\", pred ) except asyncio.TimeoutError:","if not CHOICE_RE.match(choice_text): await ctx.send( f\"Failed to parse `{choice_text}` to a choice as","@slashtag.command(\"add\", aliases=[\"create\", \"+\"]) async def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript:","-> str: if pred is None: pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query)","def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\"add\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context,","): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\"remove\", aliases=[\"delete\", \"-\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context,","await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def get_choices(self, ctx:","from the bot user ID. This only applies to legacy bots. If you","ctx.send(query) try: message = await self.bot.wait_for(\"message\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise","discord.Embed(title=\"Slash Tag Stats\", color=await ctx.embed_color()) embeds = [] for usage_data in chunks(counter.most_common(), 10):","tag.edit_name(name)) @slashtag_edit.command(\"description\") async def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *, description: str","f\"Failed to parse `{choice_text}` to a choice as its name and value \"","OR OTHER DEALINGS IN THE SOFTWARE. \"\"\" import asyncio import logging import re","\"-\"]) async def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Delete a slash tag.\"\"\"","command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you like","parse `{choice_text}` to a choice as \" \"its name or value exceeded the","def create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript: str, *, is_global: bool =","commands.Context, *, tag: GuildTagConverter): \"\"\"Delete a slash tag.\"\"\" await ctx.send(await tag.delete()) @slashtag.command(\"info\") async","you sure you want to delete all slash tags on this server? (Y/n)\",","Only bot owners can use this.\", options=[ SlashOption(name=\"body\", description=\"Code body to evaluate.\", required=True)","async def slashtagset_rmeval(self, ctx: commands.Context): \"\"\"Remove the slash eval command.\"\"\" if not self.eval_command:","`|`. Example:\\n`dog:Doggo|cat:Catto`\" ) response = await self.send_and_query_response(ctx, query) choices = [] for choice_text","true_or_false if true_or_false is not None else not await self.config.testing_enabled() ) if target_state","asyncio import logging import re import types from collections import Counter from copy","permission notice shall be included in all copies or substantial portions of the","hidden=True) async def slashtag_restore(self, ctx: commands.Context): \"\"\"Restore all slash tags from the database.\"\"\"","\"weren't seperated by a `:`.\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await ctx.send(","pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from tabulate import","Pastebin link. \"\"\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) async","commands.Context, tags: Dict[int, SlashTag], *, is_global: bool, ): description = [ self.format_tagscript(tag) for","str: title = f\"`{tag.type.get_prefix()}{tag.name}` - \" limit -= len(title) tagscript = tag.tagscript if","OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH","tag: GuildTagConverter, *, description: str ): \"\"\"Edit a slash tag's description.\"\"\" await ctx.send(await","self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None): tags","else: await ctx.send( \"This argument was automatically made optional as the previous one","if guild else \"There are no global slash tags.\" ) return await ctx.send(message)","this.\", options=[ SlashOption(name=\"body\", description=\"Code body to evaluate.\", required=True) ], ) await slasheval.register() await","limit - 3: tagscript = tagscript[:limit] + \"...\" tagscript = tagscript.replace(\"\\n\", \" \")","Counter({tag.name: tag.uses for tag in tags.copy().values()}) e = discord.Embed(title=\"Slash Tag Stats\", color=await ctx.embed_color())","name.startswith(\"SUB\") ] valid_option_types.append(\"choices\") option_query = [ \"What should the argument type be?\", f\"Valid","options.append(option) if i == 10: break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx,","await ctx.send(text) except Exception: log.error(\"Failed to create command {command!r} on guild {ctx.guild!r}\") #","owners can use this.\", options=[ SlashOption(name=\"body\", description=\"Code body to evaluate.\", required=True) ], )","the application ID for [botname] slash commands if it differs from the bot","ctx: commands.Context) -> List[ApplicationOptionChoice]: query = ( \"Send the list of choice names","is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"message\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False),","by a `:`.\", \"Example: `member:A member of this server.`\\n\", \"*Slash argument names may","self.config.eval_command.clear() self.eval_command = None await ctx.send(\"`/eval` has been deleted.\") @slashtagset.command(\"testing\") async def slashtagset_testing(self,","@copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ):","pred: MessagePredicate = None, *, timeout: int = 60, ) -> str: if","@commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"pastebin\", aliases=[\"++\"]) async def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link:","MessagePredicate from tabulate import tabulate from ..abc import MixinMeta from ..converters import (","a message command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag(","commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\"name\") @copy_doc(slashtag_edit_name)","tag: GlobalTagConverter, *, description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\"arguments\", aliases=[\"options\"]) @copy_doc(slashtag_edit_arguments) async","= False for i in range(1, 11): try: option = await self.get_option(ctx, added_required=added_required)","def format_tagscript(cls, tag: SlashTag, limit: int = 60) -> str: title = f\"`{tag.type.get_prefix()}{tag.name}`","is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id]","been deleted.\") @slashtagset.command(\"testing\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None): \"\"\"","tag.edit_tagscript(tagscript)) @slashtag_edit.command(\"tagscript\") async def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter","Settings\", description=\"\\n\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\"appid\") async def slashtagset_appid(self, ctx: commands.Context, id: int","= logging.getLogger(\"red.phenom4n4n.slashtags.commands\") def _sub(match: re.Match) -> str: if match.group(1): return \"[p]slashtag global\" repl","to create command {command!r} on guild {ctx.guild!r}\", exc_info=error ) text = ( \"Looks","tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None): tags =","def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx,","tagscript.replace(\"\\n\", \" \") return f\"{title}{discord.utils.escape_markdown(tagscript)}\" async def view_slash_tags( self, ctx: commands.Context, tags: Dict[int,","= self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not tags: message = ( \"This","ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\"raw\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self,","pred, ) required = pred.result else: await ctx.send( \"This argument was automatically made","@commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"user\") async def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript:","tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\"name\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self,","overriden._help_override = doc else: overriden.__doc__ = doc return overriden return decorator class Commands(MixinMeta):","copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and","( \"Send the list of choice names and values you would like to","if guild else self.global_tag_cache if not tags: message = ( \"This server has","you want to delete all slash tags on this server? (Y/n)\", pred )","doc) if isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__ = doc return overriden","required = False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"message\")","self.bot.wait_for(\"message\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return","if it differs from the bot user ID. This only applies to legacy","name.lower() for name in SlashOptionType.__members__.keys() if not name.startswith(\"SUB\") ] valid_option_types.append(\"choices\") option_query = [","f\"Failed to parse `{choice_text}` to a choice as \" \"its name or value","name, description = match.group(1), match.group(2) valid_option_types = [ name.lower() for name in SlashOptionType.__members__.keys()","commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ): \"\"\"Edit a slash tag's name.\"\"\" await","self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\"clear\", hidden=True) async def slashtag_clear(self, ctx: commands.Context): \"\"\"Clear all slash","HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN","guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async def get_options( self, ctx: commands.Context,","ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\"arguments\", aliases=[\"options\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \"\"\" Edit","ctx: commands.Context, tag_name: str, tagscript: str, *, is_global: bool = False, command_type: ApplicationCommandType","following conditions: The above copyright notice and this permission notice shall be included","= \"global slash tags\" e.set_author(name=\"Global Slash Tags\", icon_url=ctx.me.avatar_url) else: slash_tags = \"slash tags\"","message = ( \"This server has no slash tags.\" if guild else \"There","await self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, )","member of this server.`\\n\", \"*Slash argument names may not exceed 32 characters and","out, not adding arguments.\") else: if pred.result is True: await self.get_options(ctx, options) command","await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\"arguments\", aliases=[\"options\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter):","else not await self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded = \"loaded\" if","@slashtag_global_edit.command(\"arguments\", aliases=[\"options\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\"argument\",","len(title) tagscript = tag.tagscript if len(tagscript) > limit - 3: tagscript = tagscript[:limit]","The above copyright notice and this permission notice shall be included in all","): \"\"\" Add a slash tag with a Pastebin link. \"\"\" await self.create_slash_tag(ctx,","+= name if name.istitle(): repl = repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]):","asyncio.TimeoutError: return await ctx.send(\"Tag addition timed out.\") else: description = \"\" if command_type","self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear()","ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\"argument\", aliases=[\"option\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self,","def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \"\"\"","link, is_global=True) @slashtag_global.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context, tag:","\"\"\"View SlashTags settings.\"\"\" eval_command = f\"✅ (**{self.eval_command}**)\" if self.eval_command else \"❎\" testing_enabled =","eval_command = f\"✅ (**{self.eval_command}**)\" if self.eval_command else \"❎\" testing_enabled = \"✅\" if self.testing_enabled","arguments. \"\"\" await tag.edit_options(ctx) @slashtag_edit.command(\"argument\", aliases=[\"option\"]) async def slashtag_edit_argument( self, ctx: commands.Context, tag:","await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\"list\") async def slashtag_list(self, ctx: commands.Context):","granted, free of charge, to any person obtaining a copy of this software","limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell","eval command for debugging.\"\"\" if self.eval_command: return await ctx.send(\"An eval command is already","with TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to","= page embed.set_footer(text=f\"{index}/{len(pages)} | {len(tags)} {slash_tags}\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await","ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF","WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO","like to add as choices to \" \"the tag. Choice names and values","ctx: commands.Context): \"\"\"View SlashTags settings.\"\"\" eval_command = f\"✅ (**{self.eval_command}**)\" if self.eval_command else \"❎\"","debugging.\"\"\" if self.eval_command: return await ctx.send(\"An eval command is already registered.\") slasheval =","on slash tag arguments. \"\"\" await tag.edit_options(ctx) @slashtag_edit.command(\"argument\", aliases=[\"option\"]) async def slashtag_edit_argument( self,","else original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override = doc else:","List, Union import discord from redbot.core import commands from redbot.core.utils.chat_formatting import box, humanize_list,","tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\"user\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context,","tag. Choice names and values should be seperated by `:`, and each choice","= MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message = await self.bot.wait_for(\"message\", check=pred, timeout=timeout)","command=command, ) await ctx.send(await tag.initialize()) async def get_options( self, ctx: commands.Context, options: List[SlashOption]","async def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ):","a slash tag's TagScript.\"\"\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\"name\") async def slashtag_edit_name( self,","timed out.\", delete_after=15) break options.append(option) if i == 10: break pred = MessagePredicate.yes_or_no(ctx)","= [ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t: t.name) ] description =","tags.copy().values()}) e = discord.Embed(title=\"Slash Tag Stats\", color=await ctx.embed_color()) embeds = [] for usage_data","not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \"Is this argument required? (Y/n)\\n*Keep","ctx.send(\"Adding this argument timed out.\", delete_after=15) break options.append(option) if i == 10: break","a slash tag.\"\"\" await ctx.send(await tag.delete()) @slashtag.command(\"info\") async def slashtag_info(self, ctx: commands.Context, *,",") response = await self.send_and_query_response(ctx, query) choices = [] for choice_text in response.split(\"|\"):","self.application_id = app_id await ctx.send(f\"Application ID set to `{id}`.\") @commands.check(dev_check) @slashtagset.command(\"addeval\") async def","info about a slash tag that is stored on this server.\"\"\" await tag.send_info(ctx)","async def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ): \"\"\"Edit","is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter,","= 60) -> str: title = f\"`{tag.type.get_prefix()}{tag.name}` - \" limit -= len(title) tagscript","required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\"`/eval` has","\"\"\" Add a slash tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await","guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not","tags on this server? (Y/n)\", pred ) except asyncio.TimeoutError: return await ctx.send(\"Timed out,","\"The argument description must be less than or equal to 100 characters.*\", ]","= None await ctx.send(\"`/eval` has been deleted.\") @slashtagset.command(\"testing\") async def slashtagset_testing(self, ctx: commands.Context,","doc return overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\"st\"]) async def slashtag(self, ctx:",">= CHOICE_LIMIT: await ctx.send(f\"Reached max choices ({CHOICE_LIMIT}).\") break return choices async def get_option(","- 3: tagscript = tagscript[:limit] + \"...\" tagscript = tagscript.replace(\"\\n\", \" \") return","@slashtagset.command(\"testing\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None): \"\"\" Load or","f\"Eval command: {eval_command}\", f\"Test cog loaded: {testing_enabled}\", ] embed = discord.Embed( color=0xC9C9C9, title=\"SlashTags","self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \"\"\" Add a slash","tag description to be? (maximum 100 characters)\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return","MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you like to add arguments to this","= repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc","{ctx.guild!r}\") # exc info unneeded since error handler should print it, however info","@slashtag_global_edit.command(\"argument\", aliases=[\"option\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str","): \"\"\" Add a message command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html)","*, is_global: bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] =","pred is None: pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message =","await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\"usage\", aliases=[\"stats\"]) async def slashtag_usage(self, ctx: commands.Context): \"\"\" See","async def slashtag_restore(self, ctx: commands.Context): \"\"\"Restore all slash tags from the database.\"\"\" await","and/or sell copies of the Software, and to permit persons to whom the","CHOICE_RE.match(choice_text): await ctx.send( f\"Failed to parse `{choice_text}` to a choice as \" \"its","e.copy() embed.description = page embed.set_footer(text=f\"{index}/{len(pages)} | {len(tags)} {slash_tags}\") embeds.append(embed) # await menu(ctx, embeds,","async def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\"raw\") @copy_doc(slashtag_raw)","slash tags.\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values():","of charge, to any person obtaining a copy of this software and associated","TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType,","\"\\n\".join(name_desc), name_pred) match = name_pred.result name, description = match.group(1), match.group(2) valid_option_types = [","async def slashtag(self, ctx: commands.Context): \"\"\" Slash Tag management with TagScript. These commands","ctx.embed_color()) embeds = [] for usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\"Tag\",","command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"user\") async def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False),","usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\"Tag\", \"Uses\")), \"prolog\") embed = e.copy()",") if target_state is self.testing_enabled: loaded = \"loaded\" if target_state else \"unloaded\" return","ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you like to add","\"Failed to create command {command!r} on guild {ctx.guild!r}\", exc_info=error ) text = (","= tag.tagscript if len(tagscript) > limit - 3: tagscript = tagscript[:limit] + \"...\"","= MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \"Is this argument required? (Y/n)\\n*Keep in mind that","= doc else: overriden.__doc__ = doc return overriden return decorator class Commands(MixinMeta): @commands.guild_only()","await ctx.send(message) counter = Counter({tag.name: tag.uses for tag in tags.copy().values()}) e = discord.Embed(title=\"Slash","@commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\", aliases=[\"e\"], invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *,","slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \"\"\"Get a slash tag's raw content.\"\"\" await","tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"pastebin\", aliases=[\"++\"]) async def slashtag_pastebin( self, ctx: commands.Context,","options is needed raise tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, )","commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \"\"\"Edit a slash tag's TagScript.\"\"\" await","app_id await ctx.send(f\"Application ID set to `{id}`.\") @commands.check(dev_check) @slashtagset.command(\"addeval\") async def slashtagset_addeval(self, ctx:","= match.group(1), match.group(2) valid_option_types = [ name.lower() for name in SlashOptionType.__members__.keys() if not","[] for choice_text in response.split(\"|\"): if \":\" not in choice_text: await ctx.send( f\"Failed","+ \"...\" tagscript = tagscript.replace(\"\\n\", \" \") return f\"{title}{discord.utils.escape_markdown(tagscript)}\" async def view_slash_tags( self,","= [] option_type = SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response(","= SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \"Is this","await self.send_and_query_response( ctx, \"What should the tag description to be? (maximum 100 characters)\",","for tag in sorted(tags.values(), key=lambda t: t.name) ] description = \"\\n\".join(description) e =","\"✅\" if self.testing_enabled else \"❎\" description = [ f\"Application ID: **{self.application_id}**\", f\"Eval command:","collections import Counter from copy import copy from typing import Dict, List, Union","tag: GuildTagConverter, argument: str ): \"\"\"Edit a single slash tag's argument by name.\"\"\"","\"Example: `member:A member of this server.`\\n\", \"*Slash argument names may not exceed 32","name and description should be split by a `:`.\", \"Example: `member:A member of","pages = list(pagify(description)) for index, page in enumerate(pages, 1): embed = e.copy() embed.description","TagScriptConverter ): \"\"\"Edit a slash tag's TagScript.\"\"\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\"name\") async","SlashTag from ..testing.button_menus import menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check","\"Looks like I don't have permission to add Slash Commands here. Reinvite me","commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required = False for i in range(1,","tagscript=tagscript) @slashtag_edit.command(\"name\") async def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False)","command. Only bot owners can use this.\", options=[ SlashOption(name=\"body\", description=\"Code body to evaluate.\",","argument type be?\", f\"Valid option types: {humanize_list([inline(n) for n in valid_option_types])}\", \"(select `string`","addition timed out.\") else: description = \"\" if command_type == ApplicationCommandType.CHAT_INPUT: pred =","slashtagset_addeval(self, ctx: commands.Context): \"\"\"Add a slash eval command for debugging.\"\"\" if self.eval_command: return","WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. \"\"\"","guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"pastebin\", aliases=[\"++\"])","hidden=True) async def slashtag_clear(self, ctx: commands.Context): \"\"\"Clear all slash tags for this server.\"\"\"","self.add_test_cog() else: loaded = \"Unloaded\" self.remove_test_cog() await ctx.send(f\"{loaded} the SlashTag interaction testing cog.\")","commands.Context, tag: GlobalTagConverter, *, description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\"arguments\", aliases=[\"options\"]) @copy_doc(slashtag_edit_arguments)","pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \"Would you like to add arguments","is False: break return options async def send_and_query_response( self, ctx: commands.Context, query: str,","@copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter,","choice = ApplicationOptionChoice(*choice_text.split(\":\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\"Reached max choices","add as choices to \" \"the tag. Choice names and values should be","@slashtag_edit.command(\"name\") async def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ):","await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\"`/eval` has been registered.\") @commands.check(dev_check)","portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF","Commands here. Reinvite me \" \"with this invite link and try again: <https://discordapp.com/oauth2/authorize\"","tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\"pastebin\", aliases=[\"++\"])","DEFAULT_CONTROLS) @slashtag.command(\"usage\", aliases=[\"stats\"]) async def slashtag_usage(self, ctx: commands.Context): \"\"\" See this slash tag","self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\"slashset\"]) async def slashtagset(self, ctx: commands.Context): \"\"\"Manage SlashTags settings.\"\"\" @slashtagset.command(\"settings\")","limit -= len(title) tagscript = tag.tagscript if len(tagscript) > limit - 3: tagscript","chunks, dev_check TAG_RE = re.compile(r\"(?i)(\\[p\\])?\\b(slash\\s?)?tag'?s?\\b\") CHOICE_RE = re.compile(r\".{1,100}:.{1,100}\") CHOICE_LIMIT = 25 log =","to evaluate.\", required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await","@commands.is_owner() @commands.group(aliases=[\"slashset\"]) async def slashtagset(self, ctx: commands.Context): \"\"\"Manage SlashTags settings.\"\"\" @slashtagset.command(\"settings\") async def","show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id] if guild else","def get_option( self, ctx: commands.Context, *, added_required: bool = False ) -> SlashOption:","= usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\"usage\", aliases=[\"stats\"]) async def slashtag_usage(self, ctx:","\"\"\"View stored slash tags.\"\"\" tags = self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\"There","options=[ SlashOption(name=\"body\", description=\"Code body to evaluate.\", required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id)",") required = pred.result else: await ctx.send( \"This argument was automatically made optional","ctx: commands.Context, id: int = None): \"\"\" Manually set the application ID for","async def slashtagset_addeval(self, ctx: commands.Context): \"\"\"Add a slash eval command for debugging.\"\"\" if","await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\"name\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context, tag:","not in choice_text: await ctx.send( f\"Failed to parse `{choice_text}` to a choice as","target_state is self.testing_enabled: loaded = \"loaded\" if target_state else \"unloaded\" return await ctx.send(f\"The","should the tag description to be? (maximum 100 characters)\", pred=MessagePredicate.length_less(101, ctx), ) except","commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override = doc","description must be less than or equal to 100 characters.*\", ] name_pred =","def slashtag_list(self, ctx: commands.Context): \"\"\"View stored slash tags.\"\"\" tags = self.guild_tag_cache[ctx.guild.id] if not","commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\"argument\", aliases=[\"option\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx:","len(tagscript) > limit - 3: tagscript = tagscript[:limit] + \"...\" tagscript = tagscript.replace(\"\\n\",","with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \"\"\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False,","IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE","TagScript.\"\"\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\"name\") async def slashtag_edit_name( self, ctx: commands.Context, tag:","argument) @slashtag_global.command(\"remove\", aliases=[\"delete\", \"-\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter):","`{choice_text}` to a choice as \" \"its name or value exceeded the 100","2020-present phenom4n4n Permission is hereby granted, free of charge, to any person obtaining",") @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"user\") async def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *,","about a slash tag that is stored on this server.\"\"\" await tag.send_info(ctx) @slashtag.command(\"raw\")","\") return f\"{title}{discord.utils.escape_markdown(tagscript)}\" async def view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag], *,","argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"remove\", aliases=[\"delete\", \"-\"]) async def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter):","# exc info unneeded since error handler should print it, however info on","\" limit -= len(title) tagscript = tag.tagscript if len(tagscript) > limit - 3:","await self.config.guild(guild).tags.clear() await ctx.send(\"Tags deleted.\") @commands.is_owner() @slashtag.group(\"global\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context):","doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__ =","EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS","@slashtagset.command(\"addeval\") async def slashtagset_addeval(self, ctx: commands.Context): \"\"\"Add a slash eval command for debugging.\"\"\"","\"\"\"Edit a slash tag's description.\"\"\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\"arguments\", aliases=[\"options\"]) async def slashtag_edit_arguments(self,","subject to the following conditions: The above copyright notice and this permission notice","PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE","\" \"the tag. Choice names and values should be seperated by `:`, and","the list of choice names and values you would like to add as","], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\"`/eval` has been","re.compile(r\".{1,100}:.{1,100}\") CHOICE_LIMIT = 25 log = logging.getLogger(\"red.phenom4n4n.slashtags.commands\") def _sub(match: re.Match) -> str: if","None): \"\"\" Manually set the application ID for [botname] slash commands if it","description = [ f\"Application ID: **{self.application_id}**\", f\"Eval command: {eval_command}\", f\"Test cog loaded: {testing_enabled}\",","def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id] if guild",") continue choice = ApplicationOptionChoice(*choice_text.split(\":\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\"Reached","FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,","ctx.send(message) counter = Counter({tag.name: tag.uses for tag in tags.copy().values()}) e = discord.Embed(title=\"Slash Tag","be optional.*\", pred, ) required = pred.result else: await ctx.send( \"This argument was","to legacy bots. If you don't know what this means, you don't need","in valid_option_types])}\", \"(select `string` if you don't understand)\", ] option_type = await self.send_and_query_response(","\"global slash tags\" e.set_author(name=\"Global Slash Tags\", icon_url=ctx.me.avatar_url) else: slash_tags = \"slash tags\" e.set_author(name=\"Stored","delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await ctx.send( f\"Failed to parse `{choice_text}` to","true_or_false: bool = None): \"\"\" Load or unload the SlashTag interaction development test","hereby granted, free of charge, to any person obtaining a copy of this","options: List[SlashOption] = [] guild_id = None if is_global else ctx.guild.id if command_type","embed = e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\"usage\", aliases=[\"stats\"])","{testing_enabled}\", ] embed = discord.Embed( color=0xC9C9C9, title=\"SlashTags Settings\", description=\"\\n\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\"appid\")","= await self.send_and_query_response( ctx, \"What should the tag description to be? (maximum 100","embed.set_footer(text=f\"{index}/{len(pages)} | {len(tags)} {slash_tags}\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds)","*, tag: GuildTagConverter): \"\"\"Get a slash tag's raw content.\"\"\" await tag.send_raw_tagscript(ctx) @classmethod def","slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if not tags: return await ctx.send(\"There are","one was optional.\", delete_after=15, ) required = False return SlashOption( name=name.lower(), description=description, option_type=option_type,","the argument name be and description be?\", \"The argument name and description should","def slashtagset_rmeval(self, ctx: commands.Context): \"\"\"Remove the slash eval command.\"\"\" if not self.eval_command: return","restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute,","must be less than or equal to 100 characters.*\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION,","discord.Guild = None): tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not tags:","def slashtagset_addeval(self, ctx: commands.Context): \"\"\"Add a slash eval command for debugging.\"\"\" if self.eval_command:","await ctx.send( f\"Failed to parse `{choice_text}` to a choice as \" \"its name","characters and can only contain characters \" \"that are alphanumeric or '_' or","tag's argument by name.\"\"\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\"remove\", aliases=[\"delete\", \"-\"]) async def","import Dict, List, Union import discord from redbot.core import commands from redbot.core.utils.chat_formatting import","@copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\"add\") @copy_doc(slashtag_add) async def slashtag_global_add( self,","= \"\\n\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \"global slash tags\"","ctx.guild) @commands.is_owner() @slashtag.command(\"clear\", hidden=True) async def slashtag_clear(self, ctx: commands.Context): \"\"\"Clear all slash tags","@slashtagset.command(\"appid\") async def slashtagset_appid(self, ctx: commands.Context, id: int = None): \"\"\" Manually set","@slashtag.group(\"global\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\"add\") @copy_doc(slashtag_add) async def slashtag_global_add(","= tagscript.replace(\"\\n\", \" \") return f\"{title}{discord.utils.escape_markdown(tagscript)}\" async def view_slash_tags( self, ctx: commands.Context, tags:"],"string":"[\n \"AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,\",\n \"a Pastebin link. \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True)\",\n \"@classmethod def format_tagscript(cls, tag: SlashTag, limit: int = 60) -> str: title =\",\n \"slashtagset_rmeval(self, ctx: commands.Context): \\\"\\\"\\\"Remove the slash eval command.\\\"\\\"\\\" if not self.eval_command: return await\",\n \"color=0xC9C9C9, title=\\\"SlashTags Settings\\\", description=\\\"\\\\n\\\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\\\"appid\\\") async def slashtagset_appid(self, ctx: commands.Context,\",\n \"Edit a slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on\",\n \"to make this argument optional, all following arguments must also be optional.*\\\", pred,\",\n \"async def slashtag_list(self, ctx: commands.Context): \\\"\\\"\\\"View stored slash tags.\\\"\\\"\\\" tags = self.guild_tag_cache[ctx.guild.id] if\",\n \"tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript,\",\n \"@slashtag_global.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link:\",\n \"loaded = \\\"loaded\\\" if target_state else \\\"unloaded\\\" return await ctx.send(f\\\"The SlashTag interaction testing\",\n \"not self.eval_command: return await ctx.send(\\\"The eval command hasn't been registered.\\\") try: await self.http.remove_slash_command(self.eval_command)\",\n \"TagScriptConverter, ): \\\"\\\"\\\" Add a user command tag with TagScript. [Slash tag usage\",\n \"this software and associated documentation files (the \\\"Software\\\"), to deal in the Software\",\n \"OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE\",\n \"commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\\\"restore\\\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx,\",\n \"Load or unload the SlashTag interaction development test cog. \\\"\\\"\\\" target_state = (\",\n \"self.config.guild(guild).tags.clear() await ctx.send(\\\"Tags deleted.\\\") @commands.is_owner() @slashtag.group(\\\"global\\\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass\",\n \") except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding additional arguments.\\\") break if\",\n \"the Software without restriction, including without limitation the rights to use, copy, modify,\",\n \"the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies\",\n \"ctx.send(\\\"Timed out, not deleting slash tags.\\\") if not pred.result: return await ctx.send(\\\"Ok, not\",\n \"without restriction, including without limitation the rights to use, copy, modify, merge, publish,\",\n \"\\\"\\\"\\\" Add a slash tag with a Pastebin link. \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name,\",\n \"name and value \\\" \\\"weren't seperated by a `:`.\\\", delete_after=15, ) continue if\",\n \"name=\\\"eval\\\", description=\\\"SlashTags debugging eval command. Only bot owners can use this.\\\", options=[ SlashOption(name=\\\"body\\\",\",\n \"Union import discord from redbot.core import commands from redbot.core.utils.chat_formatting import box, humanize_list, inline,\",\n \"choice names and values you would like to add as choices to \\\"\",\n \"Tag Stats\\\", color=await ctx.embed_color()) embeds = [] for usage_data in chunks(counter.most_common(), 10): usage_chart\",\n \"async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None): \\\"\\\"\\\" Load or unload\",\n \"import logging import re import types from collections import Counter from copy import\",\n \"\\\"\\\"\\\" app_id = id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\\\"Application\",\n \"target_state: loaded = \\\"Loaded\\\" self.add_test_cog() else: loaded = \\\"Unloaded\\\" self.remove_test_cog() await ctx.send(f\\\"{loaded} the\",\n \"slash tag's TagScript.\\\"\\\"\\\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\\\"name\\\") async def slashtag_edit_name( self, ctx:\",\n \") -> List[SlashOption]: added_required = False for i in range(1, 11): try: option\",\n \"TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER\",\n \"exceeded the 100 character limit.\\\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\\\":\\\", 1)) choices.append(choice)\",\n \"def _sub(match: re.Match) -> str: if match.group(1): return \\\"[p]slashtag global\\\" repl = \\\"global\",\n \"tag's name.\\\"\\\"\\\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\\\"description\\\") async def slashtag_edit_description( self, ctx: commands.Context, tag:\",\n \"await ctx.send(\\\"Query timed out, not adding additional arguments.\\\") break if pred.result is False:\",\n \"registered.\\\") @commands.check(dev_check) @slashtagset.command(\\\"rmeval\\\") async def slashtagset_rmeval(self, ctx: commands.Context): \\\"\\\"\\\"Remove the slash eval command.\\\"\\\"\\\"\",\n \"@slashtag.command(\\\"clear\\\", hidden=True) async def slashtag_clear(self, ctx: commands.Context): \\\"\\\"\\\"Clear all slash tags for this\",\n \"sublicense, and/or sell copies of the Software, and to permit persons to whom\",\n \"no global slash tags.\\\" ) return await ctx.send(message) counter = Counter({tag.name: tag.uses for\",\n \"is not None else not await self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded\",\n \"logging import re import types from collections import Counter from copy import copy\",\n \"`{choice_text}` to a choice as its name and value \\\" \\\"weren't seperated by\",\n \"See this slash tag usage stats. **Example:** `[p]slashtag usage` \\\"\\\"\\\" await self.show_slash_tag_usage(ctx, ctx.guild)\",\n \"@slashtag_global.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await\",\n \"tag usage stats. **Example:** `[p]slashtag usage` \\\"\\\"\\\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"restore\\\", hidden=True)\",\n \"commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\\\"list\\\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context):\",\n \"( true_or_false if true_or_false is not None else not await self.config.testing_enabled() ) if\",\n \"notice and this permission notice shall be included in all copies or substantial\",\n \"self.send_and_query_response(ctx, query) choices = [] for choice_text in response.split(\\\"|\\\"): if \\\":\\\" not in\",\n \"tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"message\\\")\",\n \"if option_type.lower() == \\\"choices\\\": choices = await self.get_choices(ctx) option_type = \\\"STRING\\\" else: choices\",\n \"async def view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global: bool, ):\",\n \"for more information on slash tag arguments. \\\"\\\"\\\" await tag.edit_options(ctx) @slashtag_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) async\",\n \"command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name,\",\n \"self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None await ctx.send(\\\"`/eval` has been\",\n \"See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag arguments. \\\"\\\"\\\" await\",\n \"from redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate from ..abc import MixinMeta from\",\n \"return \\\"[p]slashtag global\\\" repl = \\\"global \\\" name = match.group(0) repl += name\",\n \"tags on this server.\\\") await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context,\",\n \"32 characters and can only contain characters \\\" \\\"that are alphanumeric or '_'\",\n \"async def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx,\",\n \"except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None await ctx.send(\\\"`/eval` has been deleted.\\\")\",\n \"slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Delete a slash tag.\\\"\\\"\\\" await ctx.send(await tag.delete())\",\n \"If you don't know what this means, you don't need to worry about\",\n \"False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"message\\\") async def\",\n \"( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType\",\n \"ctx, \\\"Would you like to add another argument? (Y/n)\\\", pred ) except asyncio.TimeoutError:\",\n \"ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\\\"description\\\") @copy_doc(slashtag_edit_description)\",\n \"async def get_option( self, ctx: commands.Context, *, added_required: bool = False ) ->\",\n \"slashtag_usage(self, ctx: commands.Context): \\\"\\\"\\\" See this slash tag usage stats. **Example:** `[p]slashtag usage`\",\n \"slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \\\"\\\"\\\" Add a\",\n \"body to evaluate.\\\", required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id\",\n \"this server.\\\"\\\"\\\" await tag.send_info(ctx) @slashtag.command(\\\"raw\\\") async def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter):\",\n \"@copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ):\",\n \"tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"user\\\") async def slashtag_user( self, ctx: commands.Context, tag_name:\",\n \"from collections import Counter from copy import copy from typing import Dict, List,\",\n \"This only applies to legacy bots. If you don't know what this means,\",\n \"ctx.send(f\\\"The SlashTag interaction testing cog is already {loaded}.\\\") await self.config.testing_enabled.set(target_state) if target_state: loaded\",\n \"original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__\",\n \"MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \\\"Is this argument required? (Y/n)\\\\n*Keep in mind that if\",\n \"@slashtag.command(\\\"info\\\") async def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \\\"\\\"\\\"Get info about a\",\n \"self.eval_command = None await ctx.send(\\\"`/eval` has been deleted.\\\") @slashtagset.command(\\\"testing\\\") async def slashtagset_testing(self, ctx:\",\n \"raw content.\\\"\\\"\\\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit: int = 60)\",\n \"@slashtag_global.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\\\"restore\\\", hidden=True) @copy_doc(slashtag_restore)\",\n \"this server? (Y/n)\\\", pred ) except asyncio.TimeoutError: return await ctx.send(\\\"Timed out, not deleting\",\n \"@slashtag_global.command(\\\"list\\\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if not tags:\",\n \"discord from redbot.core import commands from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from\",\n \"delete_after=15) break options.append(option) if i == 10: break pred = MessagePredicate.yes_or_no(ctx) try: await\",\n \"await ctx.send(f\\\"Reached max choices ({CHOICE_LIMIT}).\\\") break return choices async def get_option( self, ctx:\",\n \"(Y/n)\\\\n*Keep in mind that if you choose to make this argument optional, all\",\n \"commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a slash tag with\",\n \"copy from typing import Dict, List, Union import discord from redbot.core import commands\",\n \"\\\"\\\"\\\"Get info about a slash tag that is stored on this server.\\\"\\\"\\\" await\",\n \"to deal in the Software without restriction, including without limitation the rights to\",\n \"deleted.\\\") @slashtagset.command(\\\"testing\\\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None): \\\"\\\"\\\" Load\",\n \"*, is_global: bool, ): description = [ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda\",\n \"response = await self.send_and_query_response(ctx, query) choices = [] for choice_text in response.split(\\\"|\\\"): if\",\n \"ctx: commands.Context, tag: GuildTagConverter, argument: str ): \\\"\\\"\\\"Edit a single slash tag's argument\",\n \"await self.send_and_query_response( ctx, \\\"Would you like to add arguments to this tag? (Y/n)\\\",\",\n \"list of choice names and values you would like to add as choices\",\n \"\\\"\\\"\\\"Delete a slash tag.\\\"\\\"\\\" await ctx.send(await tag.delete()) @slashtag.command(\\\"info\\\") async def slashtag_info(self, ctx: commands.Context,\",\n \"None: pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message = await self.bot.wait_for(\\\"message\\\",\",\n \"slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None): \\\"\\\"\\\" Load or unload the SlashTag\",\n \"global\\\" repl = \\\"global \\\" name = match.group(0) repl += name if name.istitle():\",\n \"Software without restriction, including without limitation the rights to use, copy, modify, merge,\",\n \"async def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\\\"list\\\") @copy_doc(slashtag_list) async\",\n \"ctx), ) except asyncio.TimeoutError: return await ctx.send(\\\"Tag addition timed out.\\\") else: description =\",\n \"tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"user\\\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx:\",\n \"def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add\",\n \"on this server? (Y/n)\\\", pred ) except asyncio.TimeoutError: return await ctx.send(\\\"Timed out, not\",\n \"@commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"add\\\", aliases=[\\\"create\\\", \\\"+\\\"]) async def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *,\",\n \"def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\\\"slashset\\\"]) async def slashtagset(self, ctx:\",\n \"self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"message\\\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context,\",\n \"commands.Context, tag: GuildTagConverter): \\\"\\\"\\\" Edit a slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html)\",\n \"if name.istitle(): repl = repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden:\",\n \"if true_or_false is not None else not await self.config.testing_enabled() ) if target_state is\",\n \"def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await\",\n \"slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add\",\n \"async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) @copy_doc(slashtag_edit_argument) async\",\n \"choice_text in response.split(\\\"|\\\"): if \\\":\\\" not in choice_text: await ctx.send( f\\\"Failed to parse\",\n \"OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. \\\"\\\"\\\" import asyncio import\",\n \"= \\\"global \\\" name = match.group(0) repl += name if name.istitle(): repl =\",\n \"valid_option_types])}\\\", \\\"(select `string` if you don't understand)\\\", ] option_type = await self.send_and_query_response( ctx,\",\n \"match.group(0) repl += name if name.istitle(): repl = repl.title() return repl def copy_doc(original:\",\n \"is stored on this server.\\\"\\\"\\\" await tag.send_info(ctx) @slashtag.command(\\\"raw\\\") async def slashtag_raw(self, ctx: commands.Context,\",\n \"name.istitle(): repl = repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command,\",\n \"\\\"\\\" if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would\",\n \"range(1, 11): try: option = await self.get_option(ctx, added_required=added_required) if not option.required: added_required =\",\n \"icon_url=ctx.me.avatar_url) else: slash_tags = \\\"slash tags\\\" e.set_author(name=\\\"Stored Slash Tags\\\", icon_url=ctx.guild.icon_url) embeds = []\",\n \"async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \\\"\\\"\\\" Edit a slash tag's arguments.\",\n \"global slash tags.\\\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self,\",\n \"tag with a Pastebin link. \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\\\"edit\\\",\",\n \"@slashtag.command(\\\"restore\\\", hidden=True) async def slashtag_restore(self, ctx: commands.Context): \\\"\\\"\\\"Restore all slash tags from the\",\n \"= MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \\\"\\\\n\\\".join(name_desc), name_pred) match = name_pred.result name, description =\",\n \"a slash tag's raw content.\\\"\\\"\\\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit:\",\n \"from copy import copy from typing import Dict, List, Union import discord from\",\n \"ctx: commands.Context): \\\"\\\"\\\"Manage SlashTags settings.\\\"\\\"\\\" @slashtagset.command(\\\"settings\\\") async def slashtagset_settings(self, ctx: commands.Context): \\\"\\\"\\\"View SlashTags\",\n \"f\\\"Test cog loaded: {testing_enabled}\\\", ] embed = discord.Embed( color=0xC9C9C9, title=\\\"SlashTags Settings\\\", description=\\\"\\\\n\\\".join(description) )\",\n \"commands.Context, id: int = None): \\\"\\\"\\\" Manually set the application ID for [botname]\",\n \"slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *, description: str ): \\\"\\\"\\\"Edit a slash\",\n \"description = [ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t: t.name) ] description\",\n \"async def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *, description: str ): \\\"\\\"\\\"Edit\",\n \"TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\\\"tagscript\\\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context,\",\n \"tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag.\\\"\\\"\\\" await ctx.send(await tag.edit_tagscript(tagscript))\",\n \"await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None):\",\n \"ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ): \\\"\\\"\\\"Edit a slash tag's name.\\\"\\\"\\\"\",\n \"tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context,\",\n \"tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) async def slashtag_pastebin( self, ctx:\",\n \"else self.global_tag_cache if not tags: message = ( \\\"This server has no slash\",\n \"MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you like to add another argument? (Y/n)\\\",\",\n \"@slashtag_global.command(\\\"raw\\\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\\\"list\\\")\",\n \"free of charge, to any person obtaining a copy of this software and\",\n \"and this permission notice shall be included in all copies or substantial portions\",\n \"get_option( self, ctx: commands.Context, *, added_required: bool = False ) -> SlashOption: name_desc\",\n \"tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a slash tag with TagScript.\",\n \"ctx.send(\\\"`/eval` has been deleted.\\\") @slashtagset.command(\\\"testing\\\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool =\",\n \"already {loaded}.\\\") await self.config.testing_enabled.set(target_state) if target_state: loaded = \\\"Loaded\\\" self.add_test_cog() else: loaded =\",\n \"don't know what this means, you don't need to worry about it. \\\"\\\"\\\"\",\n \"rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of\",\n \"await ctx.send(await tag.delete()) @slashtag.command(\\\"info\\\") async def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \\\"\\\"\\\"Get\",\n \"..http import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus\",\n \"self, ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\\\"description\\\")\",\n \"already registered.\\\") slasheval = ApplicationCommand( self, name=\\\"eval\\\", description=\\\"SlashTags debugging eval command. Only bot\",\n \"was automatically made optional as the previous one was optional.\\\", delete_after=15, ) required\",\n \"\\\"+\\\"]) async def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ):\",\n \"headers=(\\\"Tag\\\", \\\"Uses\\\")), \\\"prolog\\\") embed = e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds,\",\n \"except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def\",\n \"EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES\",\n \"added_required = True except asyncio.TimeoutError: await ctx.send(\\\"Adding this argument timed out.\\\", delete_after=15) break\",\n \"\\\"\\\"\\\"Clear all slash tags for this server.\\\"\\\"\\\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response(\",\n \"use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use TagScript blocks. \\\"\\\"\\\"\",\n \"\\\"What should the tag description to be? (maximum 100 characters)\\\", pred=MessagePredicate.length_less(101, ctx), )\",\n \"id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\\\"Application ID set to\",\n \"`member:A member of this server.`\\\\n\\\", \\\"*Slash argument names may not exceed 32 characters\",\n \"name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"message\\\") async def slashtag_message( self, ctx:\",\n \"query = ( \\\"Send the list of choice names and values you would\",\n \"DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\\\"list\\\") async def slashtag_list(self, ctx: commands.Context): \\\"\\\"\\\"View stored slash\",\n \"notice shall be included in all copies or substantial portions of the Software.\",\n \"= ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag\",\n \"slashtag_list(self, ctx: commands.Context): \\\"\\\"\\\"View stored slash tags.\\\"\\\"\\\" tags = self.guild_tag_cache[ctx.guild.id] if not tags:\",\n \"..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu as button_menu from\",\n \"commands.Context): tags = self.global_tag_cache if not tags: return await ctx.send(\\\"There are no global\",\n \"tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True,\",\n \"tag.edit_description(description)) @slashtag_global_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx)\",\n \"stored on this server.\\\"\\\"\\\" await tag.send_info(ctx) @slashtag.command(\\\"raw\\\") async def slashtag_raw(self, ctx: commands.Context, *,\",\n \"*, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\\\"pastebin\\\",\",\n \"optional.*\\\", pred, ) required = pred.result else: await ctx.send( \\\"This argument was automatically\",\n \"{slash_tags}\\\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\\\"list\\\") async def\",\n \") except asyncio.TimeoutError: return await ctx.send(\\\"Tag addition timed out.\\\") else: description = \\\"\\\"\",\n \"tags, is_global=True) @slashtag_global.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\\\"restore\\\",\",\n \"command {command!r} on guild {ctx.guild!r}\\\") # exc info unneeded since error handler should\",\n \"import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\") CHOICE_RE = re.compile(r\\\".{1,100}:.{1,100}\\\") CHOICE_LIMIT = 25\",\n \"ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION\",\n \"argument name be and description be?\\\", \\\"The argument name and description should be\",\n \"await ctx.send(embed=embed) @slashtagset.command(\\\"appid\\\") async def slashtagset_appid(self, ctx: commands.Context, id: int = None): \\\"\\\"\\\"\",\n \"and description be?\\\", \\\"The argument name and description should be split by a\",\n \"..abc import MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter,\",\n \"commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\\\"tagscript\\\") @copy_doc(slashtag_edit_tagscript) async\",\n \"`:`, and each choice \\\" \\\"should be seperated by `|`. Example:\\\\n`dog:Doggo|cat:Catto`\\\" ) response\",\n \"try again: <https://discordapp.com/oauth2/authorize\\\" f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\" ) return await ctx.send(text) except Exception: log.error(\\\"Failed to create\",\n \"if target_state else \\\"unloaded\\\" return await ctx.send(f\\\"The SlashTag interaction testing cog is already\",\n \"\\\"prolog\\\") embed = e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\\\"usage\\\",\",\n \"): description = [ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t: t.name) ]\",\n \"CHOICE_LIMIT: await ctx.send(f\\\"Reached max choices ({CHOICE_LIMIT}).\\\") break return choices async def get_option( self,\",\n \"bool = None): \\\"\\\"\\\" Load or unload the SlashTag interaction development test cog.\",\n \"in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\\\"Tag\\\", \\\"Uses\\\")), \\\"prolog\\\") embed = e.copy() embed.description\",\n \"choose to make this argument optional, all following arguments must also be optional.*\\\",\",\n \"a slash tag's description.\\\"\\\"\\\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) async def slashtag_edit_arguments(self, ctx:\",\n \"for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\\\"Tags\",\n \"tags\\\" e.set_author(name=\\\"Global Slash Tags\\\", icon_url=ctx.me.avatar_url) else: slash_tags = \\\"slash tags\\\" e.set_author(name=\\\"Stored Slash Tags\\\",\",\n \"@slashtag_global_edit.command(\\\"tagscript\\\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter\",\n \"TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a user command tag with\",\n \"OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\",\n \"not adding additional arguments.\\\") break if pred.result is False: break return options async\",\n \"it differs from the bot user ID. This only applies to legacy bots.\",\n \"\\\"\\\"\\\"Get a slash tag's raw content.\\\"\\\"\\\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag,\",\n \"publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons\",\n \"tag.edit_description(description)) @slashtag_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \\\"\\\"\\\" Edit a\",\n \"MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Are you sure you want to delete all\",\n \"def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Get a slash tag's raw content.\\\"\\\"\\\"\",\n \"await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await\",\n \"type=command_type, ) try: await command.register() except discord.Forbidden as error: log.error( \\\"Failed to create\",\n \"ctx: commands.Context): \\\"\\\"\\\"Restore all slash tags from the database.\\\"\\\"\\\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner()\",\n \"tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a user command tag with TagScript. [Slash tag\",\n \"def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await\",\n \"THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. \\\"\\\"\\\" import\",\n \"and values should be seperated by `:`, and each choice \\\" \\\"should be\",\n \"1): embed = e.copy() embed.description = page embed.set_footer(text=f\\\"{index}/{len(pages)} | {len(tags)} {slash_tags}\\\") embeds.append(embed) #\",\n \"tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"user\\\") async def slashtag_user( self, ctx: commands.Context,\",\n \"ctx.send(\\\"Ok, not deleting slash tags.\\\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for\",\n \"{eval_command}\\\", f\\\"Test cog loaded: {testing_enabled}\\\", ] embed = discord.Embed( color=0xC9C9C9, title=\\\"SlashTags Settings\\\", description=\\\"\\\\n\\\".join(description)\",\n \"list(pagify(description)) for index, page in enumerate(pages, 1): embed = e.copy() embed.description = page\",\n \"def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx,\",\n \"slash_tags = \\\"slash tags\\\" e.set_author(name=\\\"Stored Slash Tags\\\", icon_url=ctx.guild.icon_url) embeds = [] pages =\",\n \"TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag.\\\"\\\"\\\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\\\"tagscript\\\") async def slashtag_edit_tagscript(\",\n \"\\\"What should the argument name be and description be?\\\", \\\"The argument name and\",\n \"SlashTags settings.\\\"\\\"\\\" eval_command = f\\\"✅ (**{self.eval_command}**)\\\" if self.eval_command else \\\"❎\\\" testing_enabled = \\\"✅\\\"\",\n \"slash tags for this server.\\\"\\\"\\\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Are\",\n \"embeds = [] pages = list(pagify(description)) for index, page in enumerate(pages, 1): embed\",\n \"dev_check TAG_RE = re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\") CHOICE_RE = re.compile(r\\\".{1,100}:.{1,100}\\\") CHOICE_LIMIT = 25 log = logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\")\",\n \"`{id}`.\\\") @commands.check(dev_check) @slashtagset.command(\\\"addeval\\\") async def slashtagset_addeval(self, ctx: commands.Context): \\\"\\\"\\\"Add a slash eval command\",\n \"def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *, description: str ): await ctx.send(await\",\n \"SlashOption, SlashTag from ..testing.button_menus import menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks,\",\n \"option_type = SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \\\"Is\",\n \"embeds) @slashtag.command(\\\"list\\\") async def slashtag_list(self, ctx: commands.Context): \\\"\\\"\\\"View stored slash tags.\\\"\\\"\\\" tags =\",\n \"isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__ = doc return overriden return decorator\",\n \"): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"user\\\") @copy_doc(slashtag_user) async\",\n \"\\\"loaded\\\" if target_state else \\\"unloaded\\\" return await ctx.send(f\\\"The SlashTag interaction testing cog is\",\n \"= e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) async\",\n \"ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Delete a slash tag.\\\"\\\"\\\" await ctx.send(await tag.delete()) @slashtag.command(\\\"info\\\")\",\n \"tag.initialize()) async def get_options( self, ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required\",\n \"SOFTWARE. \\\"\\\"\\\" import asyncio import logging import re import types from collections import\",\n \"if target_state: loaded = \\\"Loaded\\\" self.add_test_cog() else: loaded = \\\"Unloaded\\\" self.remove_test_cog() await ctx.send(f\\\"{loaded}\",\n \"= original.help if isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden,\",\n \"self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not tags: message = ( \\\"This server\",\n \"\\\"unloaded\\\" return await ctx.send(f\\\"The SlashTag interaction testing cog is already {loaded}.\\\") await self.config.testing_enabled.set(target_state)\",\n \"await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) async def slashtag_edit( self,\",\n \"argument was automatically made optional as the previous one was optional.\\\", delete_after=15, )\",\n \"self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\\\"Application ID set to `{id}`.\\\") @commands.check(dev_check)\",\n \"@commands.is_owner() @slashtag.group(\\\"global\\\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\\\"add\\\") @copy_doc(slashtag_add) async def\",\n \"slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\\\"restore\\\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context):\",\n \"message = await self.bot.wait_for(\\\"message\\\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask)\",\n \"\\\"The argument name and description should be split by a `:`.\\\", \\\"Example: `member:A\",\n \"( \\\"This server has no slash tags.\\\" if guild else \\\"There are no\",\n \"ctx), ) if option_type.lower() == \\\"choices\\\": choices = await self.get_choices(ctx) option_type = \\\"STRING\\\"\",\n \"above copyright notice and this permission notice shall be included in all copies\",\n \"registered.\\\") slasheval = ApplicationCommand( self, name=\\\"eval\\\", description=\\\"SlashTags debugging eval command. Only bot owners\",\n \"commands.Context): \\\"\\\"\\\"Remove the slash eval command.\\\"\\\"\\\" if not self.eval_command: return await ctx.send(\\\"The eval\",\n \"choice_text: await ctx.send( f\\\"Failed to parse `{choice_text}` to a choice as its name\",\n \"f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\" async def view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global: bool,\",\n \"self.send_and_query_response( ctx, \\\"Are you sure you want to delete all slash tags on\",\n \"tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\\\"list\\\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags =\",\n \"await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]:\",\n \"await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\\\"tagscript\\\") async def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *,\",\n \"documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag arguments. \\\"\\\"\\\" await tag.edit_options(ctx) @slashtag_edit.command(\\\"argument\\\",\",\n \"f\\\"`{tag.type.get_prefix()}{tag.name}` - \\\" limit -= len(title) tagscript = tag.tagscript if len(tagscript) > limit\",\n \"than or equal to 100 characters.*\\\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx,\",\n \"await self.send_and_query_response(ctx, query) choices = [] for choice_text in response.split(\\\"|\\\"): if \\\":\\\" not\",\n \"slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ): \\\"\\\"\\\"Edit a slash\",\n \"FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS\",\n \"copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original, commands.Command)\",\n \"ctx.guild) @commands.is_owner() @slashtag.command(\\\"restore\\\", hidden=True) async def slashtag_restore(self, ctx: commands.Context): \\\"\\\"\\\"Restore all slash tags\",\n \"ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name,\",\n \"ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag's TagScript.\\\"\\\"\\\"\",\n \"commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\\\"slashset\\\"]) async def slashtagset(self, ctx: commands.Context): \\\"\\\"\\\"Manage SlashTags\",\n \"is True: await self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options,\",\n \"@slashtag_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \\\"\\\"\\\" Edit a slash\",\n \"else: if pred.result is True: await self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name,\",\n \"Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\\\"st\\\"]) async def slashtag(self, ctx: commands.Context): \\\"\\\"\\\" Slash Tag management with\",\n \"info unneeded since error handler should print it, however info on the command\",\n \"Tags\\\", icon_url=ctx.me.avatar_url) else: slash_tags = \\\"slash tags\\\" e.set_author(name=\\\"Stored Slash Tags\\\", icon_url=ctx.guild.icon_url) embeds =\",\n \"def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query = ( \\\"Send the list of\",\n \"arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag arguments. \\\"\\\"\\\"\",\n \"automatically made optional as the previous one was optional.\\\", delete_after=15, ) required =\",\n \"await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) async def slashtag_remove(self, ctx: commands.Context, *,\",\n \"embeds = [] for usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\\\"Tag\\\", \\\"Uses\\\")),\",\n \"in mind that if you choose to make this argument optional, all following\",\n \"be split by a `:`.\\\", \\\"Example: `member:A member of this server.`\\\\n\\\", \\\"*Slash argument\",\n \"commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\\\"description\\\") @copy_doc(slashtag_edit_description) async\",\n \"await ctx.send(\\\"Timed out, not deleting slash tags.\\\") if not pred.result: return await ctx.send(\\\"Ok,\",\n \"furnished to do so, subject to the following conditions: The above copyright notice\",\n \"usage_chart = box(tabulate(usage_data, headers=(\\\"Tag\\\", \\\"Uses\\\")), \\\"prolog\\\") embed = e.copy() embed.description = usage_chart embeds.append(embed)\",\n \"tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True)\",\n \"== \\\"choices\\\": choices = await self.get_choices(ctx) option_type = \\\"STRING\\\" else: choices = []\",\n \"permit persons to whom the Software is furnished to do so, subject to\",\n \"ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION,\",\n \"menu from redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate from ..abc import MixinMeta\",\n \"= list(pagify(description)) for index, page in enumerate(pages, 1): embed = e.copy() embed.description =\",\n \"copies of the Software, and to permit persons to whom the Software is\",\n \"a `:`.\\\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await ctx.send( f\\\"Failed to parse\",\n \"aliases=[\\\"stats\\\"]) async def slashtag_usage(self, ctx: commands.Context): \\\"\\\"\\\" See this slash tag usage stats.\",\n \"\\\"\\\"\\\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"restore\\\", hidden=True) async def slashtag_restore(self, ctx: commands.Context): \\\"\\\"\\\"Restore\",\n \"command_type=ApplicationCommandType.USER ) @slashtag_global.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False),\",\n \"\\\"\\\"\\\"Add a slash eval command for debugging.\\\"\\\"\\\" if self.eval_command: return await ctx.send(\\\"An eval\",\n \"await ctx.send(f\\\"The SlashTag interaction testing cog is already {loaded}.\\\") await self.config.testing_enabled.set(target_state) if target_state:\",\n \"= False ) -> SlashOption: name_desc = [ \\\"What should the argument name\",\n \"tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag arguments.\",\n \"ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"user\\\") @copy_doc(slashtag_user) async def slashtag_global_user( self,\",\n \"await self.send_and_query_response(ctx, \\\"\\\\n\\\".join(name_desc), name_pred) match = name_pred.result name, description = match.group(1), match.group(2) valid_option_types\",\n \"a single slash tag's argument by name.\\\"\\\"\\\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"remove\\\", aliases=[\\\"delete\\\",\",\n \"= TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__ = doc\",\n \"if not name.startswith(\\\"SUB\\\") ] valid_option_types.append(\\\"choices\\\") option_query = [ \\\"What should the argument type\",\n \"await ctx.send(\\\"There are no slash tags on this server.\\\") await self.view_slash_tags(ctx, tags, is_global=False)\",\n \"SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu as\",\n \"class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\\\"st\\\"]) async def slashtag(self, ctx: commands.Context): \\\"\\\"\\\" Slash Tag management\",\n \"this argument optional, all following arguments must also be optional.*\\\", pred, ) required\",\n \"= box(tabulate(usage_data, headers=(\\\"Tag\\\", \\\"Uses\\\")), \\\"prolog\\\") embed = e.copy() embed.description = usage_chart embeds.append(embed) await\",\n \"@slashtag_global.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *,\",\n \"await ctx.send(\\\"The eval command hasn't been registered.\\\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass\",\n \"is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"user\\\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context, tag_name:\",\n \"@slashtag.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) async def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter,\",\n \"check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE )\",\n \"page embed.set_footer(text=f\\\"{index}/{len(pages)} | {len(tags)} {slash_tags}\\\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx,\",\n \"argument name and description should be split by a `:`.\\\", \\\"Example: `member:A member\",\n \"pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message = await self.bot.wait_for(\\\"message\\\", check=pred,\",\n \"await ctx.send( \\\"This argument was automatically made optional as the previous one was\",\n \"if pred.result is False: break return options async def send_and_query_response( self, ctx: commands.Context,\",\n \"tags for this server.\\\"\\\"\\\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Are you\",\n \"def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a\",\n \"slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\\\"raw\\\") @copy_doc(slashtag_raw) async def\",\n \"if isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__ = doc return overriden return\",\n \"match.group(2) valid_option_types = [ name.lower() for name in SlashOptionType.__members__.keys() if not name.startswith(\\\"SUB\\\") ]\",\n \"e.set_author(name=\\\"Global Slash Tags\\\", icon_url=ctx.me.avatar_url) else: slash_tags = \\\"slash tags\\\" e.set_author(name=\\\"Stored Slash Tags\\\", icon_url=ctx.guild.icon_url)\",\n \"CHOICE_LIMIT = 25 log = logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\") def _sub(match: re.Match) -> str: if match.group(1):\",\n \"@copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\\\"raw\\\")\",\n \"await self.send_and_query_response( ctx, \\\"Are you sure you want to delete all slash tags\",\n \"to use TagScript blocks. \\\"\\\"\\\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"add\\\", aliases=[\\\"create\\\", \\\"+\\\"]) async def slashtag_add( self,\",\n \"def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None): \\\"\\\"\\\" Load or unload the\",\n \"as error: log.error( \\\"Failed to create command {command!r} on guild {ctx.guild!r}\\\", exc_info=error )\",\n \"be seperated by `|`. Example:\\\\n`dog:Doggo|cat:Catto`\\\" ) response = await self.send_and_query_response(ctx, query) choices =\",\n \"loaded: {testing_enabled}\\\", ] embed = discord.Embed( color=0xC9C9C9, title=\\\"SlashTags Settings\\\", description=\\\"\\\\n\\\".join(description) ) await ctx.send(embed=embed)\",\n \"= [] for choice_text in response.split(\\\"|\\\"): if \\\":\\\" not in choice_text: await ctx.send(\",\n \"bot owners can use this.\\\", options=[ SlashOption(name=\\\"body\\\", description=\\\"Code body to evaluate.\\\", required=True) ],\",\n \"slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\\\"remove\\\",\",\n \"mind that if you choose to make this argument optional, all following arguments\",\n \"= 25 log = logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\") def _sub(match: re.Match) -> str: if match.group(1): return\",\n \"ID for [botname] slash commands if it differs from the bot user ID.\",\n \"async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\\\"add\\\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx:\",\n \"is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"user\\\") async def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False,\",\n \"*, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) @copy_doc(slashtag_edit)\",\n \"if self.testing_enabled else \\\"❎\\\" description = [ f\\\"Application ID: **{self.application_id}**\\\", f\\\"Eval command: {eval_command}\\\",\",\n \"of this software and associated documentation files (the \\\"Software\\\"), to deal in the\",\n \"tag? (Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding arguments.\\\")\",\n \"@copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if not tags: return\",\n \"enumerate(pages, 1): embed = e.copy() embed.description = page embed.set_footer(text=f\\\"{index}/{len(pages)} | {len(tags)} {slash_tags}\\\") embeds.append(embed)\",\n \"repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if\",\n \"all following arguments must also be optional.*\\\", pred, ) required = pred.result else:\",\n \"await ctx.send( f\\\"Failed to parse `{choice_text}` to a choice as its name and\",\n \"text = ( \\\"Looks like I don't have permission to add Slash Commands\",\n \"can use this.\\\", options=[ SlashOption(name=\\\"body\\\", description=\\\"Code body to evaluate.\\\", required=True) ], ) await\",\n \"sell copies of the Software, and to permit persons to whom the Software\",\n \"\\\"\\\"\\\" Add a user command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\"\",\n \"SlashOptionType.__members__.keys() if not name.startswith(\\\"SUB\\\") ] valid_option_types.append(\\\"choices\\\") option_query = [ \\\"What should the argument\",\n \"self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): \\\"\\\"\\\"Edit a single slash tag's\",\n \"tagscript, is_global=False) async def create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript: str, *,\",\n \"] description = \\\"\\\\n\\\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \\\"global\",\n \"@commands.is_owner() @slashtag.command(\\\"restore\\\", hidden=True) async def slashtag_restore(self, ctx: commands.Context): \\\"\\\"\\\"Restore all slash tags from\",\n \"def get_options( self, ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required = False\",\n \"await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self,\",\n \"TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"message\\\") @copy_doc(slashtag_message)\",\n \"types: {humanize_list([inline(n) for n in valid_option_types])}\\\", \\\"(select `string` if you don't understand)\\\", ]\",\n \"get_options( self, ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required = False for\",\n \"choices = [] option_type = SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx) await\",\n \"List[SlashOption] ) -> List[SlashOption]: added_required = False for i in range(1, 11): try:\",\n \"tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\\\"tagscript\\\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx:\",\n \"self.send_and_query_response( ctx, \\\"What should the tag description to be? (maximum 100 characters)\\\", pred=MessagePredicate.length_less(101,\",\n \"description.\\\"\\\"\\\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter):\",\n \"else \\\"❎\\\" testing_enabled = \\\"✅\\\" if self.testing_enabled else \\\"❎\\\" description = [ f\\\"Application\",\n \"a slash tag's name.\\\"\\\"\\\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\\\"description\\\") async def slashtag_edit_description( self, ctx:\",\n \"tag: GuildTagConverter): \\\"\\\"\\\"Delete a slash tag.\\\"\\\"\\\" await ctx.send(await tag.delete()) @slashtag.command(\\\"info\\\") async def slashtag_info(self,\",\n \"a slash tag with a Pastebin link. \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, link, is_global=False)\",\n \"Slash Tags\\\", icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description)) for index, page in\",\n \"check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content\",\n \"command {command!r} on guild {ctx.guild!r}\\\", exc_info=error ) text = ( \\\"Looks like I\",\n \"import types from collections import Counter from copy import copy from typing import\",\n \"await ctx.send(\\\"Tag addition timed out.\\\") else: description = \\\"\\\" if command_type == ApplicationCommandType.CHAT_INPUT:\",\n \"t: t.name) ] description = \\\"\\\\n\\\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags\",\n \"true_or_false is not None else not await self.config.testing_enabled() ) if target_state is self.testing_enabled:\",\n \"self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"user\\\") async def slashtag_user( self,\",\n \"name: TagName(check_global=False) ): \\\"\\\"\\\"Edit a slash tag's name.\\\"\\\"\\\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\\\"description\\\") async\",\n \"= await self.get_choices(ctx) option_type = \\\"STRING\\\" else: choices = [] option_type = SlashOptionType[option_type.upper()]\",\n \"ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag.\\\"\\\"\\\" await\",\n \"if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you\",\n \"of the Software, and to permit persons to whom the Software is furnished\",\n \") except asyncio.TimeoutError: return await ctx.send(\\\"Timed out, not deleting slash tags.\\\") if not\",\n \"bot user ID. This only applies to legacy bots. If you don't know\",\n \"async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await\",\n \"doc else: overriden.__doc__ = doc return overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\\\"st\\\"])\",\n \"tag.send_raw_tagscript(ctx) @slashtag_global.command(\\\"list\\\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if not\",\n \"is None: pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message = await\",\n \"`string` if you don't understand)\\\", ] option_type = await self.send_and_query_response( ctx, \\\"\\\\n\\\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types,\",\n \"adding additional arguments.\\\") break if pred.result is False: break return options async def\",\n \"like to add arguments to this tag? (Y/n)\\\", pred ) except asyncio.TimeoutError: await\",\n \"copyright notice and this permission notice shall be included in all copies or\",\n \"usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"user\\\")\",\n \"tags from the database.\\\"\\\"\\\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"clear\\\", hidden=True) async def slashtag_clear(self,\",\n \"if self.eval_command: return await ctx.send(\\\"An eval command is already registered.\\\") slasheval = ApplicationCommand(\",\n \"`:`.\\\", \\\"Example: `member:A member of this server.`\\\\n\\\", \\\"*Slash argument names may not exceed\",\n \"TAG_RE = re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\") CHOICE_RE = re.compile(r\\\".{1,100}:.{1,100}\\\") CHOICE_LIMIT = 25 log = logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\") def\",\n \"database.\\\"\\\"\\\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"clear\\\", hidden=True) async def slashtag_clear(self, ctx: commands.Context): \\\"\\\"\\\"Clear\",\n \"aliases=[\\\"++\\\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter,\",\n \"str: if match.group(1): return \\\"[p]slashtag global\\\" repl = \\\"global \\\" name = match.group(0)\",\n \"def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \\\"\\\"\\\" Edit a slash tag's arguments. See\",\n \"set the application ID for [botname] slash commands if it differs from the\",\n \"name.\\\"\\\"\\\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\\\"description\\\") async def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter,\",\n \"async def slashtag_usage(self, ctx: commands.Context): \\\"\\\"\\\" See this slash tag usage stats. **Example:**\",\n \"True except asyncio.TimeoutError: await ctx.send(\\\"Adding this argument timed out.\\\", delete_after=15) break options.append(option) if\",\n \"about it. \\\"\\\"\\\" app_id = id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id\",\n \"use TagScript blocks. \\\"\\\"\\\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"add\\\", aliases=[\\\"create\\\", \\\"+\\\"]) async def slashtag_add( self, ctx:\",\n \"log = logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\") def _sub(match: re.Match) -> str: if match.group(1): return \\\"[p]slashtag global\\\"\",\n \"@slashtag_edit.command(\\\"description\\\") async def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *, description: str ):\",\n \"List[ApplicationOptionChoice]: query = ( \\\"Send the list of choice names and values you\",\n \"tabulate import tabulate from ..abc import MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter,\",\n \"THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\",\n \"check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a message command tag with TagScript.\",\n \"TagConverter, TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand,\",\n \"await command.register() except discord.Forbidden as error: log.error( \\\"Failed to create command {command!r} on\",\n \"since error handler should print it, however info on the command options is\",\n \"the tag description to be? (maximum 100 characters)\\\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError:\",\n \"n in valid_option_types])}\\\", \\\"(select `string` if you don't understand)\\\", ] option_type = await\",\n \"global slash tags.\\\" ) return await ctx.send(message) counter = Counter({tag.name: tag.uses for tag\",\n \"f\\\"✅ (**{self.eval_command}**)\\\" if self.eval_command else \\\"❎\\\" testing_enabled = \\\"✅\\\" if self.testing_enabled else \\\"❎\\\"\",\n \"[This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use TagScript blocks. \\\"\\\"\\\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"add\\\",\",\n \"SlashTag interaction testing cog is already {loaded}.\\\") await self.config.testing_enabled.set(target_state) if target_state: loaded =\",\n \"not CHOICE_RE.match(choice_text): await ctx.send( f\\\"Failed to parse `{choice_text}` to a choice as \\\"\",\n \"ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\\\"slashset\\\"]) async def slashtagset(self, ctx: commands.Context): \\\"\\\"\\\"Manage\",\n \"async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id] if\",\n \"{humanize_list([inline(n) for n in valid_option_types])}\\\", \\\"(select `string` if you don't understand)\\\", ] option_type\",\n \"required = pred.result else: await ctx.send( \\\"This argument was automatically made optional as\",\n \"option.required: added_required = True except asyncio.TimeoutError: await ctx.send(\\\"Adding this argument timed out.\\\", delete_after=15)\",\n \"format_tagscript(cls, tag: SlashTag, limit: int = 60) -> str: title = f\\\"`{tag.type.get_prefix()}{tag.name}` -\",\n \"import asyncio import logging import re import types from collections import Counter from\",\n \"GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context, tag:\",\n \"None, *, timeout: int = 60, ) -> str: if pred is None:\",\n \"@slashtag.command(\\\"list\\\") async def slashtag_list(self, ctx: commands.Context): \\\"\\\"\\\"View stored slash tags.\\\"\\\"\\\" tags = self.guild_tag_cache[ctx.guild.id]\",\n \"choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"message\\\") async def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False),\",\n \"await tag.send_info(ctx) @slashtag.command(\\\"raw\\\") async def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Get a\",\n \"tag_name: str, tagscript: str, *, is_global: bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT,\",\n \"slash commands if it differs from the bot user ID. This only applies\",\n \"cog. \\\"\\\"\\\" target_state = ( true_or_false if true_or_false is not None else not\",\n \"ctx.send(f\\\"Reached max choices ({CHOICE_LIMIT}).\\\") break return choices async def get_option( self, ctx: commands.Context,\",\n \"ctx.send(await tag.delete()) @slashtag_global.command(\\\"raw\\\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await\",\n \"Manually set the application ID for [botname] slash commands if it differs from\",\n \"`[p]slashtag usage` \\\"\\\"\\\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"restore\\\", hidden=True) async def slashtag_restore(self, ctx:\",\n \"= ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id = None if is_global else\",\n \"= None if is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description =\",\n \"or '-'.\\\", \\\"The argument description must be less than or equal to 100\",\n \") text = ( \\\"Looks like I don't have permission to add Slash\",\n \"tag.edit_name(name)) @slashtag_global_edit.command(\\\"description\\\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *, description:\",\n \"distribute, sublicense, and/or sell copies of the Software, and to permit persons to\",\n \"out, not adding additional arguments.\\\") break if pred.result is False: break return options\",\n \"software and associated documentation files (the \\\"Software\\\"), to deal in the Software without\",\n \"key=lambda t: t.name) ] description = \\\"\\\\n\\\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global:\",\n \"SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"message\\\") async def slashtag_message( self,\",\n \"async def get_options( self, ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required =\",\n \"= discord.Embed(title=\\\"Slash Tag Stats\\\", color=await ctx.embed_color()) embeds = [] for usage_data in chunks(counter.most_common(),\",\n \"= False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id =\",\n \"tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a message command tag\",\n \"await self.show_slash_tag_usage(ctx) @slashtag_global.command(\\\"restore\\\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None)\",\n \"name_pred.result name, description = match.group(1), match.group(2) valid_option_types = [ name.lower() for name in\",\n \"TagScript blocks. \\\"\\\"\\\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"add\\\", aliases=[\\\"create\\\", \\\"+\\\"]) async def slashtag_add( self, ctx: commands.Context,\",\n \"shall be included in all copies or substantial portions of the Software. THE\",\n \"slash tag's description.\\\"\\\"\\\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) async def slashtag_edit_arguments(self, ctx: commands.Context,\",\n \"commands.Context): \\\"\\\"\\\"View SlashTags settings.\\\"\\\"\\\" eval_command = f\\\"✅ (**{self.eval_command}**)\\\" if self.eval_command else \\\"❎\\\" testing_enabled\",\n \"i in range(1, 11): try: option = await self.get_option(ctx, added_required=added_required) if not option.required:\",\n \"ctx, \\\"Is this argument required? (Y/n)\\\\n*Keep in mind that if you choose to\",\n \"): options: List[SlashOption] = [] guild_id = None if is_global else ctx.guild.id if\",\n \"following arguments must also be optional.*\\\", pred, ) required = pred.result else: await\",\n \"): \\\"\\\"\\\"Edit a slash tag's TagScript.\\\"\\\"\\\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\\\"name\\\") async def\",\n \"NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,\",\n \"str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx:\",\n \"this invite link and try again: <https://discordapp.com/oauth2/authorize\\\" f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\" ) return await ctx.send(text) except\",\n \") except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding arguments.\\\") else: if pred.result\",\n \") @slashtag_global.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *,\",\n \"not tags: message = ( \\\"This server has no slash tags.\\\" if guild\",\n \"this means, you don't need to worry about it. \\\"\\\"\\\" app_id = id\",\n \"ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a user\",\n \"await ctx.send(await tag.delete()) @slashtag_global.command(\\\"raw\\\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter):\",\n \"its name and value \\\" \\\"weren't seperated by a `:`.\\\", delete_after=15, ) continue\",\n \"await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \\\"\\\"\\\"\",\n \"ctx: commands.Context): \\\"\\\"\\\"Remove the slash eval command.\\\"\\\"\\\" if not self.eval_command: return await ctx.send(\\\"The\",\n \"app_id = id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\\\"Application ID\",\n \"from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu as button_menu\",\n \"link. \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) async def\",\n \"e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) async def\",\n \"async def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\"\",\n \"= await self.send_and_query_response( ctx, \\\"\\\\n\\\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \\\"choices\\\": choices\",\n \"and each choice \\\" \\\"should be seperated by `|`. Example:\\\\n`dog:Doggo|cat:Catto`\\\" ) response =\",\n \"commands.Context): pass @slashtag_global.command(\\\"add\\\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *,\",\n \"..testing.button_menus import menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE =\",\n \"want to delete all slash tags on this server? (Y/n)\\\", pred ) except\",\n \"is hereby granted, free of charge, to any person obtaining a copy of\",\n \"except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding arguments.\\\") else: if pred.result is\",\n \"aliases=[\\\"delete\\\", \\\"-\\\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await\",\n \"await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) async def\",\n \"timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async\",\n \"you like to add arguments to this tag? (Y/n)\\\", pred ) except asyncio.TimeoutError:\",\n \"*, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag.\\\"\\\"\\\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\\\"tagscript\\\") async\",\n \"import menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\")\",\n \"\\\"What should the argument type be?\\\", f\\\"Valid option types: {humanize_list([inline(n) for n in\",\n \"-= len(title) tagscript = tag.tagscript if len(tagscript) > limit - 3: tagscript =\",\n \"match.group(1), match.group(2) valid_option_types = [ name.lower() for name in SlashOptionType.__members__.keys() if not name.startswith(\\\"SUB\\\")\",\n \"timed out, not adding additional arguments.\\\") break if pred.result is False: break return\",\n \"ID set to `{id}`.\\\") @commands.check(dev_check) @slashtagset.command(\\\"addeval\\\") async def slashtagset_addeval(self, ctx: commands.Context): \\\"\\\"\\\"Add a\",\n \"\\\"\\\\n\\\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \\\"choices\\\": choices = await self.get_choices(ctx) option_type\",\n \"== 10: break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you like\",\n \"[]) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await\",\n \"import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu as button_menu from ..utils\",\n \"def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument)\",\n \"tags: return await ctx.send(\\\"There are no global slash tags.\\\") await self.view_slash_tags(ctx, tags, is_global=True)\",\n \"error: log.error( \\\"Failed to create command {command!r} on guild {ctx.guild!r}\\\", exc_info=error ) text\",\n \"OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\",\n \"discord.Forbidden as error: log.error( \\\"Failed to create command {command!r} on guild {ctx.guild!r}\\\", exc_info=error\",\n \"log.error( \\\"Failed to create command {command!r} on guild {ctx.guild!r}\\\", exc_info=error ) text =\",\n \"pass @slashtag_global.command(\\\"add\\\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript:\",\n \"(maximum 100 characters)\\\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await ctx.send(\\\"Tag addition timed\",\n \"): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) @copy_doc(slashtag_pastebin) async\",\n \"self, ctx: commands.Context, *, added_required: bool = False ) -> SlashOption: name_desc =\",\n \") -> SlashOption: name_desc = [ \\\"What should the argument name be and\",\n \"await ctx.send(\\\"Tags deleted.\\\") @commands.is_owner() @slashtag.group(\\\"global\\\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\\\"add\\\")\",\n \"eval command. Only bot owners can use this.\\\", options=[ SlashOption(name=\\\"body\\\", description=\\\"Code body to\",\n \"embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\\\"list\\\") async def slashtag_list(self, ctx: commands.Context): \\\"\\\"\\\"View stored\",\n \"repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc =\",\n \"from the database.\\\"\\\"\\\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"clear\\\", hidden=True) async def slashtag_clear(self, ctx:\",\n \"humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from\",\n \"TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER\",\n \"slash tag arguments. \\\"\\\"\\\" await tag.edit_options(ctx) @slashtag_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) async def slashtag_edit_argument( self, ctx:\",\n \"commands.Context, query: str, pred: MessagePredicate = None, *, timeout: int = 60, )\",\n \"repl += name if name.istitle(): repl = repl.title() return repl def copy_doc(original: Union[commands.Command,\",\n \"if not pred.result: return await ctx.send(\\\"Ok, not deleting slash tags.\\\") guild: discord.Guild =\",\n \"types from collections import Counter from copy import copy from typing import Dict,\",\n \"command options is needed raise tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command,\",\n \"= None, *, timeout: int = 60, ) -> str: if pred is\",\n \"the SlashTag interaction development test cog. \\\"\\\"\\\" target_state = ( true_or_false if true_or_false\",\n \"= discord.Embed( color=0xC9C9C9, title=\\\"SlashTags Settings\\\", description=\\\"\\\\n\\\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\\\"appid\\\") async def slashtagset_appid(self,\",\n \"SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. \\\"\\\"\\\" import asyncio\",\n \"ctx: commands.Context, query: str, pred: MessagePredicate = None, *, timeout: int = 60,\",\n \"menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\\\"list\\\") async def slashtag_list(self, ctx: commands.Context): \\\"\\\"\\\"View\",\n \"you would like to add as choices to \\\" \\\"the tag. Choice names\",\n \"= \\\"loaded\\\" if target_state else \\\"unloaded\\\" return await ctx.send(f\\\"The SlashTag interaction testing cog\",\n \"delete all slash tags on this server? (Y/n)\\\", pred ) except asyncio.TimeoutError: return\",\n \"ctx: commands.Context): \\\"\\\"\\\"Clear all slash tags for this server.\\\"\\\"\\\" pred = MessagePredicate.yes_or_no(ctx) try:\",\n \"ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True)\",\n \"embed = discord.Embed( color=0xC9C9C9, title=\\\"SlashTags Settings\\\", description=\\\"\\\\n\\\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\\\"appid\\\") async def\",\n \"optional.\\\", delete_after=15, ) required = False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices,\",\n \"THE USE OR OTHER DEALINGS IN THE SOFTWARE. \\\"\\\"\\\" import asyncio import logging\",\n \"eval command.\\\"\\\"\\\" if not self.eval_command: return await ctx.send(\\\"The eval command hasn't been registered.\\\")\",\n \"\\\"\\\"\\\" await tag.edit_options(ctx) @slashtag_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) async def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter,\",\n \"GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType from\",\n \"self.get_option(ctx, added_required=added_required) if not option.required: added_required = True except asyncio.TimeoutError: await ctx.send(\\\"Adding this\",\n \"self.eval_command = slasheval.id await ctx.send(\\\"`/eval` has been registered.\\\") @commands.check(dev_check) @slashtagset.command(\\\"rmeval\\\") async def slashtagset_rmeval(self,\",\n \"be?\\\", \\\"The argument name and description should be split by a `:`.\\\", \\\"Example:\",\n \"cog loaded: {testing_enabled}\\\", ] embed = discord.Embed( color=0xC9C9C9, title=\\\"SlashTags Settings\\\", description=\\\"\\\\n\\\".join(description) ) await\",\n \"hasn't been registered.\\\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command =\",\n \"tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context,\",\n \"copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\\\"Tags deleted.\\\") @commands.is_owner() @slashtag.group(\\\"global\\\")\",\n \"interaction testing cog is already {loaded}.\\\") await self.config.testing_enabled.set(target_state) if target_state: loaded = \\\"Loaded\\\"\",\n \"cog is already {loaded}.\\\") await self.config.testing_enabled.set(target_state) if target_state: loaded = \\\"Loaded\\\" self.add_test_cog() else:\",\n \"merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit\",\n \"= MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you like to add another argument?\",\n \"commands.Context, tag_name: str, tagscript: str, *, is_global: bool = False, command_type: ApplicationCommandType =\",\n \"@slashtag_global_edit.command(\\\"name\\\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True),\",\n \"List[SlashOption] = [] guild_id = None if is_global else ctx.guild.id if command_type ==\",\n \"another argument? (Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding\",\n \"description be?\\\", \\\"The argument name and description should be split by a `:`.\\\",\",\n \"commands.Context): \\\"\\\"\\\"Manage SlashTags settings.\\\"\\\"\\\" @slashtagset.command(\\\"settings\\\") async def slashtagset_settings(self, ctx: commands.Context): \\\"\\\"\\\"View SlashTags settings.\\\"\\\"\\\"\",\n \"tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \\\"\\\"\\\" Add a slash tag with a\",\n \"= [ \\\"What should the argument type be?\\\", f\\\"Valid option types: {humanize_list([inline(n) for\",\n \"= await self.bot.wait_for(\\\"message\\\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await\",\n \"\\\"\\\"\\\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"add\\\", aliases=[\\\"create\\\", \\\"+\\\"]) async def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False),\",\n \"tag's raw content.\\\"\\\"\\\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit: int =\",\n \"should the argument type be?\\\", f\\\"Valid option types: {humanize_list([inline(n) for n in valid_option_types])}\\\",\",\n \"await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag( self, ctx: commands.Context, tag_name: str,\",\n \"PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def\",\n \"character limit.\\\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\\\":\\\", 1)) choices.append(choice) if len(choices) >=\",\n \"( \\\"Looks like I don't have permission to add Slash Commands here. Reinvite\",\n \"ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT\",\n \"= ( \\\"Send the list of choice names and values you would like\",\n \"\\\"\\\"\\\" target_state = ( true_or_false if true_or_false is not None else not await\",\n \"async def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if not tags: return await\",\n \"tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"message\\\") @copy_doc(slashtag_message) async def\",\n \"WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT\",\n \"LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF\",\n \"from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from\",\n \"tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag's TagScript.\\\"\\\"\\\" await self.slashtag_edit(ctx,\",\n \"slash tags\\\" e.set_author(name=\\\"Global Slash Tags\\\", icon_url=ctx.me.avatar_url) else: slash_tags = \\\"slash tags\\\" e.set_author(name=\\\"Stored Slash\",\n \"inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from tabulate\",\n \"= f\\\"`{tag.type.get_prefix()}{tag.name}` - \\\" limit -= len(title) tagscript = tag.tagscript if len(tagscript) >\",\n \"import box, humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import\",\n \"argument by name.\\\"\\\"\\\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) async def slashtag_remove(self,\",\n \"= tagscript[:limit] + \\\"...\\\" tagscript = tagscript.replace(\\\"\\\\n\\\", \\\" \\\") return f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\" async def\",\n \"tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a slash tag with TagScript. [Slash tag usage\",\n \"if len(choices) >= CHOICE_LIMIT: await ctx.send(f\\\"Reached max choices ({CHOICE_LIMIT}).\\\") break return choices async\",\n \"redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate from\",\n \"TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE\",\n \"*, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\\\"tagscript\\\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self,\",\n \"you choose to make this argument optional, all following arguments must also be\",\n \"Dict, List, Union import discord from redbot.core import commands from redbot.core.utils.chat_formatting import box,\",\n \"only contain characters \\\" \\\"that are alphanumeric or '_' or '-'.\\\", \\\"The argument\",\n \"charge, to any person obtaining a copy of this software and associated documentation\",\n \"def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original,\",\n \"False ) -> SlashOption: name_desc = [ \\\"What should the argument name be\",\n \"KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\",\n \"commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript,\",\n \"-> List[ApplicationOptionChoice]: query = ( \\\"Send the list of choice names and values\",\n \"ApplicationCommand( self, name=\\\"eval\\\", description=\\\"SlashTags debugging eval command. Only bot owners can use this.\\\",\",\n \"like to add another argument? (Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed\",\n \"options async def send_and_query_response( self, ctx: commands.Context, query: str, pred: MessagePredicate = None,\",\n \"= 60, ) -> str: if pred is None: pred = MessagePredicate.same_context(ctx) ask\",\n \"self.get_choices(ctx) option_type = \\\"STRING\\\" else: choices = [] option_type = SlashOptionType[option_type.upper()] if not\",\n \"in SlashOptionType.__members__.keys() if not name.startswith(\\\"SUB\\\") ] valid_option_types.append(\\\"choices\\\") option_query = [ \\\"What should the\",\n \"<reponame>Myst1c-a/phen-cogs<filename>slashtags/mixins/commands.py<gh_stars>0 \\\"\\\"\\\" MIT License Copyright (c) 2020-present phenom4n4n Permission is hereby granted, free\",\n \"ctx.send(\\\"There are no slash tags on this server.\\\") await self.view_slash_tags(ctx, tags, is_global=False) async\",\n \"@commands.group(aliases=[\\\"slashset\\\"]) async def slashtagset(self, ctx: commands.Context): \\\"\\\"\\\"Manage SlashTags settings.\\\"\\\"\\\" @slashtagset.command(\\\"settings\\\") async def slashtagset_settings(self,\",\n \"message command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx,\",\n \"persons to whom the Software is furnished to do so, subject to the\",\n \"ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\\\"restore\\\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await\",\n \"IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY\",\n \"view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global: bool, ): description =\",\n \"await ctx.send(f\\\"Application ID set to `{id}`.\\\") @commands.check(dev_check) @slashtagset.command(\\\"addeval\\\") async def slashtagset_addeval(self, ctx: commands.Context):\",\n \"\\\"\\\"\\\" Add a message command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\"\",\n \"deleting slash tags.\\\") if not pred.result: return await ctx.send(\\\"Ok, not deleting slash tags.\\\")\",\n \"argument: str ): \\\"\\\"\\\"Edit a single slash tag's argument by name.\\\"\\\"\\\" await tag.edit_single_option(ctx,\",\n \"NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND\",\n \"slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\\\"list\\\") @copy_doc(slashtag_list) async def slashtag_global_list(self,\",\n \"usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) async def slashtag_usage(self, ctx: commands.Context):\",\n \"tags\\\" e.set_author(name=\\\"Stored Slash Tags\\\", icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description)) for index,\",\n \"settings.\\\"\\\"\\\" eval_command = f\\\"✅ (**{self.eval_command}**)\\\" if self.eval_command else \\\"❎\\\" testing_enabled = \\\"✅\\\" if\",\n \"TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def\",\n \"GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag.\\\"\\\"\\\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\\\"tagscript\\\")\",\n \"IN THE SOFTWARE. \\\"\\\"\\\" import asyncio import logging import re import types from\",\n \"in sorted(tags.values(), key=lambda t: t.name) ] description = \\\"\\\\n\\\".join(description) e = discord.Embed(color=await ctx.embed_color())\",\n \"commands.Context): \\\"\\\"\\\"Add a slash eval command for debugging.\\\"\\\"\\\" if self.eval_command: return await ctx.send(\\\"An\",\n \"await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\\\"description\\\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter,\",\n \"= re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\") CHOICE_RE = re.compile(r\\\".{1,100}:.{1,100}\\\") CHOICE_LIMIT = 25 log = logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\") def _sub(match:\",\n \"tag's description.\\\"\\\"\\\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag:\",\n \"logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\") def _sub(match: re.Match) -> str: if match.group(1): return \\\"[p]slashtag global\\\" repl =\",\n \"ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu as button_menu from ..utils import\",\n \"to whom the Software is furnished to do so, subject to the following\",\n \"60, ) -> str: if pred is None: pred = MessagePredicate.same_context(ctx) ask =\",\n \"if not tags: message = ( \\\"This server has no slash tags.\\\" if\",\n \"and can only contain characters \\\" \\\"that are alphanumeric or '_' or '-'.\\\",\",\n \"Slash Tags\\\", icon_url=ctx.me.avatar_url) else: slash_tags = \\\"slash tags\\\" e.set_author(name=\\\"Stored Slash Tags\\\", icon_url=ctx.guild.icon_url) embeds\",\n \"usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag( self, ctx:\",\n \"applies to legacy bots. If you don't know what this means, you don't\",\n \"to add arguments to this tag? (Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query\",\n \"if is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response(\",\n \"in the Software without restriction, including without limitation the rights to use, copy,\",\n \"OTHER DEALINGS IN THE SOFTWARE. \\\"\\\"\\\" import asyncio import logging import re import\",\n \"description=\\\"SlashTags debugging eval command. Only bot owners can use this.\\\", options=[ SlashOption(name=\\\"body\\\", description=\\\"Code\",\n \"self, ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required = False for i\",\n \"set to `{id}`.\\\") @commands.check(dev_check) @slashtagset.command(\\\"addeval\\\") async def slashtagset_addeval(self, ctx: commands.Context): \\\"\\\"\\\"Add a slash\",\n \"TagName(check_global=False), *, link: PastebinConverter, ): \\\"\\\"\\\" Add a slash tag with a Pastebin\",\n \") try: await command.register() except discord.Forbidden as error: log.error( \\\"Failed to create command\",\n \"return f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\" async def view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global:\",\n \"management with TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how\",\n \"\\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) async\",\n \"match = name_pred.result name, description = match.group(1), match.group(2) valid_option_types = [ name.lower() for\",\n \"bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id\",\n \"try: option = await self.get_option(ctx, added_required=added_required) if not option.required: added_required = True except\",\n \") @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) async def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *,\",\n \"ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required = False for i in\",\n \"return message.content async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query = ( \\\"Send\",\n \"if not tags: return await ctx.send(\\\"There are no global slash tags.\\\") await self.view_slash_tags(ctx,\",\n \"eval command hasn't been registered.\\\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear()\",\n \"Exception: log.error(\\\"Failed to create command {command!r} on guild {ctx.guild!r}\\\") # exc info unneeded\",\n \"= [ f\\\"Application ID: **{self.application_id}**\\\", f\\\"Eval command: {eval_command}\\\", f\\\"Test cog loaded: {testing_enabled}\\\", ]\",\n \"self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx:\",\n \"self.send_and_query_response( ctx, \\\"Would you like to add another argument? (Y/n)\\\", pred ) except\",\n \"10): usage_chart = box(tabulate(usage_data, headers=(\\\"Tag\\\", \\\"Uses\\\")), \\\"prolog\\\") embed = e.copy() embed.description = usage_chart\",\n \"pred.result: return await ctx.send(\\\"Ok, not deleting slash tags.\\\") guild: discord.Guild = ctx.guild await\",\n \"tag in tags.copy().values()}) e = discord.Embed(title=\\\"Slash Tag Stats\\\", color=await ctx.embed_color()) embeds = []\",\n \"\\\"slash tags\\\" e.set_author(name=\\\"Stored Slash Tags\\\", icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description)) for\",\n \"ctx: commands.Context, tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"])\",\n \"made optional as the previous one was optional.\\\", delete_after=15, ) required = False\",\n \"tag.send_info(ctx) @slashtag.command(\\\"raw\\\") async def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Get a slash\",\n \"async def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): \\\"\\\"\\\"Edit a\",\n \"await ctx.send(\\\"`/eval` has been deleted.\\\") @slashtagset.command(\\\"testing\\\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool\",\n \"= None): tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not tags: message\",\n \"async def slashtagset_settings(self, ctx: commands.Context): \\\"\\\"\\\"View SlashTags settings.\\\"\\\"\\\" eval_command = f\\\"✅ (**{self.eval_command}**)\\\" if\",\n \"option_type = await self.send_and_query_response( ctx, \\\"\\\\n\\\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \\\"choices\\\":\",\n \"value exceeded the 100 character limit.\\\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\\\":\\\", 1))\",\n \"description = \\\"\\\" if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response(\",\n \"except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding additional arguments.\\\") break if pred.result\",\n \"def slashtag_restore(self, ctx: commands.Context): \\\"\\\"\\\"Restore all slash tags from the database.\\\"\\\"\\\" await self.restore_tags(ctx,\",\n \"try: description = await self.send_and_query_response( ctx, \\\"What should the tag description to be?\",\n \"): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag:\",\n \"as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\") CHOICE_RE =\",\n \"@slashtag_global_edit.command(\\\"description\\\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *, description: str\",\n \"don't have permission to add Slash Commands here. Reinvite me \\\" \\\"with this\",\n \"async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query = ( \\\"Send the list\",\n \"choice as \\\" \\\"its name or value exceeded the 100 character limit.\\\", delete_after=15,\",\n \"timed out.\\\") else: description = \\\"\\\" if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx)\",\n \"name.\\\"\\\"\\\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) async def slashtag_remove(self, ctx: commands.Context,\",\n \"str ): \\\"\\\"\\\"Edit a single slash tag's argument by name.\\\"\\\"\\\" await tag.edit_single_option(ctx, argument)\",\n \"associated documentation files (the \\\"Software\\\"), to deal in the Software without restriction, including\",\n \"return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help\",\n \"\\\"\\\"\\\" Manually set the application ID for [botname] slash commands if it differs\",\n \"async def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \\\"\\\"\\\"\",\n \"BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE\",\n \"self, ctx: commands.Context, tag: GlobalTagConverter, *, description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\\\"arguments\\\",\",\n \"you don't understand)\\\", ] option_type = await self.send_and_query_response( ctx, \\\"\\\\n\\\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), )\",\n \"# await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\\\"list\\\") async def slashtag_list(self, ctx:\",\n \"\\\" name = match.group(0) repl += name if name.istitle(): repl = repl.title() return\",\n \"names and values should be seperated by `:`, and each choice \\\" \\\"should\",\n \"legacy bots. If you don't know what this means, you don't need to\",\n \"understand)\\\", ] option_type = await self.send_and_query_response( ctx, \\\"\\\\n\\\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower()\",\n \"slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a\",\n \"None) @commands.is_owner() @commands.group(aliases=[\\\"slashset\\\"]) async def slashtagset(self, ctx: commands.Context): \\\"\\\"\\\"Manage SlashTags settings.\\\"\\\"\\\" @slashtagset.command(\\\"settings\\\") async\",\n \"raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def get_choices(self, ctx: commands.Context) ->\",\n \"type be?\\\", f\\\"Valid option types: {humanize_list([inline(n) for n in valid_option_types])}\\\", \\\"(select `string` if\",\n \"> limit - 3: tagscript = tagscript[:limit] + \\\"...\\\" tagscript = tagscript.replace(\\\"\\\\n\\\", \\\"\",\n \"self.global_tag_cache if not tags: message = ( \\\"This server has no slash tags.\\\"\",\n \"ID. This only applies to legacy bots. If you don't know what this\",\n \"if match.group(1): return \\\"[p]slashtag global\\\" repl = \\\"global \\\" name = match.group(0) repl\",\n \"obtaining a copy of this software and associated documentation files (the \\\"Software\\\"), to\",\n \"GlobalTagConverter, *, description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) @copy_doc(slashtag_edit_arguments) async def\",\n \"ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\\\"name\\\")\",\n \"break return choices async def get_option( self, ctx: commands.Context, *, added_required: bool =\",\n \"isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override =\",\n \"if not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \\\"Is this argument required?\",\n \"Reinvite me \\\" \\\"with this invite link and try again: <https://discordapp.com/oauth2/authorize\\\" f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\" )\",\n \"= [] guild_id = None if is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT:\",\n \"= [] pages = list(pagify(description)) for index, page in enumerate(pages, 1): embed =\",\n \"\\\"\\\"\\\"Edit a slash tag's TagScript.\\\"\\\"\\\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\\\"name\\\") async def slashtag_edit_name(\",\n \"to create command {command!r} on guild {ctx.guild!r}\\\") # exc info unneeded since error\",\n \"exc_info=error ) text = ( \\\"Looks like I don't have permission to add\",\n \"guild_id = None if is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description\",\n \"\\\"the tag. Choice names and values should be seperated by `:`, and each\",\n \"slashtagset_appid(self, ctx: commands.Context, id: int = None): \\\"\\\"\\\" Manually set the application ID\",\n \"MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \\\"choices\\\": choices = await self.get_choices(ctx) option_type =\",\n \"if isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override\",\n \"including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense,\",\n \"import re import types from collections import Counter from copy import copy from\",\n \"sure you want to delete all slash tags on this server? (Y/n)\\\", pred\",\n \"description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx:\",\n \"names and values you would like to add as choices to \\\" \\\"the\",\n \"to a choice as \\\" \\\"its name or value exceeded the 100 character\",\n \"or substantial portions of the Software. THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT\",\n \"by a `:`.\\\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await ctx.send( f\\\"Failed to\",\n \"@copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\\\"slashset\\\"]) async def\",\n \"TagName(check_global=False) ): \\\"\\\"\\\"Edit a slash tag's name.\\\"\\\"\\\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\\\"description\\\") async def\",\n \"f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\" ) return await ctx.send(text) except Exception: log.error(\\\"Failed to create command {command!r} on\",\n \"): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\\\"tagscript\\\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag:\",\n \"seperated by `|`. Example:\\\\n`dog:Doggo|cat:Catto`\\\" ) response = await self.send_and_query_response(ctx, query) choices = []\",\n \"3: tagscript = tagscript[:limit] + \\\"...\\\" tagscript = tagscript.replace(\\\"\\\\n\\\", \\\" \\\") return f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\"\",\n \"ctx.send(await tag.initialize()) async def get_options( self, ctx: commands.Context, options: List[SlashOption] ) -> List[SlashOption]:\",\n \"{ctx.guild!r}\\\", exc_info=error ) text = ( \\\"Looks like I don't have permission to\",\n \"commands.Context) -> List[ApplicationOptionChoice]: query = ( \\\"Send the list of choice names and\",\n \"ctx: commands.Context, tag: GuildTagConverter): \\\"\\\"\\\" Edit a slash tag's arguments. See [this documentation\",\n \"command_type == ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx, \\\"What should the tag\",\n \"re.Match) -> str: if match.group(1): return \\\"[p]slashtag global\\\" repl = \\\"global \\\" name\",\n \"a slash eval command for debugging.\\\"\\\"\\\" if self.eval_command: return await ctx.send(\\\"An eval command\",\n \"choices = await self.get_choices(ctx) option_type = \\\"STRING\\\" else: choices = [] option_type =\",\n \"*, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a user command tag with TagScript. [Slash\",\n \"await ctx.send(query) try: message = await self.bot.wait_for(\\\"message\\\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask)\",\n \"self.delete_quietly(message) return message.content async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query = (\",\n \"False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id = None\",\n \"ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\") CHOICE_RE = re.compile(r\\\".{1,100}:.{1,100}\\\") CHOICE_LIMIT = 25 log\",\n \"names may not exceed 32 characters and can only contain characters \\\" \\\"that\",\n \"try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None await ctx.send(\\\"`/eval`\",\n \"False: break return options async def send_and_query_response( self, ctx: commands.Context, query: str, pred:\",\n \"added_required = False for i in range(1, 11): try: option = await self.get_option(ctx,\",\n \"choices = [] for choice_text in response.split(\\\"|\\\"): if \\\":\\\" not in choice_text: await\",\n \") @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"user\\\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False),\",\n \"self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\\\"remove\\\", aliases=[\\\"delete\\\",\",\n \"Add a message command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await\",\n \"COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN\",\n \"description=\\\"\\\\n\\\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\\\"appid\\\") async def slashtagset_appid(self, ctx: commands.Context, id: int =\",\n \"and values you would like to add as choices to \\\" \\\"the tag.\",\n \"from ..abc import MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName,\",\n \"link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context, tag:\",\n \"ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE\",\n \"await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit: int = 60) -> str:\",\n \"redbot.core import commands from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from redbot.core.utils.menus import\",\n \"ctx: commands.Context, tag: GuildTagConverter, *, description: str ): \\\"\\\"\\\"Edit a slash tag's description.\\\"\\\"\\\"\",\n \"ctx: commands.Context): \\\"\\\"\\\" See this slash tag usage stats. **Example:** `[p]slashtag usage` \\\"\\\"\\\"\",\n \"\\\" \\\"weren't seperated by a `:`.\\\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await\",\n \"= \\\"STRING\\\" else: choices = [] option_type = SlashOptionType[option_type.upper()] if not added_required: pred\",\n \"\\\"\\\"\\\" See this slash tag usage stats. **Example:** `[p]slashtag usage` \\\"\\\"\\\" await self.show_slash_tag_usage(ctx,\",\n \"permission to add Slash Commands here. Reinvite me \\\" \\\"with this invite link\",\n \"await tag.send_raw_tagscript(ctx) @slashtag_global.command(\\\"list\\\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if\",\n \"(Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding arguments.\\\") else:\",\n \"means, you don't need to worry about it. \\\"\\\"\\\" app_id = id or\",\n \"\\\"...\\\" tagscript = tagscript.replace(\\\"\\\\n\\\", \\\" \\\") return f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\" async def view_slash_tags( self, ctx:\",\n \"a choice as its name and value \\\" \\\"weren't seperated by a `:`.\\\",\",\n \"icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description)) for index, page in enumerate(pages, 1):\",\n \"guild else \\\"There are no global slash tags.\\\" ) return await ctx.send(message) counter\",\n \"def view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global: bool, ): description\",\n \"tag: GuildTagConverter, *, name: TagName(check_global=False) ): \\\"\\\"\\\"Edit a slash tag's name.\\\"\\\"\\\" await ctx.send(await\",\n \"@copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ):\",\n \"debugging eval command. Only bot owners can use this.\\\", options=[ SlashOption(name=\\\"body\\\", description=\\\"Code body\",\n \"slasheval.id await ctx.send(\\\"`/eval` has been registered.\\\") @commands.check(dev_check) @slashtagset.command(\\\"rmeval\\\") async def slashtagset_rmeval(self, ctx: commands.Context):\",\n \"None if is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description = await\",\n \"raise tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize())\",\n \"\\\"\\\"\\\" MIT License Copyright (c) 2020-present phenom4n4n Permission is hereby granted, free of\",\n \"slash tag's raw content.\\\"\\\"\\\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit: int\",\n \"from tabulate import tabulate from ..abc import MixinMeta from ..converters import ( GlobalTagConverter,\",\n \"required? (Y/n)\\\\n*Keep in mind that if you choose to make this argument optional,\",\n \"= id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\\\"Application ID set\",\n \"if command_type == ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx, \\\"What should the\",\n \"def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\\\"raw\\\") @copy_doc(slashtag_raw) async\",\n \"def slashtagset_appid(self, ctx: commands.Context, id: int = None): \\\"\\\"\\\" Manually set the application\",\n \"the following conditions: The above copyright notice and this permission notice shall be\",\n \"@copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ):\",\n \"it. \\\"\\\"\\\" app_id = id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await\",\n \"[] option_type = SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx,\",\n \"settings.\\\"\\\"\\\" @slashtagset.command(\\\"settings\\\") async def slashtagset_settings(self, ctx: commands.Context): \\\"\\\"\\\"View SlashTags settings.\\\"\\\"\\\" eval_command = f\\\"✅\",\n \"= True except asyncio.TimeoutError: await ctx.send(\\\"Adding this argument timed out.\\\", delete_after=15) break options.append(option)\",\n \"asyncio.TimeoutError: return await ctx.send(\\\"Timed out, not deleting slash tags.\\\") if not pred.result: return\",\n \"valid_option_types = [ name.lower() for name in SlashOptionType.__members__.keys() if not name.startswith(\\\"SUB\\\") ] valid_option_types.append(\\\"choices\\\")\",\n \"\\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"user\\\") async def\",\n \"*, tag: TagConverter): \\\"\\\"\\\"Get info about a slash tag that is stored on\",\n \"await tag.edit_options(ctx) @slashtag_global_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter,\",\n \"GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\\\"list\\\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache\",\n \"\\\"❎\\\" testing_enabled = \\\"✅\\\" if self.testing_enabled else \\\"❎\\\" description = [ f\\\"Application ID:\",\n \"Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub,\",\n \"name_pred) match = name_pred.result name, description = match.group(1), match.group(2) valid_option_types = [ name.lower()\",\n \"commands.Context): \\\"\\\"\\\"Restore all slash tags from the database.\\\"\\\"\\\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"clear\\\",\",\n \"values should be seperated by `:`, and each choice \\\" \\\"should be seperated\",\n \"slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *, description: str ): await ctx.send(await tag.edit_description(description))\",\n \"tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\\\"Tags deleted.\\\") @commands.is_owner() @slashtag.group(\\\"global\\\") @copy_doc(slashtag) async def slashtag_global(self,\",\n \"await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"restore\\\", hidden=True) async def slashtag_restore(self, ctx: commands.Context): \\\"\\\"\\\"Restore all\",\n \"name_desc = [ \\\"What should the argument name be and description be?\\\", \\\"The\",\n \"return overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\\\"st\\\"]) async def slashtag(self, ctx: commands.Context):\",\n \"optional as the previous one was optional.\\\", delete_after=15, ) required = False return\",\n \"str, *, is_global: bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption]\",\n \"CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\",\n \"to parse `{choice_text}` to a choice as its name and value \\\" \\\"weren't\",\n \"(Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding additional arguments.\\\")\",\n \"included in all copies or substantial portions of the Software. THE SOFTWARE IS\",\n \"await self.get_option(ctx, added_required=added_required) if not option.required: added_required = True except asyncio.TimeoutError: await ctx.send(\\\"Adding\",\n \"@commands.group(aliases=[\\\"st\\\"]) async def slashtag(self, ctx: commands.Context): \\\"\\\"\\\" Slash Tag management with TagScript. These\",\n \"*, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a slash tag with TagScript. [Slash tag\",\n \"GuildTagConverter, argument: str ): \\\"\\\"\\\"Edit a single slash tag's argument by name.\\\"\\\"\\\" await\",\n \"for tag in tags.copy().values()}) e = discord.Embed(title=\\\"Slash Tag Stats\\\", color=await ctx.embed_color()) embeds =\",\n \"ctx, \\\"What should the tag description to be? (maximum 100 characters)\\\", pred=MessagePredicate.length_less(101, ctx),\",\n \"= slasheval.id await ctx.send(\\\"`/eval` has been registered.\\\") @commands.check(dev_check) @slashtagset.command(\\\"rmeval\\\") async def slashtagset_rmeval(self, ctx:\",\n \"test cog. \\\"\\\"\\\" target_state = ( true_or_false if true_or_false is not None else\",\n \"(**{self.eval_command}**)\\\" if self.eval_command else \\\"❎\\\" testing_enabled = \\\"✅\\\" if self.testing_enabled else \\\"❎\\\" description\",\n \"return await ctx.send(\\\"Ok, not deleting slash tags.\\\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id,\",\n \"Slash Tag management with TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation\",\n \"use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,\",\n \"ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a slash tag\",\n \"content.\\\"\\\"\\\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit: int = 60) ->\",\n \"limit: int = 60) -> str: title = f\\\"`{tag.type.get_prefix()}{tag.name}` - \\\" limit -=\",\n \"\\\"This server has no slash tags.\\\" if guild else \\\"There are no global\",\n \"async def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Delete a slash tag.\\\"\\\"\\\" await\",\n \"aliases=[\\\"option\\\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ):\",\n \"ctx.send(embed=embed) @slashtagset.command(\\\"appid\\\") async def slashtagset_appid(self, ctx: commands.Context, id: int = None): \\\"\\\"\\\" Manually\",\n \"await ctx.send(\\\"Adding this argument timed out.\\\", delete_after=15) break options.append(option) if i == 10:\",\n \"redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates\",\n \"optional, all following arguments must also be optional.*\\\", pred, ) required = pred.result\",\n \"name be and description be?\\\", \\\"The argument name and description should be split\",\n \"NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR\",\n \"[Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag(\",\n \"Dict[int, SlashTag], *, is_global: bool, ): description = [ self.format_tagscript(tag) for tag in\",\n \"commands.Context): \\\"\\\"\\\" See this slash tag usage stats. **Example:** `[p]slashtag usage` \\\"\\\"\\\" await\",\n \"'-'.\\\", \\\"The argument description must be less than or equal to 100 characters.*\\\",\",\n \"name or value exceeded the 100 character limit.\\\", delete_after=15, ) continue choice =\",\n \"async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\\\"slashset\\\"]) async def slashtagset(self,\",\n \"embeds, DEFAULT_CONTROLS) @slashtag.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) async def slashtag_usage(self, ctx: commands.Context): \\\"\\\"\\\" See this slash\",\n \"await self.send_and_query_response( ctx, \\\"Is this argument required? (Y/n)\\\\n*Keep in mind that if you\",\n \"description: str ): \\\"\\\"\\\"Edit a slash tag's description.\\\"\\\"\\\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"])\",\n \"def slashtagset(self, ctx: commands.Context): \\\"\\\"\\\"Manage SlashTags settings.\\\"\\\"\\\" @slashtagset.command(\\\"settings\\\") async def slashtagset_settings(self, ctx: commands.Context):\",\n \"the argument type be?\\\", f\\\"Valid option types: {humanize_list([inline(n) for n in valid_option_types])}\\\", \\\"(select\",\n \"in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\\\"Tags deleted.\\\") @commands.is_owner()\",\n \"asyncio.TimeoutError: await ctx.send(\\\"Adding this argument timed out.\\\", delete_after=15) break options.append(option) if i ==\",\n \"License Copyright (c) 2020-present phenom4n4n Permission is hereby granted, free of charge, to\",\n \") @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"message\\\") async def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *,\",\n \"for n in valid_option_types])}\\\", \\\"(select `string` if you don't understand)\\\", ] option_type =\",\n \"\\\"Software\\\"), to deal in the Software without restriction, including without limitation the rights\",\n \") return await ctx.send(text) except Exception: log.error(\\\"Failed to create command {command!r} on guild\",\n \"deal in the Software without restriction, including without limitation the rights to use,\",\n \"= [ name.lower() for name in SlashOptionType.__members__.keys() if not name.startswith(\\\"SUB\\\") ] valid_option_types.append(\\\"choices\\\") option_query\",\n \"tag: GuildTagConverter): \\\"\\\"\\\" Edit a slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for\",\n \"\\\"\\\"\\\"Edit a slash tag.\\\"\\\"\\\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\\\"tagscript\\\") async def slashtag_edit_tagscript( self, ctx:\",\n \"ApplicationOptionChoice(*choice_text.split(\\\":\\\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\\\"Reached max choices ({CHOICE_LIMIT}).\\\") break\",\n \"to `{id}`.\\\") @commands.check(dev_check) @slashtagset.command(\\\"addeval\\\") async def slashtagset_addeval(self, ctx: commands.Context): \\\"\\\"\\\"Add a slash eval\",\n \"choice as its name and value \\\" \\\"weren't seperated by a `:`.\\\", delete_after=15,\",\n \") await ctx.send(await tag.initialize()) async def get_options( self, ctx: commands.Context, options: List[SlashOption] )\",\n \"AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE\",\n \"if self.eval_command else \\\"❎\\\" testing_enabled = \\\"✅\\\" if self.testing_enabled else \\\"❎\\\" description =\",\n \"discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \\\"global slash tags\\\" e.set_author(name=\\\"Global Slash Tags\\\", icon_url=ctx.me.avatar_url)\",\n \"embed.description = page embed.set_footer(text=f\\\"{index}/{len(pages)} | {len(tags)} {slash_tags}\\\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS)\",\n \"\\\"that are alphanumeric or '_' or '-'.\\\", \\\"The argument description must be less\",\n \"command: {eval_command}\\\", f\\\"Test cog loaded: {testing_enabled}\\\", ] embed = discord.Embed( color=0xC9C9C9, title=\\\"SlashTags Settings\\\",\",\n \"TagScriptConverter, ): \\\"\\\"\\\" Add a slash tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html)\",\n \"= \\\"\\\" if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx,\",\n \"not deleting slash tags.\\\") if not pred.result: return await ctx.send(\\\"Ok, not deleting slash\",\n \"guild {ctx.guild!r}\\\", exc_info=error ) text = ( \\\"Looks like I don't have permission\",\n \"query: str, pred: MessagePredicate = None, *, timeout: int = 60, ) ->\",\n \"await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\\\"name\\\") async def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter,\",\n \"def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original, commands.Command) else original.__doc__ doc\",\n \"self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\\\"There are no slash tags on this\",\n \"@commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"message\\\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *,\",\n \"] option_type = await self.send_and_query_response( ctx, \\\"\\\\n\\\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() ==\",\n \"await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None await ctx.send(\\\"`/eval` has\",\n \"CHOICE_RE = re.compile(r\\\".{1,100}:.{1,100}\\\") CHOICE_LIMIT = 25 log = logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\") def _sub(match: re.Match) ->\",\n \"overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\\\"st\\\"]) async def slashtag(self, ctx: commands.Context): \\\"\\\"\\\"\",\n \"name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try: await command.register() except discord.Forbidden as error:\",\n \"TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\\\"description\\\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context,\",\n \"tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"user\\\")\",\n \"is_global=False) async def create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript: str, *, is_global:\",\n \") return await ctx.send(message) counter = Counter({tag.name: tag.uses for tag in tags.copy().values()}) e\",\n \"tag.edit_options(ctx) @slashtag_global_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument:\",\n \"bots. If you don't know what this means, you don't need to worry\",\n \"repl = \\\"global \\\" name = match.group(0) repl += name if name.istitle(): repl\",\n \"@commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"message\\\") async def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript:\",\n \"less than or equal to 100 characters.*\\\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await\",\n \"to add Slash Commands here. Reinvite me \\\" \\\"with this invite link and\",\n \"that if you choose to make this argument optional, all following arguments must\",\n \"pred.result else: await ctx.send( \\\"This argument was automatically made optional as the previous\",\n \"aliases=[\\\"delete\\\", \\\"-\\\"]) async def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Delete a slash\",\n \"so, subject to the following conditions: The above copyright notice and this permission\",\n \"100 characters)\\\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await ctx.send(\\\"Tag addition timed out.\\\")\",\n \"tag.uses for tag in tags.copy().values()}) e = discord.Embed(title=\\\"Slash Tag Stats\\\", color=await ctx.embed_color()) embeds\",\n \"added_required: bool = False ) -> SlashOption: name_desc = [ \\\"What should the\",\n \"\\\" \\\") return f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\" async def view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag],\",\n \"ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\\\"tagscript\\\") @copy_doc(slashtag_edit_tagscript)\",\n \"\\\"\\\"\\\"Restore all slash tags from the database.\\\"\\\"\\\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"clear\\\", hidden=True)\",\n \"await ctx.send(\\\"An eval command is already registered.\\\") slasheval = ApplicationCommand( self, name=\\\"eval\\\", description=\\\"SlashTags\",\n \"import Counter from copy import copy from typing import Dict, List, Union import\",\n \"each choice \\\" \\\"should be seperated by `|`. Example:\\\\n`dog:Doggo|cat:Catto`\\\" ) response = await\",\n \"] embed = discord.Embed( color=0xC9C9C9, title=\\\"SlashTags Settings\\\", description=\\\"\\\\n\\\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\\\"appid\\\") async\",\n \"Counter from copy import copy from typing import Dict, List, Union import discord\",\n \"slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\\\"slashset\\\"]) async def slashtagset(self, ctx: commands.Context):\",\n \"characters)\\\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await ctx.send(\\\"Tag addition timed out.\\\") else:\",\n \"commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\\\"edit\\\",\",\n \"if you choose to make this argument optional, all following arguments must also\",\n \"ctx: commands.Context, *, added_required: bool = False ) -> SlashOption: name_desc = [\",\n \"= pred.result else: await ctx.send( \\\"This argument was automatically made optional as the\",\n \"has no slash tags.\\\" if guild else \\\"There are no global slash tags.\\\"\",\n \"try: await self.send_and_query_response( ctx, \\\"Are you sure you want to delete all slash\",\n \"if you don't understand)\\\", ] option_type = await self.send_and_query_response( ctx, \\\"\\\\n\\\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx),\",\n \"@slashtag_edit.command(\\\"tagscript\\\") async def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ):\",\n \"@copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *, description: str ):\",\n \"async def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await\",\n \"from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http\",\n \"no global slash tags.\\\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) @copy_doc(slashtag_usage) async def\",\n \"usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"pastebin\\\",\",\n \"on guild {ctx.guild!r}\\\") # exc info unneeded since error handler should print it,\",\n \"to 100 characters.*\\\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \\\"\\\\n\\\".join(name_desc), name_pred) match\",\n \"is self.testing_enabled: loaded = \\\"loaded\\\" if target_state else \\\"unloaded\\\" return await ctx.send(f\\\"The SlashTag\",\n \"slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash\",\n \"f\\\"Application ID: **{self.application_id}**\\\", f\\\"Eval command: {eval_command}\\\", f\\\"Test cog loaded: {testing_enabled}\\\", ] embed =\",\n \"discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None await ctx.send(\\\"`/eval` has been deleted.\\\") @slashtagset.command(\\\"testing\\\")\",\n \"ctx.send(\\\"Tags deleted.\\\") @commands.is_owner() @slashtag.group(\\\"global\\\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\\\"add\\\") @copy_doc(slashtag_add)\",\n \"menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) async def slashtag_usage(self, ctx: commands.Context): \\\"\\\"\\\" See this\",\n \"to parse `{choice_text}` to a choice as \\\" \\\"its name or value exceeded\",\n \"\\\"Are you sure you want to delete all slash tags on this server?\",\n \"self.global_tag_cache if not tags: return await ctx.send(\\\"There are no global slash tags.\\\") await\",\n \"not pred.result: return await ctx.send(\\\"Ok, not deleting slash tags.\\\") guild: discord.Guild = ctx.guild\",\n \"may not exceed 32 characters and can only contain characters \\\" \\\"that are\",\n \"arguments to this tag? (Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed out,\",\n \"conditions: The above copyright notice and this permission notice shall be included in\",\n \"THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO\",\n \"tag.delete()) @slashtag_global.command(\\\"raw\\\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx)\",\n \"*, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a message command tag with TagScript. [Slash\",\n \"option_type.lower() == \\\"choices\\\": choices = await self.get_choices(ctx) option_type = \\\"STRING\\\" else: choices =\",\n \"async def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \\\"\\\"\\\"Get info about a slash\",\n \"tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag's TagScript.\\\"\\\"\\\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\\\"name\\\")\",\n \"is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx,\",\n \"None await ctx.send(\\\"`/eval` has been deleted.\\\") @slashtagset.command(\\\"testing\\\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false:\",\n \"pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding additional arguments.\\\") break\",\n \"ctx.send(\\\"There are no global slash tags.\\\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) @copy_doc(slashtag_usage)\",\n \"[] guild_id = None if is_global else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try:\",\n \"should be seperated by `:`, and each choice \\\" \\\"should be seperated by\",\n \"ctx: commands.Context): tags = self.global_tag_cache if not tags: return await ctx.send(\\\"There are no\",\n \"name in SlashOptionType.__members__.keys() if not name.startswith(\\\"SUB\\\") ] valid_option_types.append(\\\"choices\\\") option_query = [ \\\"What should\",\n \"alphanumeric or '_' or '-'.\\\", \\\"The argument description must be less than or\",\n \"slash tags.\\\") if not pred.result: return await ctx.send(\\\"Ok, not deleting slash tags.\\\") guild:\",\n \"ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\\\"tagscript\\\") async def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript:\",\n \"\\\"\\\\n\\\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \\\"global slash tags\\\" e.set_author(name=\\\"Global\",\n \"slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name,\",\n \"*, added_required: bool = False ) -> SlashOption: name_desc = [ \\\"What should\",\n \"return await ctx.send(f\\\"The SlashTag interaction testing cog is already {loaded}.\\\") await self.config.testing_enabled.set(target_state) if\",\n \"FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR\",\n \"not tags: return await ctx.send(\\\"There are no global slash tags.\\\") await self.view_slash_tags(ctx, tags,\",\n \"for name in SlashOptionType.__members__.keys() if not name.startswith(\\\"SUB\\\") ] valid_option_types.append(\\\"choices\\\") option_query = [ \\\"What\",\n \"@slashtag_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) async def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ):\",\n \"tagscript=tagscript) @slashtag_global_edit.command(\\\"name\\\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *, name:\",\n \"if \\\":\\\" not in choice_text: await ctx.send( f\\\"Failed to parse `{choice_text}` to a\",\n \"slashtag_clear(self, ctx: commands.Context): \\\"\\\"\\\"Clear all slash tags for this server.\\\"\\\"\\\" pred = MessagePredicate.yes_or_no(ctx)\",\n \"def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\\\"restore\\\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx:\",\n \"slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument(\",\n \"e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \\\"global slash tags\\\" e.set_author(name=\\\"Global Slash\",\n \"delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\\\":\\\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await\",\n \"e.set_author(name=\\\"Stored Slash Tags\\\", icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description)) for index, page\",\n \"ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self,\",\n \"commands.Context, tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) @copy_doc(slashtag_remove)\",\n \"unneeded since error handler should print it, however info on the command options\",\n \"str ): \\\"\\\"\\\"Edit a slash tag's description.\\\"\\\"\\\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) async\",\n \"): \\\"\\\"\\\"Edit a slash tag.\\\"\\\"\\\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\\\"tagscript\\\") async def slashtag_edit_tagscript( self,\",\n \"True: await self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type,\",\n \"pass await self.config.eval_command.clear() self.eval_command = None await ctx.send(\\\"`/eval` has been deleted.\\\") @slashtagset.command(\\\"testing\\\") async\",\n \"\\\"with this invite link and try again: <https://discordapp.com/oauth2/authorize\\\" f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\" ) return await ctx.send(text)\",\n \"a user command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag(\",\n \"GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) @copy_doc(slashtag_remove) async def\",\n \"or self.bot.user.id await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\\\"Application ID set to `{id}`.\\\")\",\n \"if pred.result is True: await self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name, description=description,\",\n \"slash tags from the database.\\\"\\\"\\\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"clear\\\", hidden=True) async def\",\n \"embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\\\"list\\\") async def slashtag_list(self,\",\n \"= ( \\\"This server has no slash tags.\\\" if guild else \\\"There are\",\n \"id: int = None): \\\"\\\"\\\" Manually set the application ID for [botname] slash\",\n \"choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\\\"Reached max choices ({CHOICE_LIMIT}).\\\") break return choices\",\n \"tags.\\\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context):\",\n \"else: choices = [] option_type = SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx)\",\n \"\\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag( self, ctx: commands.Context, tag_name:\",\n \"): \\\"\\\"\\\"Edit a slash tag's name.\\\"\\\"\\\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\\\"description\\\") async def slashtag_edit_description(\",\n \") continue if not CHOICE_RE.match(choice_text): await ctx.send( f\\\"Failed to parse `{choice_text}` to a\",\n \"slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \\\"\\\"\\\" Edit a slash tag's arguments. See [this\",\n \"aliases=[\\\"e\\\"], invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter\",\n \"in enumerate(pages, 1): embed = e.copy() embed.description = page embed.set_footer(text=f\\\"{index}/{len(pages)} | {len(tags)} {slash_tags}\\\")\",\n \"testing cog is already {loaded}.\\\") await self.config.testing_enabled.set(target_state) if target_state: loaded = \\\"Loaded\\\" self.add_test_cog()\",\n \"..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http import\",\n \"= None): \\\"\\\"\\\" Manually set the application ID for [botname] slash commands if\",\n \"LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.\",\n \"stored slash tags.\\\"\\\"\\\" tags = self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\\\"There are\",\n \"{loaded}.\\\") await self.config.testing_enabled.set(target_state) if target_state: loaded = \\\"Loaded\\\" self.add_test_cog() else: loaded = \\\"Unloaded\\\"\",\n \"SlashTag, limit: int = 60) -> str: title = f\\\"`{tag.type.get_prefix()}{tag.name}` - \\\" limit\",\n \"slash_tags = \\\"global slash tags\\\" e.set_author(name=\\\"Global Slash Tags\\\", icon_url=ctx.me.avatar_url) else: slash_tags = \\\"slash\",\n \"*, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\\\"list\\\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx: commands.Context): tags\",\n \"else \\\"There are no global slash tags.\\\" ) return await ctx.send(message) counter =\",\n \"*, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True)\",\n \"PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT\",\n \"ctx: commands.Context): \\\"\\\"\\\"View stored slash tags.\\\"\\\"\\\" tags = self.guild_tag_cache[ctx.guild.id] if not tags: return\",\n \"tags.\\\") if not pred.result: return await ctx.send(\\\"Ok, not deleting slash tags.\\\") guild: discord.Guild\",\n \"\\\"Uses\\\")), \\\"prolog\\\") embed = e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS)\",\n \"ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\\\"tagscript\\\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *,\",\n \"TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use TagScript blocks. \\\"\\\"\\\" @commands.mod_or_permissions(manage_guild=True)\",\n \"the Software is furnished to do so, subject to the following conditions: The\",\n \"argument? (Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding additional\",\n \"tagscript: str, *, is_global: bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options:\",\n \"if pred is None: pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message\",\n \"IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING\",\n \"DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate from ..abc import\",\n \"color=await ctx.embed_color()) embeds = [] for usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data,\",\n \"return await ctx.send(text) except Exception: log.error(\\\"Failed to create command {command!r} on guild {ctx.guild!r}\\\")\",\n \"has been deleted.\\\") @slashtagset.command(\\\"testing\\\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None):\",\n \"A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT\",\n \"60) -> str: title = f\\\"`{tag.type.get_prefix()}{tag.name}` - \\\" limit -= len(title) tagscript =\",\n \"decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original, commands.Command) else original.__doc__ doc =\",\n \"title = f\\\"`{tag.type.get_prefix()}{tag.name}` - \\\" limit -= len(title) tagscript = tag.tagscript if len(tagscript)\",\n \"async def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await\",\n \"tabulate from ..abc import MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter,\",\n \"GuildTagConverter): \\\"\\\"\\\" Edit a slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more\",\n \"command.register() except discord.Forbidden as error: log.error( \\\"Failed to create command {command!r} on guild\",\n \"commands if it differs from the bot user ID. This only applies to\",\n \"ctx: commands.Context, true_or_false: bool = None): \\\"\\\"\\\" Load or unload the SlashTag interaction\",\n \"page in enumerate(pages, 1): embed = e.copy() embed.description = page embed.set_footer(text=f\\\"{index}/{len(pages)} | {len(tags)}\",\n \"GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\\\"name\\\") @copy_doc(slashtag_edit_name) async def\",\n \"by name.\\\"\\\"\\\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) async def slashtag_remove(self, ctx:\",\n \"ctx.send(text) except Exception: log.error(\\\"Failed to create command {command!r} on guild {ctx.guild!r}\\\") # exc\",\n \"characters.*\\\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \\\"\\\\n\\\".join(name_desc), name_pred) match = name_pred.result\",\n \"self.eval_command: return await ctx.send(\\\"The eval command hasn't been registered.\\\") try: await self.http.remove_slash_command(self.eval_command) except\",\n \"[] for usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\\\"Tag\\\", \\\"Uses\\\")), \\\"prolog\\\") embed\",\n \"re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\") CHOICE_RE = re.compile(r\\\".{1,100}:.{1,100}\\\") CHOICE_LIMIT = 25 log = logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\") def _sub(match: re.Match)\",\n \"tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\\\"Tags deleted.\\\")\",\n \"def slashtagset_settings(self, ctx: commands.Context): \\\"\\\"\\\"View SlashTags settings.\\\"\\\"\\\" eval_command = f\\\"✅ (**{self.eval_command}**)\\\" if self.eval_command\",\n \"@slashtag.command(\\\"user\\\") async def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter,\",\n \"MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message = await self.bot.wait_for(\\\"message\\\", check=pred, timeout=timeout) except\",\n \"): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"message\\\") @copy_doc(slashtag_message) async def slashtag_global_message( self,\",\n \"async def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await\",\n \"len(choices) >= CHOICE_LIMIT: await ctx.send(f\\\"Reached max choices ({CHOICE_LIMIT}).\\\") break return choices async def\",\n \"OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR\",\n \"make this argument optional, all following arguments must also be optional.*\\\", pred, )\",\n \"to the following conditions: The above copyright notice and this permission notice shall\",\n \"aliases=[\\\"options\\\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"])\",\n \"tag.\\\"\\\"\\\" await ctx.send(await tag.delete()) @slashtag.command(\\\"info\\\") async def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter):\",\n \"= await self.get_option(ctx, added_required=added_required) if not option.required: added_required = True except asyncio.TimeoutError: await\",\n \"Software, and to permit persons to whom the Software is furnished to do\",\n \"Add a user command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await\",\n \"slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(\",\n \"= \\\"slash tags\\\" e.set_author(name=\\\"Stored Slash Tags\\\", icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description))\",\n \"try: await self.send_and_query_response( ctx, \\\"Would you like to add arguments to this tag?\",\n \"break if pred.result is False: break return options async def send_and_query_response( self, ctx:\",\n \"@slashtag_global.command(\\\"add\\\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter,\",\n \"@slashtag_global.command(\\\"restore\\\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\\\"slashset\\\"])\",\n \"\\\"choices\\\": choices = await self.get_choices(ctx) option_type = \\\"STRING\\\" else: choices = [] option_type\",\n \"is_global=True) @slashtag_global.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\\\"restore\\\", hidden=True)\",\n \"ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\\\"description\\\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *,\",\n \"commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag.\\\"\\\"\\\" await ctx.send(await\",\n \"ctx.send(\\\"Query timed out, not adding additional arguments.\\\") break if pred.result is False: break\",\n \"*, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag's TagScript.\\\"\\\"\\\" await self.slashtag_edit(ctx, tag, tagscript=tagscript)\",\n \"@copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\\\"restore\\\", hidden=True) @copy_doc(slashtag_restore) async def\",\n \") await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\\\"`/eval` has been registered.\\\")\",\n \"\\\":\\\" not in choice_text: await ctx.send( f\\\"Failed to parse `{choice_text}` to a choice\",\n \"is already {loaded}.\\\") await self.config.testing_enabled.set(target_state) if target_state: loaded = \\\"Loaded\\\" self.add_test_cog() else: loaded\",\n \"await self.config.eval_command.clear() self.eval_command = None await ctx.send(\\\"`/eval` has been deleted.\\\") @slashtagset.command(\\\"testing\\\") async def\",\n \"These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use TagScript\",\n \"MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\",\n \"self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def get_choices(self, ctx: commands.Context)\",\n \"'_' or '-'.\\\", \\\"The argument description must be less than or equal to\",\n \"IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED\",\n \"commands.Context): \\\"\\\"\\\"Clear all slash tags for this server.\\\"\\\"\\\" pred = MessagePredicate.yes_or_no(ctx) try: await\",\n \"tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag: SlashTag, limit: int = 60) -> str: title\",\n \"await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"user\\\") @copy_doc(slashtag_user) async def\",\n \"and value \\\" \\\"weren't seperated by a `:`.\\\", delete_after=15, ) continue if not\",\n \"\\\" \\\"should be seperated by `|`. Example:\\\\n`dog:Doggo|cat:Catto`\\\" ) response = await self.send_and_query_response(ctx, query)\",\n \"link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) @copy_doc(slashtag_edit) async\",\n \"ctx.send( f\\\"Failed to parse `{choice_text}` to a choice as its name and value\",\n \"check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a user command tag with TagScript.\",\n \"server has no slash tags.\\\" if guild else \\\"There are no global slash\",\n \"self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript,\",\n \"i == 10: break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you\",\n \"self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\\\"name\\\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter,\",\n \"self.testing_enabled: loaded = \\\"loaded\\\" if target_state else \\\"unloaded\\\" return await ctx.send(f\\\"The SlashTag interaction\",\n \"server.\\\"\\\"\\\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Are you sure you want\",\n \"return await ctx.send(\\\"Timed out, not deleting slash tags.\\\") if not pred.result: return await\",\n \"aliases=[\\\"stats\\\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\\\"restore\\\", hidden=True) @copy_doc(slashtag_restore) async\",\n \"in tags.copy().values()}) e = discord.Embed(title=\\\"Slash Tag Stats\\\", color=await ctx.embed_color()) embeds = [] for\",\n \"self.eval_command: return await ctx.send(\\\"An eval command is already registered.\\\") slasheval = ApplicationCommand( self,\",\n \"embed = e.copy() embed.description = page embed.set_footer(text=f\\\"{index}/{len(pages)} | {len(tags)} {slash_tags}\\\") embeds.append(embed) # await\",\n \"options) command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try: await\",\n \"not exceed 32 characters and can only contain characters \\\" \\\"that are alphanumeric\",\n \"= app_id await ctx.send(f\\\"Application ID set to `{id}`.\\\") @commands.check(dev_check) @slashtagset.command(\\\"addeval\\\") async def slashtagset_addeval(self,\",\n \"CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR\",\n \"been registered.\\\") @commands.check(dev_check) @slashtagset.command(\\\"rmeval\\\") async def slashtagset_rmeval(self, ctx: commands.Context): \\\"\\\"\\\"Remove the slash eval\",\n \"added_required=added_required) if not option.required: added_required = True except asyncio.TimeoutError: await ctx.send(\\\"Adding this argument\",\n \"again: <https://discordapp.com/oauth2/authorize\\\" f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\" ) return await ctx.send(text) except Exception: log.error(\\\"Failed to create command\",\n \"a choice as \\\" \\\"its name or value exceeded the 100 character limit.\\\",\",\n \"person obtaining a copy of this software and associated documentation files (the \\\"Software\\\"),\",\n \"async def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Get a slash tag's raw\",\n \"if is_global: slash_tags = \\\"global slash tags\\\" e.set_author(name=\\\"Global Slash Tags\\\", icon_url=ctx.me.avatar_url) else: slash_tags\",\n \"await self.bot.wait_for(\\\"message\\\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message)\",\n \"self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded = \\\"loaded\\\" if target_state else \\\"unloaded\\\"\",\n \"repl = repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]):\",\n \"button_menu(ctx, embeds) @slashtag.command(\\\"list\\\") async def slashtag_list(self, ctx: commands.Context): \\\"\\\"\\\"View stored slash tags.\\\"\\\"\\\" tags\",\n \"commands.Context, *, tag: TagConverter): \\\"\\\"\\\"Get info about a slash tag that is stored\",\n \"await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) @copy_doc(slashtag_pastebin) async def\",\n \"server.\\\") await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild =\",\n \"tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\\\"description\\\") @copy_doc(slashtag_edit_description) async def\",\n \"not None else not await self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded =\",\n \"is_global: bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = []\",\n \"= await self.send_and_query_response(ctx, query) choices = [] for choice_text in response.split(\\\"|\\\"): if \\\":\\\"\",\n \"usage` \\\"\\\"\\\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"restore\\\", hidden=True) async def slashtag_restore(self, ctx: commands.Context):\",\n \"only applies to legacy bots. If you don't know what this means, you\",\n \"asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def get_choices(self,\",\n \"@slashtagset.command(\\\"settings\\\") async def slashtagset_settings(self, ctx: commands.Context): \\\"\\\"\\\"View SlashTags settings.\\\"\\\"\\\" eval_command = f\\\"✅ (**{self.eval_command}**)\\\"\",\n \"in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED\",\n \"TagConverter): \\\"\\\"\\\"Get info about a slash tag that is stored on this server.\\\"\\\"\\\"\",\n \"tag, tagscript=tagscript) @slashtag_edit.command(\\\"name\\\") async def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *, name:\",\n \"for this server.\\\"\\\"\\\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Are you sure\",\n \"command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) async def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False),\",\n \"a slash tag that is stored on this server.\\\"\\\"\\\" await tag.send_info(ctx) @slashtag.command(\\\"raw\\\") async\",\n \"name = match.group(0) repl += name if name.istitle(): repl = repl.title() return repl\",\n \"modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to\",\n \"def slashtag_clear(self, ctx: commands.Context): \\\"\\\"\\\"Clear all slash tags for this server.\\\"\\\"\\\" pred =\",\n \"commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Get a slash tag's raw content.\\\"\\\"\\\" await tag.send_raw_tagscript(ctx) @classmethod\",\n \"out.\\\", delete_after=15) break options.append(option) if i == 10: break pred = MessagePredicate.yes_or_no(ctx) try:\",\n \"commands.Context, *, added_required: bool = False ) -> SlashOption: name_desc = [ \\\"What\",\n \"also be optional.*\\\", pred, ) required = pred.result else: await ctx.send( \\\"This argument\",\n \"pred.result is False: break return options async def send_and_query_response( self, ctx: commands.Context, query:\",\n \"response.split(\\\"|\\\"): if \\\":\\\" not in choice_text: await ctx.send( f\\\"Failed to parse `{choice_text}` to\",\n \"be?\\\", f\\\"Valid option types: {humanize_list([inline(n) for n in valid_option_types])}\\\", \\\"(select `string` if you\",\n \"aliases=[\\\"++\\\"]) async def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ):\",\n \"str, tagscript: str, *, is_global: bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ):\",\n \"as choices to \\\" \\\"the tag. Choice names and values should be seperated\",\n \"break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you like to add\",\n \"to be? (maximum 100 characters)\\\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await ctx.send(\\\"Tag\",\n \"description = await self.send_and_query_response( ctx, \\\"What should the tag description to be? (maximum\",\n \"was optional.\\\", delete_after=15, ) required = False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required,\",\n \"pred.result is True: await self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id,\",\n \"): \\\"\\\"\\\" Add a user command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html)\",\n \"slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \\\"\\\"\\\"Get info about a slash tag that\",\n \"100 characters.*\\\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \\\"\\\\n\\\".join(name_desc), name_pred) match =\",\n \"and description should be split by a `:`.\\\", \\\"Example: `member:A member of this\",\n \"seperated by a `:`.\\\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await ctx.send( f\\\"Failed\",\n \"slash tags.\\\"\\\"\\\" tags = self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\\\"There are no\",\n \"match.group(1): return \\\"[p]slashtag global\\\" repl = \\\"global \\\" name = match.group(0) repl +=\",\n \"on the command options is needed raise tag = SlashTag( self, tagscript, guild_id=guild_id,\",\n \"self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\\\"Application ID set to `{id}`.\\\") @commands.check(dev_check) @slashtagset.command(\\\"addeval\\\") async\",\n \"is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) async def slashtag_pastebin( self, ctx: commands.Context, tag_name:\",\n \"option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"message\\\") async def slashtag_message( self, ctx: commands.Context, tag_name:\",\n \"this server.\\\") await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild\",\n \"continue choice = ApplicationOptionChoice(*choice_text.split(\\\":\\\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\\\"Reached max\",\n \"site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use TagScript blocks. \\\"\\\"\\\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"add\\\", aliases=[\\\"create\\\",\",\n \"commands.Command): overriden._help_override = doc else: overriden.__doc__ = doc return overriden return decorator class\",\n \"sorted(tags.values(), key=lambda t: t.name) ] description = \\\"\\\\n\\\".join(description) e = discord.Embed(color=await ctx.embed_color()) if\",\n \"description to be? (maximum 100 characters)\\\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await\",\n \"is already registered.\\\") slasheval = ApplicationCommand( self, name=\\\"eval\\\", description=\\\"SlashTags debugging eval command. Only\",\n \"async def slashtag_clear(self, ctx: commands.Context): \\\"\\\"\\\"Clear all slash tags for this server.\\\"\\\"\\\" pred\",\n \"\\\"❎\\\" description = [ f\\\"Application ID: **{self.application_id}**\\\", f\\\"Eval command: {eval_command}\\\", f\\\"Test cog loaded:\",\n \"\\\"\\\"\\\"Edit a single slash tag's argument by name.\\\"\\\"\\\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"remove\\\",\",\n \"GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag's TagScript.\\\"\\\"\\\" await self.slashtag_edit(ctx, tag,\",\n \"exceed 32 characters and can only contain characters \\\" \\\"that are alphanumeric or\",\n \"return options async def send_and_query_response( self, ctx: commands.Context, query: str, pred: MessagePredicate =\",\n \"\\\"(select `string` if you don't understand)\\\", ] option_type = await self.send_and_query_response( ctx, \\\"\\\\n\\\".join(option_query),\",\n \"-> str: title = f\\\"`{tag.type.get_prefix()}{tag.name}` - \\\" limit -= len(title) tagscript = tag.tagscript\",\n \"self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\\\"name\\\") async def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *,\",\n \"slash tags on this server? (Y/n)\\\", pred ) except asyncio.TimeoutError: return await ctx.send(\\\"Timed\",\n \"t.name) ] description = \\\"\\\\n\\\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags =\",\n \"create command {command!r} on guild {ctx.guild!r}\\\") # exc info unneeded since error handler\",\n \"TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a message command tag with\",\n \"tags.\\\" if guild else \\\"There are no global slash tags.\\\" ) return await\",\n \"GuildTagConverter): \\\"\\\"\\\"Get a slash tag's raw content.\\\"\\\"\\\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls, tag:\",\n \"self, name=\\\"eval\\\", description=\\\"SlashTags debugging eval command. Only bot owners can use this.\\\", options=[\",\n \"return await ctx.send(\\\"Tag addition timed out.\\\") else: description = \\\"\\\" if command_type ==\",\n \"Add a slash tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag(ctx,\",\n \"of choice names and values you would like to add as choices to\",\n \"by `:`, and each choice \\\" \\\"should be seperated by `|`. Example:\\\\n`dog:Doggo|cat:Catto`\\\" )\",\n \"ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import menu\",\n \"invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter\",\n \"): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit(\",\n \"else: overriden.__doc__ = doc return overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\\\"st\\\"]) async\",\n \"is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name:\",\n \"worry about it. \\\"\\\"\\\" app_id = id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id =\",\n \"_sub(match: re.Match) -> str: if match.group(1): return \\\"[p]slashtag global\\\" repl = \\\"global \\\"\",\n \"\\\"\\\"\\\"Remove the slash eval command.\\\"\\\"\\\" if not self.eval_command: return await ctx.send(\\\"The eval command\",\n \"None): \\\"\\\"\\\" Load or unload the SlashTag interaction development test cog. \\\"\\\"\\\" target_state\",\n \"def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \\\"\\\"\\\"Get info about a slash tag\",\n \"tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"message\\\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context, tag_name:\",\n \"server.\\\"\\\"\\\" await tag.send_info(ctx) @slashtag.command(\\\"raw\\\") async def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Get\",\n \"name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \\\"\\\\n\\\".join(name_desc), name_pred) match = name_pred.result name, description\",\n \"tag.tagscript if len(tagscript) > limit - 3: tagscript = tagscript[:limit] + \\\"...\\\" tagscript\",\n \"to any person obtaining a copy of this software and associated documentation files\",\n \"..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\") CHOICE_RE = re.compile(r\\\".{1,100}:.{1,100}\\\") CHOICE_LIMIT =\",\n \"value \\\" \\\"weren't seperated by a `:`.\\\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text):\",\n \"= match.group(0) repl += name if name.istitle(): repl = repl.title() return repl def\",\n \"@copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\\\"list\\\") @copy_doc(slashtag_list)\",\n \"on this server.\\\"\\\"\\\" await tag.send_info(ctx) @slashtag.command(\\\"raw\\\") async def slashtag_raw(self, ctx: commands.Context, *, tag:\",\n \"in range(1, 11): try: option = await self.get_option(ctx, added_required=added_required) if not option.required: added_required\",\n \"contain characters \\\" \\\"that are alphanumeric or '_' or '-'.\\\", \\\"The argument description\",\n \"link and try again: <https://discordapp.com/oauth2/authorize\\\" f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\" ) return await ctx.send(text) except Exception: log.error(\\\"Failed\",\n \"THE SOFTWARE. \\\"\\\"\\\" import asyncio import logging import re import types from collections\",\n \"ctx.send(await tag.delete()) @slashtag.command(\\\"info\\\") async def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \\\"\\\"\\\"Get info\",\n \"await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"clear\\\", hidden=True) async def slashtag_clear(self, ctx: commands.Context): \\\"\\\"\\\"Clear all\",\n \"self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link,\",\n \"int = None): \\\"\\\"\\\" Manually set the application ID for [botname] slash commands\",\n \"ctx.send(f\\\"Application ID set to `{id}`.\\\") @commands.check(dev_check) @slashtagset.command(\\\"addeval\\\") async def slashtagset_addeval(self, ctx: commands.Context): \\\"\\\"\\\"Add\",\n \"are no global slash tags.\\\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) @copy_doc(slashtag_usage) async\",\n \"the slash eval command.\\\"\\\"\\\" if not self.eval_command: return await ctx.send(\\\"The eval command hasn't\",\n \"ctx.send(\\\"Query timed out, not adding arguments.\\\") else: if pred.result is True: await self.get_options(ctx,\",\n \"= self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\\\"There are no slash tags on\",\n \"[] pages = list(pagify(description)) for index, page in enumerate(pages, 1): embed = e.copy()\",\n \"*, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\\\"raw\\\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context,\",\n \"a copy of this software and associated documentation files (the \\\"Software\\\"), to deal\",\n \"Software. THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS\",\n \"OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\",\n \"check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER )\",\n \"commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\\\"raw\\\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx:\",\n \"= MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Are you sure you want to delete\",\n \"WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF\",\n \"types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original, commands.Command) else original.__doc__\",\n \"def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) @copy_doc(slashtag_edit_argument) async def\",\n \"= doc return overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\\\"st\\\"]) async def slashtag(self,\",\n \"tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx:\",\n \"@slashtag_global.command(\\\"message\\\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript:\",\n \"are no global slash tags.\\\" ) return await ctx.send(message) counter = Counter({tag.name: tag.uses\",\n \"slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag,\",\n \"and to permit persons to whom the Software is furnished to do so,\",\n \"tags: return await ctx.send(\\\"There are no slash tags on this server.\\\") await self.view_slash_tags(ctx,\",\n \"pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \\\"Is this argument required? (Y/n)\\\\n*Keep in mind\",\n \"have permission to add Slash Commands here. Reinvite me \\\" \\\"with this invite\",\n \"commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \\\"\\\"\\\" Add a slash tag with\",\n \"break options.append(option) if i == 10: break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response(\",\n \"return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\\\"st\\\"]) async def slashtag(self, ctx: commands.Context): \\\"\\\"\\\" Slash\",\n \"self.send_and_query_response( ctx, \\\"Would you like to add arguments to this tag? (Y/n)\\\", pred\",\n \"from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate\",\n \"- \\\" limit -= len(title) tagscript = tag.tagscript if len(tagscript) > limit -\",\n \"embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) async def slashtag_usage(self,\",\n \"command is already registered.\\\") slasheval = ApplicationCommand( self, name=\\\"eval\\\", description=\\\"SlashTags debugging eval command.\",\n \"tags = self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\\\"There are no slash tags\",\n \"commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use TagScript blocks.\",\n \"ctx.send( \\\"This argument was automatically made optional as the previous one was optional.\\\",\",\n \"SlashOption: name_desc = [ \\\"What should the argument name be and description be?\\\",\",\n \"commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a message command\",\n \") -> str: if pred is None: pred = MessagePredicate.same_context(ctx) ask = await\",\n \"add arguments to this tag? (Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed\",\n \"argument timed out.\\\", delete_after=15) break options.append(option) if i == 10: break pred =\",\n \"values you would like to add as choices to \\\" \\\"the tag. Choice\",\n \"@commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) async def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Delete\",\n \"out.\\\") else: description = \\\"\\\" if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try:\",\n \"if len(tagscript) > limit - 3: tagscript = tagscript[:limit] + \\\"...\\\" tagscript =\",\n \"pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding arguments.\\\") else: if\",\n \"choices ({CHOICE_LIMIT}).\\\") break return choices async def get_option( self, ctx: commands.Context, *, added_required:\",\n \"title=\\\"SlashTags Settings\\\", description=\\\"\\\\n\\\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\\\"appid\\\") async def slashtagset_appid(self, ctx: commands.Context, id:\",\n \"from ..testing.button_menus import menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE\",\n \"@slashtag.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript:\",\n \"): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\\\"description\\\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx: commands.Context, tag:\",\n \"is_global=True) @slashtag_global.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter,\",\n \"a `:`.\\\", \\\"Example: `member:A member of this server.`\\\\n\\\", \\\"*Slash argument names may not\",\n \"= SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async def\",\n \"= ( \\\"Looks like I don't have permission to add Slash Commands here.\",\n \"GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\\\"tagscript\\\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript(\",\n \"TagScriptConverter, ): \\\"\\\"\\\" Add a message command tag with TagScript. [Slash tag usage\",\n \"copy of this software and associated documentation files (the \\\"Software\\\"), to deal in\",\n \"page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag arguments. \\\"\\\"\\\" await tag.edit_options(ctx) @slashtag_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"])\",\n \"SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \\\"Is this argument\",\n \"tag arguments. \\\"\\\"\\\" await tag.edit_options(ctx) @slashtag_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) async def slashtag_edit_argument( self, ctx: commands.Context,\",\n \"documentation on how to use TagScript blocks. \\\"\\\"\\\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"add\\\", aliases=[\\\"create\\\", \\\"+\\\"]) async\",\n \"-> SlashOption: name_desc = [ \\\"What should the argument name be and description\",\n \"async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await\",\n \"int = 60, ) -> str: if pred is None: pred = MessagePredicate.same_context(ctx)\",\n \"-> str: if match.group(1): return \\\"[p]slashtag global\\\" repl = \\\"global \\\" name =\",\n \"out, not deleting slash tags.\\\") if not pred.result: return await ctx.send(\\\"Ok, not deleting\",\n \"return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"message\\\") async def slashtag_message(\",\n \"tag, tagscript=tagscript) @slashtag_global_edit.command(\\\"name\\\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *,\",\n \"if not tags: return await ctx.send(\\\"There are no slash tags on this server.\\\")\",\n \"[ \\\"What should the argument name be and description be?\\\", \\\"The argument name\",\n \"MessagePredicate = None, *, timeout: int = 60, ) -> str: if pred\",\n \"unload the SlashTag interaction development test cog. \\\"\\\"\\\" target_state = ( true_or_false if\",\n \"GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\\\"description\\\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description(\",\n \"for index, page in enumerate(pages, 1): embed = e.copy() embed.description = page embed.set_footer(text=f\\\"{index}/{len(pages)}\",\n \"OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR\",\n \"\\\"Loaded\\\" self.add_test_cog() else: loaded = \\\"Unloaded\\\" self.remove_test_cog() await ctx.send(f\\\"{loaded} the SlashTag interaction testing\",\n \"self, ctx: commands.Context, tag_name: str, tagscript: str, *, is_global: bool = False, command_type:\",\n \"ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\\\"list\\\") @copy_doc(slashtag_list) async def slashtag_global_list(self, ctx:\",\n \"overriden.__doc__ = doc return overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\\\"st\\\"]) async def\",\n \"choices async def get_option( self, ctx: commands.Context, *, added_required: bool = False )\",\n \"or '_' or '-'.\\\", \\\"The argument description must be less than or equal\",\n \"invite link and try again: <https://discordapp.com/oauth2/authorize\\\" f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\" ) return await ctx.send(text) except Exception:\",\n \"ctx: commands.Context, guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache\",\n \"PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType from ..objects import\",\n \"async def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ):\",\n \"tag.\\\"\\\"\\\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\\\"tagscript\\\") async def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter,\",\n \"SlashTags settings.\\\"\\\"\\\" @slashtagset.command(\\\"settings\\\") async def slashtagset_settings(self, ctx: commands.Context): \\\"\\\"\\\"View SlashTags settings.\\\"\\\"\\\" eval_command =\",\n \"else: description = \\\"\\\" if command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await\",\n \"you don't know what this means, you don't need to worry about it.\",\n \"and try again: <https://discordapp.com/oauth2/authorize\\\" f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\" ) return await ctx.send(text) except Exception: log.error(\\\"Failed to\",\n \"= self.global_tag_cache if not tags: return await ctx.send(\\\"There are no global slash tags.\\\")\",\n \"on how to use TagScript blocks. \\\"\\\"\\\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"add\\\", aliases=[\\\"create\\\", \\\"+\\\"]) async def\",\n \"message.content async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query = ( \\\"Send the\",\n \") if option_type.lower() == \\\"choices\\\": choices = await self.get_choices(ctx) option_type = \\\"STRING\\\" else:\",\n \"been registered.\\\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None\",\n \"not adding arguments.\\\") else: if pred.result is True: await self.get_options(ctx, options) command =\",\n \"to add as choices to \\\" \\\"the tag. Choice names and values should\",\n \"all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \\\"AS\",\n \"SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR\",\n \"ctx, \\\"Are you sure you want to delete all slash tags on this\",\n \"exc info unneeded since error handler should print it, however info on the\",\n \"return choices async def get_option( self, ctx: commands.Context, *, added_required: bool = False\",\n \"ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True)\",\n \"import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from ..testing.button_menus import\",\n \"this argument timed out.\\\", delete_after=15) break options.append(option) if i == 10: break pred\",\n \"send_and_query_response( self, ctx: commands.Context, query: str, pred: MessagePredicate = None, *, timeout: int\",\n \"slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\\\"add\\\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context, tag_name:\",\n \"must also be optional.*\\\", pred, ) required = pred.result else: await ctx.send( \\\"This\",\n \"pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Are you sure you want to\",\n \"pred ) except asyncio.TimeoutError: return await ctx.send(\\\"Timed out, not deleting slash tags.\\\") if\",\n \"argument description must be less than or equal to 100 characters.*\\\", ] name_pred\",\n \"discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del\",\n \"asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding arguments.\\\") else: if pred.result is True:\",\n \"options=options, type=command_type, ) try: await command.register() except discord.Forbidden as error: log.error( \\\"Failed to\",\n \"with a Pastebin link. \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\\\"edit\\\", aliases=[\\\"e\\\"],\",\n \"testing_enabled = \\\"✅\\\" if self.testing_enabled else \\\"❎\\\" description = [ f\\\"Application ID: **{self.application_id}**\\\",\",\n \"to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the\",\n \"be and description be?\\\", \\\"The argument name and description should be split by\",\n \"await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"user\\\") async def slashtag_user(\",\n \"argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self,\",\n \"): \\\"\\\"\\\" Add a slash tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\"\",\n \"arguments.\\\") break if pred.result is False: break return options async def send_and_query_response( self,\",\n \"all slash tags from the database.\\\"\\\"\\\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"clear\\\", hidden=True) async\",\n \"tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async def get_options( self, ctx:\",\n \"-> List[SlashOption]: added_required = False for i in range(1, 11): try: option =\",\n \"OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL\",\n \"10: break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you like to\",\n \"] valid_option_types.append(\\\"choices\\\") option_query = [ \\\"What should the argument type be?\\\", f\\\"Valid option\",\n \"[ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t: t.name) ] description = \\\"\\\\n\\\".join(description)\",\n \"slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name,\",\n \"def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx,\",\n \"else \\\"unloaded\\\" return await ctx.send(f\\\"The SlashTag interaction testing cog is already {loaded}.\\\") await\",\n \"I don't have permission to add Slash Commands here. Reinvite me \\\" \\\"with\",\n \"GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType from ..objects\",\n \"description = match.group(1), match.group(2) valid_option_types = [ name.lower() for name in SlashOptionType.__members__.keys() if\",\n \"\\\"\\\"\\\" Slash Tag management with TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has\",\n \"**Example:** `[p]slashtag usage` \\\"\\\"\\\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"restore\\\", hidden=True) async def slashtag_restore(self,\",\n \"ctx: commands.Context, *, tag: TagConverter): \\\"\\\"\\\"Get info about a slash tag that is\",\n \"ctx.send( f\\\"Failed to parse `{choice_text}` to a choice as \\\" \\\"its name or\",\n \"self.send_and_query_response(ctx, \\\"\\\\n\\\".join(name_desc), name_pred) match = name_pred.result name, description = match.group(1), match.group(2) valid_option_types =\",\n \"WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE\",\n \"slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add\",\n \"commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a user command\",\n \"self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a\",\n \"PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS\",\n \"button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\") CHOICE_RE = re.compile(r\\\".{1,100}:.{1,100}\\\")\",\n \"TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\\\"name\\\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx:\",\n \") from ..http import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag\",\n \"await ctx.send(\\\"Query timed out, not adding arguments.\\\") else: if pred.result is True: await\",\n \"self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\\\"Tags deleted.\\\") @commands.is_owner() @slashtag.group(\\\"global\\\") @copy_doc(slashtag) async def slashtag_global(self, ctx:\",\n \"this server.\\\"\\\"\\\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Are you sure you\",\n \"tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\\\"raw\\\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *,\",\n \"tags.\\\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache()\",\n \"loaded = \\\"Loaded\\\" self.add_test_cog() else: loaded = \\\"Unloaded\\\" self.remove_test_cog() await ctx.send(f\\\"{loaded} the SlashTag\",\n \"await ctx.send(\\\"Ok, not deleting slash tags.\\\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, [])\",\n \"self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) async def slashtag_pastebin(\",\n \"\\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT\",\n \"tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async\",\n \"continue if not CHOICE_RE.match(choice_text): await ctx.send( f\\\"Failed to parse `{choice_text}` to a choice\",\n \"*, description: str ): \\\"\\\"\\\"Edit a slash tag's description.\\\"\\\"\\\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\\\"arguments\\\",\",\n \"**{self.application_id}**\\\", f\\\"Eval command: {eval_command}\\\", f\\\"Test cog loaded: {testing_enabled}\\\", ] embed = discord.Embed( color=0xC9C9C9,\",\n \"11): try: option = await self.get_option(ctx, added_required=added_required) if not option.required: added_required = True\",\n \"commands.Context, true_or_false: bool = None): \\\"\\\"\\\" Load or unload the SlashTag interaction development\",\n \"\\\"\\\"\\\"Edit a slash tag's name.\\\"\\\"\\\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\\\"description\\\") async def slashtag_edit_description( self,\",\n \"option_type = \\\"STRING\\\" else: choices = [] option_type = SlashOptionType[option_type.upper()] if not added_required:\",\n \"any person obtaining a copy of this software and associated documentation files (the\",\n \"differs from the bot user ID. This only applies to legacy bots. If\",\n \"\\\" \\\"with this invite link and try again: <https://discordapp.com/oauth2/authorize\\\" f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\" ) return await\",\n \"slashtag(self, ctx: commands.Context): \\\"\\\"\\\" Slash Tag management with TagScript. These commands use TagScriptEngine.\",\n \"tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\\\"Tags deleted.\\\") @commands.is_owner() @slashtag.group(\\\"global\\\") @copy_doc(slashtag) async\",\n \"async def slashtag_global_edit_description( self, ctx: commands.Context, tag: GlobalTagConverter, *, description: str ): await\",\n \"slashtagset(self, ctx: commands.Context): \\\"\\\"\\\"Manage SlashTags settings.\\\"\\\"\\\" @slashtagset.command(\\\"settings\\\") async def slashtagset_settings(self, ctx: commands.Context): \\\"\\\"\\\"View\",\n \"typing import Dict, List, Union import discord from redbot.core import commands from redbot.core.utils.chat_formatting\",\n \"what this means, you don't need to worry about it. \\\"\\\"\\\" app_id =\",\n \"slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name))\",\n \"await tag.edit_options(ctx) @slashtag_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) async def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument:\",\n \"bool, ): description = [ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t: t.name)\",\n \"slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(\",\n \"asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding additional arguments.\\\") break if pred.result is\",\n \"THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\",\n \"ctx.send(\\\"The eval command hasn't been registered.\\\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await\",\n \"tags: Dict[int, SlashTag], *, is_global: bool, ): description = [ self.format_tagscript(tag) for tag\",\n \"the Software, and to permit persons to whom the Software is furnished to\",\n \"name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\\\"description\\\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self, ctx:\",\n \"tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True)\",\n \"def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\"\",\n \"link: PastebinConverter, ): \\\"\\\"\\\" Add a slash tag with a Pastebin link. \\\"\\\"\\\"\",\n \"slash tags.\\\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx:\",\n \"@commands.check(dev_check) @slashtagset.command(\\\"rmeval\\\") async def slashtagset_rmeval(self, ctx: commands.Context): \\\"\\\"\\\"Remove the slash eval command.\\\"\\\"\\\" if\",\n \"types.FunctionType]): doc = original.help if isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc)\",\n \"description should be split by a `:`.\\\", \\\"Example: `member:A member of this server.`\\\\n\\\",\",\n \") await ctx.send(embed=embed) @slashtagset.command(\\\"appid\\\") async def slashtagset_appid(self, ctx: commands.Context, id: int = None):\",\n \"box, humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate\",\n \"on this server.\\\") await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild:\",\n \"copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \\\"AS IS\\\",\",\n \"[ \\\"What should the argument type be?\\\", f\\\"Valid option types: {humanize_list([inline(n) for n\",\n \"import tabulate from ..abc import MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter,\",\n \"self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a slash\",\n \"async def create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript: str, *, is_global: bool\",\n \"SlashTag interaction development test cog. \\\"\\\"\\\" target_state = ( true_or_false if true_or_false is\",\n \"def send_and_query_response( self, ctx: commands.Context, query: str, pred: MessagePredicate = None, *, timeout:\",\n \"self.send_and_query_response( ctx, \\\"Is this argument required? (Y/n)\\\\n*Keep in mind that if you choose\",\n \"GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\\\"raw\\\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self, ctx: commands.Context, *, tag:\",\n \"decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\\\"st\\\"]) async def slashtag(self, ctx: commands.Context): \\\"\\\"\\\" Slash Tag\",\n \"phenom4n4n Permission is hereby granted, free of charge, to any person obtaining a\",\n \"= \\\"Loaded\\\" self.add_test_cog() else: loaded = \\\"Unloaded\\\" self.remove_test_cog() await ctx.send(f\\\"{loaded} the SlashTag interaction\",\n \"TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption,\",\n \"ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id = None if is_global else ctx.guild.id\",\n \"ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx, \\\"What should\",\n \"tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a message command tag with TagScript. [Slash tag\",\n \"slash tag with a Pastebin link. \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True)\",\n \"TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"message\\\") @copy_doc(slashtag_message) async def slashtag_global_message(\",\n \"await self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded = \\\"loaded\\\" if target_state else\",\n \"timeout: int = 60, ) -> str: if pred is None: pred =\",\n \"\\\"\\\"\\\"Manage SlashTags settings.\\\"\\\"\\\" @slashtagset.command(\\\"settings\\\") async def slashtagset_settings(self, ctx: commands.Context): \\\"\\\"\\\"View SlashTags settings.\\\"\\\"\\\" eval_command\",\n \"aliases=[\\\"create\\\", \\\"+\\\"]) async def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript: TagScriptConverter,\",\n \"counter = Counter({tag.name: tag.uses for tag in tags.copy().values()}) e = discord.Embed(title=\\\"Slash Tag Stats\\\",\",\n \"command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try: await command.register()\",\n \"stats. **Example:** `[p]slashtag usage` \\\"\\\"\\\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"restore\\\", hidden=True) async def\",\n \"discord.Embed( color=0xC9C9C9, title=\\\"SlashTags Settings\\\", description=\\\"\\\\n\\\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\\\"appid\\\") async def slashtagset_appid(self, ctx:\",\n \"ctx) await self.send_and_query_response(ctx, \\\"\\\\n\\\".join(name_desc), name_pred) match = name_pred.result name, description = match.group(1), match.group(2)\",\n \"`:`.\\\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await ctx.send( f\\\"Failed to parse `{choice_text}`\",\n \"\\\"\\\"\\\" Load or unload the SlashTag interaction development test cog. \\\"\\\"\\\" target_state =\",\n \"await self.send_and_query_response( ctx, \\\"Would you like to add another argument? (Y/n)\\\", pred )\",\n \"commands.Context, guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if\",\n \"self.send_and_query_response( ctx, \\\"\\\\n\\\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \\\"choices\\\": choices = await\",\n \"25 log = logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\") def _sub(match: re.Match) -> str: if match.group(1): return \\\"[p]slashtag\",\n \"self.eval_command else \\\"❎\\\" testing_enabled = \\\"✅\\\" if self.testing_enabled else \\\"❎\\\" description = [\",\n \"async def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ):\",\n \"for [botname] slash commands if it differs from the bot user ID. This\",\n \"{command!r} on guild {ctx.guild!r}\\\", exc_info=error ) text = ( \\\"Looks like I don't\",\n \"choice \\\" \\\"should be seperated by `|`. Example:\\\\n`dog:Doggo|cat:Catto`\\\" ) response = await self.send_and_query_response(ctx,\",\n \"do so, subject to the following conditions: The above copyright notice and this\",\n \"MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \\\"\\\\n\\\".join(name_desc), name_pred) match = name_pred.result name, description = match.group(1),\",\n \"additional arguments.\\\") break if pred.result is False: break return options async def send_and_query_response(\",\n \"development test cog. \\\"\\\"\\\" target_state = ( true_or_false if true_or_false is not None\",\n \"split by a `:`.\\\", \\\"Example: `member:A member of this server.`\\\\n\\\", \\\"*Slash argument names\",\n \"print it, however info on the command options is needed raise tag =\",\n \"= Counter({tag.name: tag.uses for tag in tags.copy().values()}) e = discord.Embed(title=\\\"Slash Tag Stats\\\", color=await\",\n \"tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag.\\\"\\\"\\\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\\\"tagscript\\\") async def\",\n \"application ID for [botname] slash commands if it differs from the bot user\",\n \"is furnished to do so, subject to the following conditions: The above copyright\",\n \"option_query = [ \\\"What should the argument type be?\\\", f\\\"Valid option types: {humanize_list([inline(n)\",\n \"def slashtag_usage(self, ctx: commands.Context): \\\"\\\"\\\" See this slash tag usage stats. **Example:** `[p]slashtag\",\n \"needed raise tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await\",\n \"for choice_text in response.split(\\\"|\\\"): if \\\":\\\" not in choice_text: await ctx.send( f\\\"Failed to\",\n \"*, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"message\\\") @copy_doc(slashtag_message) async\",\n \"tags = self.global_tag_cache if not tags: return await ctx.send(\\\"There are no global slash\",\n \"ctx, \\\"\\\\n\\\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \\\"choices\\\": choices = await self.get_choices(ctx)\",\n \"except asyncio.TimeoutError: return await ctx.send(\\\"Timed out, not deleting slash tags.\\\") if not pred.result:\",\n \"guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag( self, ctx: commands.Context,\",\n \"return await ctx.send(\\\"There are no slash tags on this server.\\\") await self.view_slash_tags(ctx, tags,\",\n \"this tag? (Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not adding\",\n \"Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc = original.help if isinstance(original, commands.Command) else\",\n \"FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR\",\n \"TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE\",\n \"await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\\\"`/eval` has been registered.\\\") @commands.check(dev_check) @slashtagset.command(\\\"rmeval\\\") async\",\n \"INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR\",\n \"import commands from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS,\",\n \"USE OR OTHER DEALINGS IN THE SOFTWARE. \\\"\\\"\\\" import asyncio import logging import\",\n \"await self.send_and_query_response( ctx, \\\"\\\\n\\\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if option_type.lower() == \\\"choices\\\": choices =\",\n \"Tags\\\", icon_url=ctx.guild.icon_url) embeds = [] pages = list(pagify(description)) for index, page in enumerate(pages,\",\n \"await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\\\"description\\\") async def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *,\",\n \"(Y/n)\\\", pred ) except asyncio.TimeoutError: return await ctx.send(\\\"Timed out, not deleting slash tags.\\\")\",\n \"DEALINGS IN THE SOFTWARE. \\\"\\\"\\\" import asyncio import logging import re import types\",\n \"self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try: await command.register() except discord.Forbidden as\",\n \"tag: GuildTagConverter): \\\"\\\"\\\"Get a slash tag's raw content.\\\"\\\"\\\" await tag.send_raw_tagscript(ctx) @classmethod def format_tagscript(cls,\",\n \"def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a\",\n \") required = False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True)\",\n \"[ name.lower() for name in SlashOptionType.__members__.keys() if not name.startswith(\\\"SUB\\\") ] valid_option_types.append(\\\"choices\\\") option_query =\",\n \"tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\\\"Tags deleted.\\\") @commands.is_owner() @slashtag.group(\\\"global\\\") @copy_doc(slashtag)\",\n \"(the \\\"Software\\\"), to deal in the Software without restriction, including without limitation the\",\n \"= ( true_or_false if true_or_false is not None else not await self.config.testing_enabled() )\",\n \"has been registered.\\\") @commands.check(dev_check) @slashtagset.command(\\\"rmeval\\\") async def slashtagset_rmeval(self, ctx: commands.Context): \\\"\\\"\\\"Remove the slash\",\n \"self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) @copy_doc(slashtag_pastebin) async def slashtag_global_pastebin(\",\n \"argument required? (Y/n)\\\\n*Keep in mind that if you choose to make this argument\",\n \"to permit persons to whom the Software is furnished to do so, subject\",\n \"to a choice as its name and value \\\" \\\"weren't seperated by a\",\n \"tags.\\\" ) return await ctx.send(message) counter = Counter({tag.name: tag.uses for tag in tags.copy().values()})\",\n \"command.\\\"\\\"\\\" if not self.eval_command: return await ctx.send(\\\"The eval command hasn't been registered.\\\") try:\",\n \"async def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit\",\n \"choices to \\\" \\\"the tag. Choice names and values should be seperated by\",\n \"slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag\",\n \"commands.Context, tag_name: TagName(global_priority=True), *, tagscript: TagScriptConverter, ): await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True)\",\n \"more information on slash tag arguments. \\\"\\\"\\\" await tag.edit_options(ctx) @slashtag_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) async def\",\n \"description=\\\"Code body to evaluate.\\\", required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command =\",\n \"ctx.send(\\\"`/eval` has been registered.\\\") @commands.check(dev_check) @slashtagset.command(\\\"rmeval\\\") async def slashtagset_rmeval(self, ctx: commands.Context): \\\"\\\"\\\"Remove the\",\n \"be seperated by `:`, and each choice \\\" \\\"should be seperated by `|`.\",\n \"self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try:\",\n \"create command {command!r} on guild {ctx.guild!r}\\\", exc_info=error ) text = ( \\\"Looks like\",\n \"tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\\\"edit\\\", aliases=[\\\"e\\\"],\",\n \"slash eval command.\\\"\\\"\\\" if not self.eval_command: return await ctx.send(\\\"The eval command hasn't been\",\n \"{len(tags)} {slash_tags}\\\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\\\"list\\\") async\",\n \"to worry about it. \\\"\\\"\\\" app_id = id or self.bot.user.id await self.config.application_id.set(app_id) self.application_id\",\n \"Slash Commands here. Reinvite me \\\" \\\"with this invite link and try again:\",\n \"@slashtagset.command(\\\"rmeval\\\") async def slashtagset_rmeval(self, ctx: commands.Context): \\\"\\\"\\\"Remove the slash eval command.\\\"\\\"\\\" if not\",\n \"OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER\",\n \"Permission is hereby granted, free of charge, to any person obtaining a copy\",\n \"use this.\\\", options=[ SlashOption(name=\\\"body\\\", description=\\\"Code body to evaluate.\\\", required=True) ], ) await slasheval.register()\",\n \"return await ctx.send(\\\"An eval command is already registered.\\\") slasheval = ApplicationCommand( self, name=\\\"eval\\\",\",\n \"how to use TagScript blocks. \\\"\\\"\\\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"add\\\", aliases=[\\\"create\\\", \\\"+\\\"]) async def slashtag_add(\",\n \"be included in all copies or substantial portions of the Software. THE SOFTWARE\",\n \"*, timeout: int = 60, ) -> str: if pred is None: pred\",\n \"ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx, \\\"What should the tag description to\",\n \"await self.get_choices(ctx) option_type = \\\"STRING\\\" else: choices = [] option_type = SlashOptionType[option_type.upper()] if\",\n \"whom the Software is furnished to do so, subject to the following conditions:\",\n \"previous one was optional.\\\", delete_after=15, ) required = False return SlashOption( name=name.lower(), description=description,\",\n \"tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag( self,\",\n \"user command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx,\",\n \"break return options async def send_and_query_response( self, ctx: commands.Context, query: str, pred: MessagePredicate\",\n \"self, ctx: commands.Context, tag: GuildTagConverter, *, description: str ): \\\"\\\"\\\"Edit a slash tag's\",\n \"tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"message\\\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True,\",\n \"ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\\\"description\\\") async def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *, description:\",\n \"blocks. \\\"\\\"\\\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"add\\\", aliases=[\\\"create\\\", \\\"+\\\"]) async def slashtag_add( self, ctx: commands.Context, tag_name:\",\n \"this slash tag usage stats. **Example:** `[p]slashtag usage` \\\"\\\"\\\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner()\",\n \"target_state else \\\"unloaded\\\" return await ctx.send(f\\\"The SlashTag interaction testing cog is already {loaded}.\\\")\",\n \"argument optional, all following arguments must also be optional.*\\\", pred, ) required =\",\n \"tags: message = ( \\\"This server has no slash tags.\\\" if guild else\",\n \"pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you like to add another\",\n \"\\\"Would you like to add another argument? (Y/n)\\\", pred ) except asyncio.TimeoutError: await\",\n \"of this server.`\\\\n\\\", \\\"*Slash argument names may not exceed 32 characters and can\",\n \"\\\"Is this argument required? (Y/n)\\\\n*Keep in mind that if you choose to make\",\n \"as \\\" \\\"its name or value exceeded the 100 character limit.\\\", delete_after=15, )\",\n \"argument names may not exceed 32 characters and can only contain characters \\\"\",\n \"import MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, )\",\n \"List[SlashOption]: added_required = False for i in range(1, 11): try: option = await\",\n \"hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\\\"slashset\\\"]) async\",\n \"command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"user\\\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True,\",\n \"self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async def get_options( self,\",\n \"not tags: return await ctx.send(\\\"There are no slash tags on this server.\\\") await\",\n \"slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript))\",\n \"DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,\",\n \"ID: **{self.application_id}**\\\", f\\\"Eval command: {eval_command}\\\", f\\\"Test cog loaded: {testing_enabled}\\\", ] embed = discord.Embed(\",\n \"= ApplicationOptionChoice(*choice_text.split(\\\":\\\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\\\"Reached max choices ({CHOICE_LIMIT}).\\\")\",\n \"of the Software. THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY\",\n \"not option.required: added_required = True except asyncio.TimeoutError: await ctx.send(\\\"Adding this argument timed out.\\\",\",\n \"this server.`\\\\n\\\", \\\"*Slash argument names may not exceed 32 characters and can only\",\n \"= [] for usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\\\"Tag\\\", \\\"Uses\\\")), \\\"prolog\\\")\",\n \"or value exceeded the 100 character limit.\\\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\\\":\\\",\",\n \"server? (Y/n)\\\", pred ) except asyncio.TimeoutError: return await ctx.send(\\\"Timed out, not deleting slash\",\n \"menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\") CHOICE_RE\",\n \"self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\\\"tagscript\\\")\",\n \"await tag.edit_single_option(ctx, argument) @slashtag_global.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *,\",\n \"async def send_and_query_response( self, ctx: commands.Context, query: str, pred: MessagePredicate = None, *,\",\n \"TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__ = doc return\",\n \"str: if pred is None: pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query) try:\",\n \"GuildTagConverter, *, name: TagName(check_global=False) ): \\\"\\\"\\\"Edit a slash tag's name.\\\"\\\"\\\" await ctx.send(await tag.edit_name(name))\",\n \"tag.delete()) @slashtag.command(\\\"info\\\") async def slashtag_info(self, ctx: commands.Context, *, tag: TagConverter): \\\"\\\"\\\"Get info about\",\n \"tag: TagConverter): \\\"\\\"\\\"Get info about a slash tag that is stored on this\",\n \"added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \\\"Is this argument required? (Y/n)\\\\n*Keep in\",\n \"tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context,\",\n \"ctx.send(\\\"Tag addition timed out.\\\") else: description = \\\"\\\" if command_type == ApplicationCommandType.CHAT_INPUT: pred\",\n \"MIT License Copyright (c) 2020-present phenom4n4n Permission is hereby granted, free of charge,\",\n \"\\\"Would you like to add arguments to this tag? (Y/n)\\\", pred ) except\",\n \"= re.compile(r\\\".{1,100}:.{1,100}\\\") CHOICE_LIMIT = 25 log = logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\") def _sub(match: re.Match) -> str:\",\n \"else: slash_tags = \\\"slash tags\\\" e.set_author(name=\\\"Stored Slash Tags\\\", icon_url=ctx.guild.icon_url) embeds = [] pages\",\n \"to \\\" \\\"the tag. Choice names and values should be seperated by `:`,\",\n \"async def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit\",\n \"aliases=[\\\"e\\\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript:\",\n \"this argument required? (Y/n)\\\\n*Keep in mind that if you choose to make this\",\n \"\\\" \\\"that are alphanumeric or '_' or '-'.\\\", \\\"The argument description must be\",\n \"import discord from redbot.core import commands from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify\",\n \"should the argument name be and description be?\\\", \\\"The argument name and description\",\n \"guild_id=guild_id, options=options, type=command_type, ) try: await command.register() except discord.Forbidden as error: log.error( \\\"Failed\",\n \"await self.create_slash_tag(ctx, tag_name, tagscript, is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"message\\\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx:\",\n \"= \\\"✅\\\" if self.testing_enabled else \\\"❎\\\" description = [ f\\\"Application ID: **{self.application_id}**\\\", f\\\"Eval\",\n \"<https://discordapp.com/oauth2/authorize\\\" f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\" ) return await ctx.send(text) except Exception: log.error(\\\"Failed to create command {command!r}\",\n \"in choice_text: await ctx.send( f\\\"Failed to parse `{choice_text}` to a choice as its\",\n \"\\\"Send the list of choice names and values you would like to add\",\n \"slash tags.\\\" ) return await ctx.send(message) counter = Counter({tag.name: tag.uses for tag in\",\n \"[Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE )\",\n \"({CHOICE_LIMIT}).\\\") break return choices async def get_option( self, ctx: commands.Context, *, added_required: bool\",\n \"can only contain characters \\\" \\\"that are alphanumeric or '_' or '-'.\\\", \\\"The\",\n \"\\\"There are no global slash tags.\\\" ) return await ctx.send(message) counter = Counter({tag.name:\",\n \"await self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\\\"slashset\\\"]) async def slashtagset(self, ctx: commands.Context): \\\"\\\"\\\"Manage SlashTags settings.\\\"\\\"\\\"\",\n \"the bot user ID. This only applies to legacy bots. If you don't\",\n \"has documentation on how to use TagScript blocks. \\\"\\\"\\\" @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"add\\\", aliases=[\\\"create\\\", \\\"+\\\"])\",\n \"@slashtag_global.command(\\\"user\\\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript:\",\n \"self.testing_enabled else \\\"❎\\\" description = [ f\\\"Application ID: **{self.application_id}**\\\", f\\\"Eval command: {eval_command}\\\", f\\\"Test\",\n \"and associated documentation files (the \\\"Software\\\"), to deal in the Software without restriction,\",\n \"= e.copy() embed.description = page embed.set_footer(text=f\\\"{index}/{len(pages)} | {len(tags)} {slash_tags}\\\") embeds.append(embed) # await menu(ctx,\",\n \"without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\",\n \"import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice,\",\n \"def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await\",\n \"[ f\\\"Application ID: **{self.application_id}**\\\", f\\\"Eval command: {eval_command}\\\", f\\\"Test cog loaded: {testing_enabled}\\\", ] embed\",\n \"OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER\",\n \"except discord.Forbidden as error: log.error( \\\"Failed to create command {command!r} on guild {ctx.guild!r}\\\",\",\n \"copy import copy from typing import Dict, List, Union import discord from redbot.core\",\n \"CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE\",\n \"await ctx.send(await tag.initialize()) async def get_options( self, ctx: commands.Context, options: List[SlashOption] ) ->\",\n \"handler should print it, however info on the command options is needed raise\",\n \"TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to use\",\n \"commands.Context): \\\"\\\"\\\" Slash Tag management with TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html)\",\n \"if not option.required: added_required = True except asyncio.TimeoutError: await ctx.send(\\\"Adding this argument timed\",\n \"\\\"should be seperated by `|`. Example:\\\\n`dog:Doggo|cat:Catto`\\\" ) response = await self.send_and_query_response(ctx, query) choices\",\n \"GuildTagConverter, *, description: str ): \\\"\\\"\\\"Edit a slash tag's description.\\\"\\\"\\\" await ctx.send(await tag.edit_description(description))\",\n \"info on the command options is needed raise tag = SlashTag( self, tagscript,\",\n \"command hasn't been registered.\\\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command\",\n \"from typing import Dict, List, Union import discord from redbot.core import commands from\",\n \"tags.\\\"\\\"\\\" tags = self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\\\"There are no slash\",\n \"from ..http import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType, SlashOption, SlashTag from\",\n \"self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx,\",\n \"tag_name, link, is_global=True) @slashtag_global.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context,\",\n \"all slash tags for this server.\\\"\\\"\\\" pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx,\",\n \"await ctx.send(\\\"`/eval` has been registered.\\\") @commands.check(dev_check) @slashtagset.command(\\\"rmeval\\\") async def slashtagset_rmeval(self, ctx: commands.Context): \\\"\\\"\\\"Remove\",\n \"tagscript = tagscript.replace(\\\"\\\\n\\\", \\\" \\\") return f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\" async def view_slash_tags( self, ctx: commands.Context,\",\n \"re import types from collections import Counter from copy import copy from typing\",\n \"SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async def get_options(\",\n \"@commands.is_owner() @slashtag.command(\\\"clear\\\", hidden=True) async def slashtag_clear(self, ctx: commands.Context): \\\"\\\"\\\"Clear all slash tags for\",\n \"ctx: commands.Context): pass @slashtag_global.command(\\\"add\\\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context, tag_name: TagName(global_priority=True),\",\n \"commands.Context): \\\"\\\"\\\"View stored slash tags.\\\"\\\"\\\" tags = self.guild_tag_cache[ctx.guild.id] if not tags: return await\",\n \"import copy from typing import Dict, List, Union import discord from redbot.core import\",\n \"in response.split(\\\"|\\\"): if \\\":\\\" not in choice_text: await ctx.send( f\\\"Failed to parse `{choice_text}`\",\n \"@copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter,\",\n \"as the previous one was optional.\\\", delete_after=15, ) required = False return SlashOption(\",\n \"Example:\\\\n`dog:Doggo|cat:Catto`\\\" ) response = await self.send_and_query_response(ctx, query) choices = [] for choice_text in\",\n \"slash tag.\\\"\\\"\\\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\\\"tagscript\\\") async def slashtag_edit_tagscript( self, ctx: commands.Context, tag:\",\n \"log.error(\\\"Failed to create command {command!r} on guild {ctx.guild!r}\\\") # exc info unneeded since\",\n \"need to worry about it. \\\"\\\"\\\" app_id = id or self.bot.user.id await self.config.application_id.set(app_id)\",\n \"tag: GuildTagConverter, argument: str ): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) @copy_doc(slashtag_remove) async\",\n \"return await ctx.send(\\\"There are no global slash tags.\\\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\\\"usage\\\",\",\n \"you like to add another argument? (Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query\",\n \"@copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): await\",\n \"tagscript = tagscript[:limit] + \\\"...\\\" tagscript = tagscript.replace(\\\"\\\\n\\\", \\\" \\\") return f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\" async\",\n \"tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a user command tag\",\n \"Stats\\\", color=await ctx.embed_color()) embeds = [] for usage_data in chunks(counter.most_common(), 10): usage_chart =\",\n \"a slash tag.\\\"\\\"\\\" await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_edit.command(\\\"tagscript\\\") async def slashtag_edit_tagscript( self, ctx: commands.Context,\",\n \"\\\"its name or value exceeded the 100 character limit.\\\", delete_after=15, ) continue choice\",\n \"): \\\"\\\"\\\"Edit a single slash tag's argument by name.\\\"\\\"\\\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True)\",\n \"slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash\",\n \"Add a slash tag with a Pastebin link. \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, link,\",\n \"delete_after=15, ) required = False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, )\",\n \"self, ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ): \\\"\\\"\\\"Edit a slash tag's\",\n \"self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag's\",\n \"SlashTag], *, is_global: bool, ): description = [ self.format_tagscript(tag) for tag in sorted(tags.values(),\",\n \"option = await self.get_option(ctx, added_required=added_required) if not option.required: added_required = True except asyncio.TimeoutError:\",\n \"await self.config.testing_enabled.set(target_state) if target_state: loaded = \\\"Loaded\\\" self.add_test_cog() else: loaded = \\\"Unloaded\\\" self.remove_test_cog()\",\n \"= ApplicationCommand( self, name=\\\"eval\\\", description=\\\"SlashTags debugging eval command. Only bot owners can use\",\n \"def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ): \\\"\\\"\\\"Edit a\",\n \"bool = False ) -> SlashOption: name_desc = [ \\\"What should the argument\",\n \"PastebinConverter, ): \\\"\\\"\\\" Add a slash tag with a Pastebin link. \\\"\\\"\\\" await\",\n \"{command!r} on guild {ctx.guild!r}\\\") # exc info unneeded since error handler should print\",\n \"author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async def get_options( self, ctx: commands.Context, options:\",\n \"ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \\\"\\\"\\\" Add a slash tag\",\n \"index, page in enumerate(pages, 1): embed = e.copy() embed.description = page embed.set_footer(text=f\\\"{index}/{len(pages)} |\",\n \"chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\\\"Tag\\\", \\\"Uses\\\")), \\\"prolog\\\") embed = e.copy() embed.description =\",\n \"adding arguments.\\\") else: if pred.result is True: await self.get_options(ctx, options) command = ApplicationCommand(\",\n \"a slash tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name,\",\n \"slash tag's argument by name.\\\"\\\"\\\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) async\",\n \"e = discord.Embed(title=\\\"Slash Tag Stats\\\", color=await ctx.embed_color()) embeds = [] for usage_data in\",\n \"@slashtag.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) async def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Delete a\",\n \"for debugging.\\\"\\\"\\\" if self.eval_command: return await ctx.send(\\\"An eval command is already registered.\\\") slasheval\",\n \"== ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you like to\",\n \"OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\",\n \"tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False)\",\n \"embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) async def slashtag_usage(self, ctx: commands.Context): \\\"\\\"\\\"\",\n \"tag's TagScript.\\\"\\\"\\\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\\\"name\\\") async def slashtag_edit_name( self, ctx: commands.Context,\",\n \"async def slashtagset(self, ctx: commands.Context): \\\"\\\"\\\"Manage SlashTags settings.\\\"\\\"\\\" @slashtagset.command(\\\"settings\\\") async def slashtagset_settings(self, ctx:\",\n \"be? (maximum 100 characters)\\\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await ctx.send(\\\"Tag addition\",\n \"options: List[SlashOption] ) -> List[SlashOption]: added_required = False for i in range(1, 11):\",\n \"seperated by `:`, and each choice \\\" \\\"should be seperated by `|`. Example:\\\\n`dog:Doggo|cat:Catto`\\\"\",\n \"slashtag_restore(self, ctx: commands.Context): \\\"\\\"\\\"Restore all slash tags from the database.\\\"\\\"\\\" await self.restore_tags(ctx, ctx.guild)\",\n \"| {len(tags)} {slash_tags}\\\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\\\"list\\\")\",\n \"def slashtag_global_raw(self, ctx: commands.Context, *, tag: GlobalTagConverter): await tag.send_raw_tagscript(ctx) @slashtag_global.command(\\\"list\\\") @copy_doc(slashtag_list) async def\",\n \"@copy_doc(slashtag_pastebin) async def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ):\",\n \"ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try: await command.register() except discord.Forbidden\",\n \"= ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, ) try: await command.register() except\",\n \"*, tag: GuildTagConverter): \\\"\\\"\\\"Delete a slash tag.\\\"\\\"\\\" await ctx.send(await tag.delete()) @slashtag.command(\\\"info\\\") async def\",\n \"would like to add as choices to \\\" \\\"the tag. Choice names and\",\n \"\\\"[p]slashtag global\\\" repl = \\\"global \\\" name = match.group(0) repl += name if\",\n \"ctx: commands.Context): \\\"\\\"\\\"Add a slash eval command for debugging.\\\"\\\"\\\" if self.eval_command: return await\",\n \"to this tag? (Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not\",\n \"def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): \\\"\\\"\\\"Edit a single\",\n \"you don't need to worry about it. \\\"\\\"\\\" app_id = id or self.bot.user.id\",\n \"None): tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not tags: message =\",\n \"description = \\\"\\\\n\\\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \\\"global slash\",\n \"False for i in range(1, 11): try: option = await self.get_option(ctx, added_required=added_required) if\",\n \"slash tag's name.\\\"\\\"\\\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\\\"description\\\") async def slashtag_edit_description( self, ctx: commands.Context,\",\n \"deleted.\\\") @commands.is_owner() @slashtag.group(\\\"global\\\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\\\"add\\\") @copy_doc(slashtag_add) async\",\n \"registered.\\\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException: pass await self.config.eval_command.clear() self.eval_command = None await\",\n \"this permission notice shall be included in all copies or substantial portions of\",\n \"valid_option_types.append(\\\"choices\\\") option_query = [ \\\"What should the argument type be?\\\", f\\\"Valid option types:\",\n \"SlashOption(name=\\\"body\\\", description=\\\"Code body to evaluate.\\\", required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command\",\n \"ctx: commands.Context): \\\"\\\"\\\" Slash Tag management with TagScript. These commands use TagScriptEngine. [This\",\n \"doc = original.help if isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc) if\",\n \"not await self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded = \\\"loaded\\\" if target_state\",\n \"f\\\"Valid option types: {humanize_list([inline(n) for n in valid_option_types])}\\\", \\\"(select `string` if you don't\",\n \"server.`\\\\n\\\", \\\"*Slash argument names may not exceed 32 characters and can only contain\",\n \"del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear() await ctx.send(\\\"Tags deleted.\\\") @commands.is_owner() @slashtag.group(\\\"global\\\") @copy_doc(slashtag) async def\",\n \"slash tag usage stats. **Example:** `[p]slashtag usage` \\\"\\\"\\\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"restore\\\",\",\n \"IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A\",\n \"self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query\",\n \"be less than or equal to 100 characters.*\\\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx)\",\n \"@slashtag.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) async def slashtag_usage(self, ctx: commands.Context): \\\"\\\"\\\" See this slash tag usage\",\n \"guild else self.global_tag_cache if not tags: message = ( \\\"This server has no\",\n \"ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id = None if is_global\",\n \"however info on the command options is needed raise tag = SlashTag( self,\",\n \"guild {ctx.guild!r}\\\") # exc info unneeded since error handler should print it, however\",\n \"option types: {humanize_list([inline(n) for n in valid_option_types])}\\\", \\\"(select `string` if you don't understand)\\\",\",\n \"TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) @copy_doc(slashtag_pastebin)\",\n \"by `|`. Example:\\\\n`dog:Doggo|cat:Catto`\\\" ) response = await self.send_and_query_response(ctx, query) choices = [] for\",\n \"on guild {ctx.guild!r}\\\", exc_info=error ) text = ( \\\"Looks like I don't have\",\n \"commands.Context, tag: GuildTagConverter, *, description: str ): \\\"\\\"\\\"Edit a slash tag's description.\\\"\\\"\\\" await\",\n \"don't understand)\\\", ] option_type = await self.send_and_query_response( ctx, \\\"\\\\n\\\".join(option_query), MessagePredicate.lower_contained_in(valid_option_types, ctx), ) if\",\n \"= await ctx.send(query) try: message = await self.bot.wait_for(\\\"message\\\", check=pred, timeout=timeout) except asyncio.TimeoutError: await\",\n \"from redbot.core import commands from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from redbot.core.utils.menus\",\n \"def slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if not tags: return await ctx.send(\\\"There\",\n \"*, link: PastebinConverter, ): \\\"\\\"\\\" Add a slash tag with a Pastebin link.\",\n \"*, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\\\"name\\\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name(\",\n \"tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\\\"tagscript\\\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript:\",\n \"\\\"-\\\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete())\",\n \"should be split by a `:`.\\\", \\\"Example: `member:A member of this server.`\\\\n\\\", \\\"*Slash\",\n \"BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION\",\n \"async def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ):\",\n \"self.show_slash_tag_usage(ctx) @slashtag_global.command(\\\"restore\\\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self, ctx: commands.Context): await self.restore_tags(ctx, None) @commands.is_owner()\",\n \"self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\\\"`/eval` has been registered.\\\") @commands.check(dev_check) @slashtagset.command(\\\"rmeval\\\") async def\",\n \"slasheval = ApplicationCommand( self, name=\\\"eval\\\", description=\\\"SlashTags debugging eval command. Only bot owners can\",\n \"else ctx.guild.id if command_type == ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx, \\\"What\",\n \"arguments.\\\") else: if pred.result is True: await self.get_options(ctx, options) command = ApplicationCommand( self,\",\n \"query) choices = [] for choice_text in response.split(\\\"|\\\"): if \\\":\\\" not in choice_text:\",\n \"no slash tags on this server.\\\") await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self,\",\n \"Software is furnished to do so, subject to the following conditions: The above\",\n \"\\\"\\\"\\\" Edit a slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information\",\n \"tag.edit_options(ctx) @slashtag_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) async def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str\",\n \"= f\\\"✅ (**{self.eval_command}**)\\\" if self.eval_command else \\\"❎\\\" testing_enabled = \\\"✅\\\" if self.testing_enabled else\",\n \"= False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"message\\\") async\",\n \"[botname] slash commands if it differs from the bot user ID. This only\",\n \"return await ctx.send(\\\"The eval command hasn't been registered.\\\") try: await self.http.remove_slash_command(self.eval_command) except discord.HTTPException:\",\n \"\\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) async def slashtag_edit(\",\n \"command for debugging.\\\"\\\"\\\" if self.eval_command: return await ctx.send(\\\"An eval command is already registered.\\\")\",\n \"await self.delete_quietly(message) return message.content async def get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query =\",\n \"usage stats. **Example:** `[p]slashtag usage` \\\"\\\"\\\" await self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"restore\\\", hidden=True) async\",\n \"ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"user\\\") async def slashtag_user( self, ctx:\",\n \"else \\\"❎\\\" description = [ f\\\"Application ID: **{self.application_id}**\\\", f\\\"Eval command: {eval_command}\\\", f\\\"Test cog\",\n \"except Exception: log.error(\\\"Failed to create command {command!r} on guild {ctx.guild!r}\\\") # exc info\",\n \"def slashtag(self, ctx: commands.Context): \\\"\\\"\\\" Slash Tag management with TagScript. These commands use\",\n \"for i in range(1, 11): try: option = await self.get_option(ctx, added_required=added_required) if not\",\n \"ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global: bool, ): description = [ self.format_tagscript(tag)\",\n \"try: message = await self.bot.wait_for(\\\"message\\\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await\",\n \"tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\\\"name\\\") @copy_doc(slashtag_edit_name) async\",\n \"\\\"\\\"\\\" import asyncio import logging import re import types from collections import Counter\",\n \"str, pred: MessagePredicate = None, *, timeout: int = 60, ) -> str:\",\n \"characters \\\" \\\"that are alphanumeric or '_' or '-'.\\\", \\\"The argument description must\",\n \"): \\\"\\\"\\\"Edit a slash tag's description.\\\"\\\"\\\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) async def\",\n \"except asyncio.TimeoutError: await ctx.send(\\\"Adding this argument timed out.\\\", delete_after=15) break options.append(option) if i\",\n \"documentation files (the \\\"Software\\\"), to deal in the Software without restriction, including without\",\n \"name if name.istitle(): repl = repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def\",\n \"files (the \\\"Software\\\"), to deal in the Software without restriction, including without limitation\",\n \"know what this means, you don't need to worry about it. \\\"\\\"\\\" app_id\",\n \"self.config.testing_enabled.set(target_state) if target_state: loaded = \\\"Loaded\\\" self.add_test_cog() else: loaded = \\\"Unloaded\\\" self.remove_test_cog() await\",\n \"or equal to 100 characters.*\\\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \\\"\\\\n\\\".join(name_desc),\",\n \"not deleting slash tags.\\\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag\",\n \"create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript: str, *, is_global: bool = False,\",\n \"to do so, subject to the following conditions: The above copyright notice and\",\n \"slash tags on this server.\\\") await self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx:\",\n \"Tag management with TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on\",\n \"if i == 10: break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would\",\n \"limit.\\\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\\\":\\\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT:\",\n \"[this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash tag arguments. \\\"\\\"\\\" await tag.edit_options(ctx)\",\n \"target_state = ( true_or_false if true_or_false is not None else not await self.config.testing_enabled()\",\n \"tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not tags: message = (\",\n \"*, description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self,\",\n \"pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return await ctx.send(\\\"Tag addition timed out.\\\") else: description\",\n \"await self.config.application_id.set(app_id) self.application_id = app_id await ctx.send(f\\\"Application ID set to `{id}`.\\\") @commands.check(dev_check) @slashtagset.command(\\\"addeval\\\")\",\n \"add Slash Commands here. Reinvite me \\\" \\\"with this invite link and try\",\n \"the Software. THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND,\",\n \"await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await\",\n \"@slashtag.command(\\\"raw\\\") async def slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Get a slash tag's\",\n \"AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN\",\n \"import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate from ..abc\",\n \"tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) async def slashtag_remove(self, ctx: commands.Context, *, tag:\",\n \"@commands.guild_only() @commands.group(aliases=[\\\"st\\\"]) async def slashtag(self, ctx: commands.Context): \\\"\\\"\\\" Slash Tag management with TagScript.\",\n \"\\\"This argument was automatically made optional as the previous one was optional.\\\", delete_after=15,\",\n \"def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \\\"\\\"\\\" Add\",\n \"max choices ({CHOICE_LIMIT}).\\\") break return choices async def get_option( self, ctx: commands.Context, *,\",\n \"try: await command.register() except discord.Forbidden as error: log.error( \\\"Failed to create command {command!r}\",\n \"slash tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, tagscript,\",\n \"deleting slash tags.\\\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in\",\n \"= MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you like to add arguments to\",\n \"evaluate.\\\", required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\\\"`/eval`\",\n \"a slash tag's arguments. See [this documentation page](https://phen-cogs.readthedocs.io/en/latest/slashtags/slash_arguments.html) for more information on slash\",\n \"slash tag that is stored on this server.\\\"\\\"\\\" await tag.send_info(ctx) @slashtag.command(\\\"raw\\\") async def\",\n \"\\\"*Slash argument names may not exceed 32 characters and can only contain characters\",\n \"await button_menu(ctx, embeds) @slashtag.command(\\\"list\\\") async def slashtag_list(self, ctx: commands.Context): \\\"\\\"\\\"View stored slash tags.\\\"\\\"\\\"\",\n \"should print it, however info on the command options is needed raise tag\",\n \"100 character limit.\\\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\\\":\\\", 1)) choices.append(choice) if len(choices)\",\n \"def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Delete a slash tag.\\\"\\\"\\\" await ctx.send(await\",\n \"is needed raise tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, ) await\",\n \"self, ctx: commands.Context, query: str, pred: MessagePredicate = None, *, timeout: int =\",\n \"int = 60) -> str: title = f\\\"`{tag.type.get_prefix()}{tag.name}` - \\\" limit -= len(title)\",\n \"def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ): await ctx.send(await\",\n \"box(tabulate(usage_data, headers=(\\\"Tag\\\", \\\"Uses\\\")), \\\"prolog\\\") embed = e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx,\",\n \"description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"message\\\") async def slashtag_message( self, ctx: commands.Context,\",\n \"not name.startswith(\\\"SUB\\\") ] valid_option_types.append(\\\"choices\\\") option_query = [ \\\"What should the argument type be?\\\",\",\n \"1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\\\"Reached max choices ({CHOICE_LIMIT}).\\\") break return\",\n \"slash tag.\\\"\\\"\\\" await ctx.send(await tag.delete()) @slashtag.command(\\\"info\\\") async def slashtag_info(self, ctx: commands.Context, *, tag:\",\n \"ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await\",\n \"def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *, description: str ): \\\"\\\"\\\"Edit a\",\n \"\\\"STRING\\\" else: choices = [] option_type = SlashOptionType[option_type.upper()] if not added_required: pred =\",\n \"@slashtag.command(\\\"message\\\") async def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter,\",\n \"the command options is needed raise tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id,\",\n \"guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"user\\\") async\",\n \"no slash tags.\\\" if guild else \\\"There are no global slash tags.\\\" )\",\n \"command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] = [] guild_id = None if\",\n \"= [ \\\"What should the argument name be and description be?\\\", \\\"The argument\",\n \"arguments must also be optional.*\\\", pred, ) required = pred.result else: await ctx.send(\",\n \"error handler should print it, however info on the command options is needed\",\n \"None else not await self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded = \\\"loaded\\\"\",\n \"@commands.check(dev_check) @slashtagset.command(\\\"addeval\\\") async def slashtagset_addeval(self, ctx: commands.Context): \\\"\\\"\\\"Add a slash eval command for\",\n \"] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \\\"\\\\n\\\".join(name_desc), name_pred) match = name_pred.result name,\",\n \"@commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"user\\\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *,\",\n \"tagscript[:limit] + \\\"...\\\" tagscript = tagscript.replace(\\\"\\\\n\\\", \\\" \\\") return f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\" async def view_slash_tags(\",\n \"required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"message\\\") async def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False,\",\n \"= discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \\\"global slash tags\\\" e.set_author(name=\\\"Global Slash Tags\\\",\",\n \"ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) async def slashtag_pastebin( self,\",\n \"to add another argument? (Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed out,\",\n \"self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async def create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript:\",\n \"all slash tags on this server? (Y/n)\\\", pred ) except asyncio.TimeoutError: return await\",\n \"TagName(check_global=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a slash tag with TagScript. [Slash\",\n \"like I don't have permission to add Slash Commands here. Reinvite me \\\"\",\n \"the database.\\\"\\\"\\\" await self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"clear\\\", hidden=True) async def slashtag_clear(self, ctx: commands.Context):\",\n \"await ctx.send(\\\"There are no global slash tags.\\\") await self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\\\"usage\\\", aliases=[\\\"stats\\\"])\",\n \"self, ctx: commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript)\",\n \"SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,\",\n \"tag: SlashTag, limit: int = 60) -> str: title = f\\\"`{tag.type.get_prefix()}{tag.name}` - \\\"\",\n \"get_choices(self, ctx: commands.Context) -> List[ApplicationOptionChoice]: query = ( \\\"Send the list of choice\",\n \"ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Get a slash tag's raw content.\\\"\\\"\\\" await tag.send_raw_tagscript(ctx)\",\n \"slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): \\\"\\\"\\\"Edit a single slash\",\n \"are no slash tags on this server.\\\") await self.view_slash_tags(ctx, tags, is_global=False) async def\",\n \"commands.Context, tag: GuildTagConverter, argument: str ): \\\"\\\"\\\"Edit a single slash tag's argument by\",\n \"ask = await ctx.send(query) try: message = await self.bot.wait_for(\\\"message\\\", check=pred, timeout=timeout) except asyncio.TimeoutError:\",\n \"TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE\",\n \"with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False) async\",\n \"ctx.send(\\\"An eval command is already registered.\\\") slasheval = ApplicationCommand( self, name=\\\"eval\\\", description=\\\"SlashTags debugging\",\n \"LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT\",\n \"ctx: commands.Context, tag: GlobalTagConverter, *, description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"])\",\n \"substantial portions of the Software. THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY\",\n \"self.view_slash_tags(ctx, tags, is_global=True) @slashtag_global.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) @copy_doc(slashtag_usage) async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx)\",\n \"self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) async def slashtag_edit( self, ctx:\",\n \"tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\\\"tagscript\\\") @copy_doc(slashtag_edit_tagscript) async def\",\n \"Copyright (c) 2020-present phenom4n4n Permission is hereby granted, free of charge, to any\",\n \"(c) 2020-present phenom4n4n Permission is hereby granted, free of charge, to any person\",\n \"are alphanumeric or '_' or '-'.\\\", \\\"The argument description must be less than\",\n \"self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t: t.name) ] description = \\\"\\\\n\\\".join(description) e\",\n \"try: await self.send_and_query_response( ctx, \\\"Would you like to add another argument? (Y/n)\\\", pred\",\n \"single slash tag's argument by name.\\\"\\\"\\\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"])\",\n \"slashtagset_settings(self, ctx: commands.Context): \\\"\\\"\\\"View SlashTags settings.\\\"\\\"\\\" eval_command = f\\\"✅ (**{self.eval_command}**)\\\" if self.eval_command else\",\n \"TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN\",\n \"tagscript = tag.tagscript if len(tagscript) > limit - 3: tagscript = tagscript[:limit] +\",\n \"self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"user\\\") @copy_doc(slashtag_user) async def slashtag_global_user(\",\n \"as its name and value \\\" \\\"weren't seperated by a `:`.\\\", delete_after=15, )\",\n \"): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\\\"name\\\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context,\",\n \"commands from redbot.core.utils.chat_formatting import box, humanize_list, inline, pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu\",\n \"the previous one was optional.\\\", delete_after=15, ) required = False return SlashOption( name=name.lower(),\",\n \"import MessagePredicate from tabulate import tabulate from ..abc import MixinMeta from ..converters import\",\n \"async def slashtagset_appid(self, ctx: commands.Context, id: int = None): \\\"\\\"\\\" Manually set the\",\n \"ctx.embed_color()) if is_global: slash_tags = \\\"global slash tags\\\" e.set_author(name=\\\"Global Slash Tags\\\", icon_url=ctx.me.avatar_url) else:\",\n \"tag_name, tagscript, is_global=False) async def create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript: str,\",\n \"TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"user\\\") @copy_doc(slashtag_user)\",\n \"await ctx.send(await tag.edit_tagscript(tagscript)) @slashtag_global_edit.command(\\\"tagscript\\\") @copy_doc(slashtag_edit_tagscript) async def slashtag_global_edit_tagscript( self, ctx: commands.Context, tag: GlobalTagConverter,\",\n \"IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR\",\n \"= None): \\\"\\\"\\\" Load or unload the SlashTag interaction development test cog. \\\"\\\"\\\"\",\n \"slash tags.\\\" if guild else \\\"There are no global slash tags.\\\" ) return\",\n \"self, ctx: commands.Context, tags: Dict[int, SlashTag], *, is_global: bool, ): description = [\",\n \"*, name: TagName(check_global=False) ): \\\"\\\"\\\"Edit a slash tag's name.\\\"\\\"\\\" await ctx.send(await tag.edit_name(name)) @slashtag_edit.command(\\\"description\\\")\",\n \"*, name: TagName(global_priority=True), ): await ctx.send(await tag.edit_name(name)) @slashtag_global_edit.command(\\\"description\\\") @copy_doc(slashtag_edit_description) async def slashtag_global_edit_description( self,\",\n \"\\\"global \\\" name = match.group(0) repl += name if name.istitle(): repl = repl.title()\",\n \"or unload the SlashTag interaction development test cog. \\\"\\\"\\\" target_state = ( true_or_false\",\n \"add another argument? (Y/n)\\\", pred ) except asyncio.TimeoutError: await ctx.send(\\\"Query timed out, not\",\n \"description=description, guild_id=guild_id, options=options, type=command_type, ) try: await command.register() except discord.Forbidden as error: log.error(\",\n \"self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag.\\\"\\\"\\\"\",\n \"invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ):\",\n \"TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx, tag_name, link, is_global=True) @slashtag_global.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True)\",\n \"slash eval command for debugging.\\\"\\\"\\\" if self.eval_command: return await ctx.send(\\\"An eval command is\",\n \"return await ctx.send(message) counter = Counter({tag.name: tag.uses for tag in tags.copy().values()}) e =\",\n \"equal to 100 characters.*\\\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION, ctx) await self.send_and_query_response(ctx, \\\"\\\\n\\\".join(name_desc), name_pred)\",\n \"tag.edit_single_option(ctx, argument) @slashtag_global.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *, tag:\",\n \"redbot.core.utils.predicates import MessagePredicate from tabulate import tabulate from ..abc import MixinMeta from ..converters\",\n \"is_global: bool, ): description = [ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t:\",\n \"slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\\\"`/eval` has been registered.\\\") @commands.check(dev_check) @slashtagset.command(\\\"rmeval\\\")\",\n \"me \\\" \\\"with this invite link and try again: <https://discordapp.com/oauth2/authorize\\\" f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\" ) return\",\n \"don't need to worry about it. \\\"\\\"\\\" app_id = id or self.bot.user.id await\",\n \"aliases=[\\\"options\\\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \\\"\\\"\\\" Edit a slash tag's\",\n \"timed out, not adding arguments.\\\") else: if pred.result is True: await self.get_options(ctx, options)\",\n \"except asyncio.TimeoutError: return await ctx.send(\\\"Tag addition timed out.\\\") else: description = \\\"\\\" if\",\n \"it, however info on the command options is needed raise tag = SlashTag(\",\n \"ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear()\",\n \"str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context,\",\n \"guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache()\",\n \"MixinMeta from ..converters import ( GlobalTagConverter, GuildTagConverter, PastebinConverter, TagConverter, TagName, TagScriptConverter, ) from\",\n \"@copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) @copy_doc(slashtag_edit_argument)\",\n \"async def slashtag_global_usage(self, ctx: commands.Context): await self.show_slash_tag_usage(ctx) @slashtag_global.command(\\\"restore\\\", hidden=True) @copy_doc(slashtag_restore) async def slashtag_global_restore(self,\",\n \"here. Reinvite me \\\" \\\"with this invite link and try again: <https://discordapp.com/oauth2/authorize\\\" f\\\"?client_id={self.bot.user.id}&scope=bot%20applications.commands>\\\"\",\n \"parse `{choice_text}` to a choice as its name and value \\\" \\\"weren't seperated\",\n \"the 100 character limit.\\\", delete_after=15, ) continue choice = ApplicationOptionChoice(*choice_text.split(\\\":\\\", 1)) choices.append(choice) if\",\n \"tag that is stored on this server.\\\"\\\"\\\" await tag.send_info(ctx) @slashtag.command(\\\"raw\\\") async def slashtag_raw(self,\",\n \"ctx, \\\"Would you like to add arguments to this tag? (Y/n)\\\", pred )\",\n \"== ApplicationCommandType.CHAT_INPUT: try: description = await self.send_and_query_response( ctx, \\\"What should the tag description\",\n \"from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check TAG_RE = re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\") CHOICE_RE = re.compile(r\\\".{1,100}:.{1,100}\\\") CHOICE_LIMIT\",\n \"if not self.eval_command: return await ctx.send(\\\"The eval command hasn't been registered.\\\") try: await\",\n \"OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES\",\n \"ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\" Add a message\",\n \"that is stored on this server.\\\"\\\"\\\" await tag.send_info(ctx) @slashtag.command(\\\"raw\\\") async def slashtag_raw(self, ctx:\",\n \"aliases=[\\\"option\\\"]) async def slashtag_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str ): \\\"\\\"\\\"Edit\",\n \"user ID. This only applies to legacy bots. If you don't know what\",\n \"original.help if isinstance(original, commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command):\",\n \"Choice names and values should be seperated by `:`, and each choice \\\"\",\n \"\\\" \\\"its name or value exceeded the 100 character limit.\\\", delete_after=15, ) continue\",\n \"eval command is already registered.\\\") slasheval = ApplicationCommand( self, name=\\\"eval\\\", description=\\\"SlashTags debugging eval\",\n \"[Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER )\",\n \"= name_pred.result name, description = match.group(1), match.group(2) valid_option_types = [ name.lower() for name\",\n \"is_global: slash_tags = \\\"global slash tags\\\" e.set_author(name=\\\"Global Slash Tags\\\", icon_url=ctx.me.avatar_url) else: slash_tags =\",\n \"tag in sorted(tags.values(), key=lambda t: t.name) ] description = \\\"\\\\n\\\".join(description) e = discord.Embed(color=await\",\n \"self.show_slash_tag_usage(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"restore\\\", hidden=True) async def slashtag_restore(self, ctx: commands.Context): \\\"\\\"\\\"Restore all slash\",\n \"interaction development test cog. \\\"\\\"\\\" target_state = ( true_or_false if true_or_false is not\",\n \"if target_state is self.testing_enabled: loaded = \\\"loaded\\\" if target_state else \\\"unloaded\\\" return await\",\n \"for usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\\\"Tag\\\", \\\"Uses\\\")), \\\"prolog\\\") embed =\",\n \"information on slash tag arguments. \\\"\\\"\\\" await tag.edit_options(ctx) @slashtag_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) async def slashtag_edit_argument(\",\n \"GuildTagConverter): \\\"\\\"\\\"Delete a slash tag.\\\"\\\"\\\" await ctx.send(await tag.delete()) @slashtag.command(\\\"info\\\") async def slashtag_info(self, ctx:\",\n \"to delete all slash tags on this server? (Y/n)\\\", pred ) except asyncio.TimeoutError:\",\n \"if not CHOICE_RE.match(choice_text): await ctx.send( f\\\"Failed to parse `{choice_text}` to a choice as\",\n \"@slashtag.command(\\\"add\\\", aliases=[\\\"create\\\", \\\"+\\\"]) async def slashtag_add( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, tagscript:\",\n \"-> str: if pred is None: pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query)\",\n \"def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\\\"add\\\") @copy_doc(slashtag_add) async def slashtag_global_add( self, ctx: commands.Context,\",\n \"): await tag.edit_single_option(ctx, argument) @slashtag_global.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context,\",\n \"await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return message.content async def get_choices(self, ctx:\",\n \"from the bot user ID. This only applies to legacy bots. If you\",\n \"ctx.send(query) try: message = await self.bot.wait_for(\\\"message\\\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise\",\n \"discord.Embed(title=\\\"Slash Tag Stats\\\", color=await ctx.embed_color()) embeds = [] for usage_data in chunks(counter.most_common(), 10):\",\n \"tag.edit_name(name)) @slashtag_edit.command(\\\"description\\\") async def slashtag_edit_description( self, ctx: commands.Context, tag: GuildTagConverter, *, description: str\",\n \"f\\\"Failed to parse `{choice_text}` to a choice as its name and value \\\"\",\n \"OR OTHER DEALINGS IN THE SOFTWARE. \\\"\\\"\\\" import asyncio import logging import re\",\n \"\\\"-\\\"]) async def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Delete a slash tag.\\\"\\\"\\\"\",\n \"command_type == ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you like\",\n \"parse `{choice_text}` to a choice as \\\" \\\"its name or value exceeded the\",\n \"def create_slash_tag( self, ctx: commands.Context, tag_name: str, tagscript: str, *, is_global: bool =\",\n \"commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Delete a slash tag.\\\"\\\"\\\" await ctx.send(await tag.delete()) @slashtag.command(\\\"info\\\") async\",\n \"you sure you want to delete all slash tags on this server? (Y/n)\\\",\",\n \"Only bot owners can use this.\\\", options=[ SlashOption(name=\\\"body\\\", description=\\\"Code body to evaluate.\\\", required=True)\",\n \"async def slashtagset_rmeval(self, ctx: commands.Context): \\\"\\\"\\\"Remove the slash eval command.\\\"\\\"\\\" if not self.eval_command:\",\n \"`|`. Example:\\\\n`dog:Doggo|cat:Catto`\\\" ) response = await self.send_and_query_response(ctx, query) choices = [] for choice_text\",\n \"true_or_false if true_or_false is not None else not await self.config.testing_enabled() ) if target_state\",\n \"asyncio import logging import re import types from collections import Counter from copy\",\n \"permission notice shall be included in all copies or substantial portions of the\",\n \"hidden=True) async def slashtag_restore(self, ctx: commands.Context): \\\"\\\"\\\"Restore all slash tags from the database.\\\"\\\"\\\"\",\n \"\\\"weren't seperated by a `:`.\\\", delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await ctx.send(\",\n \"pagify from redbot.core.utils.menus import DEFAULT_CONTROLS, menu from redbot.core.utils.predicates import MessagePredicate from tabulate import\",\n \"Pastebin link. \\\"\\\"\\\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) async\",\n \"commands.Context, tags: Dict[int, SlashTag], *, is_global: bool, ): description = [ self.format_tagscript(tag) for\",\n \"str: title = f\\\"`{tag.type.get_prefix()}{tag.name}` - \\\" limit -= len(title) tagscript = tag.tagscript if\",\n \"OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH\",\n \"tag: GuildTagConverter, *, description: str ): \\\"\\\"\\\"Edit a slash tag's description.\\\"\\\"\\\" await ctx.send(await\",\n \"self.view_slash_tags(ctx, tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None): tags\",\n \"else: await ctx.send( \\\"This argument was automatically made optional as the previous one\",\n \"if guild else \\\"There are no global slash tags.\\\" ) return await ctx.send(message)\",\n \"this.\\\", options=[ SlashOption(name=\\\"body\\\", description=\\\"Code body to evaluate.\\\", required=True) ], ) await slasheval.register() await\",\n \"limit - 3: tagscript = tagscript[:limit] + \\\"...\\\" tagscript = tagscript.replace(\\\"\\\\n\\\", \\\" \\\")\",\n \"Counter({tag.name: tag.uses for tag in tags.copy().values()}) e = discord.Embed(title=\\\"Slash Tag Stats\\\", color=await ctx.embed_color())\",\n \"name.startswith(\\\"SUB\\\") ] valid_option_types.append(\\\"choices\\\") option_query = [ \\\"What should the argument type be?\\\", f\\\"Valid\",\n \"options.append(option) if i == 10: break pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx,\",\n \"await ctx.send(text) except Exception: log.error(\\\"Failed to create command {command!r} on guild {ctx.guild!r}\\\") #\",\n \"owners can use this.\\\", options=[ SlashOption(name=\\\"body\\\", description=\\\"Code body to evaluate.\\\", required=True) ], )\",\n \"the application ID for [botname] slash commands if it differs from the bot\",\n \"ctx: commands.Context) -> List[ApplicationOptionChoice]: query = ( \\\"Send the list of choice names\",\n \"is_global=True) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"message\\\") @copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False),\",\n \"by a `:`.\\\", \\\"Example: `member:A member of this server.`\\\\n\\\", \\\"*Slash argument names may\",\n \"self.config.eval_command.clear() self.eval_command = None await ctx.send(\\\"`/eval` has been deleted.\\\") @slashtagset.command(\\\"testing\\\") async def slashtagset_testing(self,\",\n \"@copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context, tag: GlobalTagConverter, *, name: TagName(global_priority=True), ):\",\n \"pred: MessagePredicate = None, *, timeout: int = 60, ) -> str: if\",\n \"@commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) async def slashtag_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link:\",\n \"MessagePredicate from tabulate import tabulate from ..abc import MixinMeta from ..converters import (\",\n \"a message command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag(\",\n \"commands.Context, tag: GlobalTagConverter, *, tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\\\"name\\\") @copy_doc(slashtag_edit_name)\",\n \"tag: GlobalTagConverter, *, description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) @copy_doc(slashtag_edit_arguments) async\",\n \"= False for i in range(1, 11): try: option = await self.get_option(ctx, added_required=added_required)\",\n \"def format_tagscript(cls, tag: SlashTag, limit: int = 60) -> str: title = f\\\"`{tag.type.get_prefix()}{tag.name}`\",\n \"is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id]\",\n \"been deleted.\\\") @slashtagset.command(\\\"testing\\\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None): \\\"\\\"\\\"\",\n \"tag.edit_tagscript(tagscript)) @slashtag_edit.command(\\\"tagscript\\\") async def slashtag_edit_tagscript( self, ctx: commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter\",\n \"Settings\\\", description=\\\"\\\\n\\\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\\\"appid\\\") async def slashtagset_appid(self, ctx: commands.Context, id: int\",\n \"= logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\") def _sub(match: re.Match) -> str: if match.group(1): return \\\"[p]slashtag global\\\" repl\",\n \"to create command {command!r} on guild {ctx.guild!r}\\\", exc_info=error ) text = ( \\\"Looks\",\n \"tags, is_global=False) async def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None): tags =\",\n \"def slashtag_global_pastebin( self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): await self.create_slash_tag(ctx,\",\n \"tagscript.replace(\\\"\\\\n\\\", \\\" \\\") return f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\" async def view_slash_tags( self, ctx: commands.Context, tags: Dict[int,\",\n \"= self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not tags: message = ( \\\"This\",\n \"ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\\\"raw\\\") @copy_doc(slashtag_raw) async def slashtag_global_raw(self,\",\n \"pred, ) required = pred.result else: await ctx.send( \\\"This argument was automatically made\",\n \"@commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"user\\\") async def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript:\",\n \"tagscript: TagScriptConverter ): await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\\\"name\\\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self,\",\n \"overriden._help_override = doc else: overriden.__doc__ = doc return overriden return decorator class Commands(MixinMeta):\",\n \"copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and\",\n \"( \\\"Send the list of choice names and values you would like to\",\n \"if guild else self.global_tag_cache if not tags: message = ( \\\"This server has\",\n \"you want to delete all slash tags on this server? (Y/n)\\\", pred )\",\n \"doc) if isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__ = doc return overriden\",\n \"required = False return SlashOption( name=name.lower(), description=description, option_type=option_type, required=required, choices=choices, ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"message\\\")\",\n \"self.bot.wait_for(\\\"message\\\", check=pred, timeout=timeout) except asyncio.TimeoutError: await self.delete_quietly(ask) raise await self.delete_quietly(ask) await self.delete_quietly(message) return\",\n \"if it differs from the bot user ID. This only applies to legacy\",\n \"name.lower() for name in SlashOptionType.__members__.keys() if not name.startswith(\\\"SUB\\\") ] valid_option_types.append(\\\"choices\\\") option_query = [\",\n \"f\\\"Failed to parse `{choice_text}` to a choice as \\\" \\\"its name or value\",\n \"name, description = match.group(1), match.group(2) valid_option_types = [ name.lower() for name in SlashOptionType.__members__.keys()\",\n \"commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ): \\\"\\\"\\\"Edit a slash tag's name.\\\"\\\"\\\" await\",\n \"self.restore_tags(ctx, ctx.guild) @commands.is_owner() @slashtag.command(\\\"clear\\\", hidden=True) async def slashtag_clear(self, ctx: commands.Context): \\\"\\\"\\\"Clear all slash\",\n \"HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN\",\n \"guild_id=guild_id, author_id=ctx.author.id, command=command, ) await ctx.send(await tag.initialize()) async def get_options( self, ctx: commands.Context,\",\n \"ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) async def slashtag_edit_arguments(self, ctx: commands.Context, tag: GuildTagConverter): \\\"\\\"\\\" Edit\",\n \"ctx: commands.Context, tag_name: str, tagscript: str, *, is_global: bool = False, command_type: ApplicationCommandType\",\n \"following conditions: The above copyright notice and this permission notice shall be included\",\n \"= \\\"global slash tags\\\" e.set_author(name=\\\"Global Slash Tags\\\", icon_url=ctx.me.avatar_url) else: slash_tags = \\\"slash tags\\\"\",\n \"message = ( \\\"This server has no slash tags.\\\" if guild else \\\"There\",\n \"await self.get_options(ctx, options) command = ApplicationCommand( self, name=tag_name, description=description, guild_id=guild_id, options=options, type=command_type, )\",\n \"member of this server.`\\\\n\\\", \\\"*Slash argument names may not exceed 32 characters and\",\n \"out, not adding arguments.\\\") else: if pred.result is True: await self.get_options(ctx, options) command\",\n \"await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter):\",\n \"else not await self.config.testing_enabled() ) if target_state is self.testing_enabled: loaded = \\\"loaded\\\" if\",\n \"@slashtag_global_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) @copy_doc(slashtag_edit_arguments) async def slashtag_global_edit_arguments(self, ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\\\"argument\\\",\",\n \"len(title) tagscript = tag.tagscript if len(tagscript) > limit - 3: tagscript = tagscript[:limit]\",\n \"The above copyright notice and this permission notice shall be included in all\",\n \"): \\\"\\\"\\\" Add a slash tag with a Pastebin link. \\\"\\\"\\\" await self.create_slash_tag(ctx,\",\n \"+= name if name.istitle(): repl = repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]):\",\n \"asyncio.TimeoutError: return await ctx.send(\\\"Tag addition timed out.\\\") else: description = \\\"\\\" if command_type\",\n \"self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values(): tag.remove_from_cache() tag.command.remove_from_cache() del tag self.guild_tag_cache[guild.id].clear() await self.config.guild(guild).tags.clear()\",\n \"ctx: commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self,\",\n \"def slashtag_message( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *, tagscript: TagScriptConverter, ): \\\"\\\"\\\"\",\n \"link, is_global=True) @slashtag_global.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) @copy_doc(slashtag_edit) async def slashtag_global_edit( self, ctx: commands.Context, tag:\",\n \"\\\"\\\"\\\"View SlashTags settings.\\\"\\\"\\\" eval_command = f\\\"✅ (**{self.eval_command}**)\\\" if self.eval_command else \\\"❎\\\" testing_enabled =\",\n \"eval_command = f\\\"✅ (**{self.eval_command}**)\\\" if self.eval_command else \\\"❎\\\" testing_enabled = \\\"✅\\\" if self.testing_enabled\",\n \"arguments. \\\"\\\"\\\" await tag.edit_options(ctx) @slashtag_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) async def slashtag_edit_argument( self, ctx: commands.Context, tag:\",\n \"await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds) @slashtag.command(\\\"list\\\") async def slashtag_list(self, ctx: commands.Context):\",\n \"granted, free of charge, to any person obtaining a copy of this software\",\n \"limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\",\n \"eval command for debugging.\\\"\\\"\\\" if self.eval_command: return await ctx.send(\\\"An eval command is already\",\n \"with TagScript. These commands use TagScriptEngine. [This site](https://phen-cogs.readthedocs.io/en/latest/index.html) has documentation on how to\",\n \"= page embed.set_footer(text=f\\\"{index}/{len(pages)} | {len(tags)} {slash_tags}\\\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await\",\n \"ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF\",\n \"WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO\",\n \"like to add as choices to \\\" \\\"the tag. Choice names and values\",\n \"ctx: commands.Context): \\\"\\\"\\\"View SlashTags settings.\\\"\\\"\\\" eval_command = f\\\"✅ (**{self.eval_command}**)\\\" if self.eval_command else \\\"❎\\\"\",\n \"debugging.\\\"\\\"\\\" if self.eval_command: return await ctx.send(\\\"An eval command is already registered.\\\") slasheval =\",\n \"on slash tag arguments. \\\"\\\"\\\" await tag.edit_options(ctx) @slashtag_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) async def slashtag_edit_argument( self,\",\n \"else original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override = doc else:\",\n \"List, Union import discord from redbot.core import commands from redbot.core.utils.chat_formatting import box, humanize_list,\",\n \"tagscript, is_global=True, command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag_global.command(\\\"user\\\") @copy_doc(slashtag_user) async def slashtag_global_user( self, ctx: commands.Context,\",\n \"tag. Choice names and values should be seperated by `:`, and each choice\",\n \"= MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message = await self.bot.wait_for(\\\"message\\\", check=pred, timeout=timeout)\",\n \"command=command, ) await ctx.send(await tag.initialize()) async def get_options( self, ctx: commands.Context, options: List[SlashOption]\",\n \"async def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter, ):\",\n \"a slash tag's TagScript.\\\"\\\"\\\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\\\"name\\\") async def slashtag_edit_name( self,\",\n \"timed out.\\\", delete_after=15) break options.append(option) if i == 10: break pred = MessagePredicate.yes_or_no(ctx)\",\n \"= [ self.format_tagscript(tag) for tag in sorted(tags.values(), key=lambda t: t.name) ] description =\",\n \"tags.copy().values()}) e = discord.Embed(title=\\\"Slash Tag Stats\\\", color=await ctx.embed_color()) embeds = [] for usage_data\",\n \"not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \\\"Is this argument required? (Y/n)\\\\n*Keep\",\n \"ctx.send(\\\"Adding this argument timed out.\\\", delete_after=15) break options.append(option) if i == 10: break\",\n \"a slash tag.\\\"\\\"\\\" await ctx.send(await tag.delete()) @slashtag.command(\\\"info\\\") async def slashtag_info(self, ctx: commands.Context, *,\",\n \") response = await self.send_and_query_response(ctx, query) choices = [] for choice_text in response.split(\\\"|\\\"):\",\n \"self.application_id = app_id await ctx.send(f\\\"Application ID set to `{id}`.\\\") @commands.check(dev_check) @slashtagset.command(\\\"addeval\\\") async def\",\n \"info about a slash tag that is stored on this server.\\\"\\\"\\\" await tag.send_info(ctx)\",\n \"async def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ): \\\"\\\"\\\"Edit\",\n \"is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter,\",\n \"= 60) -> str: title = f\\\"`{tag.type.get_prefix()}{tag.name}` - \\\" limit -= len(title) tagscript\",\n \"required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\\\"`/eval` has\",\n \"\\\"\\\"\\\" Add a slash tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await\",\n \"guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not\",\n \"tags on this server? (Y/n)\\\", pred ) except asyncio.TimeoutError: return await ctx.send(\\\"Timed out,\",\n \"\\\"The argument description must be less than or equal to 100 characters.*\\\", ]\",\n \"= None await ctx.send(\\\"`/eval` has been deleted.\\\") @slashtagset.command(\\\"testing\\\") async def slashtagset_testing(self, ctx: commands.Context,\",\n \"doc return overriden return decorator class Commands(MixinMeta): @commands.guild_only() @commands.group(aliases=[\\\"st\\\"]) async def slashtag(self, ctx:\",\n \">= CHOICE_LIMIT: await ctx.send(f\\\"Reached max choices ({CHOICE_LIMIT}).\\\") break return choices async def get_option(\",\n \"- 3: tagscript = tagscript[:limit] + \\\"...\\\" tagscript = tagscript.replace(\\\"\\\\n\\\", \\\" \\\") return\",\n \"@slashtagset.command(\\\"testing\\\") async def slashtagset_testing(self, ctx: commands.Context, true_or_false: bool = None): \\\"\\\"\\\" Load or\",\n \"f\\\"Eval command: {eval_command}\\\", f\\\"Test cog loaded: {testing_enabled}\\\", ] embed = discord.Embed( color=0xC9C9C9, title=\\\"SlashTags\",\n \"self, ctx: commands.Context, tag_name: TagName(check_global=False), *, link: PastebinConverter, ): \\\"\\\"\\\" Add a slash\",\n \"tag description to be? (maximum 100 characters)\\\", pred=MessagePredicate.length_less(101, ctx), ) except asyncio.TimeoutError: return\",\n \"MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you like to add arguments to this\",\n \"= repl.title() return repl def copy_doc(original: Union[commands.Command, types.FunctionType]): def decorator(overriden: Union[commands.Command, types.FunctionType]): doc\",\n \"{ctx.guild!r}\\\") # exc info unneeded since error handler should print it, however info\",\n \"@slashtag_global_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx: commands.Context, tag: GuildTagConverter, argument: str\",\n \"): \\\"\\\"\\\" Add a message command tag with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html)\",\n \"*, is_global: bool = False, command_type: ApplicationCommandType = ApplicationCommandType.CHAT_INPUT, ): options: List[SlashOption] =\",\n \"pred is None: pred = MessagePredicate.same_context(ctx) ask = await ctx.send(query) try: message =\",\n \"await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) async def slashtag_usage(self, ctx: commands.Context): \\\"\\\"\\\" See\",\n \"async def slashtag_restore(self, ctx: commands.Context): \\\"\\\"\\\"Restore all slash tags from the database.\\\"\\\"\\\" await\",\n \"and/or sell copies of the Software, and to permit persons to whom the\",\n \"CHOICE_RE.match(choice_text): await ctx.send( f\\\"Failed to parse `{choice_text}` to a choice as \\\" \\\"its\",\n \"e.copy() embed.description = page embed.set_footer(text=f\\\"{index}/{len(pages)} | {len(tags)} {slash_tags}\\\") embeds.append(embed) # await menu(ctx, embeds,\",\n \"async def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter): await ctx.send(await tag.delete()) @slashtag_global.command(\\\"raw\\\") @copy_doc(slashtag_raw)\",\n \"slash tags.\\\") guild: discord.Guild = ctx.guild await self.http.put_guild_slash_commands(guild.id, []) for tag in copy(self.guild_tag_cache[guild.id]).values():\",\n \"of charge, to any person obtaining a copy of this software and associated\",\n \"TagName, TagScriptConverter, ) from ..http import ApplicationOptionChoice, SlashOptionType from ..objects import ApplicationCommand, ApplicationCommandType,\",\n \"\\\"\\\\n\\\".join(name_desc), name_pred) match = name_pred.result name, description = match.group(1), match.group(2) valid_option_types = [\",\n \"async def slashtag(self, ctx: commands.Context): \\\"\\\"\\\" Slash Tag management with TagScript. These commands\",\n \"ctx.embed_color()) embeds = [] for usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\\\"Tag\\\",\",\n \"command_type=ApplicationCommandType.MESSAGE ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"user\\\") async def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False),\",\n \"usage_data in chunks(counter.most_common(), 10): usage_chart = box(tabulate(usage_data, headers=(\\\"Tag\\\", \\\"Uses\\\")), \\\"prolog\\\") embed = e.copy()\",\n \") if target_state is self.testing_enabled: loaded = \\\"loaded\\\" if target_state else \\\"unloaded\\\" return\",\n \"ApplicationCommandType.CHAT_INPUT: pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you like to add\",\n \"\\\"Failed to create command {command!r} on guild {ctx.guild!r}\\\", exc_info=error ) text = (\",\n \"= tag.tagscript if len(tagscript) > limit - 3: tagscript = tagscript[:limit] + \\\"...\\\"\",\n \"= MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \\\"Is this argument required? (Y/n)\\\\n*Keep in mind that\",\n \"= doc else: overriden.__doc__ = doc return overriden return decorator class Commands(MixinMeta): @commands.guild_only()\",\n \"await ctx.send(message) counter = Counter({tag.name: tag.uses for tag in tags.copy().values()}) e = discord.Embed(title=\\\"Slash\",\n \"@commands.mod_or_permissions(manage_guild=True) @slashtag.group(\\\"edit\\\", aliases=[\\\"e\\\"], invoke_without_command=True) async def slashtag_edit( self, ctx: commands.Context, tag: GuildTagConverter, *,\",\n \"slashtag_raw(self, ctx: commands.Context, *, tag: GuildTagConverter): \\\"\\\"\\\"Get a slash tag's raw content.\\\"\\\"\\\" await\",\n \"tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"pastebin\\\", aliases=[\\\"++\\\"]) async def slashtag_pastebin( self, ctx: commands.Context,\",\n \"options is needed raise tag = SlashTag( self, tagscript, guild_id=guild_id, author_id=ctx.author.id, command=command, )\",\n \"commands.Context, tag: GuildTagConverter, *, tagscript: TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag's TagScript.\\\"\\\"\\\" await\",\n \"app_id await ctx.send(f\\\"Application ID set to `{id}`.\\\") @commands.check(dev_check) @slashtagset.command(\\\"addeval\\\") async def slashtagset_addeval(self, ctx:\",\n \"= match.group(1), match.group(2) valid_option_types = [ name.lower() for name in SlashOptionType.__members__.keys() if not\",\n \"[] for choice_text in response.split(\\\"|\\\"): if \\\":\\\" not in choice_text: await ctx.send( f\\\"Failed\",\n \"+ \\\"...\\\" tagscript = tagscript.replace(\\\"\\\\n\\\", \\\" \\\") return f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\" async def view_slash_tags( self,\",\n \"= [] option_type = SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response(\",\n \"= SlashOptionType[option_type.upper()] if not added_required: pred = MessagePredicate.yes_or_no(ctx) await self.send_and_query_response( ctx, \\\"Is this\",\n \"await self.send_and_query_response( ctx, \\\"What should the tag description to be? (maximum 100 characters)\\\",\",\n \"for tag in sorted(tags.values(), key=lambda t: t.name) ] description = \\\"\\\\n\\\".join(description) e =\",\n \"\\\"✅\\\" if self.testing_enabled else \\\"❎\\\" description = [ f\\\"Application ID: **{self.application_id}**\\\", f\\\"Eval command:\",\n \"collections import Counter from copy import copy from typing import Dict, List, Union\",\n \"tag: GuildTagConverter, argument: str ): \\\"\\\"\\\"Edit a single slash tag's argument by name.\\\"\\\"\\\"\",\n \"\\\"Example: `member:A member of this server.`\\\\n\\\", \\\"*Slash argument names may not exceed 32\",\n \"name and description should be split by a `:`.\\\", \\\"Example: `member:A member of\",\n \"pages = list(pagify(description)) for index, page in enumerate(pages, 1): embed = e.copy() embed.description\",\n \"TagScriptConverter ): \\\"\\\"\\\"Edit a slash tag's TagScript.\\\"\\\"\\\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\\\"name\\\") async\",\n \"SlashTag from ..testing.button_menus import menu as button_menu from ..utils import ARGUMENT_NAME_DESCRIPTION, chunks, dev_check\",\n \"\\\"Looks like I don't have permission to add Slash Commands here. Reinvite me\",\n \"commands.Context, options: List[SlashOption] ) -> List[SlashOption]: added_required = False for i in range(1,\",\n \"tagscript=tagscript) @slashtag_edit.command(\\\"name\\\") async def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False)\",\n \"command. Only bot owners can use this.\\\", options=[ SlashOption(name=\\\"body\\\", description=\\\"Code body to evaluate.\\\",\",\n \"argument type be?\\\", f\\\"Valid option types: {humanize_list([inline(n) for n in valid_option_types])}\\\", \\\"(select `string`\",\n \"addition timed out.\\\") else: description = \\\"\\\" if command_type == ApplicationCommandType.CHAT_INPUT: pred =\",\n \"slashtagset_addeval(self, ctx: commands.Context): \\\"\\\"\\\"Add a slash eval command for debugging.\\\"\\\"\\\" if self.eval_command: return\",\n \"WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. \\\"\\\"\\\"\",\n \"guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False, command_type=ApplicationCommandType.USER ) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"pastebin\\\", aliases=[\\\"++\\\"])\",\n \"hidden=True) async def slashtag_clear(self, ctx: commands.Context): \\\"\\\"\\\"Clear all slash tags for this server.\\\"\\\"\\\"\",\n \"self.add_test_cog() else: loaded = \\\"Unloaded\\\" self.remove_test_cog() await ctx.send(f\\\"{loaded} the SlashTag interaction testing cog.\\\")\",\n \"commands.Context, tag: GlobalTagConverter, *, description: str ): await ctx.send(await tag.edit_description(description)) @slashtag_global_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) @copy_doc(slashtag_edit_arguments)\",\n \"pred = MessagePredicate.yes_or_no(ctx) try: await self.send_and_query_response( ctx, \\\"Would you like to add arguments\",\n \"is False: break return options async def send_and_query_response( self, ctx: commands.Context, query: str,\",\n \"@copy_doc(slashtag_message) async def slashtag_global_message( self, ctx: commands.Context, tag_name: TagName(global_priority=True, check_regex=False), *, tagscript: TagScriptConverter,\",\n \"choice = ApplicationOptionChoice(*choice_text.split(\\\":\\\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\\\"Reached max choices\",\n \"add as choices to \\\" \\\"the tag. Choice names and values should be\",\n \"@slashtag_edit.command(\\\"name\\\") async def slashtag_edit_name( self, ctx: commands.Context, tag: GuildTagConverter, *, name: TagName(check_global=False) ):\",\n \"await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\\\"`/eval` has been registered.\\\") @commands.check(dev_check)\",\n \"portions of the Software. THE SOFTWARE IS PROVIDED \\\"AS IS\\\", WITHOUT WARRANTY OF\",\n \"Commands here. Reinvite me \\\" \\\"with this invite link and try again: <https://discordapp.com/oauth2/authorize\\\"\",\n \"tagscript: TagScriptConverter, ): await self.create_slash_tag( ctx, tag_name, tagscript, is_global=True, command_type=ApplicationCommandType.USER ) @slashtag_global.command(\\\"pastebin\\\", aliases=[\\\"++\\\"])\",\n \"DEFAULT_CONTROLS) @slashtag.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) async def slashtag_usage(self, ctx: commands.Context): \\\"\\\"\\\" See this slash tag\",\n \"self.restore_tags(ctx, None) @commands.is_owner() @commands.group(aliases=[\\\"slashset\\\"]) async def slashtagset(self, ctx: commands.Context): \\\"\\\"\\\"Manage SlashTags settings.\\\"\\\"\\\" @slashtagset.command(\\\"settings\\\")\",\n \"limit -= len(title) tagscript = tag.tagscript if len(tagscript) > limit - 3: tagscript\",\n \"chunks, dev_check TAG_RE = re.compile(r\\\"(?i)(\\\\[p\\\\])?\\\\b(slash\\\\s?)?tag'?s?\\\\b\\\") CHOICE_RE = re.compile(r\\\".{1,100}:.{1,100}\\\") CHOICE_LIMIT = 25 log =\",\n \"to evaluate.\\\", required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await\",\n \"@commands.is_owner() @commands.group(aliases=[\\\"slashset\\\"]) async def slashtagset(self, ctx: commands.Context): \\\"\\\"\\\"Manage SlashTags settings.\\\"\\\"\\\" @slashtagset.command(\\\"settings\\\") async def\",\n \"show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id] if guild else\",\n \"def get_option( self, ctx: commands.Context, *, added_required: bool = False ) -> SlashOption:\",\n \"= usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\\\"usage\\\", aliases=[\\\"stats\\\"]) async def slashtag_usage(self, ctx:\",\n \"\\\"\\\"\\\"View stored slash tags.\\\"\\\"\\\" tags = self.guild_tag_cache[ctx.guild.id] if not tags: return await ctx.send(\\\"There\",\n \"options=[ SlashOption(name=\\\"body\\\", description=\\\"Code body to evaluate.\\\", required=True) ], ) await slasheval.register() await self.config.eval_command.set(slasheval.id)\",\n \") required = pred.result else: await ctx.send( \\\"This argument was automatically made optional\",\n \"ctx: commands.Context, id: int = None): \\\"\\\"\\\" Manually set the application ID for\",\n \"async def slashtagset_addeval(self, ctx: commands.Context): \\\"\\\"\\\"Add a slash eval command for debugging.\\\"\\\"\\\" if\",\n \"await self.slashtag_global_edit(ctx, tag, tagscript=tagscript) @slashtag_global_edit.command(\\\"name\\\") @copy_doc(slashtag_edit_name) async def slashtag_global_edit_name( self, ctx: commands.Context, tag:\",\n \"not in choice_text: await ctx.send( f\\\"Failed to parse `{choice_text}` to a choice as\",\n \"target_state is self.testing_enabled: loaded = \\\"loaded\\\" if target_state else \\\"unloaded\\\" return await ctx.send(f\\\"The\",\n \"should the tag description to be? (maximum 100 characters)\\\", pred=MessagePredicate.length_less(101, ctx), ) except\",\n \"commands.Command) else original.__doc__ doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override = doc\",\n \"description must be less than or equal to 100 characters.*\\\", ] name_pred =\",\n \"def slashtag_list(self, ctx: commands.Context): \\\"\\\"\\\"View stored slash tags.\\\"\\\"\\\" tags = self.guild_tag_cache[ctx.guild.id] if not\",\n \"commands.Context, tag: GlobalTagConverter): await tag.edit_options(ctx) @slashtag_global_edit.command(\\\"argument\\\", aliases=[\\\"option\\\"]) @copy_doc(slashtag_edit_argument) async def slashtag_global_edit_argument( self, ctx:\",\n \"len(tagscript) > limit - 3: tagscript = tagscript[:limit] + \\\"...\\\" tagscript = tagscript.replace(\\\"\\\\n\\\",\",\n \"with TagScript. [Slash tag usage guide](https://phen-cogs.readthedocs.io/en/latest/slashtags/slashtags.html) \\\"\\\"\\\" await self.create_slash_tag( ctx, tag_name, tagscript, is_global=False,\",\n \"IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\",\n \"TagScript.\\\"\\\"\\\" await self.slashtag_edit(ctx, tag, tagscript=tagscript) @slashtag_edit.command(\\\"name\\\") async def slashtag_edit_name( self, ctx: commands.Context, tag:\",\n \"argument) @slashtag_global.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) @copy_doc(slashtag_remove) async def slashtag_global_remove(self, ctx: commands.Context, *, tag: GlobalTagConverter):\",\n \"`{choice_text}` to a choice as \\\" \\\"its name or value exceeded the 100\",\n \"2020-present phenom4n4n Permission is hereby granted, free of charge, to any person obtaining\",\n \") @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"user\\\") async def slashtag_user( self, ctx: commands.Context, tag_name: TagName(check_global=False, check_regex=False), *,\",\n \"about a slash tag that is stored on this server.\\\"\\\"\\\" await tag.send_info(ctx) @slashtag.command(\\\"raw\\\")\",\n \"\\\") return f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\" async def view_slash_tags( self, ctx: commands.Context, tags: Dict[int, SlashTag], *,\",\n \"argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) async def slashtag_remove(self, ctx: commands.Context, *, tag: GuildTagConverter):\",\n \"# exc info unneeded since error handler should print it, however info on\",\n \"\\\" limit -= len(title) tagscript = tag.tagscript if len(tagscript) > limit - 3:\",\n \"await self.config.guild(guild).tags.clear() await ctx.send(\\\"Tags deleted.\\\") @commands.is_owner() @slashtag.group(\\\"global\\\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context):\",\n \"doc = TAG_RE.sub(_sub, doc) if isinstance(overriden, commands.Command): overriden._help_override = doc else: overriden.__doc__ =\",\n \"EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS\",\n \"@slashtagset.command(\\\"addeval\\\") async def slashtagset_addeval(self, ctx: commands.Context): \\\"\\\"\\\"Add a slash eval command for debugging.\\\"\\\"\\\"\",\n \"\\\"\\\"\\\"Edit a slash tag's description.\\\"\\\"\\\" await ctx.send(await tag.edit_description(description)) @slashtag_edit.command(\\\"arguments\\\", aliases=[\\\"options\\\"]) async def slashtag_edit_arguments(self,\",\n \"subject to the following conditions: The above copyright notice and this permission notice\",\n \"PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE\",\n \"\\\" \\\"the tag. Choice names and values should be seperated by `:`, and\",\n \"the list of choice names and values you would like to add as\",\n \"], ) await slasheval.register() await self.config.eval_command.set(slasheval.id) self.eval_command = slasheval.id await ctx.send(\\\"`/eval` has been\",\n \"re.compile(r\\\".{1,100}:.{1,100}\\\") CHOICE_LIMIT = 25 log = logging.getLogger(\\\"red.phenom4n4n.slashtags.commands\\\") def _sub(match: re.Match) -> str: if\",\n \"None): \\\"\\\"\\\" Manually set the application ID for [botname] slash commands if it\",\n \"description = [ f\\\"Application ID: **{self.application_id}**\\\", f\\\"Eval command: {eval_command}\\\", f\\\"Test cog loaded: {testing_enabled}\\\",\",\n \"def show_slash_tag_usage(self, ctx: commands.Context, guild: discord.Guild = None): tags = self.guild_tag_cache[guild.id] if guild\",\n \") continue choice = ApplicationOptionChoice(*choice_text.split(\\\":\\\", 1)) choices.append(choice) if len(choices) >= CHOICE_LIMIT: await ctx.send(f\\\"Reached\",\n \"FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,\",\n \"ctx.send(message) counter = Counter({tag.name: tag.uses for tag in tags.copy().values()}) e = discord.Embed(title=\\\"Slash Tag\",\n \"be optional.*\\\", pred, ) required = pred.result else: await ctx.send( \\\"This argument was\",\n \"to legacy bots. If you don't know what this means, you don't need\",\n \"in valid_option_types])}\\\", \\\"(select `string` if you don't understand)\\\", ] option_type = await self.send_and_query_response(\",\n \"\\\"global slash tags\\\" e.set_author(name=\\\"Global Slash Tags\\\", icon_url=ctx.me.avatar_url) else: slash_tags = \\\"slash tags\\\" e.set_author(name=\\\"Stored\",\n \"delete_after=15, ) continue if not CHOICE_RE.match(choice_text): await ctx.send( f\\\"Failed to parse `{choice_text}` to\",\n \"true_or_false: bool = None): \\\"\\\"\\\" Load or unload the SlashTag interaction development test\",\n \"hereby granted, free of charge, to any person obtaining a copy of this\",\n \"options: List[SlashOption] = [] guild_id = None if is_global else ctx.guild.id if command_type\",\n \"embed = e.copy() embed.description = usage_chart embeds.append(embed) await menu(ctx, embeds, DEFAULT_CONTROLS) @slashtag.command(\\\"usage\\\", aliases=[\\\"stats\\\"])\",\n \"{testing_enabled}\\\", ] embed = discord.Embed( color=0xC9C9C9, title=\\\"SlashTags Settings\\\", description=\\\"\\\\n\\\".join(description) ) await ctx.send(embed=embed) @slashtagset.command(\\\"appid\\\")\",\n \"= await self.send_and_query_response( ctx, \\\"What should the tag description to be? (maximum 100\",\n \"embed.set_footer(text=f\\\"{index}/{len(pages)} | {len(tags)} {slash_tags}\\\") embeds.append(embed) # await menu(ctx, embeds, DEFAULT_CONTROLS) await button_menu(ctx, embeds)\",\n \"*, tag: GuildTagConverter): \\\"\\\"\\\"Get a slash tag's raw content.\\\"\\\"\\\" await tag.send_raw_tagscript(ctx) @classmethod def\",\n \"slashtag_global_list(self, ctx: commands.Context): tags = self.global_tag_cache if not tags: return await ctx.send(\\\"There are\",\n \"one was optional.\\\", delete_after=15, ) required = False return SlashOption( name=name.lower(), description=description, option_type=option_type,\",\n \"the argument name be and description be?\\\", \\\"The argument name and description should\",\n \"def slashtagset_rmeval(self, ctx: commands.Context): \\\"\\\"\\\"Remove the slash eval command.\\\"\\\"\\\" if not self.eval_command: return\",\n \"restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute,\",\n \"must be less than or equal to 100 characters.*\\\", ] name_pred = MessagePredicate.regex(ARGUMENT_NAME_DESCRIPTION,\",\n \"discord.Guild = None): tags = self.guild_tag_cache[guild.id] if guild else self.global_tag_cache if not tags:\",\n \"def slashtagset_addeval(self, ctx: commands.Context): \\\"\\\"\\\"Add a slash eval command for debugging.\\\"\\\"\\\" if self.eval_command:\",\n \"await ctx.send( f\\\"Failed to parse `{choice_text}` to a choice as \\\" \\\"its name\",\n \"characters and can only contain characters \\\" \\\"that are alphanumeric or '_' or\",\n \"tag's argument by name.\\\"\\\"\\\" await tag.edit_single_option(ctx, argument) @commands.mod_or_permissions(manage_guild=True) @slashtag.command(\\\"remove\\\", aliases=[\\\"delete\\\", \\\"-\\\"]) async def\",\n \"import Dict, List, Union import discord from redbot.core import commands from redbot.core.utils.chat_formatting import\",\n \"@copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\\\"add\\\") @copy_doc(slashtag_add) async def slashtag_global_add( self,\",\n \"= \\\"\\\\n\\\".join(description) e = discord.Embed(color=await ctx.embed_color()) if is_global: slash_tags = \\\"global slash tags\\\"\",\n \"ctx.guild) @commands.is_owner() @slashtag.command(\\\"clear\\\", hidden=True) async def slashtag_clear(self, ctx: commands.Context): \\\"\\\"\\\"Clear all slash tags\",\n \"@slashtagset.command(\\\"appid\\\") async def slashtagset_appid(self, ctx: commands.Context, id: int = None): \\\"\\\"\\\" Manually set\",\n \"@slashtag.group(\\\"global\\\") @copy_doc(slashtag) async def slashtag_global(self, ctx: commands.Context): pass @slashtag_global.command(\\\"add\\\") @copy_doc(slashtag_add) async def slashtag_global_add(\",\n \"= tagscript.replace(\\\"\\\\n\\\", \\\" \\\") return f\\\"{title}{discord.utils.escape_markdown(tagscript)}\\\" async def view_slash_tags( self, ctx: commands.Context, tags:\"\n]","isConversational":false}}},{"rowIdx":1487,"cells":{"ngram":{"kind":"list like","value":["str1 [::-1]: l1 = i+l1 print(l1) if str1 == l1: print(\"string is a","== l1: print(\"string is a palindrome\") else : print(\"string is not a palindrome\")","string :\") l1 =\"\" for i in str1 [::-1]: l1 = i+l1 print(l1)","= i+l1 print(l1) if str1 == l1: print(\"string is a palindrome\") else :","str1 == l1: print(\"string is a palindrome\") else : print(\"string is not a","in str1 [::-1]: l1 = i+l1 print(l1) if str1 == l1: print(\"string is",":\") l1 =\"\" for i in str1 [::-1]: l1 = i+l1 print(l1) if","for i in str1 [::-1]: l1 = i+l1 print(l1) if str1 == l1:","print(l1) if str1 == l1: print(\"string is a palindrome\") else : print(\"string is","a string :\") l1 =\"\" for i in str1 [::-1]: l1 = i+l1","=\"\" for i in str1 [::-1]: l1 = i+l1 print(l1) if str1 ==","input(\"enter a string :\") l1 =\"\" for i in str1 [::-1]: l1 =","str1= input(\"enter a string :\") l1 =\"\" for i in str1 [::-1]: l1","l1 = i+l1 print(l1) if str1 == l1: print(\"string is a palindrome\") else","i+l1 print(l1) if str1 == l1: print(\"string is a palindrome\") else : print(\"string","if str1 == l1: print(\"string is a palindrome\") else : print(\"string is not","i in str1 [::-1]: l1 = i+l1 print(l1) if str1 == l1: print(\"string","[::-1]: l1 = i+l1 print(l1) if str1 == l1: print(\"string is a palindrome\")","l1 =\"\" for i in str1 [::-1]: l1 = i+l1 print(l1) if str1"],"string":"[\n \"str1 [::-1]: l1 = i+l1 print(l1) if str1 == l1: print(\\\"string is a\",\n \"== l1: print(\\\"string is a palindrome\\\") else : print(\\\"string is not a palindrome\\\")\",\n \"string :\\\") l1 =\\\"\\\" for i in str1 [::-1]: l1 = i+l1 print(l1)\",\n \"= i+l1 print(l1) if str1 == l1: print(\\\"string is a palindrome\\\") else :\",\n \"str1 == l1: print(\\\"string is a palindrome\\\") else : print(\\\"string is not a\",\n \"in str1 [::-1]: l1 = i+l1 print(l1) if str1 == l1: print(\\\"string is\",\n \":\\\") l1 =\\\"\\\" for i in str1 [::-1]: l1 = i+l1 print(l1) if\",\n \"for i in str1 [::-1]: l1 = i+l1 print(l1) if str1 == l1:\",\n \"print(l1) if str1 == l1: print(\\\"string is a palindrome\\\") else : print(\\\"string is\",\n \"a string :\\\") l1 =\\\"\\\" for i in str1 [::-1]: l1 = i+l1\",\n \"=\\\"\\\" for i in str1 [::-1]: l1 = i+l1 print(l1) if str1 ==\",\n \"input(\\\"enter a string :\\\") l1 =\\\"\\\" for i in str1 [::-1]: l1 =\",\n \"str1= input(\\\"enter a string :\\\") l1 =\\\"\\\" for i in str1 [::-1]: l1\",\n \"l1 = i+l1 print(l1) if str1 == l1: print(\\\"string is a palindrome\\\") else\",\n \"i+l1 print(l1) if str1 == l1: print(\\\"string is a palindrome\\\") else : print(\\\"string\",\n \"if str1 == l1: print(\\\"string is a palindrome\\\") else : print(\\\"string is not\",\n \"i in str1 [::-1]: l1 = i+l1 print(l1) if str1 == l1: print(\\\"string\",\n \"[::-1]: l1 = i+l1 print(l1) if str1 == l1: print(\\\"string is a palindrome\\\")\",\n \"l1 =\\\"\\\" for i in str1 [::-1]: l1 = i+l1 print(l1) if str1\"\n]","isConversational":false}}},{"rowIdx":1488,"cells":{"ngram":{"kind":"list like","value":["div.xpath('.//a[@class=\"name\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or None, \"purity\":","for package_obj in packages: catalog_price = package_obj.get(\"CatalogPrice\", {}) dd = { 'brand': d.get('brand'),","rel_url), 'img_url': img_url and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get() data_cid = xp_box.xpath(\".//div[@data-cid]/@data-cid\").get()","cid=data_cid, ts=int(time())), body=u\"\", meta={\"prd_data\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \"下一页\")]/@href').get() if next_page: yield","= map(lambda x: \"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x), ascii_uppercase) prd_size_url = \"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\" def parse(self, response): for xp_url","def parse_package(self, response): s = re.findall(r\"(?<=\\().+(?=\\))\", response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data',","{}) package = first(packages, {}) if package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName')","s = re.findall(r\"(?<=\\().+(?=\\))\", response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data', {}) package =","\"CH\"), callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\") for xp_box in xp_boxes: div","from scrapy import Request from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import strip","product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name = \"jk\" allowed_domains = [\"jkchemical.com\"] base_url =","response.meta.get('prd_data', {}) package = first(packages, {}) if package: d['brand'] = d['brand'] or package.get('Product',","x: \"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x), ascii_uppercase) prd_size_url = \"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\" def parse(self, response): for xp_url in response.xpath(\"//div[@class='yy","= re.findall(r\"(?<=\\().+(?=\\))\", response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data', {}) package = first(packages,","yield JkProduct(**d) for package_obj in packages: catalog_price = package_obj.get(\"CatalogPrice\", {}) dd = {","d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\"stringFormat\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and strip(catalog_price.get('Currency')),","callback=self.parse_list) def parse_package(self, response): s = re.findall(r\"(?<=\\().+(?=\\))\", response.text)[0] packages = json.loads(s) d =","d = response.meta.get('prd_data', {}) package = first(packages, {}) if package: d['brand'] = d['brand']","Request(tmp_url.replace(\"EN\", \"CH\"), callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\") for xp_box in xp_boxes:","from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name =","rel_url and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get()","div = xp_box.xpath(\".//div[2][@class='left_right mulu_text']\") brand = strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\"name\"]/@href').get() img_url =","if package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in","\"en_name\": strip(xp_box.xpath(\".//a[@class='name']/text()\").get()), \"cn_name\": strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url,","{}) dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\"stringFormat\"), 'price': catalog_price and","\"下一页\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s = re.findall(r\"(?<=\\().+(?=\\))\",","next_page), callback=self.parse_list) def parse_package(self, response): s = re.findall(r\"(?<=\\().+(?=\\))\", response.text)[0] packages = json.loads(s) d","mulu_text']\") brand = strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\"name\"]/@href').get() img_url = div.xpath('.//img/@src').get() d =","package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in packages:","import time from urllib.parse import urljoin import scrapy from more_itertools import first from","from time import time from urllib.parse import urljoin import scrapy from more_itertools import","xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get() data_cid = xp_box.xpath(\".//div[@data-cid]/@data-cid\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\"\", meta={\"prd_data\": d}, callback=self.parse_package) next_page","dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\"stringFormat\"), 'price': catalog_price and catalog_price.get('Value'),","import json import re from string import ascii_uppercase from time import time from","urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get() data_cid =","= response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\") for xp_box in xp_boxes: div = xp_box.xpath(\".//div[2][@class='left_right mulu_text']\") brand = strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(),","\"cn_name\": strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url), }","name = \"jk\" allowed_domains = [\"jkchemical.com\"] base_url = \"http://www.jkchemical.com\" start_urls = map(lambda x:","d.get('cat_no'), 'package': package_obj.get(\"stringFormat\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and strip(catalog_price.get('Currency')), 'attrs': json.dumps(package_obj),","response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\") for xp_box in xp_boxes: div = xp_box.xpath(\".//div[2][@class='left_right mulu_text']\") brand = strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(), '')","\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\" def parse(self, response): for xp_url in response.xpath(\"//div[@class='yy toa']//a/@href\"): tmp_url = self.base_url +","'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\"stringFormat\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and","ascii_uppercase from time import time from urllib.parse import urljoin import scrapy from more_itertools","ascii_uppercase) prd_size_url = \"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\" def parse(self, response): for xp_url in response.xpath(\"//div[@class='yy toa']//a/@href\"): tmp_url","response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data', {}) package = first(packages, {}) if","'cat_no': d.get('cat_no'), 'package': package_obj.get(\"stringFormat\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and strip(catalog_price.get('Currency')), 'attrs':","import strip class JkPrdSpider(scrapy.Spider): name = \"jk\" allowed_domains = [\"jkchemical.com\"] base_url = \"http://www.jkchemical.com\"","} data_jkid = xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get() data_cid = xp_box.xpath(\".//div[@data-cid]/@data-cid\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\"\", meta={\"prd_data\":","import Request from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider):","+ xp_url.extract() yield Request(tmp_url.replace(\"EN\", \"CH\"), callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\") for","ts=int(time())), body=u\"\", meta={\"prd_data\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \"下一页\")]/@href').get() if next_page: yield Request(urljoin(response.url,","= self.base_url + xp_url.extract() yield Request(tmp_url.replace(\"EN\", \"CH\"), callback=self.parse_list) def parse_list(self, response): xp_boxes =","JkPrdSpider(scrapy.Spider): name = \"jk\" allowed_domains = [\"jkchemical.com\"] base_url = \"http://www.jkchemical.com\" start_urls = map(lambda","import urljoin import scrapy from more_itertools import first from scrapy import Request from","JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name = \"jk\" allowed_domains = [\"jkchemical.com\"]","and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get() data_cid = xp_box.xpath(\".//div[@data-cid]/@data-cid\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid,","{}).get('BrandName') yield JkProduct(**d) for package_obj in packages: catalog_price = package_obj.get(\"CatalogPrice\", {}) dd =","'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url), } data_jkid =","d = { 'brand': brand.replace('-', '') or None, \"purity\": div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(), \"cas\": strip(div.xpath(\".//li[2]//a/text()\").get()), \"cat_no\":","Request from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name","{}) if package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj","yield Request(tmp_url.replace(\"EN\", \"CH\"), callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\") for xp_box in","strip(div.xpath(\".//li[2]//a/text()\").get()), \"cat_no\": div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(), \"en_name\": strip(xp_box.xpath(\".//a[@class='name']/text()\").get()), \"cn_name\": strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url':","div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(), \"cas\": strip(div.xpath(\".//li[2]//a/text()\").get()), \"cat_no\": div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(), \"en_name\": strip(xp_box.xpath(\".//a[@class='name']/text()\").get()), \"cn_name\": strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()), 'prd_url': rel_url and urljoin(response.url,","more_itertools import first from scrapy import Request from product_spider.items import JkProduct, JKPackage from","strip(xp_box.xpath(\".//a[@class='name']/text()\").get()), \"cn_name\": strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url),","= xp_box.xpath(\".//div[@data-cid]/@data-cid\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\"\", meta={\"prd_data\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(),","packages: catalog_price = package_obj.get(\"CatalogPrice\", {}) dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package':","yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\"\", meta={\"prd_data\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \"下一页\")]/@href').get() if","next_page = response.xpath('//a[contains(text(), \"下一页\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response):","string import ascii_uppercase from time import time from urllib.parse import urljoin import scrapy","import ascii_uppercase from time import time from urllib.parse import urljoin import scrapy from","d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in packages: catalog_price","meta={\"prd_data\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \"下一页\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list)","packages = json.loads(s) d = response.meta.get('prd_data', {}) package = first(packages, {}) if package:","import first from scrapy import Request from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions","scrapy import Request from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import strip class","scrapy from more_itertools import first from scrapy import Request from product_spider.items import JkProduct,","json import re from string import ascii_uppercase from time import time from urllib.parse","= [\"jkchemical.com\"] base_url = \"http://www.jkchemical.com\" start_urls = map(lambda x: \"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x), ascii_uppercase) prd_size_url =","xp_boxes = response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\") for xp_box in xp_boxes: div = xp_box.xpath(\".//div[2][@class='left_right mulu_text']\") brand =","in xp_boxes: div = xp_box.xpath(\".//div[2][@class='left_right mulu_text']\") brand = strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\"name\"]/@href').get()","= \"jk\" allowed_domains = [\"jkchemical.com\"] base_url = \"http://www.jkchemical.com\" start_urls = map(lambda x: \"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x),","parse_package(self, response): s = re.findall(r\"(?<=\\().+(?=\\))\", response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data', {})","{ 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\"stringFormat\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price","re.findall(r\"(?<=\\().+(?=\\))\", response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data', {}) package = first(packages, {})","callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \"下一页\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self,","re from string import ascii_uppercase from time import time from urllib.parse import urljoin","urljoin import scrapy from more_itertools import first from scrapy import Request from product_spider.items","response.xpath(\"//div[@class='yy toa']//a/@href\"): tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\"EN\", \"CH\"), callback=self.parse_list) def parse_list(self,","or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in packages: catalog_price = package_obj.get(\"CatalogPrice\", {})","base_url = \"http://www.jkchemical.com\" start_urls = map(lambda x: \"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x), ascii_uppercase) prd_size_url = \"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\" def","from urllib.parse import urljoin import scrapy from more_itertools import first from scrapy import","= d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in packages: catalog_price =","class JkPrdSpider(scrapy.Spider): name = \"jk\" allowed_domains = [\"jkchemical.com\"] base_url = \"http://www.jkchemical.com\" start_urls =","package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in packages: catalog_price = package_obj.get(\"CatalogPrice\", {}) dd","body=u\"\", meta={\"prd_data\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \"下一页\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page),","catalog_price = package_obj.get(\"CatalogPrice\", {}) dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\"stringFormat\"),","for xp_box in xp_boxes: div = xp_box.xpath(\".//div[2][@class='left_right mulu_text']\") brand = strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(), '') rel_url","if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s = re.findall(r\"(?<=\\().+(?=\\))\", response.text)[0]","first(packages, {}) if package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for","\"purity\": div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(), \"cas\": strip(div.xpath(\".//li[2]//a/text()\").get()), \"cat_no\": div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(), \"en_name\": strip(xp_box.xpath(\".//a[@class='name']/text()\").get()), \"cn_name\": strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()), 'prd_url': rel_url and","brand = strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\"name\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = {","Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\"\", meta={\"prd_data\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \"下一页\")]/@href').get() if next_page:","time from urllib.parse import urljoin import scrapy from more_itertools import first from scrapy","img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or None, \"purity\": div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(),","package_obj.get(\"CatalogPrice\", {}) dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\"stringFormat\"), 'price': catalog_price","Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s = re.findall(r\"(?<=\\().+(?=\\))\", response.text)[0] packages = json.loads(s)","= { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\"stringFormat\"), 'price': catalog_price and catalog_price.get('Value'), 'currency':","def parse(self, response): for xp_url in response.xpath(\"//div[@class='yy toa']//a/@href\"): tmp_url = self.base_url + xp_url.extract()","= \"http://www.jkchemical.com\" start_urls = map(lambda x: \"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x), ascii_uppercase) prd_size_url = \"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\" def parse(self,","= div.xpath('.//a[@class=\"name\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or None,","package_obj in packages: catalog_price = package_obj.get(\"CatalogPrice\", {}) dd = { 'brand': d.get('brand'), 'cat_no':","'package': package_obj.get(\"stringFormat\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and strip(catalog_price.get('Currency')), 'attrs': json.dumps(package_obj), }","first from scrapy import Request from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import","img_url), } data_jkid = xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get() data_cid = xp_box.xpath(\".//div[@data-cid]/@data-cid\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\"\",","xp_box.xpath(\".//div[2][@class='left_right mulu_text']\") brand = strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\"name\"]/@href').get() img_url = div.xpath('.//img/@src').get() d","tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\"EN\", \"CH\"), callback=self.parse_list) def parse_list(self, response): xp_boxes","'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and strip(catalog_price.get('Currency')), 'attrs': json.dumps(package_obj), } yield JKPackage(**dd)","allowed_domains = [\"jkchemical.com\"] base_url = \"http://www.jkchemical.com\" start_urls = map(lambda x: \"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x), ascii_uppercase) prd_size_url","= json.loads(s) d = response.meta.get('prd_data', {}) package = first(packages, {}) if package: d['brand']","= xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get() data_cid = xp_box.xpath(\".//div[@data-cid]/@data-cid\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\"\", meta={\"prd_data\": d}, callback=self.parse_package)","package_obj.get(\"stringFormat\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and strip(catalog_price.get('Currency')), 'attrs': json.dumps(package_obj), } yield","div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(), \"en_name\": strip(xp_box.xpath(\".//a[@class='name']/text()\").get()), \"cn_name\": strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url and","xp_box.xpath(\".//div[@data-cid]/@data-cid\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\"\", meta={\"prd_data\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \"下一页\")]/@href').get()","= response.xpath('//a[contains(text(), \"下一页\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s","self.base_url + xp_url.extract() yield Request(tmp_url.replace(\"EN\", \"CH\"), callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\")","parse_list(self, response): xp_boxes = response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\") for xp_box in xp_boxes: div = xp_box.xpath(\".//div[2][@class='left_right mulu_text']\")","brand.replace('-', '') or None, \"purity\": div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(), \"cas\": strip(div.xpath(\".//li[2]//a/text()\").get()), \"cat_no\": div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(), \"en_name\": strip(xp_box.xpath(\".//a[@class='name']/text()\").get()), \"cn_name\":","= response.meta.get('prd_data', {}) package = first(packages, {}) if package: d['brand'] = d['brand'] or","d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \"下一页\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def","product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name = \"jk\"","import re from string import ascii_uppercase from time import time from urllib.parse import","\"http://www.jkchemical.com\" start_urls = map(lambda x: \"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x), ascii_uppercase) prd_size_url = \"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\" def parse(self, response):","\"cat_no\": div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(), \"en_name\": strip(xp_box.xpath(\".//a[@class='name']/text()\").get()), \"cn_name\": strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url","data_jkid = xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get() data_cid = xp_box.xpath(\".//div[@data-cid]/@data-cid\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\"\", meta={\"prd_data\": d},","parse(self, response): for xp_url in response.xpath(\"//div[@class='yy toa']//a/@href\"): tmp_url = self.base_url + xp_url.extract() yield","next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s = re.findall(r\"(?<=\\().+(?=\\))\", response.text)[0] packages","d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in packages: catalog_price = package_obj.get(\"CatalogPrice\",","= package_obj.get(\"CatalogPrice\", {}) dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\"stringFormat\"), 'price':","= first(packages, {}) if package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d)","from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name = \"jk\" allowed_domains = [\"jkchemical.com\"] base_url","response): for xp_url in response.xpath(\"//div[@class='yy toa']//a/@href\"): tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\"EN\",","for xp_url in response.xpath(\"//div[@class='yy toa']//a/@href\"): tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\"EN\", \"CH\"),","import scrapy from more_itertools import first from scrapy import Request from product_spider.items import","[\"jkchemical.com\"] base_url = \"http://www.jkchemical.com\" start_urls = map(lambda x: \"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x), ascii_uppercase) prd_size_url = \"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\"","rel_url = div.xpath('.//a[@class=\"name\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or","import JkProduct, JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name = \"jk\" allowed_domains","strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url), } data_jkid","and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get() data_cid","'brand': brand.replace('-', '') or None, \"purity\": div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(), \"cas\": strip(div.xpath(\".//li[2]//a/text()\").get()), \"cat_no\": div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(), \"en_name\": strip(xp_box.xpath(\".//a[@class='name']/text()\").get()),","= \"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\" def parse(self, response): for xp_url in response.xpath(\"//div[@class='yy toa']//a/@href\"): tmp_url = self.base_url","strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\"name\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-',","or None, \"purity\": div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(), \"cas\": strip(div.xpath(\".//li[2]//a/text()\").get()), \"cat_no\": div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(), \"en_name\": strip(xp_box.xpath(\".//a[@class='name']/text()\").get()), \"cn_name\": strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()), 'prd_url':","yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s = re.findall(r\"(?<=\\().+(?=\\))\", response.text)[0] packages =","response): xp_boxes = response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\") for xp_box in xp_boxes: div = xp_box.xpath(\".//div[2][@class='left_right mulu_text']\") brand","JkProduct, JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name = \"jk\" allowed_domains =","map(lambda x: \"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x), ascii_uppercase) prd_size_url = \"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\" def parse(self, response): for xp_url in","\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x), ascii_uppercase) prd_size_url = \"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\" def parse(self, response): for xp_url in response.xpath(\"//div[@class='yy toa']//a/@href\"):","response): s = re.findall(r\"(?<=\\().+(?=\\))\", response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data', {}) package","in response.xpath(\"//div[@class='yy toa']//a/@href\"): tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\"EN\", \"CH\"), callback=self.parse_list) def","time import time from urllib.parse import urljoin import scrapy from more_itertools import first","toa']//a/@href\"): tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\"EN\", \"CH\"), callback=self.parse_list) def parse_list(self, response):","xp_url.extract() yield Request(tmp_url.replace(\"EN\", \"CH\"), callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\") for xp_box","'') rel_url = div.xpath('.//a[@class=\"name\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '')","xp_boxes: div = xp_box.xpath(\".//div[2][@class='left_right mulu_text']\") brand = strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\"name\"]/@href').get() img_url","urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get() data_cid = xp_box.xpath(\".//div[@data-cid]/@data-cid\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())),","urllib.parse import urljoin import scrapy from more_itertools import first from scrapy import Request","= strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\"name\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand':","JkProduct(**d) for package_obj in packages: catalog_price = package_obj.get(\"CatalogPrice\", {}) dd = { 'brand':","def parse_list(self, response): xp_boxes = response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\") for xp_box in xp_boxes: div = xp_box.xpath(\".//div[2][@class='left_right","= div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or None, \"purity\": div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(), \"cas\":","prd_size_url = \"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\" def parse(self, response): for xp_url in response.xpath(\"//div[@class='yy toa']//a/@href\"): tmp_url =","\"cas\": strip(div.xpath(\".//li[2]//a/text()\").get()), \"cat_no\": div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(), \"en_name\": strip(xp_box.xpath(\".//a[@class='name']/text()\").get()), \"cn_name\": strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url),","'') or None, \"purity\": div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(), \"cas\": strip(div.xpath(\".//li[2]//a/text()\").get()), \"cat_no\": div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(), \"en_name\": strip(xp_box.xpath(\".//a[@class='name']/text()\").get()), \"cn_name\": strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()),","from more_itertools import first from scrapy import Request from product_spider.items import JkProduct, JKPackage","= xp_box.xpath(\".//div[2][@class='left_right mulu_text']\") brand = strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\"name\"]/@href').get() img_url = div.xpath('.//img/@src').get()","in packages: catalog_price = package_obj.get(\"CatalogPrice\", {}) dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'),","xp_box in xp_boxes: div = xp_box.xpath(\".//div[2][@class='left_right mulu_text']\") brand = strip(div.xpath('.//li[@id=\"ctl00_cph_Content_li_lt_Brand\"]/text()').get(), '') rel_url =","from string import ascii_uppercase from time import time from urllib.parse import urljoin import","json.loads(s) d = response.meta.get('prd_data', {}) package = first(packages, {}) if package: d['brand'] =","= { 'brand': brand.replace('-', '') or None, \"purity\": div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(), \"cas\": strip(div.xpath(\".//li[2]//a/text()\").get()), \"cat_no\": div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(),","None, \"purity\": div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(), \"cas\": strip(div.xpath(\".//li[2]//a/text()\").get()), \"cat_no\": div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(), \"en_name\": strip(xp_box.xpath(\".//a[@class='name']/text()\").get()), \"cn_name\": strip(xp_box.xpath(\".//a[@class='name']//span[1]/text()\").get()), 'prd_url': rel_url","callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\"//table[@id]//div[@class='PRODUCT_box']\") for xp_box in xp_boxes: div =","div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or None, \"purity\": div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(), \"cas\": strip(div.xpath(\".//li[2]//a/text()\").get()),","package = first(packages, {}) if package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield","\"jk\" allowed_domains = [\"jkchemical.com\"] base_url = \"http://www.jkchemical.com\" start_urls = map(lambda x: \"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x), ascii_uppercase)","img_url and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get() data_cid = xp_box.xpath(\".//div[@data-cid]/@data-cid\").get() yield Request(self.prd_size_url.format(value=data_jkid,","xp_url in response.xpath(\"//div[@class='yy toa']//a/@href\"): tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\"EN\", \"CH\"), callback=self.parse_list)","'img_url': img_url and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\".//div[@data-jkid]/@data-jkid\").get() data_cid = xp_box.xpath(\".//div[@data-cid]/@data-cid\").get() yield","{ 'brand': brand.replace('-', '') or None, \"purity\": div.xpath(\".//li[1]/text()\").get('').split(u\"：\")[-1].strip(), \"cas\": strip(div.xpath(\".//li[2]//a/text()\").get()), \"cat_no\": div.xpath(\".//li[4]/text()\").get().split(u\"：\")[-1].strip(), \"en_name\":","data_cid = xp_box.xpath(\".//div[@data-cid]/@data-cid\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\"\", meta={\"prd_data\": d}, callback=self.parse_package) next_page =","strip class JkPrdSpider(scrapy.Spider): name = \"jk\" allowed_domains = [\"jkchemical.com\"] base_url = \"http://www.jkchemical.com\" start_urls","response.xpath('//a[contains(text(), \"下一页\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s =","start_urls = map(lambda x: \"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\".format(x), ascii_uppercase) prd_size_url = \"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\" def parse(self, response): for"],"string":"[\n \"div.xpath('.//a[@class=\\\"name\\\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or None, \\\"purity\\\":\",\n \"for package_obj in packages: catalog_price = package_obj.get(\\\"CatalogPrice\\\", {}) dd = { 'brand': d.get('brand'),\",\n \"rel_url), 'img_url': img_url and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get() data_cid = xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get()\",\n \"cid=data_cid, ts=int(time())), body=u\\\"\\\", meta={\\\"prd_data\\\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \\\"下一页\\\")]/@href').get() if next_page: yield\",\n \"= map(lambda x: \\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x), ascii_uppercase) prd_size_url = \\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\" def parse(self, response): for xp_url\",\n \"def parse_package(self, response): s = re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\", response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data',\",\n \"{}) package = first(packages, {}) if package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName')\",\n \"s = re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\", response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data', {}) package =\",\n \"\\\"CH\\\"), callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\") for xp_box in xp_boxes: div\",\n \"from scrapy import Request from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import strip\",\n \"product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name = \\\"jk\\\" allowed_domains = [\\\"jkchemical.com\\\"] base_url =\",\n \"response.meta.get('prd_data', {}) package = first(packages, {}) if package: d['brand'] = d['brand'] or package.get('Product',\",\n \"x: \\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x), ascii_uppercase) prd_size_url = \\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\" def parse(self, response): for xp_url in response.xpath(\\\"//div[@class='yy\",\n \"= re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\", response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data', {}) package = first(packages,\",\n \"yield JkProduct(**d) for package_obj in packages: catalog_price = package_obj.get(\\\"CatalogPrice\\\", {}) dd = {\",\n \"d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\\\"stringFormat\\\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and strip(catalog_price.get('Currency')),\",\n \"callback=self.parse_list) def parse_package(self, response): s = re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\", response.text)[0] packages = json.loads(s) d =\",\n \"d = response.meta.get('prd_data', {}) package = first(packages, {}) if package: d['brand'] = d['brand']\",\n \"Request(tmp_url.replace(\\\"EN\\\", \\\"CH\\\"), callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\") for xp_box in xp_boxes:\",\n \"from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name =\",\n \"rel_url and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get()\",\n \"div = xp_box.xpath(\\\".//div[2][@class='left_right mulu_text']\\\") brand = strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\\\"name\\\"]/@href').get() img_url =\",\n \"if package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in\",\n \"\\\"en_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()), \\\"cn_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url,\",\n \"{}) dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\\\"stringFormat\\\"), 'price': catalog_price and\",\n \"\\\"下一页\\\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s = re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\",\",\n \"next_page), callback=self.parse_list) def parse_package(self, response): s = re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\", response.text)[0] packages = json.loads(s) d\",\n \"mulu_text']\\\") brand = strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\\\"name\\\"]/@href').get() img_url = div.xpath('.//img/@src').get() d =\",\n \"package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in packages:\",\n \"import time from urllib.parse import urljoin import scrapy from more_itertools import first from\",\n \"from time import time from urllib.parse import urljoin import scrapy from more_itertools import\",\n \"xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get() data_cid = xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\\\"\\\", meta={\\\"prd_data\\\": d}, callback=self.parse_package) next_page\",\n \"dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\\\"stringFormat\\\"), 'price': catalog_price and catalog_price.get('Value'),\",\n \"import json import re from string import ascii_uppercase from time import time from\",\n \"urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get() data_cid =\",\n \"= response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\") for xp_box in xp_boxes: div = xp_box.xpath(\\\".//div[2][@class='left_right mulu_text']\\\") brand = strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(),\",\n \"\\\"cn_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url), }\",\n \"name = \\\"jk\\\" allowed_domains = [\\\"jkchemical.com\\\"] base_url = \\\"http://www.jkchemical.com\\\" start_urls = map(lambda x:\",\n \"d.get('cat_no'), 'package': package_obj.get(\\\"stringFormat\\\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and strip(catalog_price.get('Currency')), 'attrs': json.dumps(package_obj),\",\n \"response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\") for xp_box in xp_boxes: div = xp_box.xpath(\\\".//div[2][@class='left_right mulu_text']\\\") brand = strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(), '')\",\n \"\\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\" def parse(self, response): for xp_url in response.xpath(\\\"//div[@class='yy toa']//a/@href\\\"): tmp_url = self.base_url +\",\n \"'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\\\"stringFormat\\\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and\",\n \"ascii_uppercase from time import time from urllib.parse import urljoin import scrapy from more_itertools\",\n \"ascii_uppercase) prd_size_url = \\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\" def parse(self, response): for xp_url in response.xpath(\\\"//div[@class='yy toa']//a/@href\\\"): tmp_url\",\n \"response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data', {}) package = first(packages, {}) if\",\n \"'cat_no': d.get('cat_no'), 'package': package_obj.get(\\\"stringFormat\\\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and strip(catalog_price.get('Currency')), 'attrs':\",\n \"import strip class JkPrdSpider(scrapy.Spider): name = \\\"jk\\\" allowed_domains = [\\\"jkchemical.com\\\"] base_url = \\\"http://www.jkchemical.com\\\"\",\n \"} data_jkid = xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get() data_cid = xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\\\"\\\", meta={\\\"prd_data\\\":\",\n \"import Request from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider):\",\n \"+ xp_url.extract() yield Request(tmp_url.replace(\\\"EN\\\", \\\"CH\\\"), callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\") for\",\n \"ts=int(time())), body=u\\\"\\\", meta={\\\"prd_data\\\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \\\"下一页\\\")]/@href').get() if next_page: yield Request(urljoin(response.url,\",\n \"= self.base_url + xp_url.extract() yield Request(tmp_url.replace(\\\"EN\\\", \\\"CH\\\"), callback=self.parse_list) def parse_list(self, response): xp_boxes =\",\n \"JkPrdSpider(scrapy.Spider): name = \\\"jk\\\" allowed_domains = [\\\"jkchemical.com\\\"] base_url = \\\"http://www.jkchemical.com\\\" start_urls = map(lambda\",\n \"import urljoin import scrapy from more_itertools import first from scrapy import Request from\",\n \"JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name = \\\"jk\\\" allowed_domains = [\\\"jkchemical.com\\\"]\",\n \"and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get() data_cid = xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid,\",\n \"{}).get('BrandName') yield JkProduct(**d) for package_obj in packages: catalog_price = package_obj.get(\\\"CatalogPrice\\\", {}) dd =\",\n \"'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url), } data_jkid =\",\n \"d = { 'brand': brand.replace('-', '') or None, \\\"purity\\\": div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(), \\\"cas\\\": strip(div.xpath(\\\".//li[2]//a/text()\\\").get()), \\\"cat_no\\\":\",\n \"Request from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name\",\n \"{}) if package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj\",\n \"yield Request(tmp_url.replace(\\\"EN\\\", \\\"CH\\\"), callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\") for xp_box in\",\n \"strip(div.xpath(\\\".//li[2]//a/text()\\\").get()), \\\"cat_no\\\": div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(), \\\"en_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()), \\\"cn_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url':\",\n \"div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(), \\\"cas\\\": strip(div.xpath(\\\".//li[2]//a/text()\\\").get()), \\\"cat_no\\\": div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(), \\\"en_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()), \\\"cn_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()), 'prd_url': rel_url and urljoin(response.url,\",\n \"more_itertools import first from scrapy import Request from product_spider.items import JkProduct, JKPackage from\",\n \"strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()), \\\"cn_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url),\",\n \"= xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\\\"\\\", meta={\\\"prd_data\\\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(),\",\n \"packages: catalog_price = package_obj.get(\\\"CatalogPrice\\\", {}) dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package':\",\n \"yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\\\"\\\", meta={\\\"prd_data\\\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \\\"下一页\\\")]/@href').get() if\",\n \"next_page = response.xpath('//a[contains(text(), \\\"下一页\\\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response):\",\n \"string import ascii_uppercase from time import time from urllib.parse import urljoin import scrapy\",\n \"import ascii_uppercase from time import time from urllib.parse import urljoin import scrapy from\",\n \"d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in packages: catalog_price\",\n \"meta={\\\"prd_data\\\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \\\"下一页\\\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list)\",\n \"packages = json.loads(s) d = response.meta.get('prd_data', {}) package = first(packages, {}) if package:\",\n \"import first from scrapy import Request from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions\",\n \"scrapy import Request from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import strip class\",\n \"scrapy from more_itertools import first from scrapy import Request from product_spider.items import JkProduct,\",\n \"json import re from string import ascii_uppercase from time import time from urllib.parse\",\n \"= [\\\"jkchemical.com\\\"] base_url = \\\"http://www.jkchemical.com\\\" start_urls = map(lambda x: \\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x), ascii_uppercase) prd_size_url =\",\n \"xp_boxes = response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\") for xp_box in xp_boxes: div = xp_box.xpath(\\\".//div[2][@class='left_right mulu_text']\\\") brand =\",\n \"in xp_boxes: div = xp_box.xpath(\\\".//div[2][@class='left_right mulu_text']\\\") brand = strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\\\"name\\\"]/@href').get()\",\n \"= \\\"jk\\\" allowed_domains = [\\\"jkchemical.com\\\"] base_url = \\\"http://www.jkchemical.com\\\" start_urls = map(lambda x: \\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x),\",\n \"parse_package(self, response): s = re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\", response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data', {})\",\n \"{ 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\\\"stringFormat\\\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price\",\n \"re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\", response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data', {}) package = first(packages, {})\",\n \"callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \\\"下一页\\\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self,\",\n \"re from string import ascii_uppercase from time import time from urllib.parse import urljoin\",\n \"urljoin import scrapy from more_itertools import first from scrapy import Request from product_spider.items\",\n \"response.xpath(\\\"//div[@class='yy toa']//a/@href\\\"): tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\\\"EN\\\", \\\"CH\\\"), callback=self.parse_list) def parse_list(self,\",\n \"or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in packages: catalog_price = package_obj.get(\\\"CatalogPrice\\\", {})\",\n \"base_url = \\\"http://www.jkchemical.com\\\" start_urls = map(lambda x: \\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x), ascii_uppercase) prd_size_url = \\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\" def\",\n \"from urllib.parse import urljoin import scrapy from more_itertools import first from scrapy import\",\n \"= d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in packages: catalog_price =\",\n \"class JkPrdSpider(scrapy.Spider): name = \\\"jk\\\" allowed_domains = [\\\"jkchemical.com\\\"] base_url = \\\"http://www.jkchemical.com\\\" start_urls =\",\n \"package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in packages: catalog_price = package_obj.get(\\\"CatalogPrice\\\", {}) dd\",\n \"body=u\\\"\\\", meta={\\\"prd_data\\\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \\\"下一页\\\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page),\",\n \"catalog_price = package_obj.get(\\\"CatalogPrice\\\", {}) dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\\\"stringFormat\\\"),\",\n \"for xp_box in xp_boxes: div = xp_box.xpath(\\\".//div[2][@class='left_right mulu_text']\\\") brand = strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(), '') rel_url\",\n \"if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s = re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\", response.text)[0]\",\n \"first(packages, {}) if package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for\",\n \"\\\"purity\\\": div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(), \\\"cas\\\": strip(div.xpath(\\\".//li[2]//a/text()\\\").get()), \\\"cat_no\\\": div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(), \\\"en_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()), \\\"cn_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()), 'prd_url': rel_url and\",\n \"brand = strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\\\"name\\\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = {\",\n \"Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\\\"\\\", meta={\\\"prd_data\\\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \\\"下一页\\\")]/@href').get() if next_page:\",\n \"time from urllib.parse import urljoin import scrapy from more_itertools import first from scrapy\",\n \"img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or None, \\\"purity\\\": div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(),\",\n \"package_obj.get(\\\"CatalogPrice\\\", {}) dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\\\"stringFormat\\\"), 'price': catalog_price\",\n \"Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s = re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\", response.text)[0] packages = json.loads(s)\",\n \"= { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\\\"stringFormat\\\"), 'price': catalog_price and catalog_price.get('Value'), 'currency':\",\n \"def parse(self, response): for xp_url in response.xpath(\\\"//div[@class='yy toa']//a/@href\\\"): tmp_url = self.base_url + xp_url.extract()\",\n \"= \\\"http://www.jkchemical.com\\\" start_urls = map(lambda x: \\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x), ascii_uppercase) prd_size_url = \\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\" def parse(self,\",\n \"= div.xpath('.//a[@class=\\\"name\\\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or None,\",\n \"package_obj in packages: catalog_price = package_obj.get(\\\"CatalogPrice\\\", {}) dd = { 'brand': d.get('brand'), 'cat_no':\",\n \"'package': package_obj.get(\\\"stringFormat\\\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and strip(catalog_price.get('Currency')), 'attrs': json.dumps(package_obj), }\",\n \"first from scrapy import Request from product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import\",\n \"img_url), } data_jkid = xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get() data_cid = xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\\\"\\\",\",\n \"xp_box.xpath(\\\".//div[2][@class='left_right mulu_text']\\\") brand = strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\\\"name\\\"]/@href').get() img_url = div.xpath('.//img/@src').get() d\",\n \"tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\\\"EN\\\", \\\"CH\\\"), callback=self.parse_list) def parse_list(self, response): xp_boxes\",\n \"'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and strip(catalog_price.get('Currency')), 'attrs': json.dumps(package_obj), } yield JKPackage(**dd)\",\n \"allowed_domains = [\\\"jkchemical.com\\\"] base_url = \\\"http://www.jkchemical.com\\\" start_urls = map(lambda x: \\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x), ascii_uppercase) prd_size_url\",\n \"= json.loads(s) d = response.meta.get('prd_data', {}) package = first(packages, {}) if package: d['brand']\",\n \"= xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get() data_cid = xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\\\"\\\", meta={\\\"prd_data\\\": d}, callback=self.parse_package)\",\n \"package_obj.get(\\\"stringFormat\\\"), 'price': catalog_price and catalog_price.get('Value'), 'currency': catalog_price and strip(catalog_price.get('Currency')), 'attrs': json.dumps(package_obj), } yield\",\n \"div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(), \\\"en_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()), \\\"cn_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url and\",\n \"xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\\\"\\\", meta={\\\"prd_data\\\": d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \\\"下一页\\\")]/@href').get()\",\n \"= response.xpath('//a[contains(text(), \\\"下一页\\\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s\",\n \"self.base_url + xp_url.extract() yield Request(tmp_url.replace(\\\"EN\\\", \\\"CH\\\"), callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\")\",\n \"parse_list(self, response): xp_boxes = response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\") for xp_box in xp_boxes: div = xp_box.xpath(\\\".//div[2][@class='left_right mulu_text']\\\")\",\n \"brand.replace('-', '') or None, \\\"purity\\\": div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(), \\\"cas\\\": strip(div.xpath(\\\".//li[2]//a/text()\\\").get()), \\\"cat_no\\\": div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(), \\\"en_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()), \\\"cn_name\\\":\",\n \"= response.meta.get('prd_data', {}) package = first(packages, {}) if package: d['brand'] = d['brand'] or\",\n \"d}, callback=self.parse_package) next_page = response.xpath('//a[contains(text(), \\\"下一页\\\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def\",\n \"product_spider.items import JkProduct, JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name = \\\"jk\\\"\",\n \"import re from string import ascii_uppercase from time import time from urllib.parse import\",\n \"\\\"http://www.jkchemical.com\\\" start_urls = map(lambda x: \\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x), ascii_uppercase) prd_size_url = \\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\" def parse(self, response):\",\n \"\\\"cat_no\\\": div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(), \\\"en_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()), \\\"cn_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url\",\n \"data_jkid = xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get() data_cid = xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\\\"\\\", meta={\\\"prd_data\\\": d},\",\n \"parse(self, response): for xp_url in response.xpath(\\\"//div[@class='yy toa']//a/@href\\\"): tmp_url = self.base_url + xp_url.extract() yield\",\n \"next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s = re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\", response.text)[0] packages\",\n \"d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d) for package_obj in packages: catalog_price = package_obj.get(\\\"CatalogPrice\\\",\",\n \"= package_obj.get(\\\"CatalogPrice\\\", {}) dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'), 'package': package_obj.get(\\\"stringFormat\\\"), 'price':\",\n \"= first(packages, {}) if package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield JkProduct(**d)\",\n \"from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name = \\\"jk\\\" allowed_domains = [\\\"jkchemical.com\\\"] base_url\",\n \"response): for xp_url in response.xpath(\\\"//div[@class='yy toa']//a/@href\\\"): tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\\\"EN\\\",\",\n \"for xp_url in response.xpath(\\\"//div[@class='yy toa']//a/@href\\\"): tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\\\"EN\\\", \\\"CH\\\"),\",\n \"import scrapy from more_itertools import first from scrapy import Request from product_spider.items import\",\n \"[\\\"jkchemical.com\\\"] base_url = \\\"http://www.jkchemical.com\\\" start_urls = map(lambda x: \\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x), ascii_uppercase) prd_size_url = \\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\"\",\n \"rel_url = div.xpath('.//a[@class=\\\"name\\\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or\",\n \"import JkProduct, JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name = \\\"jk\\\" allowed_domains\",\n \"strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url), } data_jkid\",\n \"and urljoin(response.url, rel_url), 'img_url': img_url and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get() data_cid\",\n \"'brand': brand.replace('-', '') or None, \\\"purity\\\": div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(), \\\"cas\\\": strip(div.xpath(\\\".//li[2]//a/text()\\\").get()), \\\"cat_no\\\": div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(), \\\"en_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()),\",\n \"= \\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\" def parse(self, response): for xp_url in response.xpath(\\\"//div[@class='yy toa']//a/@href\\\"): tmp_url = self.base_url\",\n \"strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\\\"name\\\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-',\",\n \"or None, \\\"purity\\\": div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(), \\\"cas\\\": strip(div.xpath(\\\".//li[2]//a/text()\\\").get()), \\\"cat_no\\\": div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(), \\\"en_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()), \\\"cn_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()), 'prd_url':\",\n \"yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s = re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\", response.text)[0] packages =\",\n \"response): xp_boxes = response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\") for xp_box in xp_boxes: div = xp_box.xpath(\\\".//div[2][@class='left_right mulu_text']\\\") brand\",\n \"JkProduct, JKPackage from product_spider.utils.functions import strip class JkPrdSpider(scrapy.Spider): name = \\\"jk\\\" allowed_domains =\",\n \"map(lambda x: \\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x), ascii_uppercase) prd_size_url = \\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\" def parse(self, response): for xp_url in\",\n \"\\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x), ascii_uppercase) prd_size_url = \\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\" def parse(self, response): for xp_url in response.xpath(\\\"//div[@class='yy toa']//a/@href\\\"):\",\n \"response): s = re.findall(r\\\"(?<=\\\\().+(?=\\\\))\\\", response.text)[0] packages = json.loads(s) d = response.meta.get('prd_data', {}) package\",\n \"in response.xpath(\\\"//div[@class='yy toa']//a/@href\\\"): tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\\\"EN\\\", \\\"CH\\\"), callback=self.parse_list) def\",\n \"time import time from urllib.parse import urljoin import scrapy from more_itertools import first\",\n \"toa']//a/@href\\\"): tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\\\"EN\\\", \\\"CH\\\"), callback=self.parse_list) def parse_list(self, response):\",\n \"xp_url.extract() yield Request(tmp_url.replace(\\\"EN\\\", \\\"CH\\\"), callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\") for xp_box\",\n \"'') rel_url = div.xpath('.//a[@class=\\\"name\\\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '')\",\n \"xp_boxes: div = xp_box.xpath(\\\".//div[2][@class='left_right mulu_text']\\\") brand = strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\\\"name\\\"]/@href').get() img_url\",\n \"urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get() data_cid = xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())),\",\n \"urllib.parse import urljoin import scrapy from more_itertools import first from scrapy import Request\",\n \"= strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\\\"name\\\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand':\",\n \"JkProduct(**d) for package_obj in packages: catalog_price = package_obj.get(\\\"CatalogPrice\\\", {}) dd = { 'brand':\",\n \"def parse_list(self, response): xp_boxes = response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\") for xp_box in xp_boxes: div = xp_box.xpath(\\\".//div[2][@class='left_right\",\n \"= div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or None, \\\"purity\\\": div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(), \\\"cas\\\":\",\n \"prd_size_url = \\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\" def parse(self, response): for xp_url in response.xpath(\\\"//div[@class='yy toa']//a/@href\\\"): tmp_url =\",\n \"\\\"cas\\\": strip(div.xpath(\\\".//li[2]//a/text()\\\").get()), \\\"cat_no\\\": div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(), \\\"en_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()), \\\"cn_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()), 'prd_url': rel_url and urljoin(response.url, rel_url),\",\n \"'') or None, \\\"purity\\\": div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(), \\\"cas\\\": strip(div.xpath(\\\".//li[2]//a/text()\\\").get()), \\\"cat_no\\\": div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(), \\\"en_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()), \\\"cn_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()),\",\n \"from more_itertools import first from scrapy import Request from product_spider.items import JkProduct, JKPackage\",\n \"= xp_box.xpath(\\\".//div[2][@class='left_right mulu_text']\\\") brand = strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(), '') rel_url = div.xpath('.//a[@class=\\\"name\\\"]/@href').get() img_url = div.xpath('.//img/@src').get()\",\n \"in packages: catalog_price = package_obj.get(\\\"CatalogPrice\\\", {}) dd = { 'brand': d.get('brand'), 'cat_no': d.get('cat_no'),\",\n \"xp_box in xp_boxes: div = xp_box.xpath(\\\".//div[2][@class='left_right mulu_text']\\\") brand = strip(div.xpath('.//li[@id=\\\"ctl00_cph_Content_li_lt_Brand\\\"]/text()').get(), '') rel_url =\",\n \"from string import ascii_uppercase from time import time from urllib.parse import urljoin import\",\n \"json.loads(s) d = response.meta.get('prd_data', {}) package = first(packages, {}) if package: d['brand'] =\",\n \"= { 'brand': brand.replace('-', '') or None, \\\"purity\\\": div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(), \\\"cas\\\": strip(div.xpath(\\\".//li[2]//a/text()\\\").get()), \\\"cat_no\\\": div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(),\",\n \"None, \\\"purity\\\": div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(), \\\"cas\\\": strip(div.xpath(\\\".//li[2]//a/text()\\\").get()), \\\"cat_no\\\": div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(), \\\"en_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']/text()\\\").get()), \\\"cn_name\\\": strip(xp_box.xpath(\\\".//a[@class='name']//span[1]/text()\\\").get()), 'prd_url': rel_url\",\n \"callback=self.parse_list) def parse_list(self, response): xp_boxes = response.xpath(\\\"//table[@id]//div[@class='PRODUCT_box']\\\") for xp_box in xp_boxes: div =\",\n \"div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or None, \\\"purity\\\": div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(), \\\"cas\\\": strip(div.xpath(\\\".//li[2]//a/text()\\\").get()),\",\n \"package = first(packages, {}) if package: d['brand'] = d['brand'] or package.get('Product', {}).get('BrandName') yield\",\n \"\\\"jk\\\" allowed_domains = [\\\"jkchemical.com\\\"] base_url = \\\"http://www.jkchemical.com\\\" start_urls = map(lambda x: \\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x), ascii_uppercase)\",\n \"img_url and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get() data_cid = xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get() yield Request(self.prd_size_url.format(value=data_jkid,\",\n \"xp_url in response.xpath(\\\"//div[@class='yy toa']//a/@href\\\"): tmp_url = self.base_url + xp_url.extract() yield Request(tmp_url.replace(\\\"EN\\\", \\\"CH\\\"), callback=self.parse_list)\",\n \"'img_url': img_url and urljoin(response.url, img_url), } data_jkid = xp_box.xpath(\\\".//div[@data-jkid]/@data-jkid\\\").get() data_cid = xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get() yield\",\n \"{ 'brand': brand.replace('-', '') or None, \\\"purity\\\": div.xpath(\\\".//li[1]/text()\\\").get('').split(u\\\"：\\\")[-1].strip(), \\\"cas\\\": strip(div.xpath(\\\".//li[2]//a/text()\\\").get()), \\\"cat_no\\\": div.xpath(\\\".//li[4]/text()\\\").get().split(u\\\"：\\\")[-1].strip(), \\\"en_name\\\":\",\n \"data_cid = xp_box.xpath(\\\".//div[@data-cid]/@data-cid\\\").get() yield Request(self.prd_size_url.format(value=data_jkid, cid=data_cid, ts=int(time())), body=u\\\"\\\", meta={\\\"prd_data\\\": d}, callback=self.parse_package) next_page =\",\n \"strip class JkPrdSpider(scrapy.Spider): name = \\\"jk\\\" allowed_domains = [\\\"jkchemical.com\\\"] base_url = \\\"http://www.jkchemical.com\\\" start_urls\",\n \"response.xpath('//a[contains(text(), \\\"下一页\\\")]/@href').get() if next_page: yield Request(urljoin(response.url, next_page), callback=self.parse_list) def parse_package(self, response): s =\",\n \"start_urls = map(lambda x: \\\"http://www.jkchemical.com/CH/products/index/ProductName/{0}.html\\\".format(x), ascii_uppercase) prd_size_url = \\\"http://www.jkchemical.com/Controls/Handler/GetPackAgeJsonp.ashx?callback=py27&value={value}&cid={cid}&type=product&_={ts}\\\" def parse(self, response): for\"\n]","isConversational":false}}},{"rowIdx":1489,"cells":{"ngram":{"kind":"list like","value":["todo check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2]","if not self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) >","self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 # set ego vehicle","# assert 0 <= alpha <= 1.1 # r_safe_leader = w_lateral * alpha","+ 2] = veh.pos_lat self.observation[name * 4 + 3] = veh.acce else: self.observation[name","+ 2] = 4.8 self.observation[name * 4 + 3] = 0 # todo","+ 1] = veh.speed self.observation[name * 4 + 2] = veh.pos_lat self.observation[name *","<= alpha <= 1.1 # # r_safe_tgtleader = w_lateral * alpha + w_longi","0:light; 1:medium; 2:dense :return: initial observation \"\"\" self.seed(randomseed) if sumoseed is None: self.sumoseed","= tlane self.ego.is_ego = 1 # set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0)","LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None): # todo check traffic flow density","action[0] = 1: accelerate action[0] = -1: decelerate action[0] = 0: use SUMO","'--lanechange.duration', str(3), # using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model'","2 * delta_A2 * delta_D2) TTC2 = TTC2 / delta_A2 if self.lateral_action ==","wc1 * self.ego.acce ** 2 + wc2 * self.ego.delta_acce ** 2 # reward","0, 0], # target lane leader # [0, 0, 0]] # target lane","in progress; 0:change back to original line; 1:lane change to target lane; 2:keep","= self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader)","and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left',","action[0] = 0: follow original lane leader action[0] = 1: follow closer leader","not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name,","action self.done = True # (bool): whether the episode has ended, in which","is not None: self.observation[name * 4 + 0] = veh.lanePos self.observation[name * 4","r_effi_all = r_time + r_speed + r_effi # reward related to safety w_lateral","env' self.timestep += 1 # lateral control------------------------- # episode in progress; 0:change back","'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else:","abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2 + 2","of reward returned after previous action self.done = True # (bool): whether the","['--seed', str(seed)] # gui if gui is True: self.sumoBinary += '-gui' self.sumoCmd =","assert self.done is False, 'self.done is not False' assert action is not None,","[self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary] +","and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat',","abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0 # #","self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext)","if self.ego.leaderID is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha","assert self.egoID in self.vehID_tuple_all, 'vehicle not in env' self.timestep += 1 # lateral","'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed is None: self.sumoCmd +=","# r_safe_tgtleader = w_lateral * alpha + w_longi * (1 - alpha) *","occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done = True # print('reset","TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2 + 2 * delta_A2 * delta_D2)","def _updateObservationSingle(self, name, veh): \"\"\" :param name: 0:ego; 1:leader; 2:target leader; 3:target follower","delta_D2) TTC2 = TTC2 / delta_A2 if self.lateral_action == 1 and 0 <","# # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) /","self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else:","1 ws = 1 we = 1 # reward related to comfort r_comf","<= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID is not","= np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1","r_speed + r_effi # reward related to safety w_lateral = 1 w_longi =","self.veh_dict.keys(): # must ensure safety in preStpe self.preStep() if self.timestep > 5000: raise","current lateral position if action_lateral == 2: self.is_success = self.ego.changeLane(True, -1, self.rd) #","# reward related to efficiency r_time = - wt * self.timestep r_speed =","self.sumoBinary = \"/usr/local/Cellar/sumo/1.2.0/bin/sumo\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3), # using 'Simple","4 + 1] = self.observation[1] self.observation[name * 4 + 2] = 4.8 self.observation[name","`reset()` outside env!! to reset this environment's state. Accepts an action and returns","gym import spaces import numpy as np from env.IDM import IDM from env.Road","original lane leader action[0] = 1: follow target lane leader **important**: orginal/target lane","wc1 = 1 wc2 = 1 wt = 1 ws = 1 we","self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time + r_speed","5000 timesteps') assert self.egoID in self.vehID_tuple_all, \"cannot start training while ego is not","math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action != 1 and","* self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time + r_speed + r_effi # reward","id=None, traffic=1, gui=False, seed=None): # todo check traffic flow density if traffic ==","# compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce","0:ego; 1:leader; 2:target leader; 3:target follower :param id: vehicle id corresponding to name","self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \"\"\" :param","= 0 # todo check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1]","0 if self.lateral_action == 1: # lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)","# target lane follower self.observation = np.empty(20) self.reward = None # (float) :","undefined results self.info = { 'resetFlag': 0} # (dict): contains auxiliary diagnostic information","list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \"\"\" :param name: 0:ego; 1:leader; 2:target","0 <= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe","= self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos -","wc2 * self.ego.delta_acce ** 2 # reward related to efficiency r_time = -","ego vehicle out of env if self.egoID not in self.vehID_tuple_all: self.done = True","= 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must","0, 0]] # target lane follower self.observation = np.empty(20) self.reward = None #","not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id","self.done = True # print('reset on: self.ego not in env:', self.egoID not in","# todo check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed","self.timestep += 1 # lateral control------------------------- # episode in progress; 0:change back to","the environment's dynamics. When end of episode is reached, call `reset()` outside env!!","0 < TTC2 < 2: r_long_t = - math.exp(-2 * TTC2 + 5)","r_safe = w_lateral * (r_lat_c + r_lat_t) + w_longi * (r_long_c+ r_long_t) #","# self.ego.dis2tgtLane) # ego vehicle out of env if self.egoID not in self.vehID_tuple_all:","# print(acceNext) vNext = self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update","= w_lateral * alpha + w_longi * (1 - alpha) * abs( #","in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh):","self.done, self.info def seed(self, seed=None): if seed is None: self.randomseed = datetime.datetime.now().microsecond else:","TTC2 + 5) else: r_long_t = 0 if self.lateral_action == 1: # lane","< TTC < 2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c = 0 if","must be converted to str(float/int), instead of '3.0' self.sumoBinary = \"/usr/local/Cellar/sumo/1.2.0/bin/sumo\" self.sumoCmd =","#abort lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <=","preStpe self.preStep() if self.timestep > 5000: raise Exception('cannot find ego after 5000 timesteps')","ego after 5000 timesteps') assert self.egoID in self.vehID_tuple_all, \"cannot start training while ego","- self.ego.acce if delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC =","ego may change lateral: action[1] = 1: lane change action[1] = 0: abort","wc2 = 1 wt = 1 ws = 1 we = 1 #","leader # [0, 0, 0]] # target lane follower self.observation = np.empty(20) self.reward","= 2 # self.observation = [[0, 0, 0], # ego lane position and","on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too close to ramp entrance","back to ego's original lane if action_lateral == 0: # and abs(self.ego.pos_lat -","returns a tuple (observation, reward, done, info). Args: action (object): longitudinal0: action[0] =","end of episode is reached, call `reset()` outside env!! to reset this environment's","tlane self.ego.is_ego = 1 # set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor","# reward related to safety w_lateral = 1 w_longi = 1 if self.ego.leaderID","2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action != 1 and 0 <","is not None: while self.egoID not in self.veh_dict.keys(): # must ensure safety in","** 2 + wc2 * self.ego.delta_acce ** 2 # reward related to efficiency","r_lat_c = 0 if self.ego.targetLeaderID is not None: # compute longitudinal time gap","traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \"\"\"Run one timestep of the","in env if self.egoID is not None: while self.egoID not in self.veh_dict.keys(): #","in self.vehID_tuple_all, \"cannot start training while ego is not in env\" self.done =","lane leader action[0] = 1: follow closer leader longitudinal2: action[0] = 0: follow","0 self.lateral_action = 2 # self.observation = [[0, 0, 0], # ego lane","in self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done","# # print('alpha', alpha) # assert 0 <= alpha <= 1.1 # #","_updateObservationSingle(self, name, veh): \"\"\" :param name: 0:ego; 1:leader; 2:target leader; 3:target follower :param","decelerate action[0] = 0: use SUMO default action[0] = others: acce = 0.0","- (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 *","change back to original lane action[1] = 2: keep in current lateral position","of env if self.egoID not in self.vehID_tuple_all: self.done = True # print('reset on:","math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action == 0: #abort lane change alpha","is False, 'self.done is not False' assert action is not None, 'action is","updateReward2(self): wc1 = 1 wc2 = 1 wt = 1 ws = 1","to str(float/int), instead of '3.0' self.sumoBinary = \"/usr/local/Cellar/sumo/1.2.0/bin/sumo\" self.sumoCmd = ['-c', self.cfg, #","str(3), # using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length',","print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort","5) else: r_long_t = 0 if self.lateral_action == 1: # lane change alpha","0 <= alpha <= 1.1 # # r_safe_tgtleader = w_lateral * alpha +","follow original lane leader action[0] = 1: follow closer leader longitudinal2: action[0] =","3 action_lateral = action % 3 self.lateral_action = action_lateral # action_longi = action[0]","r_safe_leader + r_safe_tgtleader # total reward r_total = r_comf + r_effi_all + r_safe","str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed is","= 0 if self.ego.targetLeaderID is not None: # compute longitudinal time gap delta_V2","action[0] = 1: follow closer leader longitudinal2: action[0] = 0: follow original lane","sumo/tools into python environment if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools)","-(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change, change back to ego's original lane","* self.timestep r_speed = ws * (self.ego.speed - self.ego_speedLimit) r_effi = we *","follow original lane leader action[0] = 1: follow target lane leader **important**: orginal/target","info). Args: action (object): longitudinal0: action[0] = 1: accelerate action[0] = -1: decelerate","def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] =","0 if self.lateral_action == 0: #abort lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)","self.timestep r_speed = ws * (self.ego.speed - self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane","if traffic == 0: # average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic","/ 3.2 # # print('alpha', alpha) # assert 0 <= alpha <= 1.1","'3.0' self.sumoBinary = \"/usr/local/Cellar/sumo/1.2.0/bin/sumo\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3), # using","return undefined results self.info = { 'resetFlag': 0} # (dict): contains auxiliary diagnostic","2: self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) #","abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert","entrance if self.ego.dis2entrance < 10.0: self.done = True # print('reset on: too close","change, change back to ego's original lane if action_lateral == 0: # and","must be string, if float/int, must be converted to str(float/int), instead of '3.0'","self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0 # # # r_safe","Road from env.Vehicle import Vehicle import math # add sumo/tools into python environment","False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 # set ego","self.ego.pos_lat) # keep current lateral position if action_lateral == 2: self.is_success = self.ego.changeLane(True,","lateral: action[1] = 1: lane change action[1] = 0: abort lane change, change","1 if self.ego.leaderID is not None: # compute longitudinal time gap delta_V =","r_lat_t) + w_longi * (r_long_c+ r_long_t) # # if self.ego.leaderID is not None:","float/int, must be converted to str(float/int), instead of '3.0' self.sumoBinary = \"/usr/local/Cellar/sumo/1.2.0/bin/sumo\" self.sumoCmd","of episode is reached, call `reset()` outside env!! to reset this environment's state.","self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if float/int, must be converted","0], # target lane leader # [0, 0, 0]] # target lane follower","- math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action == 0: #abort lane change","# abort lane change, change back to ego's original lane if action_lateral ==","[0, 0, 0]] # target lane follower self.observation = np.empty(20) self.reward = None","0]] # target lane follower self.observation = np.empty(20) self.reward = None # (float)","self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) #","- self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if","environment's state. Accepts an action and returns a tuple (observation, reward, done, info).","[0, 0, 0], # target lane leader # [0, 0, 0]] # target","an action and returns a tuple (observation, reward, done, info). Args: action (object):","vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode","<= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID","not change despite the lateral position of the ego may change lateral: action[1]","self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self):","1: follow target lane leader **important**: orginal/target lane leader will not change despite","seed is None: self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed', str(seed)] # gui","self.done = True # (bool): whether the episode has ended, in which case","vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if float/int, must be","= 0 # # # r_safe = r_safe_leader + r_safe_tgtleader # total reward","# print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) #","change to target lane; 2:keep current # lane change to target lane if","- wt * self.timestep r_speed = ws * (self.ego.speed - self.ego_speedLimit) r_effi =","abort lane change, change back to original lane action[1] = 2: keep in","# arguments must be string, if float/int, must be converted to str(float/int), instead","else: r_lat_c = 0 if self.ego.targetLeaderID is not None: # compute longitudinal time","= 0.0 longitudinal1: action[0] = 0: follow original lane leader action[0] = 1:","# print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change, change back to ego's","r_safe return r_total def is_done(self): # lane change successfully executed, episode ends, reset","debugging, and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def","episode has ended, in which case further step() calls will return undefined results","self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation() return self.observation return","abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_t =","= None self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all = () self.egoID =","time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2","acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID,","r_comf + r_effi_all + r_safe return r_total def is_done(self): # lane change successfully","self.ego.dis2entrance < 10.0: self.done = True # print('reset on: too close to ramp","# self.observation = [[0, 0, 0], # ego lane position and speed #","IDM from env.Road import Road from env.Vehicle import Vehicle import math # add","dynamics. When end of episode is reached, call `reset()` outside env!! to reset","def is_done(self): # lane change successfully executed, episode ends, reset env # todo","'--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed","4 + 0] = veh.lanePos self.observation[name * 4 + 1] = veh.speed self.observation[name",":return: initial observation \"\"\" self.seed(randomseed) if sumoseed is None: self.sumoseed = self.randomseed traci.close()","name :return: \"\"\" if veh is not None: self.observation[name * 4 + 0]","entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out of env if self.egoID not","leader # [0, 0, 0], # target lane leader # [0, 0, 0]]","to target lane if not self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat","/ self.ego.dis2entrance r_effi_all = r_time + r_speed + r_effi # reward related to","** 2 + 2 * delta_A2 * delta_D2) TTC2 = TTC2 / delta_A2","= 1 ws = 1 we = 1 # reward related to comfort","(object): longitudinal0: action[0] = 1: accelerate action[0] = -1: decelerate action[0] = 0:","lane position and speed # [0, 0, 0], # leader # [0, 0,","and speed # [0, 0, 0], # leader # [0, 0, 0], #","abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <= alpha <= 1.1 #","# else: # r_safe_tgtleader = 0 # # # r_safe = r_safe_leader +","TTC/delta_A if self.lateral_action != 1 and 0 < TTC < 2: r_long_c =","+ 2 * delta_A2 * delta_D2) TTC2 = TTC2 / delta_A2 if self.lateral_action","gym from gym import spaces import numpy as np from env.IDM import IDM","self.updateReward() return self.observation, self.reward, self.done, self.info def seed(self, seed=None): if seed is None:","self.observation[name * 4 + 0] = veh.lanePos self.observation[name * 4 + 1] =","id: vehicle id corresponding to name :return: \"\"\" if veh is not None:","self.is_success: self.done = True # print('reset on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane)","- 0.5*self.rd.laneWidth)) # abort lane change, change back to ego's original lane if","keep in current lateral position Returns: described in __init__ \"\"\" action_longi = action","# self.tgtLane = tgtlane self.is_success = False self.collision_num = 0 self.lateral_action = 2","= self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 # set ego vehicle speed","= -delta_V2 - math.sqrt(delta_V2 ** 2 + 2 * delta_A2 * delta_D2) TTC2","print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep current lateral position if action_lateral","efficiency r_time = - wt * self.timestep r_speed = ws * (self.ego.speed -","self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd =","total reward r_total = r_comf + r_effi_all + r_safe return r_total def is_done(self):","None: while self.egoID not in self.veh_dict.keys(): # must ensure safety in preStpe self.preStep()","w_lateral = 1 w_longi = 1 if self.ego.leaderID is not None: # compute","{} self.vehID_tuple_all = () self.egoID = id self.ego = None # self.tgtLane =","# self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0 # # #","in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id not","reward r_total = r_comf + r_effi_all + r_safe return r_total def is_done(self): #","__init__ \"\"\" action_longi = action // 3 action_lateral = action % 3 self.lateral_action","self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self):","False' assert action is not None, 'action is None' assert self.egoID in self.vehID_tuple_all,","2] = veh.pos_lat self.observation[name * 4 + 3] = veh.acce else: self.observation[name *","self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if","ego appears in env if self.egoID is not None: while self.egoID not in","will not change despite the lateral position of the ego may change lateral:","change to target lane if not self.is_success: if action_lateral == 1: # and","if self.egoID is not None: while self.egoID not in self.veh_dict.keys(): # must ensure","# [0, 0, 0]] # target lane follower self.observation = np.empty(20) self.reward =","self.done is False, 'self.done is not False' assert action is not None, 'action","in self.vehID_tuple_all, 'vehicle not in env' self.timestep += 1 # lateral control------------------------- #","reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \"\"\" reset env :param id: ego","tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\"please declare environment variable 'SUMO_HOME'\") import","delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0: TTC2 = - abs(delta_D2)","training while ego is not in env\" self.done = False self.ego = self.veh_dict[self.egoID]","action[1] assert self.done is False, 'self.done is not False' assert action is not","env\" self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1","# action_lateral = action[1] assert self.done is False, 'self.done is not False' assert","self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC","updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2 = 1 wt =","self.veh_dict) def _updateObservationSingle(self, name, veh): \"\"\" :param name: 0:ego; 1:leader; 2:target leader; 3:target","else: r_lat_t = 0 r_safe = w_lateral * (r_lat_c + r_lat_t) + w_longi","= None # (float) : amount of reward returned after previous action self.done","1: accelerate action[0] = -1: decelerate action[0] = 0: use SUMO default action[0]","alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID is","* self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action != 1 and 0 < TTC","* self.rd.laneWidth - self.ego.pos_lat) # keep current lateral position if action_lateral == 2:","= TTC/delta_A if self.lateral_action != 1 and 0 < TTC < 2: r_long_c","self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0: TTC2 = - abs(delta_D2) / delta_V2","updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce","(float) : amount of reward returned after previous action self.done = True #","self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done = True # print('reset on:","= veh.pos_lat self.observation[name * 4 + 3] = veh.acce else: self.observation[name * 4","== 2: # average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14","mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj =","1 wc2 = 1 wt = 1 ws = 1 we = 1","= 2: keep in current lateral position Returns: described in __init__ \"\"\" action_longi","== 2: self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi)","target lane leader **important**: orginal/target lane leader will not change despite the lateral","reward, done, info). Args: action (object): longitudinal0: action[0] = 1: accelerate action[0] =","action[1] = 1: lane change action[1] = 0: abort lane change, change back",":param id: ego vehicle id :param tfc: int. 0:light; 1:medium; 2:dense :return: initial","= 0: use SUMO default action[0] = others: acce = 0.0 longitudinal1: action[0]","if self.ego.leaderID is not None: # compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed","to name :return: \"\"\" if veh is not None: self.observation[name * 4 +","as np from env.IDM import IDM from env.Road import Road from env.Vehicle import","is None' assert self.egoID in self.vehID_tuple_all, 'vehicle not in env' self.timestep += 1","self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha =","if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat","diagnostic information (helpful for debugging, and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space =","import traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False,","= spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if veh_id","leader action[0] = 1: follow target lane leader **important**: orginal/target lane leader will","self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() #","= 1: accelerate action[0] = -1: decelerate action[0] = 0: use SUMO default","print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 #","1:medium; 2:dense :return: initial observation \"\"\" self.seed(randomseed) if sumoseed is None: self.sumoseed =","traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if","veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \"\"\" :param name: 0:ego;","0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check","environment variable 'SUMO_HOME'\") import traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def __init__(self,","randomness if seed is None: self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed', str(seed)]","= () self.egoID = id self.ego = None # self.tgtLane = tgtlane self.is_success","None self.veh_dict = {} self.vehID_tuple_all = () self.egoID = id self.ego = None","os import sys import random import datetime import gym from gym import spaces","change, dis2targetlane:', # self.ego.dis2tgtLane) # too close to ramp entrance if self.ego.dis2entrance <","-self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2 = 1 wt = 1 ws","spaces import numpy as np from env.IDM import IDM from env.Road import Road","self.observation = np.empty(20) self.reward = None # (float) : amount of reward returned","0, 0], # ego lane position and speed # [0, 0, 0], #","1: # lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0","amount of reward returned after previous action self.done = True # (bool): whether","further step() calls will return undefined results self.info = { 'resetFlag': 0} #","None # (float) : amount of reward returned after previous action self.done =","= [[0, 0, 0], # ego lane position and speed # [0, 0,","if self.lateral_action != 1 and 0 < TTC < 2: r_long_c = -","shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if veh_id not in self.veh_dict.keys():","lane change successfully executed, episode ends, reset env # todo modify if self.is_success:","0.5*self.rd.laneWidth)) # abort lane change, change back to ego's original lane if action_lateral","= 1 wc2 = 1 wt = 1 ws = 1 we =","traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all = ()","Accepts an action and returns a tuple (observation, reward, done, info). Args: action","if self.timestep > 5000: raise Exception('cannot find ego after 5000 timesteps') assert self.egoID","alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe = w_lateral","preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \"\"\"Run one timestep of","calls will return undefined results self.info = { 'resetFlag': 0} # (dict): contains","4 + 2] = 4.8 self.observation[name * 4 + 3] = 0 #","0: #abort lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0","2 + 2 * delta_A2 * delta_D2) TTC2 = TTC2 / delta_A2 if","contains auxiliary diagnostic information (helpful for debugging, and sometimes learning) self.action_space = spaces.Discrete(6)","True: self.info['resetFlag'] = True return self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward =","self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 # set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id,","leader longitudinal2: action[0] = 0: follow original lane leader action[0] = 1: follow","None self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all = () self.egoID = id","/ 3.2 assert 0 <= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c","self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \"\"\"Run one timestep of the environment's","we = 1 # reward related to comfort r_comf = wc1 * self.ego.acce","self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0: TTC2","None: # compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 =","action_longi = action // 3 action_lateral = action % 3 self.lateral_action = action_lateral","1 # set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit","= - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis)","if self.collision_num > 0: self.done = True # print('reset on: self.collision_num:', self.collision_num) def","% 3 self.lateral_action = action_lateral # action_longi = action[0] # action_lateral = action[1]","+ 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action != 1 and 0","else: self.sumoCmd += ['--seed', str(seed)] # gui if gui is True: self.sumoBinary +=","= action_lateral # action_longi = action[0] # action_lateral = action[1] assert self.done is","# gui if gui is True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] +","* 4 + 3] = veh.acce else: self.observation[name * 4 + 0] =","= traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \"\"\"Run one timestep of the environment's dynamics.","# episode in progress; 0:change back to original line; 1:lane change to target","return r_total def is_done(self): # lane change successfully executed, episode ends, reset env","self.ego.targetLeaderID is not None: # compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed -","> 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth -","w_lateral * alpha + w_longi * (1 - alpha) * abs( # self.ego.lanePos","is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat","= None # self.tgtLane = tgtlane self.is_success = False self.collision_num = 0 self.lateral_action","When end of episode is reached, call `reset()` outside env!! to reset this","tgtlane self.is_success = False self.collision_num = 0 self.lateral_action = 2 # self.observation =","* abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0 #","* TTC2 + 5) else: r_long_t = 0 if self.lateral_action == 1: #","out of env if self.egoID not in self.vehID_tuple_all: self.done = True # print('reset","-1, self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed","np.empty(20) self.reward = None # (float) : amount of reward returned after previous","= traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict)","if self.is_success: self.done = True # print('reset on: successfully lane change, dis2targetlane:', #","< 2: r_long_t = - math.exp(-2 * TTC2 + 5) else: r_long_t =","back to original line; 1:lane change to target lane; 2:keep current # lane","self.egoID not in self.vehID_tuple_all: self.done = True # print('reset on: self.ego not in","accelerate action[0] = -1: decelerate action[0] = 0: use SUMO default action[0] =","action_lateral == 2: self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext =","executed, episode ends, reset env # todo modify if self.is_success: self.done = True","self.collision_num > 0: self.done = True # print('reset on: self.collision_num:', self.collision_num) def preStep(self):","not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat -","= abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha) # assert 0","-math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe = w_lateral * (r_lat_c + r_lat_t) +","0: abort lane change, change back to original lane action[1] = 2: keep","after previous action self.done = True # (bool): whether the episode has ended,","= self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation() return self.observation","self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten()","lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha","leader will not change despite the lateral position of the ego may change","env:', self.egoID not in self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num","self.egoID is not None: while self.egoID not in self.veh_dict.keys(): # must ensure safety","self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward, self.done, self.info def seed(self, seed=None): if","# [0, 0, 0], # leader # [0, 0, 0], # target lane","self.veh_dict = {} self.vehID_tuple_all = () self.egoID = id self.ego = None #","info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done() if","back to original lane action[1] = 2: keep in current lateral position Returns:","3.2 # assert 0 <= alpha <= 1.1 # r_safe_leader = w_lateral *","modify if self.is_success: self.done = True # print('reset on: successfully lane change, dis2targetlane:',","= r_time + r_speed + r_effi # reward related to safety w_lateral =","< TTC2 < 2: r_long_t = - math.exp(-2 * TTC2 + 5) else:","9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average 19 vehicles","(0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth","- self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5)","return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2 = 1 wt = 1","1:leader; 2:target leader; 3:target follower :param id: vehicle id corresponding to name :return:","in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \"\"\" :param name: 0:ego; 1:leader;","self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action != 1 and 0 < TTC <","self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0 self.dt","self.observation[name * 4 + 0] = self.observation[0] + 300. self.observation[name * 4 +","traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done() if self.done","< 10.0: self.done = True # print('reset on: too close to ramp entrance,","too close to ramp entrance if self.ego.dis2entrance < 10.0: self.done = True #","lane leader # [0, 0, 0]] # target lane follower self.observation = np.empty(20)","+ r_safe_tgtleader # total reward r_total = r_comf + r_effi_all + r_safe return","self.ego.acce ** 2 + wc2 * self.ego.delta_acce ** 2 # reward related to","= - wt * self.timestep r_speed = ws * (self.ego.speed - self.ego_speedLimit) r_effi","self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2,","= self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V else:","reset env :param id: ego vehicle id :param tfc: int. 0:light; 1:medium; 2:dense","gui if gui is True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd","* 4 + 0] = veh.lanePos self.observation[name * 4 + 1] = veh.speed","using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed is None: self.sumoCmd","- self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0: TTC2 =","learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for","# print('alpha', alpha) # assert 0 <= alpha <= 1.1 # # r_safe_tgtleader","ego lane position and speed # [0, 0, 0], # leader # [0,","r_time + r_speed + r_effi # reward related to safety w_lateral = 1","original lane leader action[0] = 1: follow closer leader longitudinal2: action[0] = 0:","# check if episode ends self.is_done() if self.done is True: self.info['resetFlag'] = True","of the ego may change lateral: action[1] = 1: lane change action[1] =","5000: raise Exception('cannot find ego after 5000 timesteps') assert self.egoID in self.vehID_tuple_all, \"cannot","= spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in","+ 5) else: r_long_t = 0 if self.lateral_action == 1: # lane change","safety in preStpe self.preStep() if self.timestep > 5000: raise Exception('cannot find ego after","= os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\"please declare environment variable 'SUMO_HOME'\") import traci","average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg =","self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None self.veh_dict","too close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out of","// 3 action_lateral = action % 3 self.lateral_action = action_lateral # action_longi =","= id self.ego = None # self.tgtLane = tgtlane self.is_success = False self.collision_num","self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0: TTC = -","current # lane change to target lane if not self.is_success: if action_lateral ==","r_speed = ws * (self.ego.speed - self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane /","lane; 2:keep current # lane change to target lane if not self.is_success: if","= -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe = w_lateral * (r_lat_c + r_lat_t)","episode in progress; 0:change back to original line; 1:lane change to target lane;","instead of '3.0' self.sumoBinary = \"/usr/local/Cellar/sumo/1.2.0/bin/sumo\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3),","self.vehID_tuple_all, 'vehicle not in env' self.timestep += 1 # lateral control------------------------- # episode","traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until ego appears in env","True # print('reset on: too close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) #","longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce","- math.exp(-2 * TTC2 + 5) else: r_long_t = 0 if self.lateral_action ==","not None: # compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2","0: self.done = True # print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all","(0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex,","# must ensure safety in preStpe self.preStep() if self.timestep > 5000: raise Exception('cannot","-math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID is not None: # compute longitudinal","in __init__ \"\"\" action_longi = action // 3 action_lateral = action % 3","# and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) #","if self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha","if action_lateral == 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success =","def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \"\"\"Run one timestep","self.lateral_action = 2 # self.observation = [[0, 0, 0], # ego lane position","= False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 # set","+ 1] = self.observation[1] self.observation[name * 4 + 2] = 4.8 self.observation[name *","else: TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A","spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple:","self.sumoCmd += ['--seed', str(seed)] # gui if gui is True: self.sumoBinary += '-gui'","self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep current lateral","reward related to efficiency r_time = - wt * self.timestep r_speed = ws","# too close to ramp entrance if self.ego.dis2entrance < 10.0: self.done = True","os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\"please declare environment variable 'SUMO_HOME'\") import traci ######################################################################","== 0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2 +","assert action is not None, 'action is None' assert self.egoID in self.vehID_tuple_all, 'vehicle","/ delta_A2 if self.lateral_action == 1 and 0 < TTC2 < 2: r_long_t","self.observation[name * 4 + 3] = 0 # todo check if rational def","0 <= alpha <= 1.1 # r_safe_leader = w_lateral * alpha + w_longi","timestep of the environment's dynamics. When end of episode is reached, call `reset()`","lateral position if action_lateral == 2: self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal","self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def","is True: self.info['resetFlag'] = True return self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward","episode ends self.is_done() if self.done is True: self.info['resetFlag'] = True return self.observation, 0.0,","= True # print('reset on: self.ego not in env:', self.egoID not in self.vehID_tuple_all)","self.reward = self.updateReward() return self.observation, self.reward, self.done, self.info def seed(self, seed=None): if seed","results self.info = { 'resetFlag': 0} # (dict): contains auxiliary diagnostic information (helpful","'tools') sys.path.append(tools) print('success') else: sys.exit(\"please declare environment variable 'SUMO_HOME'\") import traci ###################################################################### #","# add sumo/tools into python environment if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'],","# ego lane position and speed # [0, 0, 0], # leader #","self.observation[0] + 300. self.observation[name * 4 + 1] = self.observation[1] self.observation[name * 4","= datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True,","default action[0] = others: acce = 0.0 longitudinal1: action[0] = 0: follow original","step until ego appears in env if self.egoID is not None: while self.egoID","to original line; 1:lane change to target lane; 2:keep current # lane change","* 4 + 2] = veh.pos_lat self.observation[name * 4 + 3] = veh.acce","def seed(self, seed=None): if seed is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed =","self.egoID in self.vehID_tuple_all, 'vehicle not in env' self.timestep += 1 # lateral control-------------------------","= self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0:","longitudinal2: action[0] = 0: follow original lane leader action[0] = 1: follow target","self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed +","after 5000 timesteps') assert self.egoID in self.vehID_tuple_all, \"cannot start training while ego is","() self.egoID = id self.ego = None # self.tgtLane = tgtlane self.is_success =","average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if float/int,","None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until","action[1] = 2: keep in current lateral position Returns: described in __init__ \"\"\"","None # self.tgtLane = tgtlane self.is_success = False self.collision_num = 0 self.lateral_action =","change successfully executed, episode ends, reset env # todo modify if self.is_success: self.done","control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed + acceNext * 0.1","2 + wc2 * self.ego.delta_acce ** 2 # reward related to efficiency r_time","== 0: TTC2 = - abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2 -","print('reset on: self.ego not in env:', self.egoID not in self.vehID_tuple_all) # collision occurs","else: self.observation[name * 4 + 0] = self.observation[0] + 300. self.observation[name * 4","closer leader longitudinal2: action[0] = 0: follow original lane leader action[0] = 1:","- self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0","target lane leader # [0, 0, 0]] # target lane follower self.observation =","# longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed + acceNext","def updateReward2(self): wc1 = 1 wc2 = 1 wt = 1 ws =","1 # lateral control------------------------- # episode in progress; 0:change back to original line;","> 0: self.done = True # print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep()","self.ego.lanePos if delta_A2 == 0: TTC2 = - abs(delta_D2) / delta_V2 else: TTC2","target lane if not self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat -","# print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2 =","# set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit =","veh.lanePos self.observation[name * 4 + 1] = veh.speed self.observation[name * 4 + 2]","add sumo/tools into python environment if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools')","alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1","self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane","until ego appears in env if self.egoID is not None: while self.egoID not","numpy as np from env.IDM import IDM from env.Road import Road from env.Vehicle","+ self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed","self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat","r_comf = wc1 * self.ego.acce ** 2 + wc2 * self.ego.delta_acce ** 2","check if episode ends self.is_done() if self.done is True: self.info['resetFlag'] = True return","1.1 # # r_safe_tgtleader = w_lateral * alpha + w_longi * (1 -","self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 =","lane if not self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth)","action is not None, 'action is None' assert self.egoID in self.vehID_tuple_all, 'vehicle not","2:target leader; 3:target follower :param id: vehicle id corresponding to name :return: \"\"\"","1 and 0 < TTC < 2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c","self.observation[name * 4 + 3] = veh.acce else: self.observation[name * 4 + 0]","= [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0 self.dt =","if delta_A2 == 0: TTC2 = - abs(delta_D2) / delta_V2 else: TTC2 =","todo modify if self.is_success: self.done = True # print('reset on: successfully lane change,","# randomness if seed is None: self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed',","self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time + r_speed + r_effi # reward related","str(0.1)] # randomness if seed is None: self.sumoCmd += ['--random'] else: self.sumoCmd +=","= True # print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID)","self.timestep > 5000: raise Exception('cannot find ego after 5000 timesteps') assert self.egoID in","= - math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action == 0: #abort lane","2] = 4.8 self.observation[name * 4 + 3] = 0 # todo check","in self.veh_dict.keys(): # must ensure safety in preStpe self.preStep() if self.timestep > 5000:","self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 #","sumoseed=None, randomseed=None): \"\"\" reset env :param id: ego vehicle id :param tfc: int.","not None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat -","+= ['--seed', str(seed)] # gui if gui is True: self.sumoBinary += '-gui' self.sumoCmd","(1 - alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader","if episode ends self.is_done() if self.done is True: self.info['resetFlag'] = True return self.observation,","vehicle id corresponding to name :return: \"\"\" if veh is not None: self.observation[name","self.randomseed = None self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all = () self.egoID","self.observation = [[0, 0, 0], # ego lane position and speed # [0,","ensure safety in preStpe self.preStep() if self.timestep > 5000: raise Exception('cannot find ego","is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat","todo check traffic flow density if traffic == 0: # average 9 vehicles","abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC =","self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed', str(seed)] # gui if gui is","longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed + acceNext *","self.rd = Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed","###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None): #","# ego vehicle out of env if self.egoID not in self.vehID_tuple_all: self.done =","self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape)","self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success","traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation() return self.observation return def close(self):","= self.observation[0] + 300. self.observation[name * 4 + 1] = self.observation[1] self.observation[name *","None, 'action is None' assert self.egoID in self.vehID_tuple_all, 'vehicle not in env' self.timestep","collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done = True #","'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change, change back","in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd,","r_lat_t = 0 r_safe = w_lateral * (r_lat_c + r_lat_t) + w_longi *","follower :param id: vehicle id corresponding to name :return: \"\"\" if veh is","egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \"\"\" reset env :param id: ego vehicle","self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until ego","self.info else: self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward, self.done, self.info def seed(self,","the ego may change lateral: action[1] = 1: lane change action[1] = 0:","self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple:","+ r_speed + r_effi # reward related to safety w_lateral = 1 w_longi","in env' self.timestep += 1 # lateral control------------------------- # episode in progress; 0:change","= TTC2 / delta_A2 if self.lateral_action == 1 and 0 < TTC2 <","3.2 # # print('alpha', alpha) # assert 0 <= alpha <= 1.1 #","action_lateral # action_longi = action[0] # action_lateral = action[1] assert self.done is False,","- self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha',","0 # todo check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] =","original line; 1:lane change to target lane; 2:keep current # lane change to","datetime import gym from gym import spaces import numpy as np from env.IDM","= True # print('reset on: too close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane)","= action[1] assert self.done is False, 'self.done is not False' assert action is","lane leader will not change despite the lateral position of the ego may","lane change, change back to ego's original lane if action_lateral == 0: #","assert 0 <= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0","reward related to comfort r_comf = wc1 * self.ego.acce ** 2 + wc2","self.tgtLane = tgtlane self.is_success = False self.collision_num = 0 self.lateral_action = 2 #","= - math.exp(-2 * TTC2 + 5) else: r_long_t = 0 if self.lateral_action","r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID is not None: #","\"\"\" self.seed(randomseed) if sumoseed is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui,","r_safe_leader = w_lateral * alpha + w_longi * (1 - alpha) * abs(self.ego.leaderDis)","assert 0 <= alpha <= 1.1 # r_safe_leader = w_lateral * alpha +","np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2","os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\"please declare environment variable 'SUMO_HOME'\")","call `reset()` outside env!! to reset this environment's state. Accepts an action and","self.ego.dis2entrance r_effi_all = r_time + r_speed + r_effi # reward related to safety","\"cannot start training while ego is not in env\" self.done = False self.ego","case further step() calls will return undefined results self.info = { 'resetFlag': 0}","self.done = True # print('reset on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) #","1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd)","related to safety w_lateral = 1 w_longi = 1 if self.ego.leaderID is not","is reached, call `reset()` outside env!! to reset this environment's state. Accepts an","position and speed # [0, 0, 0], # leader # [0, 0, 0],","information (helpful for debugging, and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf,","self.ego.acce if delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V","# update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends","alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1","else: TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2 + 2 * delta_A2 *","and 0 < TTC < 2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c =","= 0 self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None self.veh_dict =","a tuple (observation, reward, done, info). Args: action (object): longitudinal0: action[0] = 1:","delta_A2 if self.lateral_action == 1 and 0 < TTC2 < 2: r_long_t =","veh_id in veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for","self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward, self.done,","else: r_long_c = 0 if self.lateral_action == 0: #abort lane change alpha =","r_safe_tgtleader # total reward r_total = r_comf + r_effi_all + r_safe return r_total","acce = 0.0 longitudinal1: action[0] = 0: follow original lane leader action[0] =","seed=self.sumoseed) # continue step until ego appears in env if self.egoID is not","random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \"\"\" reset env :param","self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done =","if gui is True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd +","if self.ego.dis2entrance < 10.0: self.done = True # print('reset on: too close to","w_longi * (1 - alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else:","+ 3] = 0 # todo check if rational def updateObservation(self): self.observation[0] =","name: 0:ego; 1:leader; 2:target leader; 3:target follower :param id: vehicle id corresponding to","= r_safe_leader + r_safe_tgtleader # total reward r_total = r_comf + r_effi_all +","= abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <= alpha <= 1.1","= -math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID is not None: # compute","on: self.ego not in env:', self.egoID not in self.vehID_tuple_all) # collision occurs self.collision_num","if action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success =","be converted to str(float/int), instead of '3.0' self.sumoBinary = \"/usr/local/Cellar/sumo/1.2.0/bin/sumo\" self.sumoCmd = ['-c',","veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self,","0 if self.ego.targetLeaderID is not None: # compute longitudinal time gap delta_V2 =","False self.collision_num = 0 self.lateral_action = 2 # self.observation = [[0, 0, 0],","print('success') else: sys.exit(\"please declare environment variable 'SUMO_HOME'\") import traci ###################################################################### # simulation environments","Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None","0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth)","self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) #","will return undefined results self.info = { 'resetFlag': 0} # (dict): contains auxiliary","abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5","veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in","= -1: decelerate action[0] = 0: use SUMO default action[0] = others: acce","position Returns: described in __init__ \"\"\" action_longi = action // 3 action_lateral =","veh is not None: self.observation[name * 4 + 0] = veh.lanePos self.observation[name *","= 1 we = 1 # reward related to comfort r_comf = wc1","self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return","self.ego.dis2tgtLane) # ego vehicle out of env if self.egoID not in self.vehID_tuple_all: self.done","veh.acce else: self.observation[name * 4 + 0] = self.observation[0] + 300. self.observation[name *","in current lateral position Returns: described in __init__ \"\"\" action_longi = action //","True # print('reset on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too close","veh.pos_lat self.observation[name * 4 + 3] = veh.acce else: self.observation[name * 4 +","self.reward, self.done, self.info def seed(self, seed=None): if seed is None: self.randomseed = datetime.datetime.now().microsecond","self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id","0], # leader # [0, 0, 0], # target lane leader # [0,","lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness","for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \"\"\" :param name:","# self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1","Continuous lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] #","self.egoID not in self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num >","action[0] = -1: decelerate action[0] = 0: use SUMO default action[0] = others:","if self.done is True: self.info['resetFlag'] = True return self.observation, 0.0, self.done, self.info else:","using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length',","env.IDM import IDM from env.Road import Road from env.Vehicle import Vehicle import math","self.lateral_action == 0: #abort lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2","state. Accepts an action and returns a tuple (observation, reward, done, info). Args:","# todo check traffic flow density if traffic == 0: # average 9","traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until ego appears in env if self.egoID","if self.lateral_action == 1: # lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) /","delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A ==","+ w_longi * (1 - alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) #","+ ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd","self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0: TTC","ego is not in env\" self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex =","= True # print('reset on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too","= 0 self.lateral_action = 2 # self.observation = [[0, 0, 0], # ego","= True # (bool): whether the episode has ended, in which case further","ends, reset env # todo modify if self.is_success: self.done = True # print('reset","0, 0], # leader # [0, 0, 0], # target lane leader #","to ramp entrance if self.ego.dis2entrance < 10.0: self.done = True # print('reset on:","not in env' self.timestep += 1 # lateral control------------------------- # episode in progress;","- self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <= alpha <= 1.1 # r_safe_leader","reached, call `reset()` outside env!! to reset this environment's state. Accepts an action","reset env # todo modify if self.is_success: self.done = True # print('reset on:","compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce -","+ 3] = veh.acce else: self.observation[name * 4 + 0] = self.observation[0] +","= ws * (self.ego.speed - self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance","is not False' assert action is not None, 'action is None' assert self.egoID","comfort r_comf = wc1 * self.ego.acce ** 2 + wc2 * self.ego.delta_acce **","traffic == 0: # average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic ==","TTC = TTC/delta_A if self.lateral_action != 1 and 0 < TTC < 2:","alpha + w_longi * (1 - alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos)","keep current lateral position if action_lateral == 2: self.is_success = self.ego.changeLane(True, -1, self.rd)","3] = veh.acce else: self.observation[name * 4 + 0] = self.observation[0] + 300.","if self.egoID not in self.vehID_tuple_all: self.done = True # print('reset on: self.ego not","self.lateral_action == 1 and 0 < TTC2 < 2: r_long_t = - math.exp(-2","= None self.veh_dict = {} self.vehID_tuple_all = () self.egoID = id self.ego =","lateral position of the ego may change lateral: action[1] = 1: lane change","print(acceNext) vNext = self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------","= others: acce = 0.0 longitudinal1: action[0] = 0: follow original lane leader","traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None):","2:dense :return: initial observation \"\"\" self.seed(randomseed) if sumoseed is None: self.sumoseed = self.randomseed","self.vehID_tuple_all = () self.egoID = id self.ego = None # self.tgtLane = tgtlane","= 1 if self.ego.leaderID is not None: # compute longitudinal time gap delta_V","id self.ego = None # self.tgtLane = tgtlane self.is_success = False self.collision_num =","leader; 3:target follower :param id: vehicle id corresponding to name :return: \"\"\" if","follower self.observation = np.empty(20) self.reward = None # (float) : amount of reward","env!! to reset this environment's state. Accepts an action and returns a tuple","\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3), # using 'Simple Continuous lane-change","traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM()","done, info). Args: action (object): longitudinal0: action[0] = 1: accelerate action[0] = -1:","TTC < 2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action","# compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce","1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep current lateral position if action_lateral ==","# r_safe_leader = 0 # if self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader',","if self.lateral_action == 1 and 0 < TTC2 < 2: r_long_t = -","self.egoID in self.vehID_tuple_all, \"cannot start training while ego is not in env\" self.done","the lateral position of the ego may change lateral: action[1] = 1: lane","flow density if traffic == 0: # average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg'","env if self.egoID not in self.vehID_tuple_all: self.done = True # print('reset on: self.ego","sys.exit(\"please declare environment variable 'SUMO_HOME'\") import traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env):","step() calls will return undefined results self.info = { 'resetFlag': 0} # (dict):","self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0 # # # r_safe = r_safe_leader","longitudinal0: action[0] = 1: accelerate action[0] = -1: decelerate action[0] = 0: use","= action // 3 action_lateral = action % 3 self.lateral_action = action_lateral #","traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done = True # print('reset on: self.collision_num:', self.collision_num)","str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road()","acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all)","0] = veh.lanePos self.observation[name * 4 + 1] = veh.speed self.observation[name * 4","= 1: follow closer leader longitudinal2: action[0] = 0: follow original lane leader","self.ego.leaderID is not None: # compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed -","lane change to target lane if not self.is_success: if action_lateral == 1: #","and returns a tuple (observation, reward, done, info). Args: action (object): longitudinal0: action[0]","> 5000: raise Exception('cannot find ego after 5000 timesteps') assert self.egoID in self.vehID_tuple_all,","self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 # set ego vehicle speed mode","* abs(self.ego.leaderDis) # else: # r_safe_leader = 0 # if self.ego.targetLeaderID is not","action_longi = action[0] # action_lateral = action[1] assert self.done is False, 'self.done is","self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3), # using 'Simple Continuous lane-change model'","we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time + r_speed + r_effi #","self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)]","self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all","str(seed)] # gui if gui is True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary]","environment's dynamics. When end of episode is reached, call `reset()` outside env!! to","self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep current","# leader # [0, 0, 0], # target lane leader # [0, 0,","[self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT()","despite the lateral position of the ego may change lateral: action[1] = 1:","self.done = True # print('reset on: too close to ramp entrance, dis2targetlane:', #","= 1 # reward related to comfort r_comf = wc1 * self.ego.acce **","change back to ego's original lane if action_lateral == 0: # and abs(self.ego.pos_lat","ego's original lane if action_lateral == 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) >","import IDM from env.Road import Road from env.Vehicle import Vehicle import math #","update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] =","# r_safe_leader = w_lateral * alpha + w_longi * (1 - alpha) *","1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID is not None:","self.lateral_action != 1 and 0 < TTC < 2: r_long_c = - math.exp(-2*TTC+5)","time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if","else: # average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string,","may change lateral: action[1] = 1: lane change action[1] = 0: abort lane","if seed is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def","+ 300. self.observation[name * 4 + 1] = self.observation[1] self.observation[name * 4 +","= self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation =","action (object): longitudinal0: action[0] = 1: accelerate action[0] = -1: decelerate action[0] =","is_done(self): # lane change successfully executed, episode ends, reset env # todo modify","= w_lateral * alpha + w_longi * (1 - alpha) * abs(self.ego.leaderDis) #",":param id: vehicle id corresponding to name :return: \"\"\" if veh is not","ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor *","self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane","episode is reached, call `reset()` outside env!! to reset this environment's state. Accepts","== 1 and 0 < TTC2 < 2: r_long_t = - math.exp(-2 *","== 1: # lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert","this environment's state. Accepts an action and returns a tuple (observation, reward, done,","r_long_c = - math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action == 0: #abort","lane leader action[0] = 1: follow target lane leader **important**: orginal/target lane leader","2 # self.observation = [[0, 0, 0], # ego lane position and speed","None: self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed', str(seed)] # gui if gui","19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg'","veh_id in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()):","is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid,","whether the episode has ended, in which case further step() calls will return","arguments must be string, if float/int, must be converted to str(float/int), instead of","# r_safe = r_safe_leader + r_safe_tgtleader # total reward r_total = r_comf +","- self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha) # assert 0 <= alpha","abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat,","Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for","import gym from gym import spaces import numpy as np from env.IDM import","<= 1.1 # r_safe_leader = w_lateral * alpha + w_longi * (1 -","progress; 0:change back to original line; 1:lane change to target lane; 2:keep current","delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V","# average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg","on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2):","<= 1.1 # # r_safe_tgtleader = w_lateral * alpha + w_longi * (1","seed(self, seed=None): if seed is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed","('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 #","from gym import spaces import numpy as np from env.IDM import IDM from","self.ego not in env:', self.egoID not in self.vehID_tuple_all) # collision occurs self.collision_num =","self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1,","* delta_A2 * delta_D2) TTC2 = TTC2 / delta_A2 if self.lateral_action == 1","= 0 r_safe = w_lateral * (r_lat_c + r_lat_t) + w_longi * (r_long_c+","appears in env if self.egoID is not None: while self.egoID not in self.veh_dict.keys():","if self.lateral_action == 0: #abort lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) /","not in env:', self.egoID not in self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber()","<= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe = w_lateral *","self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <= alpha <= 1.1 # r_safe_leader =","= seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \"\"\" reset","is_gui=True, sumoseed=None, randomseed=None): \"\"\" reset env :param id: ego vehicle id :param tfc:","r_safe_tgtleader = w_lateral * alpha + w_longi * (1 - alpha) * abs(","python environment if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else:","sys import random import datetime import gym from gym import spaces import numpy","# simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None): # todo","to comfort r_comf = wc1 * self.ego.acce ** 2 + wc2 * self.ego.delta_acce","lane action[1] = 2: keep in current lateral position Returns: described in __init__","from env.Vehicle import Vehicle import math # add sumo/tools into python environment if","reset this environment's state. Accepts an action and returns a tuple (observation, reward,","line; 1:lane change to target lane; 2:keep current # lane change to target","else: # r_safe_leader = 0 # if self.ego.targetLeaderID is not None: # #","= action % 3 self.lateral_action = action_lateral # action_longi = action[0] # action_lateral","+ 0] = veh.lanePos self.observation[name * 4 + 1] = veh.speed self.observation[name *","r_long_t = 0 if self.lateral_action == 1: # lane change alpha = abs(self.ego.pos_lat","# keep current lateral position if action_lateral == 2: self.is_success = self.ego.changeLane(True, -1,","= self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right',","2: # average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles","in veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id","4 + 0] = self.observation[0] + 300. self.observation[name * 4 + 1] =","= abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_t","4 + 2] = veh.pos_lat self.observation[name * 4 + 3] = veh.acce else:","# self.ego.dis2tgtLane) # too close to ramp entrance if self.ego.dis2entrance < 10.0: self.done","list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict)","# alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha) #","= Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id)","print('alpha', alpha) # assert 0 <= alpha <= 1.1 # # r_safe_tgtleader =","- math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action != 1","0 # # # r_safe = r_safe_leader + r_safe_tgtleader # total reward r_total","0:change back to original line; 1:lane change to target lane; 2:keep current #","self.seed(randomseed) if sumoseed is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed)","self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd,","self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos","r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe = w_lateral * (r_lat_c +","is not None, 'action is None' assert self.egoID in self.vehID_tuple_all, 'vehicle not in","self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done() if self.done is True: self.info['resetFlag'] =","!= 1 and 0 < TTC < 2: r_long_c = - math.exp(-2*TTC+5) else:","r_effi_all + r_safe return r_total def is_done(self): # lane change successfully executed, episode","abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # #","1: follow closer leader longitudinal2: action[0] = 0: follow original lane leader action[0]","environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None): # todo check traffic","target lane follower self.observation = np.empty(20) self.reward = None # (float) : amount","env :param id: ego vehicle id :param tfc: int. 0:light; 1:medium; 2:dense :return:","# else: # r_safe_leader = 0 # if self.ego.targetLeaderID is not None: #","+ r_effi # reward related to safety w_lateral = 1 w_longi = 1","dis2targetlane:', # self.ego.dis2tgtLane) # too close to ramp entrance if self.ego.dis2entrance < 10.0:","{ 'resetFlag': 0} # (dict): contains auxiliary diagnostic information (helpful for debugging, and","# (bool): whether the episode has ended, in which case further step() calls","* self.ego.acce ** 2 + wc2 * self.ego.delta_acce ** 2 # reward related","# ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2","self.vehID_tuple_all: self.done = True # print('reset on: self.ego not in env:', self.egoID not","= veh.speed self.observation[name * 4 + 2] = veh.pos_lat self.observation[name * 4 +","<= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe =","is not in env\" self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane","True return self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward = self.updateReward() return self.observation,","= self.updateReward() return self.observation, self.reward, self.done, self.info def seed(self, seed=None): if seed is","<= alpha <= 1.1 # r_safe_leader = w_lateral * alpha + w_longi *","if sumoseed is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) #","True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start',","traffic=1, gui=False, seed=None): # todo check traffic flow density if traffic == 0:","\"\"\" :param name: 0:ego; 1:leader; 2:target leader; 3:target follower :param id: vehicle id","abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_c =","r_time = - wt * self.timestep r_speed = ws * (self.ego.speed - self.ego_speedLimit)","converted to str(float/int), instead of '3.0' self.sumoBinary = \"/usr/local/Cellar/sumo/1.2.0/bin/sumo\" self.sumoCmd = ['-c', self.cfg,","'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\"please declare environment","high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if veh_id not in","while ego is not in env\" self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex","lane follower self.observation = np.empty(20) self.reward = None # (float) : amount of","compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce -","self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha)","action=2): \"\"\"Run one timestep of the environment's dynamics. When end of episode is","follow target lane leader **important**: orginal/target lane leader will not change despite the","action[0] = 0: use SUMO default action[0] = others: acce = 0.0 longitudinal1:","vehicle id :param tfc: int. 0:light; 1:medium; 2:dense :return: initial observation \"\"\" self.seed(randomseed)","0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit)","== 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex,","alpha) # assert 0 <= alpha <= 1.1 # # r_safe_tgtleader = w_lateral","r_long_t) # # if self.ego.leaderID is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat -","import spaces import numpy as np from env.IDM import IDM from env.Road import","None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)","action_lateral = action[1] assert self.done is False, 'self.done is not False' assert action","# lane change to target lane if not self.is_success: if action_lateral == 1:","id: ego vehicle id :param tfc: int. 0:light; 1:medium; 2:dense :return: initial observation","else: sys.exit(\"please declare environment variable 'SUMO_HOME'\") import traci ###################################################################### # simulation environments class","* alpha + w_longi * (1 - alpha) * abs( # self.ego.lanePos -","0.0 longitudinal1: action[0] = 0: follow original lane leader action[0] = 1: follow","# using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed is None:","= traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done() if self.done is True:","self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all = () self.egoID = id self.ego","TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if","abort lane change, change back to ego's original lane if action_lateral == 0:","self.ego.is_ego = 1 # set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor =","veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \"\"\"","3:target follower :param id: vehicle id corresponding to name :return: \"\"\" if veh","'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if float/int, must be converted to str(float/int),","traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \"\"\"Run one timestep of the environment's dynamics. When","traffic flow density if traffic == 0: # average 9 vehicles self.cfg =","* 4 + 1] = veh.speed self.observation[name * 4 + 2] = veh.pos_lat","self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id not in","action[0] = others: acce = 0.0 longitudinal1: action[0] = 0: follow original lane","+ 0] = self.observation[0] + 300. self.observation[name * 4 + 1] = self.observation[1]","not False' assert action is not None, 'action is None' assert self.egoID in","= self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext)","episode ends, reset env # todo modify if self.is_success: self.done = True #","'--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed is None: self.sumoCmd += ['--random']","- self.ego.pos_lat) # keep current lateral position if action_lateral == 2: self.is_success =","leader action[0] = 1: follow closer leader longitudinal2: action[0] = 0: follow original","delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2 + 2 * delta_A2","* (1 - alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader = 0 #","self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else:","= action[0] # action_lateral = action[1] assert self.done is False, 'self.done is not","from env.Road import Road from env.Vehicle import Vehicle import math # add sumo/tools","action and returns a tuple (observation, reward, done, info). Args: action (object): longitudinal0:","# r_safe_tgtleader = 0 # # # r_safe = r_safe_leader + r_safe_tgtleader #","if delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V -","alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader = 0 # if self.ego.targetLeaderID is","self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2","action[0] = 1: follow target lane leader **important**: orginal/target lane leader will not","to efficiency r_time = - wt * self.timestep r_speed = ws * (self.ego.speed","lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too close to ramp entrance if self.ego.dis2entrance","self.info['resetFlag'] = True return self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward = self.updateReward()","ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out of env if self.egoID","self.collision_num = 0 self.lateral_action = 2 # self.observation = [[0, 0, 0], #","delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 ==","close to ramp entrance if self.ego.dis2entrance < 10.0: self.done = True # print('reset","self.observation[1] self.observation[name * 4 + 2] = 4.8 self.observation[name * 4 + 3]","w_lateral * (r_lat_c + r_lat_t) + w_longi * (r_long_c+ r_long_t) # # if","string, if float/int, must be converted to str(float/int), instead of '3.0' self.sumoBinary =","0: follow original lane leader action[0] = 1: follow target lane leader **important**:","self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed =","be string, if float/int, must be converted to str(float/int), instead of '3.0' self.sumoBinary","in env:', self.egoID not in self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if","1 and 0 < TTC2 < 2: r_long_t = - math.exp(-2 * TTC2","self.observation[name * 4 + 1] = self.observation[1] self.observation[name * 4 + 2] =","assert self.egoID in self.vehID_tuple_all, \"cannot start training while ego is not in env\"","sys.path.append(tools) print('success') else: sys.exit(\"please declare environment variable 'SUMO_HOME'\") import traci ###################################################################### # simulation","= self.observation[1] self.observation[name * 4 + 2] = 4.8 self.observation[name * 4 +","name, veh): \"\"\" :param name: 0:ego; 1:leader; 2:target leader; 3:target follower :param id:","= 1: lane change action[1] = 0: abort lane change, change back to","not self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01:","# using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1),","# target lane leader # [0, 0, 0]] # target lane follower self.observation","# if self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) #","# lateral control------------------------- # episode in progress; 0:change back to original line; 1:lane","import math # add sumo/tools into python environment if 'SUMO_HOME' in os.environ: tools","None: self.observation[name * 4 + 0] = veh.lanePos self.observation[name * 4 + 1]","tuple (observation, reward, done, info). Args: action (object): longitudinal0: action[0] = 1: accelerate","* 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) #","= wc1 * self.ego.acce ** 2 + wc2 * self.ego.delta_acce ** 2 #","'resetFlag': 0} # (dict): contains auxiliary diagnostic information (helpful for debugging, and sometimes","self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all =","timesteps') assert self.egoID in self.vehID_tuple_all, \"cannot start training while ego is not in","= -delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action","self.info = { 'resetFlag': 0} # (dict): contains auxiliary diagnostic information (helpful for","which case further step() calls will return undefined results self.info = { 'resetFlag':","follow closer leader longitudinal2: action[0] = 0: follow original lane leader action[0] =","= self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0: TTC2 = - abs(delta_D2) /","* 4 + 2] = 4.8 self.observation[name * 4 + 3] = 0","target lane; 2:keep current # lane change to target lane if not self.is_success:","self.info def seed(self, seed=None): if seed is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed","10.0: self.done = True # print('reset on: too close to ramp entrance, dis2targetlane:',","update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done()","self.done = True # print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all =","TTC2 < 2: r_long_t = - math.exp(-2 * TTC2 + 5) else: r_long_t","vehicle out of env if self.egoID not in self.vehID_tuple_all: self.done = True #","+= 1 # lateral control------------------------- # episode in progress; 0:change back to original","= [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary]","__init__(self, id=None, traffic=1, gui=False, seed=None): # todo check traffic flow density if traffic","'vehicle not in env' self.timestep += 1 # lateral control------------------------- # episode in","0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A","= \"/usr/local/Cellar/sumo/1.2.0/bin/sumo\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3), # using 'Simple Continuous","id corresponding to name :return: \"\"\" if veh is not None: self.observation[name *","- abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2 +","original lane if action_lateral == 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01:","3 self.lateral_action = action_lateral # action_longi = action[0] # action_lateral = action[1] assert","= { 'resetFlag': 0} # (dict): contains auxiliary diagnostic information (helpful for debugging,","for veh_id in veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd)","+ r_lat_t) + w_longi * (r_long_c+ r_long_t) # # if self.ego.leaderID is not","initial observation \"\"\" self.seed(randomseed) if sumoseed is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid,","# action_longi = action[0] # action_lateral = action[1] assert self.done is False, 'self.done",": amount of reward returned after previous action self.done = True # (bool):","r_long_c = 0 if self.lateral_action == 0: #abort lane change alpha = abs(self.ego.pos_lat","= - abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2","not None, 'action is None' assert self.egoID in self.vehID_tuple_all, 'vehicle not in env'","step(self, action=2): \"\"\"Run one timestep of the environment's dynamics. When end of episode","traffic == 2: # average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average","self.egoID not in self.veh_dict.keys(): # must ensure safety in preStpe self.preStep() if self.timestep",":return: \"\"\" if veh is not None: self.observation[name * 4 + 0] =","class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None): # todo check traffic flow","observation \"\"\" self.seed(randomseed) if sumoseed is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc,","# [0, 0, 0], # target lane leader # [0, 0, 0]] #","print('reset on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too close to ramp","change, change back to original lane action[1] = 2: keep in current lateral","# # r_safe = r_safe_leader + r_safe_tgtleader # total reward r_total = r_comf","# print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def","not None: # compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A","is None: self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed', str(seed)] # gui if","corresponding to name :return: \"\"\" if veh is not None: self.observation[name * 4","outside env!! to reset this environment's state. Accepts an action and returns a","env if self.egoID is not None: while self.egoID not in self.veh_dict.keys(): # must","Vehicle import math # add sumo/tools into python environment if 'SUMO_HOME' in os.environ:","# lane change successfully executed, episode ends, reset env # todo modify if","np from env.IDM import IDM from env.Road import Road from env.Vehicle import Vehicle","seed=None): if seed is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed)","< 2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action ==","= False self.collision_num = 0 self.lateral_action = 2 # self.observation = [[0, 0,","if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\"please declare","successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too close to ramp entrance if","self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \"\"\" :param name: 0:ego; 1:leader; 2:target leader;","tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \"\"\" reset env :param id: ego vehicle id","declare environment variable 'SUMO_HOME'\") import traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def","alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0","- self.ego.lanePos if delta_A2 == 0: TTC2 = - abs(delta_D2) / delta_V2 else:","= 1 w_longi = 1 if self.ego.leaderID is not None: # compute longitudinal","(r_lat_c + r_lat_t) + w_longi * (r_long_c+ r_long_t) # # if self.ego.leaderID is","0: # average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: #","print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2 = 1","-delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action !=","not in self.veh_dict.keys(): # must ensure safety in preStpe self.preStep() if self.timestep >","self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext =","import Vehicle import math # add sumo/tools into python environment if 'SUMO_HOME' in","= traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all =","lane if action_lateral == 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success","def __init__(self, id=None, traffic=1, gui=False, seed=None): # todo check traffic flow density if","gui=is_gui, seed=self.sumoseed) # continue step until ego appears in env if self.egoID is","self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4,","+ r_safe return r_total def is_done(self): # lane change successfully executed, episode ends,","SUMO default action[0] = others: acce = 0.0 longitudinal1: action[0] = 0: follow","= 0: abort lane change, change back to original lane action[1] = 2:","self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1,","self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \"\"\"Run one timestep of the environment's dynamics. When end","\"\"\"Run one timestep of the environment's dynamics. When end of episode is reached,","- self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0: TTC =","# # if self.ego.leaderID is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat))","self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0: TTC2 = -","= veh.acce else: self.observation[name * 4 + 0] = self.observation[0] + 300. self.observation[name","random import datetime import gym from gym import spaces import numpy as np","2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action == 0:","0.0, self.done, self.info else: self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward, self.done, self.info","is not None: # compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed","env.Road import Road from env.Vehicle import Vehicle import math # add sumo/tools into","= {} self.vehID_tuple_all = () self.egoID = id self.ego = None # self.tgtLane","'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)]","to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out of env if","/ 3.2 assert 0 <= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t","TTC2 = - abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2 **","# continue step until ego appears in env if self.egoID is not None:","if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def","0} # (dict): contains auxiliary diagnostic information (helpful for debugging, and sometimes learning)","self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha) # assert 0 <= alpha <=","must ensure safety in preStpe self.preStep() if self.timestep > 5000: raise Exception('cannot find","on: too close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out","* delta_D2) TTC2 = TTC2 / delta_A2 if self.lateral_action == 1 and 0","self.lateral_action == 1: # lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2","self.observation[name * 4 + 2] = veh.pos_lat self.observation[name * 4 + 3] =","= abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_c","previous action self.done = True # (bool): whether the episode has ended, in","the episode has ended, in which case further step() calls will return undefined","self.is_done() if self.done is True: self.info['resetFlag'] = True return self.observation, 0.0, self.done, self.info","r_safe_tgtleader = 0 # # # r_safe = r_safe_leader + r_safe_tgtleader # total","action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True,","wt = 1 ws = 1 we = 1 # reward related to","leader **important**: orginal/target lane leader will not change despite the lateral position of","2 # reward related to efficiency r_time = - wt * self.timestep r_speed","env # todo modify if self.is_success: self.done = True # print('reset on: successfully","vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' #","0: TTC2 = - abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2","self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) #","1 wt = 1 ws = 1 we = 1 # reward related","1 # reward related to comfort r_comf = wc1 * self.ego.acce ** 2","spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if veh_id not","= 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if float/int, must be converted to","self.observation[name * 4 + 1] = veh.speed self.observation[name * 4 + 2] =","2:keep current # lane change to target lane if not self.is_success: if action_lateral","if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()):","self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader)","longitudinal1: action[0] = 0: follow original lane leader action[0] = 1: follow closer","find ego after 5000 timesteps') assert self.egoID in self.vehID_tuple_all, \"cannot start training while","'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be","# # # r_safe = r_safe_leader + r_safe_tgtleader # total reward r_total =","position of the ego may change lateral: action[1] = 1: lane change action[1]","['--random'] else: self.sumoCmd += ['--seed', str(seed)] # gui if gui is True: self.sumoBinary","- self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5)","0: use SUMO default action[0] = others: acce = 0.0 longitudinal1: action[0] =","+ w_longi * (1 - alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader =","self.egoID = id self.ego = None # self.tgtLane = tgtlane self.is_success = False","# collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done = True","not in env\" self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego","= self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower)","(observation, reward, done, info). Args: action (object): longitudinal0: action[0] = 1: accelerate action[0]","self.reward = None # (float) : amount of reward returned after previous action","speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj","not None: while self.egoID not in self.veh_dict.keys(): # must ensure safety in preStpe","print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change, change back to ego's original","variable 'SUMO_HOME'\") import traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None,","(helpful for debugging, and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf,","self.done, self.info else: self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward, self.done, self.info def","average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average 19","2: r_long_t = - math.exp(-2 * TTC2 + 5) else: r_long_t = 0","tfc=1, is_gui=True, sumoseed=None, randomseed=None): \"\"\" reset env :param id: ego vehicle id :param","of '3.0' self.sumoBinary = \"/usr/local/Cellar/sumo/1.2.0/bin/sumo\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3), #","self.lateral_action = action_lateral # action_longi = action[0] # action_lateral = action[1] assert self.done","+= '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else:","+ w_longi * (r_long_c+ r_long_t) # # if self.ego.leaderID is not None: #","# total reward r_total = r_comf + r_effi_all + r_safe return r_total def","r_effi # reward related to safety w_lateral = 1 w_longi = 1 if","= self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext","to original lane action[1] = 2: keep in current lateral position Returns: described","self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <=","traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation()","0 < TTC < 2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c = 0","14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if float/int, must","self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation() return self.observation return def close(self): traci.close()","self.ego.leaderID is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha =","- self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0 # # # r_safe =","* alpha + w_longi * (1 - alpha) * abs(self.ego.leaderDis) # else: #","self.ego.dis2tgtLane) # too close to ramp entrance if self.ego.dis2entrance < 10.0: self.done =","delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos","else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0","['-c', self.cfg, # '--lanechange.duration', str(3), # using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8),","others: acce = 0.0 longitudinal1: action[0] = 0: follow original lane leader action[0]","action_lateral == 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True,","datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None,","gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A","one timestep of the environment's dynamics. When end of episode is reached, call","else: self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward, self.done, self.info def seed(self, seed=None):","while self.egoID not in self.veh_dict.keys(): # must ensure safety in preStpe self.preStep() if","ws = 1 we = 1 # reward related to comfort r_comf =","in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\"please declare environment variable","self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \"\"\"Run one","4.8 self.observation[name * 4 + 3] = 0 # todo check if rational","True # (bool): whether the episode has ended, in which case further step()","3.2 assert 0 <= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c =","reward returned after previous action self.done = True # (bool): whether the episode","# '--lanechange.duration', str(3), # using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), # using","\"\"\" if veh is not None: self.observation[name * 4 + 0] = veh.lanePos","self.observation, self.reward, self.done, self.info def seed(self, seed=None): if seed is None: self.randomseed =","2: keep in current lateral position Returns: described in __init__ \"\"\" action_longi =","action % 3 self.lateral_action = action_lateral # action_longi = action[0] # action_lateral =","* self.ego.delta_acce ** 2 # reward related to efficiency r_time = - wt","if float/int, must be converted to str(float/int), instead of '3.0' self.sumoBinary = \"/usr/local/Cellar/sumo/1.2.0/bin/sumo\"","(bool): whether the episode has ended, in which case further step() calls will","[0, 0, 0], # leader # [0, 0, 0], # target lane leader","math.sqrt(delta_V2 ** 2 + 2 * delta_A2 * delta_D2) TTC2 = TTC2 /","TTC2 = TTC2 / delta_A2 if self.lateral_action == 1 and 0 < TTC2","* (self.ego.speed - self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all =","self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) #","delta_A2 * delta_D2) TTC2 = TTC2 / delta_A2 if self.lateral_action == 1 and","veh_id_tuple): for veh_id in veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id,","# # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) /","abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha) # assert 0 <=","print('reset on: too close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle","\"\"\" action_longi = action // 3 action_lateral = action % 3 self.lateral_action =","r_safe = r_safe_leader + r_safe_tgtleader # total reward r_total = r_comf + r_effi_all","self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change, change","self.ego.delta_acce ** 2 # reward related to efficiency r_time = - wt *","None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid, tlane=0,","alpha + w_longi * (1 - alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader","0 # if self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat))","# average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if","* 4 + 0] = self.observation[0] + 300. self.observation[name * 4 + 1]","w_longi * (1 - alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader = 0","ramp entrance if self.ego.dis2entrance < 10.0: self.done = True # print('reset on: too","if self.ego.targetLeaderID is not None: # compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed","== 0: # average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2:","r_long_t = - math.exp(-2 * TTC2 + 5) else: r_long_t = 0 if","tfc: int. 0:light; 1:medium; 2:dense :return: initial observation \"\"\" self.seed(randomseed) if sumoseed is","change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha <=","# alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <= alpha","= 0 if self.lateral_action == 0: #abort lane change alpha = abs(self.ego.pos_lat -","lane change action[1] = 0: abort lane change, change back to original lane","None' assert self.egoID in self.vehID_tuple_all, 'vehicle not in env' self.timestep += 1 #","(1 - alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader = 0 # if","check traffic flow density if traffic == 0: # average 9 vehicles self.cfg","self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments","# todo modify if self.is_success: self.done = True # print('reset on: successfully lane","- self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time +","in self.vehID_tuple_all: self.done = True # print('reset on: self.ego not in env:', self.egoID","0 r_safe = w_lateral * (r_lat_c + r_lat_t) + w_longi * (r_long_c+ r_long_t)","self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation","import sys import random import datetime import gym from gym import spaces import","ends self.is_done() if self.done is True: self.info['resetFlag'] = True return self.observation, 0.0, self.done,","TTC2 / delta_A2 if self.lateral_action == 1 and 0 < TTC2 < 2:","w_lateral * alpha + w_longi * (1 - alpha) * abs(self.ego.leaderDis) # else:","change lateral: action[1] = 1: lane change action[1] = 0: abort lane change,","else: # r_safe_tgtleader = 0 # # # r_safe = r_safe_leader + r_safe_tgtleader","None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)","= self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0:","delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2","3] = 0 # todo check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos","self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower)","None: # compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A =","set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor","# (float) : amount of reward returned after previous action self.done = True","not in self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0:","= 0: follow original lane leader action[0] = 1: follow target lane leader","== 0: #abort lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert","change action[1] = 0: abort lane change, change back to original lane action[1]","vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average 19 vehicles self.cfg","r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time + r_speed +","to reset this environment's state. Accepts an action and returns a tuple (observation,","to target lane; 2:keep current # lane change to target lane if not","0 self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None self.veh_dict = {}","action[0] # action_lateral = action[1] assert self.done is False, 'self.done is not False'","ws * (self.ego.speed - self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all","auxiliary diagnostic information (helpful for debugging, and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space","= 1: follow target lane leader **important**: orginal/target lane leader will not change","print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self,","# if self.ego.leaderID is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) #","0: follow original lane leader action[0] = 1: follow closer leader longitudinal2: action[0]","related to efficiency r_time = - wt * self.timestep r_speed = ws *","vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID))","successfully executed, episode ends, reset env # todo modify if self.is_success: self.done =","in which case further step() calls will return undefined results self.info = {","related to comfort r_comf = wc1 * self.ego.acce ** 2 + wc2 *","is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step","= 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg'","gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 =",":param tfc: int. 0:light; 1:medium; 2:dense :return: initial observation \"\"\" self.seed(randomseed) if sumoseed","-1: decelerate action[0] = 0: use SUMO default action[0] = others: acce =","4 + 1] = veh.speed self.observation[name * 4 + 2] = veh.pos_lat self.observation[name","0] = self.observation[0] + 300. self.observation[name * 4 + 1] = self.observation[1] self.observation[name","returned after previous action self.done = True # (bool): whether the episode has","Returns: described in __init__ \"\"\" action_longi = action // 3 action_lateral = action","import datetime import gym from gym import spaces import numpy as np from","lane leader **important**: orginal/target lane leader will not change despite the lateral position","w_longi * (r_long_c+ r_long_t) # # if self.ego.leaderID is not None: # #","control------------------------- # episode in progress; 0:change back to original line; 1:lane change to","math.exp(-2 * TTC2 + 5) else: r_long_t = 0 if self.lateral_action == 1:","+ acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID)","alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <= alpha <=","vNext = self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep()","'--start', str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep","1 w_longi = 1 if self.ego.leaderID is not None: # compute longitudinal time","lateral control------------------------- # episode in progress; 0:change back to original line; 1:lane change","self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \"\"\"","-delta_V2 - math.sqrt(delta_V2 ** 2 + 2 * delta_A2 * delta_D2) TTC2 =","import numpy as np from env.IDM import IDM from env.Road import Road from","self.is_success = False self.collision_num = 0 self.lateral_action = 2 # self.observation = [[0,","alpha <= 1.1 # r_safe_leader = w_lateral * alpha + w_longi * (1","described in __init__ \"\"\" action_longi = action // 3 action_lateral = action %","* traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation() return self.observation return def","import Road from env.Vehicle import Vehicle import math # add sumo/tools into python","[[0, 0, 0], # ego lane position and speed # [0, 0, 0],","speed # [0, 0, 0], # leader # [0, 0, 0], # target","safety w_lateral = 1 w_longi = 1 if self.ego.leaderID is not None: #","= 4.8 self.observation[name * 4 + 3] = 0 # todo check if","= 1 # set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid)","seed is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def reset(self,","gui=False, seed=None): # todo check traffic flow density if traffic == 0: #","self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done() if self.done is","self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until ego appears in","longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce","# print('reset on: self.ego not in env:', self.egoID not in self.vehID_tuple_all) # collision","and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self,","self.preStep() if self.timestep > 5000: raise Exception('cannot find ego after 5000 timesteps') assert","veh.speed self.observation[name * 4 + 2] = veh.pos_lat self.observation[name * 4 + 3]","lateral position Returns: described in __init__ \"\"\" action_longi = action // 3 action_lateral","to safety w_lateral = 1 w_longi = 1 if self.ego.leaderID is not None:","self.cfg, # '--lanechange.duration', str(3), # using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), #","ego vehicle id :param tfc: int. 0:light; 1:medium; 2:dense :return: initial observation \"\"\"","- math.sqrt(delta_V2 ** 2 + 2 * delta_A2 * delta_D2) TTC2 = TTC2","(self.ego.speed - self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time","r_total def is_done(self): # lane change successfully executed, episode ends, reset env #","# print('reset on: too close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego","self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd)","action // 3 action_lateral = action % 3 self.lateral_action = action_lateral # action_longi","False, 'self.done is not False' assert action is not None, 'action is None'","4 + 3] = 0 # todo check if rational def updateObservation(self): self.observation[0]","self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat -","orginal/target lane leader will not change despite the lateral position of the ego","Args: action (object): longitudinal0: action[0] = 1: accelerate action[0] = -1: decelerate action[0]","self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until ego appears in env if","w_longi = 1 if self.ego.leaderID is not None: # compute longitudinal time gap","- alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader = 0 # if self.ego.targetLeaderID","'SUMO_HOME'\") import traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1,","4 + 3] = veh.acce else: self.observation[name * 4 + 0] = self.observation[0]","1] = self.observation[1] self.observation[name * 4 + 2] = 4.8 self.observation[name * 4","else: r_long_t = 0 if self.lateral_action == 1: # lane change alpha =","**important**: orginal/target lane leader will not change despite the lateral position of the","1:lane change to target lane; 2:keep current # lane change to target lane","** 2 # reward related to efficiency r_time = - wt * self.timestep","True # print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all)","if seed is None: self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed', str(seed)] #","delta_A2 == 0: TTC2 = - abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2","id :param tfc: int. 0:light; 1:medium; 2:dense :return: initial observation \"\"\" self.seed(randomseed) if","has ended, in which case further step() calls will return undefined results self.info","r_safe_leader = 0 # if self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat","from env.IDM import IDM from env.Road import Road from env.Vehicle import Vehicle import","# print('reset on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too close to","+ r_effi_all + r_safe return r_total def is_done(self): # lane change successfully executed,","self.rd) # print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep current lateral position","\"\"\" reset env :param id: ego vehicle id :param tfc: int. 0:light; 1:medium;","= self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all","action_lateral = action % 3 self.lateral_action = action_lateral # action_longi = action[0] #","environment if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\"please","in preStpe self.preStep() if self.timestep > 5000: raise Exception('cannot find ego after 5000","* 4 + 3] = 0 # todo check if rational def updateObservation(self):","alpha <= 1.1 # # r_safe_tgtleader = w_lateral * alpha + w_longi *","(r_long_c+ r_long_t) # # if self.ego.leaderID is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat","seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \"\"\" reset env","gui is True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end',","assert 0 <= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0","of the environment's dynamics. When end of episode is reached, call `reset()` outside","0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd)","= 1 wt = 1 ws = 1 we = 1 # reward","TTC = - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A *","assert 0 <= alpha <= 1.1 # # r_safe_tgtleader = w_lateral * alpha","veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if",":param name: 0:ego; 1:leader; 2:target leader; 3:target follower :param id: vehicle id corresponding","start training while ego is not in env\" self.done = False self.ego =","- alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader =","'--default.action-step-length', str(0.1)] # randomness if seed is None: self.sumoCmd += ['--random'] else: self.sumoCmd","'action is None' assert self.egoID in self.vehID_tuple_all, 'vehicle not in env' self.timestep +=","self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth))","0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat)","= self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3,","+= ['--random'] else: self.sumoCmd += ['--seed', str(seed)] # gui if gui is True:","change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha <=","'-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd","not in self.vehID_tuple_all: self.done = True # print('reset on: self.ego not in env:',","# average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average","= 0: follow original lane leader action[0] = 1: follow closer leader longitudinal2:","action[1] = 0: abort lane change, change back to original lane action[1] =","= veh.lanePos self.observation[name * 4 + 1] = veh.speed self.observation[name * 4 +","= self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until ego appears","import os import sys import random import datetime import gym from gym import","simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None): # todo check","density if traffic == 0: # average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif","change despite the lateral position of the ego may change lateral: action[1] =","self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change, change back to","self.rd.laneWidth - self.ego.pos_lat) # keep current lateral position if action_lateral == 2: self.is_success","randomseed=None): \"\"\" reset env :param id: ego vehicle id :param tfc: int. 0:light;","+ self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd","= tgtlane self.is_success = False self.collision_num = 0 self.lateral_action = 2 # self.observation","3.2 assert 0 <= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t =","== 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex,","0], # ego lane position and speed # [0, 0, 0], # leader","# # r_safe_tgtleader = w_lateral * alpha + w_longi * (1 - alpha)","1: lane change action[1] = 0: abort lane change, change back to original","= True return self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward = self.updateReward() return","for debugging, and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,))","= self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep","= we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time + r_speed + r_effi","self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \"\"\"Run","* (r_lat_c + r_lat_t) + w_longi * (r_long_c+ r_long_t) # # if self.ego.leaderID","1] = veh.speed self.observation[name * 4 + 2] = veh.pos_lat self.observation[name * 4","str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed is None: self.sumoCmd += ['--random'] else:","str(float/int), instead of '3.0' self.sumoBinary = \"/usr/local/Cellar/sumo/1.2.0/bin/sumo\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration',","return self.observation, self.reward, self.done, self.info def seed(self, seed=None): if seed is None: self.randomseed","and 0 < TTC2 < 2: r_long_t = - math.exp(-2 * TTC2 +","1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe = w_lateral * (r_lat_c","# print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep current lateral position if","lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha","traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done() if self.done is True: self.info['resetFlag']","self.vehID_tuple_all, \"cannot start training while ego is not in env\" self.done = False","reward related to safety w_lateral = 1 w_longi = 1 if self.ego.leaderID is","self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def","sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple):","- abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC","r_total = r_comf + r_effi_all + r_safe return r_total def is_done(self): # lane","'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change,","self.observation[name * 4 + 2] = 4.8 self.observation[name * 4 + 3] =","self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id","['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd =","# (dict): contains auxiliary diagnostic information (helpful for debugging, and sometimes learning) self.action_space","(dict): contains auxiliary diagnostic information (helpful for debugging, and sometimes learning) self.action_space =","abs(self.ego.leaderDis) # else: # r_safe_leader = 0 # if self.ego.targetLeaderID is not None:","if veh is not None: self.observation[name * 4 + 0] = veh.lanePos self.observation[name","continue step until ego appears in env if self.egoID is not None: while","# print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2","# assert 0 <= alpha <= 1.1 # # r_safe_tgtleader = w_lateral *","lane change, change back to original lane action[1] = 2: keep in current","self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation() return","def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2 = 1 wt","300. self.observation[name * 4 + 1] = self.observation[1] self.observation[name * 4 + 2]","* (1 - alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: #","= traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done = True # print('reset on: self.collision_num:',","= Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed =","current lateral position Returns: described in __init__ \"\"\" action_longi = action // 3","rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3]","env.Vehicle import Vehicle import math # add sumo/tools into python environment if 'SUMO_HOME'","wt * self.timestep r_speed = ws * (self.ego.speed - self.ego_speedLimit) r_effi = we","is not None: # compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed","original lane action[1] = 2: keep in current lateral position Returns: described in","= ['-c', self.cfg, # '--lanechange.duration', str(3), # using 'Simple Continuous lane-change model' '--lateral-resolution',","self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average 19 vehicles self.cfg =","self.done is True: self.info['resetFlag'] = True return self.observation, 0.0, self.done, self.info else: self.updateObservation()","* (r_long_c+ r_long_t) # # if self.ego.leaderID is not None: # # ('lateralPos2leader',","- (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane',","/ delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2 + 2 *","+ wc2 * self.ego.delta_acce ** 2 # reward related to efficiency r_time =","elif traffic == 2: # average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: #","alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha) # assert","True # print('reset on: self.ego not in env:', self.egoID not in self.vehID_tuple_all) #","'self.done is not False' assert action is not None, 'action is None' assert","= 0 if self.lateral_action == 1: # lane change alpha = abs(self.ego.pos_lat -","1.1 # r_safe_leader = w_lateral * alpha + w_longi * (1 - alpha)","def step(self, action=2): \"\"\"Run one timestep of the environment's dynamics. When end of","# and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) #","else: self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None):","int. 0:light; 1:medium; 2:dense :return: initial observation \"\"\" self.seed(randomseed) if sumoseed is None:","ended, in which case further step() calls will return undefined results self.info =","model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if","return self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward,","position if action_lateral == 2: self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal control2---------------------","if action_lateral == 2: self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext","def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \"\"\" reset env :param id:","Exception('cannot find ego after 5000 timesteps') assert self.egoID in self.vehID_tuple_all, \"cannot start training","math # add sumo/tools into python environment if 'SUMO_HOME' in os.environ: tools =","# lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <=","is True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True),","raise Exception('cannot find ego after 5000 timesteps') assert self.egoID in self.vehID_tuple_all, \"cannot start","= w_lateral * (r_lat_c + r_lat_t) + w_longi * (r_long_c+ r_long_t) # #","> 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith',","traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed = None","into python environment if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success')","import random import datetime import gym from gym import spaces import numpy as","seed=None): # todo check traffic flow density if traffic == 0: # average","# reward related to comfort r_comf = wc1 * self.ego.acce ** 2 +","= np.empty(20) self.reward = None # (float) : amount of reward returned after","veh): \"\"\" :param name: 0:ego; 1:leader; 2:target leader; 3:target follower :param id: vehicle","/ 3.2 # assert 0 <= alpha <= 1.1 # r_safe_leader = w_lateral","dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out of env if self.egoID not in","not None: self.observation[name * 4 + 0] = veh.lanePos self.observation[name * 4 +","for veh_id in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in","use SUMO default action[0] = others: acce = 0.0 longitudinal1: action[0] = 0:","in env\" self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego =","str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep =","self.ego = None # self.tgtLane = tgtlane self.is_success = False self.collision_num = 0","to ego's original lane if action_lateral == 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth)","= r_comf + r_effi_all + r_safe return r_total def is_done(self): # lane change","close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out of env","0 <= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0 if","1 we = 1 # reward related to comfort r_comf = wc1 *","= 0 # if self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat -","sumoseed is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue","check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] =","action[0] = 0: follow original lane leader action[0] = 1: follow target lane","* 4 + 1] = self.observation[1] self.observation[name * 4 + 2] = 4.8","def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id]"],"string":"[\n \"todo check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2]\",\n \"if not self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) >\",\n \"self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 # set ego vehicle\",\n \"# assert 0 <= alpha <= 1.1 # r_safe_leader = w_lateral * alpha\",\n \"+ 2] = veh.pos_lat self.observation[name * 4 + 3] = veh.acce else: self.observation[name\",\n \"+ 2] = 4.8 self.observation[name * 4 + 3] = 0 # todo\",\n \"+ 1] = veh.speed self.observation[name * 4 + 2] = veh.pos_lat self.observation[name *\",\n \"<= alpha <= 1.1 # # r_safe_tgtleader = w_lateral * alpha + w_longi\",\n \"0:light; 1:medium; 2:dense :return: initial observation \\\"\\\"\\\" self.seed(randomseed) if sumoseed is None: self.sumoseed\",\n \"= tlane self.ego.is_ego = 1 # set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0)\",\n \"LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None): # todo check traffic flow density\",\n \"action[0] = 1: accelerate action[0] = -1: decelerate action[0] = 0: use SUMO\",\n \"'--lanechange.duration', str(3), # using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model'\",\n \"2 * delta_A2 * delta_D2) TTC2 = TTC2 / delta_A2 if self.lateral_action ==\",\n \"wc1 * self.ego.acce ** 2 + wc2 * self.ego.delta_acce ** 2 # reward\",\n \"0, 0], # target lane leader # [0, 0, 0]] # target lane\",\n \"in progress; 0:change back to original line; 1:lane change to target lane; 2:keep\",\n \"= self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader)\",\n \"and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left',\",\n \"action[0] = 0: follow original lane leader action[0] = 1: follow closer leader\",\n \"not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name,\",\n \"action self.done = True # (bool): whether the episode has ended, in which\",\n \"is not None: self.observation[name * 4 + 0] = veh.lanePos self.observation[name * 4\",\n \"r_effi_all = r_time + r_speed + r_effi # reward related to safety w_lateral\",\n \"env' self.timestep += 1 # lateral control------------------------- # episode in progress; 0:change back\",\n \"'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else:\",\n \"abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2 + 2\",\n \"of reward returned after previous action self.done = True # (bool): whether the\",\n \"['--seed', str(seed)] # gui if gui is True: self.sumoBinary += '-gui' self.sumoCmd =\",\n \"assert self.done is False, 'self.done is not False' assert action is not None,\",\n \"[self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary] +\",\n \"and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat',\",\n \"abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0 # #\",\n \"self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext)\",\n \"if self.ego.leaderID is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha\",\n \"assert self.egoID in self.vehID_tuple_all, 'vehicle not in env' self.timestep += 1 # lateral\",\n \"'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed is None: self.sumoCmd +=\",\n \"# r_safe_tgtleader = w_lateral * alpha + w_longi * (1 - alpha) *\",\n \"occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done = True # print('reset\",\n \"TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2 + 2 * delta_A2 * delta_D2)\",\n \"def _updateObservationSingle(self, name, veh): \\\"\\\"\\\" :param name: 0:ego; 1:leader; 2:target leader; 3:target follower\",\n \"delta_D2) TTC2 = TTC2 / delta_A2 if self.lateral_action == 1 and 0 <\",\n \"# # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) /\",\n \"self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else:\",\n \"1 ws = 1 we = 1 # reward related to comfort r_comf\",\n \"<= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID is not\",\n \"= np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1\",\n \"r_speed + r_effi # reward related to safety w_lateral = 1 w_longi =\",\n \"self.veh_dict.keys(): # must ensure safety in preStpe self.preStep() if self.timestep > 5000: raise\",\n \"current lateral position if action_lateral == 2: self.is_success = self.ego.changeLane(True, -1, self.rd) #\",\n \"# reward related to efficiency r_time = - wt * self.timestep r_speed =\",\n \"self.sumoBinary = \\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3), # using 'Simple\",\n \"4 + 1] = self.observation[1] self.observation[name * 4 + 2] = 4.8 self.observation[name\",\n \"`reset()` outside env!! to reset this environment's state. Accepts an action and returns\",\n \"gym import spaces import numpy as np from env.IDM import IDM from env.Road\",\n \"original lane leader action[0] = 1: follow target lane leader **important**: orginal/target lane\",\n \"wc1 = 1 wc2 = 1 wt = 1 ws = 1 we\",\n \"self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time + r_speed\",\n \"5000 timesteps') assert self.egoID in self.vehID_tuple_all, \\\"cannot start training while ego is not\",\n \"math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action != 1 and\",\n \"* self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time + r_speed + r_effi # reward\",\n \"id=None, traffic=1, gui=False, seed=None): # todo check traffic flow density if traffic ==\",\n \"# compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce\",\n \"0:ego; 1:leader; 2:target leader; 3:target follower :param id: vehicle id corresponding to name\",\n \"self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \\\"\\\"\\\" :param\",\n \"= 0 # todo check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1]\",\n \"0 if self.lateral_action == 1: # lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)\",\n \"# target lane follower self.observation = np.empty(20) self.reward = None # (float) :\",\n \"undefined results self.info = { 'resetFlag': 0} # (dict): contains auxiliary diagnostic information\",\n \"list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \\\"\\\"\\\" :param name: 0:ego; 1:leader; 2:target\",\n \"0 <= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe\",\n \"= self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos -\",\n \"wc2 * self.ego.delta_acce ** 2 # reward related to efficiency r_time = -\",\n \"ego vehicle out of env if self.egoID not in self.vehID_tuple_all: self.done = True\",\n \"= 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must\",\n \"0, 0]] # target lane follower self.observation = np.empty(20) self.reward = None #\",\n \"not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id\",\n \"self.done = True # print('reset on: self.ego not in env:', self.egoID not in\",\n \"# todo check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed\",\n \"self.timestep += 1 # lateral control------------------------- # episode in progress; 0:change back to\",\n \"the environment's dynamics. When end of episode is reached, call `reset()` outside env!!\",\n \"0 < TTC2 < 2: r_long_t = - math.exp(-2 * TTC2 + 5)\",\n \"r_safe = w_lateral * (r_lat_c + r_lat_t) + w_longi * (r_long_c+ r_long_t) #\",\n \"# self.ego.dis2tgtLane) # ego vehicle out of env if self.egoID not in self.vehID_tuple_all:\",\n \"# print(acceNext) vNext = self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update\",\n \"= w_lateral * alpha + w_longi * (1 - alpha) * abs( #\",\n \"in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh):\",\n \"self.done, self.info def seed(self, seed=None): if seed is None: self.randomseed = datetime.datetime.now().microsecond else:\",\n \"TTC2 + 5) else: r_long_t = 0 if self.lateral_action == 1: # lane\",\n \"< TTC < 2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c = 0 if\",\n \"must be converted to str(float/int), instead of '3.0' self.sumoBinary = \\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\" self.sumoCmd =\",\n \"#abort lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <=\",\n \"preStpe self.preStep() if self.timestep > 5000: raise Exception('cannot find ego after 5000 timesteps')\",\n \"ego after 5000 timesteps') assert self.egoID in self.vehID_tuple_all, \\\"cannot start training while ego\",\n \"- self.ego.acce if delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC =\",\n \"ego may change lateral: action[1] = 1: lane change action[1] = 0: abort\",\n \"wc2 = 1 wt = 1 ws = 1 we = 1 #\",\n \"leader # [0, 0, 0]] # target lane follower self.observation = np.empty(20) self.reward\",\n \"= 2 # self.observation = [[0, 0, 0], # ego lane position and\",\n \"on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too close to ramp entrance\",\n \"back to ego's original lane if action_lateral == 0: # and abs(self.ego.pos_lat -\",\n \"returns a tuple (observation, reward, done, info). Args: action (object): longitudinal0: action[0] =\",\n \"end of episode is reached, call `reset()` outside env!! to reset this environment's\",\n \"tlane self.ego.is_ego = 1 # set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor\",\n \"# reward related to safety w_lateral = 1 w_longi = 1 if self.ego.leaderID\",\n \"2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action != 1 and 0 <\",\n \"is not None: while self.egoID not in self.veh_dict.keys(): # must ensure safety in\",\n \"** 2 + wc2 * self.ego.delta_acce ** 2 # reward related to efficiency\",\n \"r_lat_c = 0 if self.ego.targetLeaderID is not None: # compute longitudinal time gap\",\n \"traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \\\"\\\"\\\"Run one timestep of the\",\n \"in env if self.egoID is not None: while self.egoID not in self.veh_dict.keys(): #\",\n \"in self.vehID_tuple_all, \\\"cannot start training while ego is not in env\\\" self.done =\",\n \"lane leader action[0] = 1: follow closer leader longitudinal2: action[0] = 0: follow\",\n \"0 self.lateral_action = 2 # self.observation = [[0, 0, 0], # ego lane\",\n \"in self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done\",\n \"# # print('alpha', alpha) # assert 0 <= alpha <= 1.1 # #\",\n \"_updateObservationSingle(self, name, veh): \\\"\\\"\\\" :param name: 0:ego; 1:leader; 2:target leader; 3:target follower :param\",\n \"decelerate action[0] = 0: use SUMO default action[0] = others: acce = 0.0\",\n \"- (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 *\",\n \"change back to original lane action[1] = 2: keep in current lateral position\",\n \"of env if self.egoID not in self.vehID_tuple_all: self.done = True # print('reset on:\",\n \"math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action == 0: #abort lane change alpha\",\n \"is False, 'self.done is not False' assert action is not None, 'action is\",\n \"updateReward2(self): wc1 = 1 wc2 = 1 wt = 1 ws = 1\",\n \"to str(float/int), instead of '3.0' self.sumoBinary = \\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\" self.sumoCmd = ['-c', self.cfg, #\",\n \"str(3), # using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length',\",\n \"print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort\",\n \"5) else: r_long_t = 0 if self.lateral_action == 1: # lane change alpha\",\n \"0 <= alpha <= 1.1 # # r_safe_tgtleader = w_lateral * alpha +\",\n \"follow original lane leader action[0] = 1: follow closer leader longitudinal2: action[0] =\",\n \"3 action_lateral = action % 3 self.lateral_action = action_lateral # action_longi = action[0]\",\n \"r_safe_leader + r_safe_tgtleader # total reward r_total = r_comf + r_effi_all + r_safe\",\n \"str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed is\",\n \"= 0 if self.ego.targetLeaderID is not None: # compute longitudinal time gap delta_V2\",\n \"action[0] = 1: follow closer leader longitudinal2: action[0] = 0: follow original lane\",\n \"sumo/tools into python environment if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools)\",\n \"-(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change, change back to ego's original lane\",\n \"* self.timestep r_speed = ws * (self.ego.speed - self.ego_speedLimit) r_effi = we *\",\n \"follow original lane leader action[0] = 1: follow target lane leader **important**: orginal/target\",\n \"info). Args: action (object): longitudinal0: action[0] = 1: accelerate action[0] = -1: decelerate\",\n \"def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] =\",\n \"0 if self.lateral_action == 0: #abort lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)\",\n \"self.timestep r_speed = ws * (self.ego.speed - self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane\",\n \"if traffic == 0: # average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic\",\n \"/ 3.2 # # print('alpha', alpha) # assert 0 <= alpha <= 1.1\",\n \"'3.0' self.sumoBinary = \\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3), # using\",\n \"return undefined results self.info = { 'resetFlag': 0} # (dict): contains auxiliary diagnostic\",\n \"2: self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) #\",\n \"abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert\",\n \"entrance if self.ego.dis2entrance < 10.0: self.done = True # print('reset on: too close\",\n \"change, change back to ego's original lane if action_lateral == 0: # and\",\n \"must be string, if float/int, must be converted to str(float/int), instead of '3.0'\",\n \"self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0 # # # r_safe\",\n \"Road from env.Vehicle import Vehicle import math # add sumo/tools into python environment\",\n \"False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 # set ego\",\n \"self.ego.pos_lat) # keep current lateral position if action_lateral == 2: self.is_success = self.ego.changeLane(True,\",\n \"lateral: action[1] = 1: lane change action[1] = 0: abort lane change, change\",\n \"1 if self.ego.leaderID is not None: # compute longitudinal time gap delta_V =\",\n \"r_lat_t) + w_longi * (r_long_c+ r_long_t) # # if self.ego.leaderID is not None:\",\n \"float/int, must be converted to str(float/int), instead of '3.0' self.sumoBinary = \\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\" self.sumoCmd\",\n \"of episode is reached, call `reset()` outside env!! to reset this environment's state.\",\n \"self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if float/int, must be converted\",\n \"0], # target lane leader # [0, 0, 0]] # target lane follower\",\n \"- math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action == 0: #abort lane change\",\n \"# abort lane change, change back to ego's original lane if action_lateral ==\",\n \"[0, 0, 0]] # target lane follower self.observation = np.empty(20) self.reward = None\",\n \"0]] # target lane follower self.observation = np.empty(20) self.reward = None # (float)\",\n \"self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) #\",\n \"- self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if\",\n \"environment's state. Accepts an action and returns a tuple (observation, reward, done, info).\",\n \"[0, 0, 0], # target lane leader # [0, 0, 0]] # target\",\n \"an action and returns a tuple (observation, reward, done, info). Args: action (object):\",\n \"vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode\",\n \"<= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID\",\n \"not change despite the lateral position of the ego may change lateral: action[1]\",\n \"self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self):\",\n \"1: follow target lane leader **important**: orginal/target lane leader will not change despite\",\n \"seed is None: self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed', str(seed)] # gui\",\n \"self.done = True # (bool): whether the episode has ended, in which case\",\n \"vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if float/int, must be\",\n \"= 0 # # # r_safe = r_safe_leader + r_safe_tgtleader # total reward\",\n \"# print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) #\",\n \"change to target lane; 2:keep current # lane change to target lane if\",\n \"- wt * self.timestep r_speed = ws * (self.ego.speed - self.ego_speedLimit) r_effi =\",\n \"abort lane change, change back to original lane action[1] = 2: keep in\",\n \"# arguments must be string, if float/int, must be converted to str(float/int), instead\",\n \"else: r_lat_c = 0 if self.ego.targetLeaderID is not None: # compute longitudinal time\",\n \"= 0.0 longitudinal1: action[0] = 0: follow original lane leader action[0] = 1:\",\n \"# print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change, change back to ego's\",\n \"r_safe return r_total def is_done(self): # lane change successfully executed, episode ends, reset\",\n \"debugging, and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def\",\n \"episode has ended, in which case further step() calls will return undefined results\",\n \"self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation() return self.observation return\",\n \"abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_t =\",\n \"= None self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all = () self.egoID =\",\n \"time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2\",\n \"acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID,\",\n \"r_comf + r_effi_all + r_safe return r_total def is_done(self): # lane change successfully\",\n \"self.ego.dis2entrance < 10.0: self.done = True # print('reset on: too close to ramp\",\n \"# self.observation = [[0, 0, 0], # ego lane position and speed #\",\n \"IDM from env.Road import Road from env.Vehicle import Vehicle import math # add\",\n \"dynamics. When end of episode is reached, call `reset()` outside env!! to reset\",\n \"def is_done(self): # lane change successfully executed, episode ends, reset env # todo\",\n \"'--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed\",\n \"4 + 0] = veh.lanePos self.observation[name * 4 + 1] = veh.speed self.observation[name\",\n \":return: initial observation \\\"\\\"\\\" self.seed(randomseed) if sumoseed is None: self.sumoseed = self.randomseed traci.close()\",\n \"name :return: \\\"\\\"\\\" if veh is not None: self.observation[name * 4 + 0]\",\n \"entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out of env if self.egoID not\",\n \"leader # [0, 0, 0], # target lane leader # [0, 0, 0]]\",\n \"to target lane if not self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat\",\n \"/ self.ego.dis2entrance r_effi_all = r_time + r_speed + r_effi # reward related to\",\n \"** 2 + 2 * delta_A2 * delta_D2) TTC2 = TTC2 / delta_A2\",\n \"= 1 ws = 1 we = 1 # reward related to comfort\",\n \"(object): longitudinal0: action[0] = 1: accelerate action[0] = -1: decelerate action[0] = 0:\",\n \"lane position and speed # [0, 0, 0], # leader # [0, 0,\",\n \"and speed # [0, 0, 0], # leader # [0, 0, 0], #\",\n \"abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <= alpha <= 1.1 #\",\n \"# else: # r_safe_tgtleader = 0 # # # r_safe = r_safe_leader +\",\n \"TTC/delta_A if self.lateral_action != 1 and 0 < TTC < 2: r_long_c =\",\n \"+ 2 * delta_A2 * delta_D2) TTC2 = TTC2 / delta_A2 if self.lateral_action\",\n \"gym from gym import spaces import numpy as np from env.IDM import IDM\",\n \"self.updateReward() return self.observation, self.reward, self.done, self.info def seed(self, seed=None): if seed is None:\",\n \"self.observation[name * 4 + 0] = veh.lanePos self.observation[name * 4 + 1] =\",\n \"id: vehicle id corresponding to name :return: \\\"\\\"\\\" if veh is not None:\",\n \"self.is_success: self.done = True # print('reset on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane)\",\n \"- 0.5*self.rd.laneWidth)) # abort lane change, change back to ego's original lane if\",\n \"keep in current lateral position Returns: described in __init__ \\\"\\\"\\\" action_longi = action\",\n \"# self.tgtLane = tgtlane self.is_success = False self.collision_num = 0 self.lateral_action = 2\",\n \"= self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 # set ego vehicle speed\",\n \"= -delta_V2 - math.sqrt(delta_V2 ** 2 + 2 * delta_A2 * delta_D2) TTC2\",\n \"print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep current lateral position if action_lateral\",\n \"efficiency r_time = - wt * self.timestep r_speed = ws * (self.ego.speed -\",\n \"self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd =\",\n \"total reward r_total = r_comf + r_effi_all + r_safe return r_total def is_done(self):\",\n \"None: while self.egoID not in self.veh_dict.keys(): # must ensure safety in preStpe self.preStep()\",\n \"w_lateral = 1 w_longi = 1 if self.ego.leaderID is not None: # compute\",\n \"{} self.vehID_tuple_all = () self.egoID = id self.ego = None # self.tgtLane =\",\n \"# self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0 # # #\",\n \"in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id not\",\n \"reward r_total = r_comf + r_effi_all + r_safe return r_total def is_done(self): #\",\n \"__init__ \\\"\\\"\\\" action_longi = action // 3 action_lateral = action % 3 self.lateral_action\",\n \"self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self):\",\n \"False' assert action is not None, 'action is None' assert self.egoID in self.vehID_tuple_all,\",\n \"2] = veh.pos_lat self.observation[name * 4 + 3] = veh.acce else: self.observation[name *\",\n \"self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if\",\n \"ego appears in env if self.egoID is not None: while self.egoID not in\",\n \"will not change despite the lateral position of the ego may change lateral:\",\n \"change to target lane if not self.is_success: if action_lateral == 1: # and\",\n \"if self.egoID is not None: while self.egoID not in self.veh_dict.keys(): # must ensure\",\n \"# [0, 0, 0]] # target lane follower self.observation = np.empty(20) self.reward =\",\n \"self.done is False, 'self.done is not False' assert action is not None, 'action\",\n \"in self.vehID_tuple_all, 'vehicle not in env' self.timestep += 1 # lateral control------------------------- #\",\n \"reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \\\"\\\"\\\" reset env :param id: ego\",\n \"tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\\\"please declare environment variable 'SUMO_HOME'\\\") import\",\n \"delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0: TTC2 = - abs(delta_D2)\",\n \"training while ego is not in env\\\" self.done = False self.ego = self.veh_dict[self.egoID]\",\n \"action[1] assert self.done is False, 'self.done is not False' assert action is not\",\n \"env\\\" self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1\",\n \"# action_lateral = action[1] assert self.done is False, 'self.done is not False' assert\",\n \"self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC\",\n \"updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2 = 1 wt =\",\n \"self.veh_dict) def _updateObservationSingle(self, name, veh): \\\"\\\"\\\" :param name: 0:ego; 1:leader; 2:target leader; 3:target\",\n \"else: r_lat_t = 0 r_safe = w_lateral * (r_lat_c + r_lat_t) + w_longi\",\n \"= None # (float) : amount of reward returned after previous action self.done\",\n \"1: accelerate action[0] = -1: decelerate action[0] = 0: use SUMO default action[0]\",\n \"alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID is\",\n \"* self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action != 1 and 0 < TTC\",\n \"* self.rd.laneWidth - self.ego.pos_lat) # keep current lateral position if action_lateral == 2:\",\n \"= TTC/delta_A if self.lateral_action != 1 and 0 < TTC < 2: r_long_c\",\n \"self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0: TTC2 = - abs(delta_D2) / delta_V2\",\n \"updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce\",\n \"(float) : amount of reward returned after previous action self.done = True #\",\n \"self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done = True # print('reset on:\",\n \"= veh.pos_lat self.observation[name * 4 + 3] = veh.acce else: self.observation[name * 4\",\n \"== 2: # average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14\",\n \"mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj =\",\n \"1 wc2 = 1 wt = 1 ws = 1 we = 1\",\n \"= 2: keep in current lateral position Returns: described in __init__ \\\"\\\"\\\" action_longi\",\n \"== 2: self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi)\",\n \"target lane leader **important**: orginal/target lane leader will not change despite the lateral\",\n \"reward, done, info). Args: action (object): longitudinal0: action[0] = 1: accelerate action[0] =\",\n \"action[1] = 1: lane change action[1] = 0: abort lane change, change back\",\n \":param id: ego vehicle id :param tfc: int. 0:light; 1:medium; 2:dense :return: initial\",\n \"= 0: use SUMO default action[0] = others: acce = 0.0 longitudinal1: action[0]\",\n \"if self.ego.leaderID is not None: # compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed\",\n \"to name :return: \\\"\\\"\\\" if veh is not None: self.observation[name * 4 +\",\n \"as np from env.IDM import IDM from env.Road import Road from env.Vehicle import\",\n \"is None' assert self.egoID in self.vehID_tuple_all, 'vehicle not in env' self.timestep += 1\",\n \"self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha =\",\n \"if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat\",\n \"diagnostic information (helpful for debugging, and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space =\",\n \"import traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False,\",\n \"= spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if veh_id\",\n \"leader action[0] = 1: follow target lane leader **important**: orginal/target lane leader will\",\n \"self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() #\",\n \"= 1: accelerate action[0] = -1: decelerate action[0] = 0: use SUMO default\",\n \"print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 #\",\n \"1:medium; 2:dense :return: initial observation \\\"\\\"\\\" self.seed(randomseed) if sumoseed is None: self.sumoseed =\",\n \"traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if\",\n \"veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \\\"\\\"\\\" :param name: 0:ego;\",\n \"0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check\",\n \"environment variable 'SUMO_HOME'\\\") import traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def __init__(self,\",\n \"randomness if seed is None: self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed', str(seed)]\",\n \"= () self.egoID = id self.ego = None # self.tgtLane = tgtlane self.is_success\",\n \"None self.veh_dict = {} self.vehID_tuple_all = () self.egoID = id self.ego = None\",\n \"os import sys import random import datetime import gym from gym import spaces\",\n \"change, dis2targetlane:', # self.ego.dis2tgtLane) # too close to ramp entrance if self.ego.dis2entrance <\",\n \"-self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2 = 1 wt = 1 ws\",\n \"spaces import numpy as np from env.IDM import IDM from env.Road import Road\",\n \"self.observation = np.empty(20) self.reward = None # (float) : amount of reward returned\",\n \"0, 0], # ego lane position and speed # [0, 0, 0], #\",\n \"1: # lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0\",\n \"amount of reward returned after previous action self.done = True # (bool): whether\",\n \"further step() calls will return undefined results self.info = { 'resetFlag': 0} #\",\n \"None # (float) : amount of reward returned after previous action self.done =\",\n \"= [[0, 0, 0], # ego lane position and speed # [0, 0,\",\n \"if self.lateral_action != 1 and 0 < TTC < 2: r_long_c = -\",\n \"shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if veh_id not in self.veh_dict.keys():\",\n \"lane change successfully executed, episode ends, reset env # todo modify if self.is_success:\",\n \"0.5*self.rd.laneWidth)) # abort lane change, change back to ego's original lane if action_lateral\",\n \"= 1 wc2 = 1 wt = 1 ws = 1 we =\",\n \"traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all = ()\",\n \"Accepts an action and returns a tuple (observation, reward, done, info). Args: action\",\n \"if self.timestep > 5000: raise Exception('cannot find ego after 5000 timesteps') assert self.egoID\",\n \"alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe = w_lateral\",\n \"preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \\\"\\\"\\\"Run one timestep of\",\n \"calls will return undefined results self.info = { 'resetFlag': 0} # (dict): contains\",\n \"4 + 2] = 4.8 self.observation[name * 4 + 3] = 0 #\",\n \"0: #abort lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0\",\n \"2 + 2 * delta_A2 * delta_D2) TTC2 = TTC2 / delta_A2 if\",\n \"contains auxiliary diagnostic information (helpful for debugging, and sometimes learning) self.action_space = spaces.Discrete(6)\",\n \"True: self.info['resetFlag'] = True return self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward =\",\n \"self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 # set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id,\",\n \"leader longitudinal2: action[0] = 0: follow original lane leader action[0] = 1: follow\",\n \"None self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all = () self.egoID = id\",\n \"/ 3.2 assert 0 <= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c\",\n \"self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \\\"\\\"\\\"Run one timestep of the environment's\",\n \"we = 1 # reward related to comfort r_comf = wc1 * self.ego.acce\",\n \"self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0: TTC2\",\n \"None: # compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 =\",\n \"action_longi = action // 3 action_lateral = action % 3 self.lateral_action = action_lateral\",\n \"1 # set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit\",\n \"= - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis)\",\n \"if self.collision_num > 0: self.done = True # print('reset on: self.collision_num:', self.collision_num) def\",\n \"% 3 self.lateral_action = action_lateral # action_longi = action[0] # action_lateral = action[1]\",\n \"+ 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action != 1 and 0\",\n \"else: self.sumoCmd += ['--seed', str(seed)] # gui if gui is True: self.sumoBinary +=\",\n \"= action_lateral # action_longi = action[0] # action_lateral = action[1] assert self.done is\",\n \"# gui if gui is True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] +\",\n \"* 4 + 3] = veh.acce else: self.observation[name * 4 + 0] =\",\n \"= traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \\\"\\\"\\\"Run one timestep of the environment's dynamics.\",\n \"# episode in progress; 0:change back to original line; 1:lane change to target\",\n \"return r_total def is_done(self): # lane change successfully executed, episode ends, reset env\",\n \"self.ego.targetLeaderID is not None: # compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed -\",\n \"> 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth -\",\n \"w_lateral * alpha + w_longi * (1 - alpha) * abs( # self.ego.lanePos\",\n \"is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat\",\n \"= None # self.tgtLane = tgtlane self.is_success = False self.collision_num = 0 self.lateral_action\",\n \"When end of episode is reached, call `reset()` outside env!! to reset this\",\n \"tgtlane self.is_success = False self.collision_num = 0 self.lateral_action = 2 # self.observation =\",\n \"* abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0 #\",\n \"* TTC2 + 5) else: r_long_t = 0 if self.lateral_action == 1: #\",\n \"out of env if self.egoID not in self.vehID_tuple_all: self.done = True # print('reset\",\n \"-1, self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed\",\n \"np.empty(20) self.reward = None # (float) : amount of reward returned after previous\",\n \"= traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict)\",\n \"if self.is_success: self.done = True # print('reset on: successfully lane change, dis2targetlane:', #\",\n \"< 2: r_long_t = - math.exp(-2 * TTC2 + 5) else: r_long_t =\",\n \"back to original line; 1:lane change to target lane; 2:keep current # lane\",\n \"self.egoID not in self.vehID_tuple_all: self.done = True # print('reset on: self.ego not in\",\n \"accelerate action[0] = -1: decelerate action[0] = 0: use SUMO default action[0] =\",\n \"action_lateral == 2: self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext =\",\n \"executed, episode ends, reset env # todo modify if self.is_success: self.done = True\",\n \"self.collision_num > 0: self.done = True # print('reset on: self.collision_num:', self.collision_num) def preStep(self):\",\n \"not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat -\",\n \"= abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha) # assert 0\",\n \"-math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe = w_lateral * (r_lat_c + r_lat_t) +\",\n \"0: abort lane change, change back to original lane action[1] = 2: keep\",\n \"after previous action self.done = True # (bool): whether the episode has ended,\",\n \"= self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation() return self.observation\",\n \"self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten()\",\n \"lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha\",\n \"leader will not change despite the lateral position of the ego may change\",\n \"env:', self.egoID not in self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num\",\n \"self.egoID is not None: while self.egoID not in self.veh_dict.keys(): # must ensure safety\",\n \"self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward, self.done, self.info def seed(self, seed=None): if\",\n \"# [0, 0, 0], # leader # [0, 0, 0], # target lane\",\n \"self.veh_dict = {} self.vehID_tuple_all = () self.egoID = id self.ego = None #\",\n \"info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done() if\",\n \"back to original lane action[1] = 2: keep in current lateral position Returns:\",\n \"3.2 # assert 0 <= alpha <= 1.1 # r_safe_leader = w_lateral *\",\n \"modify if self.is_success: self.done = True # print('reset on: successfully lane change, dis2targetlane:',\",\n \"= r_time + r_speed + r_effi # reward related to safety w_lateral =\",\n \"< TTC2 < 2: r_long_t = - math.exp(-2 * TTC2 + 5) else:\",\n \"9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average 19 vehicles\",\n \"(0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth\",\n \"- self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5)\",\n \"return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2 = 1 wt = 1\",\n \"1:leader; 2:target leader; 3:target follower :param id: vehicle id corresponding to name :return:\",\n \"in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \\\"\\\"\\\" :param name: 0:ego; 1:leader;\",\n \"self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action != 1 and 0 < TTC <\",\n \"self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0 self.dt\",\n \"self.observation[name * 4 + 0] = self.observation[0] + 300. self.observation[name * 4 +\",\n \"traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done() if self.done\",\n \"< 10.0: self.done = True # print('reset on: too close to ramp entrance,\",\n \"too close to ramp entrance if self.ego.dis2entrance < 10.0: self.done = True #\",\n \"lane leader # [0, 0, 0]] # target lane follower self.observation = np.empty(20)\",\n \"+ r_safe_tgtleader # total reward r_total = r_comf + r_effi_all + r_safe return\",\n \"self.ego.acce ** 2 + wc2 * self.ego.delta_acce ** 2 # reward related to\",\n \"= - wt * self.timestep r_speed = ws * (self.ego.speed - self.ego_speedLimit) r_effi\",\n \"self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2,\",\n \"= self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V else:\",\n \"reset env :param id: ego vehicle id :param tfc: int. 0:light; 1:medium; 2:dense\",\n \"gui if gui is True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd\",\n \"* 4 + 0] = veh.lanePos self.observation[name * 4 + 1] = veh.speed\",\n \"using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed is None: self.sumoCmd\",\n \"- self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0: TTC2 =\",\n \"learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for\",\n \"# print('alpha', alpha) # assert 0 <= alpha <= 1.1 # # r_safe_tgtleader\",\n \"ego lane position and speed # [0, 0, 0], # leader # [0,\",\n \"r_time + r_speed + r_effi # reward related to safety w_lateral = 1\",\n \"original lane leader action[0] = 1: follow closer leader longitudinal2: action[0] = 0:\",\n \"# check if episode ends self.is_done() if self.done is True: self.info['resetFlag'] = True\",\n \"of the ego may change lateral: action[1] = 1: lane change action[1] =\",\n \"5000: raise Exception('cannot find ego after 5000 timesteps') assert self.egoID in self.vehID_tuple_all, \\\"cannot\",\n \"= spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in\",\n \"+ 5) else: r_long_t = 0 if self.lateral_action == 1: # lane change\",\n \"safety in preStpe self.preStep() if self.timestep > 5000: raise Exception('cannot find ego after\",\n \"= os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\\\"please declare environment variable 'SUMO_HOME'\\\") import traci\",\n \"average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg =\",\n \"self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None self.veh_dict\",\n \"too close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out of\",\n \"// 3 action_lateral = action % 3 self.lateral_action = action_lateral # action_longi =\",\n \"= id self.ego = None # self.tgtLane = tgtlane self.is_success = False self.collision_num\",\n \"self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0: TTC = -\",\n \"current # lane change to target lane if not self.is_success: if action_lateral ==\",\n \"r_speed = ws * (self.ego.speed - self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane /\",\n \"lane; 2:keep current # lane change to target lane if not self.is_success: if\",\n \"= -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe = w_lateral * (r_lat_c + r_lat_t)\",\n \"episode in progress; 0:change back to original line; 1:lane change to target lane;\",\n \"instead of '3.0' self.sumoBinary = \\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3),\",\n \"self.vehID_tuple_all, 'vehicle not in env' self.timestep += 1 # lateral control------------------------- # episode\",\n \"traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until ego appears in env\",\n \"True # print('reset on: too close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) #\",\n \"longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce\",\n \"- math.exp(-2 * TTC2 + 5) else: r_long_t = 0 if self.lateral_action ==\",\n \"not None: # compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2\",\n \"0: self.done = True # print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all\",\n \"(0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex,\",\n \"# must ensure safety in preStpe self.preStep() if self.timestep > 5000: raise Exception('cannot\",\n \"-math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID is not None: # compute longitudinal\",\n \"in __init__ \\\"\\\"\\\" action_longi = action // 3 action_lateral = action % 3\",\n \"# and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) #\",\n \"if self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha\",\n \"if action_lateral == 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success =\",\n \"def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \\\"\\\"\\\"Run one timestep\",\n \"self.lateral_action = 2 # self.observation = [[0, 0, 0], # ego lane position\",\n \"= False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 # set\",\n \"+ 1] = self.observation[1] self.observation[name * 4 + 2] = 4.8 self.observation[name *\",\n \"else: TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A\",\n \"spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple:\",\n \"self.sumoCmd += ['--seed', str(seed)] # gui if gui is True: self.sumoBinary += '-gui'\",\n \"self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep current lateral\",\n \"reward related to efficiency r_time = - wt * self.timestep r_speed = ws\",\n \"# too close to ramp entrance if self.ego.dis2entrance < 10.0: self.done = True\",\n \"os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\\\"please declare environment variable 'SUMO_HOME'\\\") import traci ######################################################################\",\n \"== 0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2 +\",\n \"assert action is not None, 'action is None' assert self.egoID in self.vehID_tuple_all, 'vehicle\",\n \"/ delta_A2 if self.lateral_action == 1 and 0 < TTC2 < 2: r_long_t\",\n \"self.observation[name * 4 + 3] = 0 # todo check if rational def\",\n \"0 <= alpha <= 1.1 # r_safe_leader = w_lateral * alpha + w_longi\",\n \"timestep of the environment's dynamics. When end of episode is reached, call `reset()`\",\n \"lateral position if action_lateral == 2: self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal\",\n \"self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def\",\n \"is True: self.info['resetFlag'] = True return self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward\",\n \"episode ends self.is_done() if self.done is True: self.info['resetFlag'] = True return self.observation, 0.0,\",\n \"= True # print('reset on: self.ego not in env:', self.egoID not in self.vehID_tuple_all)\",\n \"self.reward = self.updateReward() return self.observation, self.reward, self.done, self.info def seed(self, seed=None): if seed\",\n \"results self.info = { 'resetFlag': 0} # (dict): contains auxiliary diagnostic information (helpful\",\n \"'tools') sys.path.append(tools) print('success') else: sys.exit(\\\"please declare environment variable 'SUMO_HOME'\\\") import traci ###################################################################### #\",\n \"# add sumo/tools into python environment if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'],\",\n \"# ego lane position and speed # [0, 0, 0], # leader #\",\n \"self.observation[0] + 300. self.observation[name * 4 + 1] = self.observation[1] self.observation[name * 4\",\n \"= datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True,\",\n \"default action[0] = others: acce = 0.0 longitudinal1: action[0] = 0: follow original\",\n \"step until ego appears in env if self.egoID is not None: while self.egoID\",\n \"to original line; 1:lane change to target lane; 2:keep current # lane change\",\n \"* 4 + 2] = veh.pos_lat self.observation[name * 4 + 3] = veh.acce\",\n \"def seed(self, seed=None): if seed is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed =\",\n \"self.egoID in self.vehID_tuple_all, 'vehicle not in env' self.timestep += 1 # lateral control-------------------------\",\n \"= self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0:\",\n \"longitudinal2: action[0] = 0: follow original lane leader action[0] = 1: follow target\",\n \"self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed +\",\n \"after 5000 timesteps') assert self.egoID in self.vehID_tuple_all, \\\"cannot start training while ego is\",\n \"() self.egoID = id self.ego = None # self.tgtLane = tgtlane self.is_success =\",\n \"average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if float/int,\",\n \"None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until\",\n \"action[1] = 2: keep in current lateral position Returns: described in __init__ \\\"\\\"\\\"\",\n \"None # self.tgtLane = tgtlane self.is_success = False self.collision_num = 0 self.lateral_action =\",\n \"change successfully executed, episode ends, reset env # todo modify if self.is_success: self.done\",\n \"control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed + acceNext * 0.1\",\n \"2 + wc2 * self.ego.delta_acce ** 2 # reward related to efficiency r_time\",\n \"== 0: TTC2 = - abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2 -\",\n \"print('reset on: self.ego not in env:', self.egoID not in self.vehID_tuple_all) # collision occurs\",\n \"else: self.observation[name * 4 + 0] = self.observation[0] + 300. self.observation[name * 4\",\n \"closer leader longitudinal2: action[0] = 0: follow original lane leader action[0] = 1:\",\n \"- self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0\",\n \"target lane leader # [0, 0, 0]] # target lane follower self.observation =\",\n \"# longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed + acceNext\",\n \"def updateReward2(self): wc1 = 1 wc2 = 1 wt = 1 ws =\",\n \"1 # lateral control------------------------- # episode in progress; 0:change back to original line;\",\n \"> 0: self.done = True # print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep()\",\n \"self.ego.lanePos if delta_A2 == 0: TTC2 = - abs(delta_D2) / delta_V2 else: TTC2\",\n \"target lane if not self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat -\",\n \"# print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2 =\",\n \"# set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit =\",\n \"veh.lanePos self.observation[name * 4 + 1] = veh.speed self.observation[name * 4 + 2]\",\n \"add sumo/tools into python environment if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools')\",\n \"alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1\",\n \"self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane\",\n \"until ego appears in env if self.egoID is not None: while self.egoID not\",\n \"numpy as np from env.IDM import IDM from env.Road import Road from env.Vehicle\",\n \"+ self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed\",\n \"self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat\",\n \"r_comf = wc1 * self.ego.acce ** 2 + wc2 * self.ego.delta_acce ** 2\",\n \"check if episode ends self.is_done() if self.done is True: self.info['resetFlag'] = True return\",\n \"1.1 # # r_safe_tgtleader = w_lateral * alpha + w_longi * (1 -\",\n \"self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 =\",\n \"lane if not self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth)\",\n \"action is not None, 'action is None' assert self.egoID in self.vehID_tuple_all, 'vehicle not\",\n \"2:target leader; 3:target follower :param id: vehicle id corresponding to name :return: \\\"\\\"\\\"\",\n \"1 and 0 < TTC < 2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c\",\n \"self.observation[name * 4 + 3] = veh.acce else: self.observation[name * 4 + 0]\",\n \"= [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0 self.dt =\",\n \"if delta_A2 == 0: TTC2 = - abs(delta_D2) / delta_V2 else: TTC2 =\",\n \"todo modify if self.is_success: self.done = True # print('reset on: successfully lane change,\",\n \"# randomness if seed is None: self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed',\",\n \"self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time + r_speed + r_effi # reward related\",\n \"str(0.1)] # randomness if seed is None: self.sumoCmd += ['--random'] else: self.sumoCmd +=\",\n \"= True # print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID)\",\n \"self.timestep > 5000: raise Exception('cannot find ego after 5000 timesteps') assert self.egoID in\",\n \"= - math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action == 0: #abort lane\",\n \"2] = 4.8 self.observation[name * 4 + 3] = 0 # todo check\",\n \"in self.veh_dict.keys(): # must ensure safety in preStpe self.preStep() if self.timestep > 5000:\",\n \"self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 #\",\n \"sumoseed=None, randomseed=None): \\\"\\\"\\\" reset env :param id: ego vehicle id :param tfc: int.\",\n \"not None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat -\",\n \"+= ['--seed', str(seed)] # gui if gui is True: self.sumoBinary += '-gui' self.sumoCmd\",\n \"(1 - alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader\",\n \"if episode ends self.is_done() if self.done is True: self.info['resetFlag'] = True return self.observation,\",\n \"vehicle id corresponding to name :return: \\\"\\\"\\\" if veh is not None: self.observation[name\",\n \"self.randomseed = None self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all = () self.egoID\",\n \"self.observation = [[0, 0, 0], # ego lane position and speed # [0,\",\n \"ensure safety in preStpe self.preStep() if self.timestep > 5000: raise Exception('cannot find ego\",\n \"is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat\",\n \"todo check traffic flow density if traffic == 0: # average 9 vehicles\",\n \"abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC =\",\n \"self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed', str(seed)] # gui if gui is\",\n \"longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed + acceNext *\",\n \"self.rd = Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed\",\n \"###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None): #\",\n \"# ego vehicle out of env if self.egoID not in self.vehID_tuple_all: self.done =\",\n \"self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape)\",\n \"self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success\",\n \"traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation() return self.observation return def close(self):\",\n \"= self.observation[0] + 300. self.observation[name * 4 + 1] = self.observation[1] self.observation[name *\",\n \"None, 'action is None' assert self.egoID in self.vehID_tuple_all, 'vehicle not in env' self.timestep\",\n \"collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done = True #\",\n \"'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change, change back\",\n \"in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd,\",\n \"r_lat_t = 0 r_safe = w_lateral * (r_lat_c + r_lat_t) + w_longi *\",\n \"follower :param id: vehicle id corresponding to name :return: \\\"\\\"\\\" if veh is\",\n \"egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \\\"\\\"\\\" reset env :param id: ego vehicle\",\n \"self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until ego\",\n \"self.info else: self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward, self.done, self.info def seed(self,\",\n \"the ego may change lateral: action[1] = 1: lane change action[1] = 0:\",\n \"self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple:\",\n \"+ r_speed + r_effi # reward related to safety w_lateral = 1 w_longi\",\n \"in env' self.timestep += 1 # lateral control------------------------- # episode in progress; 0:change\",\n \"= TTC2 / delta_A2 if self.lateral_action == 1 and 0 < TTC2 <\",\n \"3.2 # # print('alpha', alpha) # assert 0 <= alpha <= 1.1 #\",\n \"action_lateral # action_longi = action[0] # action_lateral = action[1] assert self.done is False,\",\n \"- self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha',\",\n \"0 # todo check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] =\",\n \"original line; 1:lane change to target lane; 2:keep current # lane change to\",\n \"datetime import gym from gym import spaces import numpy as np from env.IDM\",\n \"= True # print('reset on: too close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane)\",\n \"= action[1] assert self.done is False, 'self.done is not False' assert action is\",\n \"lane leader will not change despite the lateral position of the ego may\",\n \"lane change, change back to ego's original lane if action_lateral == 0: #\",\n \"assert 0 <= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0\",\n \"reward related to comfort r_comf = wc1 * self.ego.acce ** 2 + wc2\",\n \"self.tgtLane = tgtlane self.is_success = False self.collision_num = 0 self.lateral_action = 2 #\",\n \"= - math.exp(-2 * TTC2 + 5) else: r_long_t = 0 if self.lateral_action\",\n \"r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID is not None: #\",\n \"\\\"\\\"\\\" self.seed(randomseed) if sumoseed is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui,\",\n \"r_safe_leader = w_lateral * alpha + w_longi * (1 - alpha) * abs(self.ego.leaderDis)\",\n \"assert 0 <= alpha <= 1.1 # r_safe_leader = w_lateral * alpha +\",\n \"np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2\",\n \"os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\\\"please declare environment variable 'SUMO_HOME'\\\")\",\n \"call `reset()` outside env!! to reset this environment's state. Accepts an action and\",\n \"self.ego.dis2entrance r_effi_all = r_time + r_speed + r_effi # reward related to safety\",\n \"\\\"cannot start training while ego is not in env\\\" self.done = False self.ego\",\n \"case further step() calls will return undefined results self.info = { 'resetFlag': 0}\",\n \"self.done = True # print('reset on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) #\",\n \"1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd)\",\n \"related to safety w_lateral = 1 w_longi = 1 if self.ego.leaderID is not\",\n \"is reached, call `reset()` outside env!! to reset this environment's state. Accepts an\",\n \"position and speed # [0, 0, 0], # leader # [0, 0, 0],\",\n \"information (helpful for debugging, and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf,\",\n \"self.ego.acce if delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V\",\n \"# update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends\",\n \"alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1\",\n \"else: TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2 + 2 * delta_A2 *\",\n \"and 0 < TTC < 2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c =\",\n \"= 0 self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None self.veh_dict =\",\n \"a tuple (observation, reward, done, info). Args: action (object): longitudinal0: action[0] = 1:\",\n \"delta_A2 if self.lateral_action == 1 and 0 < TTC2 < 2: r_long_t =\",\n \"veh_id in veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for\",\n \"self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward, self.done,\",\n \"else: r_long_c = 0 if self.lateral_action == 0: #abort lane change alpha =\",\n \"r_safe_tgtleader # total reward r_total = r_comf + r_effi_all + r_safe return r_total\",\n \"acce = 0.0 longitudinal1: action[0] = 0: follow original lane leader action[0] =\",\n \"seed=self.sumoseed) # continue step until ego appears in env if self.egoID is not\",\n \"random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \\\"\\\"\\\" reset env :param\",\n \"self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done =\",\n \"if gui is True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd +\",\n \"if self.ego.dis2entrance < 10.0: self.done = True # print('reset on: too close to\",\n \"w_longi * (1 - alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else:\",\n \"+ 3] = 0 # todo check if rational def updateObservation(self): self.observation[0] =\",\n \"name: 0:ego; 1:leader; 2:target leader; 3:target follower :param id: vehicle id corresponding to\",\n \"= r_safe_leader + r_safe_tgtleader # total reward r_total = r_comf + r_effi_all +\",\n \"= abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <= alpha <= 1.1\",\n \"= -math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID is not None: # compute\",\n \"on: self.ego not in env:', self.egoID not in self.vehID_tuple_all) # collision occurs self.collision_num\",\n \"if action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success =\",\n \"be converted to str(float/int), instead of '3.0' self.sumoBinary = \\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\" self.sumoCmd = ['-c',\",\n \"veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self,\",\n \"0 if self.ego.targetLeaderID is not None: # compute longitudinal time gap delta_V2 =\",\n \"False self.collision_num = 0 self.lateral_action = 2 # self.observation = [[0, 0, 0],\",\n \"print('success') else: sys.exit(\\\"please declare environment variable 'SUMO_HOME'\\\") import traci ###################################################################### # simulation environments\",\n \"Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None\",\n \"0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth)\",\n \"self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) #\",\n \"will return undefined results self.info = { 'resetFlag': 0} # (dict): contains auxiliary\",\n \"abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5\",\n \"veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in\",\n \"= -1: decelerate action[0] = 0: use SUMO default action[0] = others: acce\",\n \"position Returns: described in __init__ \\\"\\\"\\\" action_longi = action // 3 action_lateral =\",\n \"veh is not None: self.observation[name * 4 + 0] = veh.lanePos self.observation[name *\",\n \"= 1 we = 1 # reward related to comfort r_comf = wc1\",\n \"self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return\",\n \"self.ego.dis2tgtLane) # ego vehicle out of env if self.egoID not in self.vehID_tuple_all: self.done\",\n \"veh.acce else: self.observation[name * 4 + 0] = self.observation[0] + 300. self.observation[name *\",\n \"in current lateral position Returns: described in __init__ \\\"\\\"\\\" action_longi = action //\",\n \"True # print('reset on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too close\",\n \"veh.pos_lat self.observation[name * 4 + 3] = veh.acce else: self.observation[name * 4 +\",\n \"self.reward, self.done, self.info def seed(self, seed=None): if seed is None: self.randomseed = datetime.datetime.now().microsecond\",\n \"self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id\",\n \"0], # leader # [0, 0, 0], # target lane leader # [0,\",\n \"lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness\",\n \"for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \\\"\\\"\\\" :param name:\",\n \"# self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1\",\n \"Continuous lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] #\",\n \"self.egoID not in self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num >\",\n \"action[0] = -1: decelerate action[0] = 0: use SUMO default action[0] = others:\",\n \"if self.done is True: self.info['resetFlag'] = True return self.observation, 0.0, self.done, self.info else:\",\n \"using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length',\",\n \"env.IDM import IDM from env.Road import Road from env.Vehicle import Vehicle import math\",\n \"self.lateral_action == 0: #abort lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2\",\n \"state. Accepts an action and returns a tuple (observation, reward, done, info). Args:\",\n \"# todo check traffic flow density if traffic == 0: # average 9\",\n \"traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until ego appears in env if self.egoID\",\n \"if self.lateral_action == 1: # lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) /\",\n \"delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A ==\",\n \"+ w_longi * (1 - alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) #\",\n \"+ ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd\",\n \"self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0: TTC\",\n \"ego is not in env\\\" self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex =\",\n \"= True # print('reset on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too\",\n \"= 0 self.lateral_action = 2 # self.observation = [[0, 0, 0], # ego\",\n \"= True # (bool): whether the episode has ended, in which case further\",\n \"ends, reset env # todo modify if self.is_success: self.done = True # print('reset\",\n \"0, 0], # leader # [0, 0, 0], # target lane leader #\",\n \"to ramp entrance if self.ego.dis2entrance < 10.0: self.done = True # print('reset on:\",\n \"not in env' self.timestep += 1 # lateral control------------------------- # episode in progress;\",\n \"- self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <= alpha <= 1.1 # r_safe_leader\",\n \"reached, call `reset()` outside env!! to reset this environment's state. Accepts an action\",\n \"reset env # todo modify if self.is_success: self.done = True # print('reset on:\",\n \"compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce -\",\n \"+ 3] = veh.acce else: self.observation[name * 4 + 0] = self.observation[0] +\",\n \"= ws * (self.ego.speed - self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance\",\n \"is not False' assert action is not None, 'action is None' assert self.egoID\",\n \"comfort r_comf = wc1 * self.ego.acce ** 2 + wc2 * self.ego.delta_acce **\",\n \"traffic == 0: # average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic ==\",\n \"TTC = TTC/delta_A if self.lateral_action != 1 and 0 < TTC < 2:\",\n \"alpha + w_longi * (1 - alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos)\",\n \"keep current lateral position if action_lateral == 2: self.is_success = self.ego.changeLane(True, -1, self.rd)\",\n \"3] = veh.acce else: self.observation[name * 4 + 0] = self.observation[0] + 300.\",\n \"if self.egoID not in self.vehID_tuple_all: self.done = True # print('reset on: self.ego not\",\n \"self.lateral_action == 1 and 0 < TTC2 < 2: r_long_t = - math.exp(-2\",\n \"= None self.veh_dict = {} self.vehID_tuple_all = () self.egoID = id self.ego =\",\n \"lateral position of the ego may change lateral: action[1] = 1: lane change\",\n \"print(acceNext) vNext = self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------\",\n \"= others: acce = 0.0 longitudinal1: action[0] = 0: follow original lane leader\",\n \"traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None):\",\n \"2:dense :return: initial observation \\\"\\\"\\\" self.seed(randomseed) if sumoseed is None: self.sumoseed = self.randomseed\",\n \"self.vehID_tuple_all = () self.egoID = id self.ego = None # self.tgtLane = tgtlane\",\n \"= 1 if self.ego.leaderID is not None: # compute longitudinal time gap delta_V\",\n \"id self.ego = None # self.tgtLane = tgtlane self.is_success = False self.collision_num =\",\n \"leader; 3:target follower :param id: vehicle id corresponding to name :return: \\\"\\\"\\\" if\",\n \"follower self.observation = np.empty(20) self.reward = None # (float) : amount of reward\",\n \"env!! to reset this environment's state. Accepts an action and returns a tuple\",\n \"\\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3), # using 'Simple Continuous lane-change\",\n \"traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM()\",\n \"done, info). Args: action (object): longitudinal0: action[0] = 1: accelerate action[0] = -1:\",\n \"TTC < 2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action\",\n \"# compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce\",\n \"1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep current lateral position if action_lateral ==\",\n \"# r_safe_leader = 0 # if self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader',\",\n \"if self.lateral_action == 1 and 0 < TTC2 < 2: r_long_t = -\",\n \"self.egoID in self.vehID_tuple_all, \\\"cannot start training while ego is not in env\\\" self.done\",\n \"the lateral position of the ego may change lateral: action[1] = 1: lane\",\n \"flow density if traffic == 0: # average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg'\",\n \"env if self.egoID not in self.vehID_tuple_all: self.done = True # print('reset on: self.ego\",\n \"sys.exit(\\\"please declare environment variable 'SUMO_HOME'\\\") import traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env):\",\n \"step() calls will return undefined results self.info = { 'resetFlag': 0} # (dict):\",\n \"self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0 # # # r_safe = r_safe_leader\",\n \"longitudinal0: action[0] = 1: accelerate action[0] = -1: decelerate action[0] = 0: use\",\n \"= action // 3 action_lateral = action % 3 self.lateral_action = action_lateral #\",\n \"traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done = True # print('reset on: self.collision_num:', self.collision_num)\",\n \"str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road()\",\n \"acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all)\",\n \"0] = veh.lanePos self.observation[name * 4 + 1] = veh.speed self.observation[name * 4\",\n \"= 1: follow closer leader longitudinal2: action[0] = 0: follow original lane leader\",\n \"self.ego.leaderID is not None: # compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed -\",\n \"lane change to target lane if not self.is_success: if action_lateral == 1: #\",\n \"and returns a tuple (observation, reward, done, info). Args: action (object): longitudinal0: action[0]\",\n \"> 5000: raise Exception('cannot find ego after 5000 timesteps') assert self.egoID in self.vehID_tuple_all,\",\n \"self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego = 1 # set ego vehicle speed mode\",\n \"* abs(self.ego.leaderDis) # else: # r_safe_leader = 0 # if self.ego.targetLeaderID is not\",\n \"action_longi = action[0] # action_lateral = action[1] assert self.done is False, 'self.done is\",\n \"self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3), # using 'Simple Continuous lane-change model'\",\n \"we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time + r_speed + r_effi #\",\n \"self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)]\",\n \"self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all\",\n \"str(seed)] # gui if gui is True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary]\",\n \"environment's dynamics. When end of episode is reached, call `reset()` outside env!! to\",\n \"self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep current\",\n \"# leader # [0, 0, 0], # target lane leader # [0, 0,\",\n \"[self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT()\",\n \"despite the lateral position of the ego may change lateral: action[1] = 1:\",\n \"self.done = True # print('reset on: too close to ramp entrance, dis2targetlane:', #\",\n \"= 1 # reward related to comfort r_comf = wc1 * self.ego.acce **\",\n \"change back to ego's original lane if action_lateral == 0: # and abs(self.ego.pos_lat\",\n \"ego's original lane if action_lateral == 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) >\",\n \"import IDM from env.Road import Road from env.Vehicle import Vehicle import math #\",\n \"update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] =\",\n \"# r_safe_leader = w_lateral * alpha + w_longi * (1 - alpha) *\",\n \"1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0 if self.ego.targetLeaderID is not None:\",\n \"self.lateral_action != 1 and 0 < TTC < 2: r_long_c = - math.exp(-2*TTC+5)\",\n \"time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if\",\n \"else: # average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string,\",\n \"may change lateral: action[1] = 1: lane change action[1] = 0: abort lane\",\n \"if seed is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def\",\n \"+ 300. self.observation[name * 4 + 1] = self.observation[1] self.observation[name * 4 +\",\n \"= self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation =\",\n \"action (object): longitudinal0: action[0] = 1: accelerate action[0] = -1: decelerate action[0] =\",\n \"is_done(self): # lane change successfully executed, episode ends, reset env # todo modify\",\n \"= w_lateral * alpha + w_longi * (1 - alpha) * abs(self.ego.leaderDis) #\",\n \":param id: vehicle id corresponding to name :return: \\\"\\\"\\\" if veh is not\",\n \"ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor *\",\n \"self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane\",\n \"episode is reached, call `reset()` outside env!! to reset this environment's state. Accepts\",\n \"== 1 and 0 < TTC2 < 2: r_long_t = - math.exp(-2 *\",\n \"== 1: # lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert\",\n \"this environment's state. Accepts an action and returns a tuple (observation, reward, done,\",\n \"r_long_c = - math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action == 0: #abort\",\n \"lane leader action[0] = 1: follow target lane leader **important**: orginal/target lane leader\",\n \"2 # self.observation = [[0, 0, 0], # ego lane position and speed\",\n \"None: self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed', str(seed)] # gui if gui\",\n \"19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg'\",\n \"veh_id in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()):\",\n \"is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid,\",\n \"whether the episode has ended, in which case further step() calls will return\",\n \"arguments must be string, if float/int, must be converted to str(float/int), instead of\",\n \"# r_safe = r_safe_leader + r_safe_tgtleader # total reward r_total = r_comf +\",\n \"- self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha) # assert 0 <= alpha\",\n \"abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat,\",\n \"Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for\",\n \"import gym from gym import spaces import numpy as np from env.IDM import\",\n \"<= 1.1 # r_safe_leader = w_lateral * alpha + w_longi * (1 -\",\n \"progress; 0:change back to original line; 1:lane change to target lane; 2:keep current\",\n \"delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V\",\n \"# average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg\",\n \"on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2):\",\n \"<= 1.1 # # r_safe_tgtleader = w_lateral * alpha + w_longi * (1\",\n \"seed(self, seed=None): if seed is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed\",\n \"('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 #\",\n \"from gym import spaces import numpy as np from env.IDM import IDM from\",\n \"self.ego not in env:', self.egoID not in self.vehID_tuple_all) # collision occurs self.collision_num =\",\n \"self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1,\",\n \"* delta_A2 * delta_D2) TTC2 = TTC2 / delta_A2 if self.lateral_action == 1\",\n \"= 0 r_safe = w_lateral * (r_lat_c + r_lat_t) + w_longi * (r_long_c+\",\n \"appears in env if self.egoID is not None: while self.egoID not in self.veh_dict.keys():\",\n \"if self.lateral_action == 0: #abort lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) /\",\n \"not in env:', self.egoID not in self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber()\",\n \"<= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe = w_lateral *\",\n \"self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <= alpha <= 1.1 # r_safe_leader =\",\n \"= seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \\\"\\\"\\\" reset\",\n \"is_gui=True, sumoseed=None, randomseed=None): \\\"\\\"\\\" reset env :param id: ego vehicle id :param tfc:\",\n \"r_safe_tgtleader = w_lateral * alpha + w_longi * (1 - alpha) * abs(\",\n \"python environment if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else:\",\n \"sys import random import datetime import gym from gym import spaces import numpy\",\n \"# simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None): # todo\",\n \"to comfort r_comf = wc1 * self.ego.acce ** 2 + wc2 * self.ego.delta_acce\",\n \"lane action[1] = 2: keep in current lateral position Returns: described in __init__\",\n \"from env.Vehicle import Vehicle import math # add sumo/tools into python environment if\",\n \"reset this environment's state. Accepts an action and returns a tuple (observation, reward,\",\n \"line; 1:lane change to target lane; 2:keep current # lane change to target\",\n \"else: # r_safe_leader = 0 # if self.ego.targetLeaderID is not None: # #\",\n \"= action % 3 self.lateral_action = action_lateral # action_longi = action[0] # action_lateral\",\n \"+ 0] = veh.lanePos self.observation[name * 4 + 1] = veh.speed self.observation[name *\",\n \"r_long_t = 0 if self.lateral_action == 1: # lane change alpha = abs(self.ego.pos_lat\",\n \"# keep current lateral position if action_lateral == 2: self.is_success = self.ego.changeLane(True, -1,\",\n \"= self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right',\",\n \"2: # average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles\",\n \"in veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id\",\n \"4 + 0] = self.observation[0] + 300. self.observation[name * 4 + 1] =\",\n \"= abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_t\",\n \"4 + 2] = veh.pos_lat self.observation[name * 4 + 3] = veh.acce else:\",\n \"# self.ego.dis2tgtLane) # too close to ramp entrance if self.ego.dis2entrance < 10.0: self.done\",\n \"list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict)\",\n \"# alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha) #\",\n \"= Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id)\",\n \"print('alpha', alpha) # assert 0 <= alpha <= 1.1 # # r_safe_tgtleader =\",\n \"- math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action != 1\",\n \"0 # # # r_safe = r_safe_leader + r_safe_tgtleader # total reward r_total\",\n \"0:change back to original line; 1:lane change to target lane; 2:keep current #\",\n \"self.seed(randomseed) if sumoseed is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed)\",\n \"self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd,\",\n \"self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos\",\n \"r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe = w_lateral * (r_lat_c +\",\n \"is not None, 'action is None' assert self.egoID in self.vehID_tuple_all, 'vehicle not in\",\n \"self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done() if self.done is True: self.info['resetFlag'] =\",\n \"!= 1 and 0 < TTC < 2: r_long_c = - math.exp(-2*TTC+5) else:\",\n \"r_effi_all + r_safe return r_total def is_done(self): # lane change successfully executed, episode\",\n \"abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # #\",\n \"1: follow closer leader longitudinal2: action[0] = 0: follow original lane leader action[0]\",\n \"environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None): # todo check traffic\",\n \"target lane follower self.observation = np.empty(20) self.reward = None # (float) : amount\",\n \"env :param id: ego vehicle id :param tfc: int. 0:light; 1:medium; 2:dense :return:\",\n \"# else: # r_safe_leader = 0 # if self.ego.targetLeaderID is not None: #\",\n \"+ r_effi # reward related to safety w_lateral = 1 w_longi = 1\",\n \"dis2targetlane:', # self.ego.dis2tgtLane) # too close to ramp entrance if self.ego.dis2entrance < 10.0:\",\n \"{ 'resetFlag': 0} # (dict): contains auxiliary diagnostic information (helpful for debugging, and\",\n \"# (bool): whether the episode has ended, in which case further step() calls\",\n \"* self.ego.acce ** 2 + wc2 * self.ego.delta_acce ** 2 # reward related\",\n \"# ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2\",\n \"self.vehID_tuple_all: self.done = True # print('reset on: self.ego not in env:', self.egoID not\",\n \"= veh.speed self.observation[name * 4 + 2] = veh.pos_lat self.observation[name * 4 +\",\n \"<= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe =\",\n \"is not in env\\\" self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane\",\n \"True return self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward = self.updateReward() return self.observation,\",\n \"= self.updateReward() return self.observation, self.reward, self.done, self.info def seed(self, seed=None): if seed is\",\n \"<= alpha <= 1.1 # r_safe_leader = w_lateral * alpha + w_longi *\",\n \"if sumoseed is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) #\",\n \"True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start',\",\n \"traffic=1, gui=False, seed=None): # todo check traffic flow density if traffic == 0:\",\n \"\\\"\\\"\\\" :param name: 0:ego; 1:leader; 2:target leader; 3:target follower :param id: vehicle id\",\n \"abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_c =\",\n \"r_time = - wt * self.timestep r_speed = ws * (self.ego.speed - self.ego_speedLimit)\",\n \"converted to str(float/int), instead of '3.0' self.sumoBinary = \\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\" self.sumoCmd = ['-c', self.cfg,\",\n \"'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\\\"please declare environment\",\n \"high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if veh_id not in\",\n \"while ego is not in env\\\" self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex\",\n \"lane follower self.observation = np.empty(20) self.reward = None # (float) : amount of\",\n \"compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce -\",\n \"self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha)\",\n \"action=2): \\\"\\\"\\\"Run one timestep of the environment's dynamics. When end of episode is\",\n \"follow target lane leader **important**: orginal/target lane leader will not change despite the\",\n \"action[0] = 0: use SUMO default action[0] = others: acce = 0.0 longitudinal1:\",\n \"vehicle id :param tfc: int. 0:light; 1:medium; 2:dense :return: initial observation \\\"\\\"\\\" self.seed(randomseed)\",\n \"0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit)\",\n \"== 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex,\",\n \"alpha) # assert 0 <= alpha <= 1.1 # # r_safe_tgtleader = w_lateral\",\n \"r_long_t) # # if self.ego.leaderID is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat -\",\n \"import spaces import numpy as np from env.IDM import IDM from env.Road import\",\n \"None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)\",\n \"action_lateral = action[1] assert self.done is False, 'self.done is not False' assert action\",\n \"# lane change to target lane if not self.is_success: if action_lateral == 1:\",\n \"id: ego vehicle id :param tfc: int. 0:light; 1:medium; 2:dense :return: initial observation\",\n \"else: sys.exit(\\\"please declare environment variable 'SUMO_HOME'\\\") import traci ###################################################################### # simulation environments class\",\n \"* alpha + w_longi * (1 - alpha) * abs( # self.ego.lanePos -\",\n \"0.0 longitudinal1: action[0] = 0: follow original lane leader action[0] = 1: follow\",\n \"# using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed is None:\",\n \"= traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done() if self.done is True:\",\n \"self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all = () self.egoID = id self.ego\",\n \"TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if\",\n \"abort lane change, change back to ego's original lane if action_lateral == 0:\",\n \"self.ego.is_ego = 1 # set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor =\",\n \"veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \\\"\\\"\\\"\",\n \"3:target follower :param id: vehicle id corresponding to name :return: \\\"\\\"\\\" if veh\",\n \"'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if float/int, must be converted to str(float/int),\",\n \"traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \\\"\\\"\\\"Run one timestep of the environment's dynamics. When\",\n \"traffic flow density if traffic == 0: # average 9 vehicles self.cfg =\",\n \"* 4 + 1] = veh.speed self.observation[name * 4 + 2] = veh.pos_lat\",\n \"self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if veh_id not in\",\n \"action[0] = others: acce = 0.0 longitudinal1: action[0] = 0: follow original lane\",\n \"+ 0] = self.observation[0] + 300. self.observation[name * 4 + 1] = self.observation[1]\",\n \"not False' assert action is not None, 'action is None' assert self.egoID in\",\n \"= self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext)\",\n \"episode ends, reset env # todo modify if self.is_success: self.done = True #\",\n \"'--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed is None: self.sumoCmd += ['--random']\",\n \"- self.ego.pos_lat) # keep current lateral position if action_lateral == 2: self.is_success =\",\n \"leader action[0] = 1: follow closer leader longitudinal2: action[0] = 0: follow original\",\n \"delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2 + 2 * delta_A2\",\n \"* (1 - alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader = 0 #\",\n \"self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else:\",\n \"= action[0] # action_lateral = action[1] assert self.done is False, 'self.done is not\",\n \"from env.Road import Road from env.Vehicle import Vehicle import math # add sumo/tools\",\n \"action and returns a tuple (observation, reward, done, info). Args: action (object): longitudinal0:\",\n \"# r_safe_tgtleader = 0 # # # r_safe = r_safe_leader + r_safe_tgtleader #\",\n \"if delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V -\",\n \"alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader = 0 # if self.ego.targetLeaderID is\",\n \"self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2\",\n \"action[0] = 1: follow target lane leader **important**: orginal/target lane leader will not\",\n \"to efficiency r_time = - wt * self.timestep r_speed = ws * (self.ego.speed\",\n \"lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too close to ramp entrance if self.ego.dis2entrance\",\n \"self.info['resetFlag'] = True return self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward = self.updateReward()\",\n \"ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out of env if self.egoID\",\n \"self.collision_num = 0 self.lateral_action = 2 # self.observation = [[0, 0, 0], #\",\n \"delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 ==\",\n \"close to ramp entrance if self.ego.dis2entrance < 10.0: self.done = True # print('reset\",\n \"self.observation[1] self.observation[name * 4 + 2] = 4.8 self.observation[name * 4 + 3]\",\n \"w_lateral * (r_lat_c + r_lat_t) + w_longi * (r_long_c+ r_long_t) # # if\",\n \"string, if float/int, must be converted to str(float/int), instead of '3.0' self.sumoBinary =\",\n \"0: follow original lane leader action[0] = 1: follow target lane leader **important**:\",\n \"self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed =\",\n \"be string, if float/int, must be converted to str(float/int), instead of '3.0' self.sumoBinary\",\n \"in env:', self.egoID not in self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if\",\n \"1 and 0 < TTC2 < 2: r_long_t = - math.exp(-2 * TTC2\",\n \"self.observation[name * 4 + 1] = self.observation[1] self.observation[name * 4 + 2] =\",\n \"assert self.egoID in self.vehID_tuple_all, \\\"cannot start training while ego is not in env\\\"\",\n \"sys.path.append(tools) print('success') else: sys.exit(\\\"please declare environment variable 'SUMO_HOME'\\\") import traci ###################################################################### # simulation\",\n \"= self.observation[1] self.observation[name * 4 + 2] = 4.8 self.observation[name * 4 +\",\n \"name, veh): \\\"\\\"\\\" :param name: 0:ego; 1:leader; 2:target leader; 3:target follower :param id:\",\n \"= 1: lane change action[1] = 0: abort lane change, change back to\",\n \"not self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01:\",\n \"# using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1),\",\n \"# target lane leader # [0, 0, 0]] # target lane follower self.observation\",\n \"# if self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) #\",\n \"# lateral control------------------------- # episode in progress; 0:change back to original line; 1:lane\",\n \"import math # add sumo/tools into python environment if 'SUMO_HOME' in os.environ: tools\",\n \"None: self.observation[name * 4 + 0] = veh.lanePos self.observation[name * 4 + 1]\",\n \"tuple (observation, reward, done, info). Args: action (object): longitudinal0: action[0] = 1: accelerate\",\n \"* 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) #\",\n \"= wc1 * self.ego.acce ** 2 + wc2 * self.ego.delta_acce ** 2 #\",\n \"'resetFlag': 0} # (dict): contains auxiliary diagnostic information (helpful for debugging, and sometimes\",\n \"self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all =\",\n \"timesteps') assert self.egoID in self.vehID_tuple_all, \\\"cannot start training while ego is not in\",\n \"= -delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action\",\n \"self.info = { 'resetFlag': 0} # (dict): contains auxiliary diagnostic information (helpful for\",\n \"which case further step() calls will return undefined results self.info = { 'resetFlag':\",\n \"follow closer leader longitudinal2: action[0] = 0: follow original lane leader action[0] =\",\n \"= self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0: TTC2 = - abs(delta_D2) /\",\n \"* 4 + 2] = 4.8 self.observation[name * 4 + 3] = 0\",\n \"target lane; 2:keep current # lane change to target lane if not self.is_success:\",\n \"self.info def seed(self, seed=None): if seed is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed\",\n \"10.0: self.done = True # print('reset on: too close to ramp entrance, dis2targetlane:',\",\n \"update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done()\",\n \"self.done = True # print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all =\",\n \"TTC2 < 2: r_long_t = - math.exp(-2 * TTC2 + 5) else: r_long_t\",\n \"vehicle out of env if self.egoID not in self.vehID_tuple_all: self.done = True #\",\n \"+= 1 # lateral control------------------------- # episode in progress; 0:change back to original\",\n \"= [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary]\",\n \"__init__(self, id=None, traffic=1, gui=False, seed=None): # todo check traffic flow density if traffic\",\n \"'vehicle not in env' self.timestep += 1 # lateral control------------------------- # episode in\",\n \"0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A\",\n \"= \\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3), # using 'Simple Continuous\",\n \"id corresponding to name :return: \\\"\\\"\\\" if veh is not None: self.observation[name *\",\n \"- abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2 +\",\n \"original lane if action_lateral == 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01:\",\n \"3 self.lateral_action = action_lateral # action_longi = action[0] # action_lateral = action[1] assert\",\n \"= { 'resetFlag': 0} # (dict): contains auxiliary diagnostic information (helpful for debugging,\",\n \"for veh_id in veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd)\",\n \"+ r_lat_t) + w_longi * (r_long_c+ r_long_t) # # if self.ego.leaderID is not\",\n \"initial observation \\\"\\\"\\\" self.seed(randomseed) if sumoseed is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid,\",\n \"# action_longi = action[0] # action_lateral = action[1] assert self.done is False, 'self.done\",\n \": amount of reward returned after previous action self.done = True # (bool):\",\n \"r_long_c = 0 if self.lateral_action == 0: #abort lane change alpha = abs(self.ego.pos_lat\",\n \"= - abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2\",\n \"not None, 'action is None' assert self.egoID in self.vehID_tuple_all, 'vehicle not in env'\",\n \"step(self, action=2): \\\"\\\"\\\"Run one timestep of the environment's dynamics. When end of episode\",\n \"traffic == 2: # average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average\",\n \"self.egoID not in self.veh_dict.keys(): # must ensure safety in preStpe self.preStep() if self.timestep\",\n \":return: \\\"\\\"\\\" if veh is not None: self.observation[name * 4 + 0] =\",\n \"class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None): # todo check traffic flow\",\n \"observation \\\"\\\"\\\" self.seed(randomseed) if sumoseed is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc,\",\n \"# [0, 0, 0], # target lane leader # [0, 0, 0]] #\",\n \"print('reset on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too close to ramp\",\n \"change, change back to original lane action[1] = 2: keep in current lateral\",\n \"# # r_safe = r_safe_leader + r_safe_tgtleader # total reward r_total = r_comf\",\n \"# print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def\",\n \"not None: # compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A\",\n \"is None: self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed', str(seed)] # gui if\",\n \"corresponding to name :return: \\\"\\\"\\\" if veh is not None: self.observation[name * 4\",\n \"outside env!! to reset this environment's state. Accepts an action and returns a\",\n \"env if self.egoID is not None: while self.egoID not in self.veh_dict.keys(): # must\",\n \"Vehicle import math # add sumo/tools into python environment if 'SUMO_HOME' in os.environ:\",\n \"# lane change successfully executed, episode ends, reset env # todo modify if\",\n \"np from env.IDM import IDM from env.Road import Road from env.Vehicle import Vehicle\",\n \"seed=None): if seed is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed)\",\n \"< 2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action ==\",\n \"= False self.collision_num = 0 self.lateral_action = 2 # self.observation = [[0, 0,\",\n \"if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\\\"please declare\",\n \"successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too close to ramp entrance if\",\n \"self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def _updateObservationSingle(self, name, veh): \\\"\\\"\\\" :param name: 0:ego; 1:leader; 2:target leader;\",\n \"tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \\\"\\\"\\\" reset env :param id: ego vehicle id\",\n \"declare environment variable 'SUMO_HOME'\\\") import traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def\",\n \"alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0\",\n \"- self.ego.lanePos if delta_A2 == 0: TTC2 = - abs(delta_D2) / delta_V2 else:\",\n \"= 1 w_longi = 1 if self.ego.leaderID is not None: # compute longitudinal\",\n \"(r_lat_c + r_lat_t) + w_longi * (r_long_c+ r_long_t) # # if self.ego.leaderID is\",\n \"0: # average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: #\",\n \"print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2 = 1\",\n \"-delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC = TTC/delta_A if self.lateral_action !=\",\n \"not in self.veh_dict.keys(): # must ensure safety in preStpe self.preStep() if self.timestep >\",\n \"self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext =\",\n \"import Vehicle import math # add sumo/tools into python environment if 'SUMO_HOME' in\",\n \"= traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None self.veh_dict = {} self.vehID_tuple_all =\",\n \"lane if action_lateral == 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success\",\n \"def __init__(self, id=None, traffic=1, gui=False, seed=None): # todo check traffic flow density if\",\n \"gui=is_gui, seed=self.sumoseed) # continue step until ego appears in env if self.egoID is\",\n \"self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4,\",\n \"+ r_safe return r_total def is_done(self): # lane change successfully executed, episode ends,\",\n \"SUMO default action[0] = others: acce = 0.0 longitudinal1: action[0] = 0: follow\",\n \"= 0: abort lane change, change back to original lane action[1] = 2:\",\n \"self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1,\",\n \"self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \\\"\\\"\\\"Run one timestep of the environment's dynamics. When end\",\n \"\\\"\\\"\\\"Run one timestep of the environment's dynamics. When end of episode is reached,\",\n \"- self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A == 0: TTC =\",\n \"# # if self.ego.leaderID is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat))\",\n \"self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0: TTC2 = -\",\n \"= veh.acce else: self.observation[name * 4 + 0] = self.observation[0] + 300. self.observation[name\",\n \"random import datetime import gym from gym import spaces import numpy as np\",\n \"2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c = 0 if self.lateral_action == 0:\",\n \"0.0, self.done, self.info else: self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward, self.done, self.info\",\n \"is not None: # compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed\",\n \"env.Road import Road from env.Vehicle import Vehicle import math # add sumo/tools into\",\n \"= {} self.vehID_tuple_all = () self.egoID = id self.ego = None # self.tgtLane\",\n \"'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)]\",\n \"to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out of env if\",\n \"/ 3.2 assert 0 <= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t\",\n \"TTC2 = - abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2 **\",\n \"# continue step until ego appears in env if self.egoID is not None:\",\n \"if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in list(self.veh_dict.keys()): self.veh_dict[veh_id].update_info(self.rd, self.veh_dict) def\",\n \"0} # (dict): contains auxiliary diagnostic information (helpful for debugging, and sometimes learning)\",\n \"self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha) # assert 0 <= alpha <=\",\n \"must ensure safety in preStpe self.preStep() if self.timestep > 5000: raise Exception('cannot find\",\n \"on: too close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out\",\n \"* delta_D2) TTC2 = TTC2 / delta_A2 if self.lateral_action == 1 and 0\",\n \"self.lateral_action == 1: # lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2\",\n \"self.observation[name * 4 + 2] = veh.pos_lat self.observation[name * 4 + 3] =\",\n \"= abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_c\",\n \"previous action self.done = True # (bool): whether the episode has ended, in\",\n \"the episode has ended, in which case further step() calls will return undefined\",\n \"self.is_done() if self.done is True: self.info['resetFlag'] = True return self.observation, 0.0, self.done, self.info\",\n \"r_safe_tgtleader = 0 # # # r_safe = r_safe_leader + r_safe_tgtleader # total\",\n \"action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True,\",\n \"wt = 1 ws = 1 we = 1 # reward related to\",\n \"leader **important**: orginal/target lane leader will not change despite the lateral position of\",\n \"2 # reward related to efficiency r_time = - wt * self.timestep r_speed\",\n \"env # todo modify if self.is_success: self.done = True # print('reset on: successfully\",\n \"vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' #\",\n \"0: TTC2 = - abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2\",\n \"self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext = self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) #\",\n \"1 wt = 1 ws = 1 we = 1 # reward related\",\n \"1 # reward related to comfort r_comf = wc1 * self.ego.acce ** 2\",\n \"spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if veh_id not\",\n \"= 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if float/int, must be converted to\",\n \"self.observation[name * 4 + 1] = veh.speed self.observation[name * 4 + 2] =\",\n \"2:keep current # lane change to target lane if not self.is_success: if action_lateral\",\n \"if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()):\",\n \"self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader)\",\n \"longitudinal1: action[0] = 0: follow original lane leader action[0] = 1: follow closer\",\n \"find ego after 5000 timesteps') assert self.egoID in self.vehID_tuple_all, \\\"cannot start training while\",\n \"'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be\",\n \"# # # r_safe = r_safe_leader + r_safe_tgtleader # total reward r_total =\",\n \"position of the ego may change lateral: action[1] = 1: lane change action[1]\",\n \"['--random'] else: self.sumoCmd += ['--seed', str(seed)] # gui if gui is True: self.sumoBinary\",\n \"- self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5)\",\n \"0: use SUMO default action[0] = others: acce = 0.0 longitudinal1: action[0] =\",\n \"+ w_longi * (1 - alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader =\",\n \"self.egoID = id self.ego = None # self.tgtLane = tgtlane self.is_success = False\",\n \"# collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done = True\",\n \"not in env\\\" self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego\",\n \"= self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower)\",\n \"(observation, reward, done, info). Args: action (object): longitudinal0: action[0] = 1: accelerate action[0]\",\n \"self.reward = None # (float) : amount of reward returned after previous action\",\n \"speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj\",\n \"not None: while self.egoID not in self.veh_dict.keys(): # must ensure safety in preStpe\",\n \"print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change, change back to ego's original\",\n \"variable 'SUMO_HOME'\\\") import traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None,\",\n \"(helpful for debugging, and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf,\",\n \"self.done, self.info else: self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward, self.done, self.info def\",\n \"average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average 19\",\n \"2: r_long_t = - math.exp(-2 * TTC2 + 5) else: r_long_t = 0\",\n \"tfc=1, is_gui=True, sumoseed=None, randomseed=None): \\\"\\\"\\\" reset env :param id: ego vehicle id :param\",\n \"of '3.0' self.sumoBinary = \\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration', str(3), #\",\n \"self.lateral_action = action_lateral # action_longi = action[0] # action_lateral = action[1] assert self.done\",\n \"+= '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else:\",\n \"+ w_longi * (r_long_c+ r_long_t) # # if self.ego.leaderID is not None: #\",\n \"# total reward r_total = r_comf + r_effi_all + r_safe return r_total def\",\n \"r_effi # reward related to safety w_lateral = 1 w_longi = 1 if\",\n \"= self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext = self.ego.updateLongitudinalSpeedIDM(action_longi) # print(acceNext) vNext\",\n \"to original lane action[1] = 2: keep in current lateral position Returns: described\",\n \"self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <=\",\n \"traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation()\",\n \"0 < TTC < 2: r_long_c = - math.exp(-2*TTC+5) else: r_long_c = 0\",\n \"14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if float/int, must\",\n \"self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation() return self.observation return def close(self): traci.close()\",\n \"self.ego.leaderID is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha =\",\n \"- self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader = 0 # # # r_safe =\",\n \"* alpha + w_longi * (1 - alpha) * abs(self.ego.leaderDis) # else: #\",\n \"self.ego.dis2tgtLane) # too close to ramp entrance if self.ego.dis2entrance < 10.0: self.done =\",\n \"delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos\",\n \"else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0\",\n \"['-c', self.cfg, # '--lanechange.duration', str(3), # using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8),\",\n \"others: acce = 0.0 longitudinal1: action[0] = 0: follow original lane leader action[0]\",\n \"action_lateral == 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True,\",\n \"datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None,\",\n \"gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce if delta_A\",\n \"one timestep of the environment's dynamics. When end of episode is reached, call\",\n \"else: self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward, self.done, self.info def seed(self, seed=None):\",\n \"while self.egoID not in self.veh_dict.keys(): # must ensure safety in preStpe self.preStep() if\",\n \"ws = 1 we = 1 # reward related to comfort r_comf =\",\n \"in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\\\"please declare environment variable\",\n \"self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \\\"\\\"\\\"Run one\",\n \"4.8 self.observation[name * 4 + 3] = 0 # todo check if rational\",\n \"True # (bool): whether the episode has ended, in which case further step()\",\n \"3.2 assert 0 <= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c =\",\n \"reward returned after previous action self.done = True # (bool): whether the episode\",\n \"# '--lanechange.duration', str(3), # using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), # using\",\n \"\\\"\\\"\\\" if veh is not None: self.observation[name * 4 + 0] = veh.lanePos\",\n \"self.observation, self.reward, self.done, self.info def seed(self, seed=None): if seed is None: self.randomseed =\",\n \"2: keep in current lateral position Returns: described in __init__ \\\"\\\"\\\" action_longi =\",\n \"action % 3 self.lateral_action = action_lateral # action_longi = action[0] # action_lateral =\",\n \"* self.ego.delta_acce ** 2 # reward related to efficiency r_time = - wt\",\n \"if float/int, must be converted to str(float/int), instead of '3.0' self.sumoBinary = \\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\"\",\n \"(bool): whether the episode has ended, in which case further step() calls will\",\n \"[0, 0, 0], # leader # [0, 0, 0], # target lane leader\",\n \"math.sqrt(delta_V2 ** 2 + 2 * delta_A2 * delta_D2) TTC2 = TTC2 /\",\n \"TTC2 = TTC2 / delta_A2 if self.lateral_action == 1 and 0 < TTC2\",\n \"* (self.ego.speed - self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all =\",\n \"self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) #\",\n \"delta_A2 * delta_D2) TTC2 = TTC2 / delta_A2 if self.lateral_action == 1 and\",\n \"veh_id_tuple): for veh_id in veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id,\",\n \"# # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) /\",\n \"abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha) # assert 0 <=\",\n \"print('reset on: too close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle\",\n \"\\\"\\\"\\\" action_longi = action // 3 action_lateral = action % 3 self.lateral_action =\",\n \"r_safe = r_safe_leader + r_safe_tgtleader # total reward r_total = r_comf + r_effi_all\",\n \"self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change, change\",\n \"self.ego.delta_acce ** 2 # reward related to efficiency r_time = - wt *\",\n \"None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid, tlane=0,\",\n \"alpha + w_longi * (1 - alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader\",\n \"0 # if self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat))\",\n \"# average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments must be string, if\",\n \"* 4 + 0] = self.observation[0] + 300. self.observation[name * 4 + 1]\",\n \"w_longi * (1 - alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader = 0\",\n \"ramp entrance if self.ego.dis2entrance < 10.0: self.done = True # print('reset on: too\",\n \"if self.ego.targetLeaderID is not None: # compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed\",\n \"== 0: # average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2:\",\n \"r_long_t = - math.exp(-2 * TTC2 + 5) else: r_long_t = 0 if\",\n \"tfc: int. 0:light; 1:medium; 2:dense :return: initial observation \\\"\\\"\\\" self.seed(randomseed) if sumoseed is\",\n \"change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha <=\",\n \"# alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <= alpha\",\n \"= 0 if self.lateral_action == 0: #abort lane change alpha = abs(self.ego.pos_lat -\",\n \"lane change action[1] = 0: abort lane change, change back to original lane\",\n \"None' assert self.egoID in self.vehID_tuple_all, 'vehicle not in env' self.timestep += 1 #\",\n \"(1 - alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader = 0 # if\",\n \"check traffic flow density if traffic == 0: # average 9 vehicles self.cfg\",\n \"self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: # average 14 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/map.sumo.cfg' # arguments\",\n \"# todo modify if self.is_success: self.done = True # print('reset on: successfully lane\",\n \"- self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time +\",\n \"in self.vehID_tuple_all: self.done = True # print('reset on: self.ego not in env:', self.egoID\",\n \"0 r_safe = w_lateral * (r_lat_c + r_lat_t) + w_longi * (r_long_c+ r_long_t)\",\n \"self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3, self.ego.trgt_leader) self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation\",\n \"import sys import random import datetime import gym from gym import spaces import\",\n \"ends self.is_done() if self.done is True: self.info['resetFlag'] = True return self.observation, 0.0, self.done,\",\n \"TTC2 / delta_A2 if self.lateral_action == 1 and 0 < TTC2 < 2:\",\n \"w_lateral * alpha + w_longi * (1 - alpha) * abs(self.ego.leaderDis) # else:\",\n \"change lateral: action[1] = 1: lane change action[1] = 0: abort lane change,\",\n \"else: # r_safe_tgtleader = 0 # # # r_safe = r_safe_leader + r_safe_tgtleader\",\n \"None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)\",\n \"= self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 = self.veh_dict[self.ego.targetLeaderID].lanePos - self.ego.lanePos if delta_A2 == 0:\",\n \"delta_A == 0: TTC = - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2\",\n \"3] = 0 # todo check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos\",\n \"self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower)\",\n \"None: # compute longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A =\",\n \"set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor\",\n \"# (float) : amount of reward returned after previous action self.done = True\",\n \"not in self.vehID_tuple_all) # collision occurs self.collision_num = traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0:\",\n \"= 0: follow original lane leader action[0] = 1: follow target lane leader\",\n \"== 0: #abort lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert\",\n \"change action[1] = 0: abort lane change, change back to original lane action[1]\",\n \"vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average 19 vehicles self.cfg\",\n \"r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time + r_speed +\",\n \"to reset this environment's state. Accepts an action and returns a tuple (observation,\",\n \"to target lane; 2:keep current # lane change to target lane if not\",\n \"0 self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed = None self.veh_dict = {}\",\n \"action[0] # action_lateral = action[1] assert self.done is False, 'self.done is not False'\",\n \"ws * (self.ego.speed - self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all\",\n \"auxiliary diagnostic information (helpful for debugging, and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space\",\n \"= 1: follow target lane leader **important**: orginal/target lane leader will not change\",\n \"print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self,\",\n \"# if self.ego.leaderID is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat)) #\",\n \"0: follow original lane leader action[0] = 1: follow closer leader longitudinal2: action[0]\",\n \"related to efficiency r_time = - wt * self.timestep r_speed = ws *\",\n \"vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid) self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID))\",\n \"successfully executed, episode ends, reset env # todo modify if self.is_success: self.done =\",\n \"in which case further step() calls will return undefined results self.info = {\",\n \"related to comfort r_comf = wc1 * self.ego.acce ** 2 + wc2 *\",\n \"is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step\",\n \"= 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg'\",\n \"gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed delta_A2 = self.veh_dict[self.ego.targetLeaderID].acce - self.ego.acce delta_D2 =\",\n \":param tfc: int. 0:light; 1:medium; 2:dense :return: initial observation \\\"\\\"\\\" self.seed(randomseed) if sumoseed\",\n \"-1: decelerate action[0] = 0: use SUMO default action[0] = others: acce =\",\n \"4 + 1] = veh.speed self.observation[name * 4 + 2] = veh.pos_lat self.observation[name\",\n \"0] = self.observation[0] + 300. self.observation[name * 4 + 1] = self.observation[1] self.observation[name\",\n \"returned after previous action self.done = True # (bool): whether the episode has\",\n \"Returns: described in __init__ \\\"\\\"\\\" action_longi = action // 3 action_lateral = action\",\n \"import datetime import gym from gym import spaces import numpy as np from\",\n \"lane leader **important**: orginal/target lane leader will not change despite the lateral position\",\n \"w_longi * (r_long_c+ r_long_t) # # if self.ego.leaderID is not None: # #\",\n \"control------------------------- # episode in progress; 0:change back to original line; 1:lane change to\",\n \"math.exp(-2 * TTC2 + 5) else: r_long_t = 0 if self.lateral_action == 1:\",\n \"+ acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID)\",\n \"alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 # assert 0 <= alpha <=\",\n \"vNext = self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep()\",\n \"'--start', str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep\",\n \"1 w_longi = 1 if self.ego.leaderID is not None: # compute longitudinal time\",\n \"lateral control------------------------- # episode in progress; 0:change back to original line; 1:lane change\",\n \"self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \\\"\\\"\\\"\",\n \"-delta_V2 - math.sqrt(delta_V2 ** 2 + 2 * delta_A2 * delta_D2) TTC2 =\",\n \"import numpy as np from env.IDM import IDM from env.Road import Road from\",\n \"self.is_success = False self.collision_num = 0 self.lateral_action = 2 # self.observation = [[0,\",\n \"alpha <= 1.1 # r_safe_leader = w_lateral * alpha + w_longi * (1\",\n \"described in __init__ \\\"\\\"\\\" action_longi = action // 3 action_lateral = action %\",\n \"* traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation() return self.observation return def\",\n \"import Road from env.Vehicle import Vehicle import math # add sumo/tools into python\",\n \"[[0, 0, 0], # ego lane position and speed # [0, 0, 0],\",\n \"speed # [0, 0, 0], # leader # [0, 0, 0], # target\",\n \"safety w_lateral = 1 w_longi = 1 if self.ego.leaderID is not None: #\",\n \"= 4.8 self.observation[name * 4 + 3] = 0 # todo check if\",\n \"= 1 # set ego vehicle speed mode traci.vehicle.setSpeedMode(self.ego.veh_id, 0) self.ego_speedFactor = traci.vehicle.getSpeedFactor(egoid)\",\n \"seed is None: self.randomseed = datetime.datetime.now().microsecond else: self.randomseed = seed random.seed(self.randomseed) def reset(self,\",\n \"gui=False, seed=None): # todo check traffic flow density if traffic == 0: #\",\n \"self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done() if self.done is\",\n \"self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until ego appears in\",\n \"longitudinal time gap delta_V = self.veh_dict[self.ego.leaderID].speed - self.ego.speed delta_A = self.veh_dict[self.ego.leaderID].acce - self.ego.acce\",\n \"# print('reset on: self.ego not in env:', self.egoID not in self.vehID_tuple_all) # collision\",\n \"and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self,\",\n \"self.preStep() if self.timestep > 5000: raise Exception('cannot find ego after 5000 timesteps') assert\",\n \"veh.speed self.observation[name * 4 + 2] = veh.pos_lat self.observation[name * 4 + 3]\",\n \"lateral position Returns: described in __init__ \\\"\\\"\\\" action_longi = action // 3 action_lateral\",\n \"to safety w_lateral = 1 w_longi = 1 if self.ego.leaderID is not None:\",\n \"self.cfg, # '--lanechange.duration', str(3), # using 'Simple Continuous lane-change model' '--lateral-resolution', str(0.8), #\",\n \"ego vehicle id :param tfc: int. 0:light; 1:medium; 2:dense :return: initial observation \\\"\\\"\\\"\",\n \"- math.sqrt(delta_V2 ** 2 + 2 * delta_A2 * delta_D2) TTC2 = TTC2\",\n \"(self.ego.speed - self.ego_speedLimit) r_effi = we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time\",\n \"r_total def is_done(self): # lane change successfully executed, episode ends, reset env #\",\n \"# print('reset on: too close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego\",\n \"self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd)\",\n \"action // 3 action_lateral = action % 3 self.lateral_action = action_lateral # action_longi\",\n \"False, 'self.done is not False' assert action is not None, 'action is None'\",\n \"4 + 3] = 0 # todo check if rational def updateObservation(self): self.observation[0]\",\n \"self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat -\",\n \"orginal/target lane leader will not change despite the lateral position of the ego\",\n \"Args: action (object): longitudinal0: action[0] = 1: accelerate action[0] = -1: decelerate action[0]\",\n \"self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until ego appears in env if\",\n \"w_longi = 1 if self.ego.leaderID is not None: # compute longitudinal time gap\",\n \"- alpha) * abs(self.ego.leaderDis) # else: # r_safe_leader = 0 # if self.ego.targetLeaderID\",\n \"'SUMO_HOME'\\\") import traci ###################################################################### # simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1,\",\n \"4 + 3] = veh.acce else: self.observation[name * 4 + 0] = self.observation[0]\",\n \"1] = self.observation[1] self.observation[name * 4 + 2] = 4.8 self.observation[name * 4\",\n \"else: r_long_t = 0 if self.lateral_action == 1: # lane change alpha =\",\n \"**important**: orginal/target lane leader will not change despite the lateral position of the\",\n \"1:lane change to target lane; 2:keep current # lane change to target lane\",\n \"** 2 # reward related to efficiency r_time = - wt * self.timestep\",\n \"True # print('reset on: self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all)\",\n \"if seed is None: self.sumoCmd += ['--random'] else: self.sumoCmd += ['--seed', str(seed)] #\",\n \"delta_A2 == 0: TTC2 = - abs(delta_D2) / delta_V2 else: TTC2 = -delta_V2\",\n \"id :param tfc: int. 0:light; 1:medium; 2:dense :return: initial observation \\\"\\\"\\\" self.seed(randomseed) if\",\n \"has ended, in which case further step() calls will return undefined results self.info\",\n \"r_safe_leader = 0 # if self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat\",\n \"from env.IDM import IDM from env.Road import Road from env.Vehicle import Vehicle import\",\n \"# print('reset on: successfully lane change, dis2targetlane:', # self.ego.dis2tgtLane) # too close to\",\n \"+ r_effi_all + r_safe return r_total def is_done(self): # lane change successfully executed,\",\n \"self.rd) # print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep current lateral position\",\n \"\\\"\\\"\\\" reset env :param id: ego vehicle id :param tfc: int. 0:light; 1:medium;\",\n \"= self.ego.speed + acceNext * 0.1 traci.vehicle.setSpeed(self.egoID, vNext) # update info------------------------------ traci.simulationStep() self.vehID_tuple_all\",\n \"action_lateral = action % 3 self.lateral_action = action_lateral # action_longi = action[0] #\",\n \"environment if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success') else: sys.exit(\\\"please\",\n \"in preStpe self.preStep() if self.timestep > 5000: raise Exception('cannot find ego after 5000\",\n \"* 4 + 3] = 0 # todo check if rational def updateObservation(self):\",\n \"alpha <= 1.1 # # r_safe_tgtleader = w_lateral * alpha + w_longi *\",\n \"(r_long_c+ r_long_t) # # if self.ego.leaderID is not None: # # ('lateralPos2leader', abs(self.ego.pos_lat\",\n \"seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \\\"\\\"\\\" reset env\",\n \"gui is True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end',\",\n \"assert 0 <= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0\",\n \"of the environment's dynamics. When end of episode is reached, call `reset()` outside\",\n \"0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd)\",\n \"= 1 wt = 1 ws = 1 we = 1 # reward\",\n \"TTC = - abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A *\",\n \"assert 0 <= alpha <= 1.1 # # r_safe_tgtleader = w_lateral * alpha\",\n \"veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id] = Vehicle(veh_id, self.rd) for veh_id in list(self.veh_dict.keys()): if\",\n \":param name: 0:ego; 1:leader; 2:target leader; 3:target follower :param id: vehicle id corresponding\",\n \"start training while ego is not in env\\\" self.done = False self.ego =\",\n \"- alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: # r_safe_tgtleader =\",\n \"'--default.action-step-length', str(0.1)] # randomness if seed is None: self.sumoCmd += ['--random'] else: self.sumoCmd\",\n \"'action is None' assert self.egoID in self.vehID_tuple_all, 'vehicle not in env' self.timestep +=\",\n \"self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth))\",\n \"0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat)\",\n \"= self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3] = self.ego.acce self._updateObservationSingle(1, self.ego.orig_leader) self._updateObservationSingle(2, self.ego.orig_follower) self._updateObservationSingle(3,\",\n \"+= ['--random'] else: self.sumoCmd += ['--seed', str(seed)] # gui if gui is True:\",\n \"change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <= alpha <=\",\n \"'-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd\",\n \"not in self.vehID_tuple_all: self.done = True # print('reset on: self.ego not in env:',\",\n \"# average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average\",\n \"= 0: follow original lane leader action[0] = 1: follow closer leader longitudinal2:\",\n \"action[1] = 0: abort lane change, change back to original lane action[1] =\",\n \"= veh.lanePos self.observation[name * 4 + 1] = veh.speed self.observation[name * 4 +\",\n \"= self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue step until ego appears\",\n \"import os import sys import random import datetime import gym from gym import\",\n \"simulation environments class LaneChangeEnv(gym.Env): def __init__(self, id=None, traffic=1, gui=False, seed=None): # todo check\",\n \"density if traffic == 0: # average 9 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif\",\n \"change despite the lateral position of the ego may change lateral: action[1] =\",\n \"self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change, change back to\",\n \"self.rd.laneWidth - self.ego.pos_lat) # keep current lateral position if action_lateral == 2: self.is_success\",\n \"randomseed=None): \\\"\\\"\\\" reset env :param id: ego vehicle id :param tfc: int. 0:light;\",\n \"+ self.sumoCmd + ['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd\",\n \"= tgtlane self.is_success = False self.collision_num = 0 self.lateral_action = 2 # self.observation\",\n \"3.2 assert 0 <= alpha <= 1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t =\",\n \"== 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.orig_laneIndex,\",\n \"0], # ego lane position and speed # [0, 0, 0], # leader\",\n \"# # r_safe_tgtleader = w_lateral * alpha + w_longi * (1 - alpha)\",\n \"1: lane change action[1] = 0: abort lane change, change back to original\",\n \"= True return self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward = self.updateReward() return\",\n \"for debugging, and sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,))\",\n \"= self.ego.changeLane(True, self.ego.orig_laneIndex, self.rd) # print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep\",\n \"= we * self.ego.dis2tgtLane / self.ego.dis2entrance r_effi_all = r_time + r_speed + r_effi\",\n \"self.collision_num:', self.collision_num) def preStep(self): traci.simulationStep() self.vehID_tuple_all = traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) def step(self, action=2): \\\"\\\"\\\"Run\",\n \"* (r_lat_c + r_lat_t) + w_longi * (r_long_c+ r_long_t) # # if self.ego.leaderID\",\n \"1] = veh.speed self.observation[name * 4 + 2] = veh.pos_lat self.observation[name * 4\",\n \"str(0.1), '--default.action-step-length', str(0.1)] # randomness if seed is None: self.sumoCmd += ['--random'] else:\",\n \"str(float/int), instead of '3.0' self.sumoBinary = \\\"/usr/local/Cellar/sumo/1.2.0/bin/sumo\\\" self.sumoCmd = ['-c', self.cfg, # '--lanechange.duration',\",\n \"return self.observation, self.reward, self.done, self.info def seed(self, seed=None): if seed is None: self.randomseed\",\n \"and 0 < TTC2 < 2: r_long_t = - math.exp(-2 * TTC2 +\",\n \"1.1 r_lat_t = -math.exp(-4*alpha+5) else: r_lat_t = 0 r_safe = w_lateral * (r_lat_c\",\n \"# print('left', 1.5 * self.rd.laneWidth - self.ego.pos_lat) # keep current lateral position if\",\n \"lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.leaderID].pos_lat) / 3.2 assert 0 <= alpha\",\n \"traci.edge.getLastStepVehicleIDs(self.rd.entranceEdgeID) self.update_veh_dict(self.vehID_tuple_all) # check if episode ends self.is_done() if self.done is True: self.info['resetFlag']\",\n \"self.vehID_tuple_all, \\\"cannot start training while ego is not in env\\\" self.done = False\",\n \"reward related to safety w_lateral = 1 w_longi = 1 if self.ego.leaderID is\",\n \"self._updateObservationSingle(4, self.ego.trgt_follower) # self.observation = np.array(self.observation).flatten() # print(self.observation.shape) def updateReward(self): return -self.ego.dis2tgtLane def\",\n \"sometimes learning) self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple):\",\n \"- abs(self.ego.leaderDis)/delta_V else: TTC = -delta_V - math.sqrt(delta_V**2 + 2*delta_A * self.ego.leaderDis) TTC\",\n \"r_total = r_comf + r_effi_all + r_safe return r_total def is_done(self): # lane\",\n \"'lane', self.ego.curr_laneIndex, 'rdWdith', self.rd.laneWidth) # print('right', -(self.ego.pos_lat - 0.5*self.rd.laneWidth)) # abort lane change,\",\n \"self.observation[name * 4 + 2] = 4.8 self.observation[name * 4 + 3] =\",\n \"self.action_space = spaces.Discrete(6) self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(20,)) def update_veh_dict(self, veh_id_tuple): for veh_id\",\n \"['--quit-on-end', str(True), '--start', str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd =\",\n \"# (dict): contains auxiliary diagnostic information (helpful for debugging, and sometimes learning) self.action_space\",\n \"(dict): contains auxiliary diagnostic information (helpful for debugging, and sometimes learning) self.action_space =\",\n \"abs(self.ego.leaderDis) # else: # r_safe_leader = 0 # if self.ego.targetLeaderID is not None:\",\n \"if veh is not None: self.observation[name * 4 + 0] = veh.lanePos self.observation[name\",\n \"continue step until ego appears in env if self.egoID is not None: while\",\n \"# print('lateralPos2tgtleader', abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat)) # alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2\",\n \"# assert 0 <= alpha <= 1.1 # # r_safe_tgtleader = w_lateral *\",\n \"lane change, change back to original lane action[1] = 2: keep in current\",\n \"self.ego_speedLimit = self.ego_speedFactor * traci.lane.getMaxSpeed(traci.vehicle.getLaneID(self.egoID)) self.ego.idm_obj = IDM() self.ego.idm_obj.__init__(self.ego_speedLimit) self.ego.update_info(self.rd, self.veh_dict) self.updateObservation() return\",\n \"def updateReward(self): return -self.ego.dis2tgtLane def updateReward2(self): wc1 = 1 wc2 = 1 wt\",\n \"300. self.observation[name * 4 + 1] = self.observation[1] self.observation[name * 4 + 2]\",\n \"* (1 - alpha) * abs( # self.ego.lanePos - self.veh_dict[self.ego.targetLeaderID].lanePos) # else: #\",\n \"= traci.simulation.getCollidingVehiclesNumber() if self.collision_num > 0: self.done = True # print('reset on: self.collision_num:',\",\n \"= Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed = None self.sumoseed =\",\n \"current lateral position Returns: described in __init__ \\\"\\\"\\\" action_longi = action // 3\",\n \"rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] = self.ego.pos_lat self.observation[3]\",\n \"env.Vehicle import Vehicle import math # add sumo/tools into python environment if 'SUMO_HOME'\",\n \"wt * self.timestep r_speed = ws * (self.ego.speed - self.ego_speedLimit) r_effi = we\",\n \"is not None: # compute longitudinal time gap delta_V2 = self.veh_dict[self.ego.targetLeaderID].speed - self.ego.speed\",\n \"original lane action[1] = 2: keep in current lateral position Returns: described in\",\n \"= ['-c', self.cfg, # '--lanechange.duration', str(3), # using 'Simple Continuous lane-change model' '--lateral-resolution',\",\n \"self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapFree.sumo.cfg' elif traffic == 2: # average 19 vehicles self.cfg =\",\n \"self.done is True: self.info['resetFlag'] = True return self.observation, 0.0, self.done, self.info else: self.updateObservation()\",\n \"* (r_long_c+ r_long_t) # # if self.ego.leaderID is not None: # # ('lateralPos2leader',\",\n \"- (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane',\",\n \"/ delta_V2 else: TTC2 = -delta_V2 - math.sqrt(delta_V2 ** 2 + 2 *\",\n \"+ wc2 * self.ego.delta_acce ** 2 # reward related to efficiency r_time =\",\n \"elif traffic == 2: # average 19 vehicles self.cfg = 'C:/Users/<NAME>/Desktop/map/ramp3/mapDense.sumo.cfg' else: #\",\n \"alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 # # print('alpha', alpha) # assert\",\n \"True # print('reset on: self.ego not in env:', self.egoID not in self.vehID_tuple_all) #\",\n \"'self.done is not False' assert action is not None, 'action is None' assert\",\n \"= 0 if self.lateral_action == 1: # lane change alpha = abs(self.ego.pos_lat -\",\n \"1.1 # r_safe_leader = w_lateral * alpha + w_longi * (1 - alpha)\",\n \"def step(self, action=2): \\\"\\\"\\\"Run one timestep of the environment's dynamics. When end of\",\n \"# and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) > 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) #\",\n \"else: self.randomseed = seed random.seed(self.randomseed) def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None):\",\n \"int. 0:light; 1:medium; 2:dense :return: initial observation \\\"\\\"\\\" self.seed(randomseed) if sumoseed is None:\",\n \"ended, in which case further step() calls will return undefined results self.info =\",\n \"model' '--lateral-resolution', str(0.8), # using 'Sublane-Model' '--step-length', str(0.1), '--default.action-step-length', str(0.1)] # randomness if\",\n \"return self.observation, 0.0, self.done, self.info else: self.updateObservation() self.reward = self.updateReward() return self.observation, self.reward,\",\n \"position if action_lateral == 2: self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal control2---------------------\",\n \"if action_lateral == 2: self.is_success = self.ego.changeLane(True, -1, self.rd) # longitudinal control2--------------------- acceNext\",\n \"def reset(self, egoid, tlane=0, tfc=1, is_gui=True, sumoseed=None, randomseed=None): \\\"\\\"\\\" reset env :param id:\",\n \"Exception('cannot find ego after 5000 timesteps') assert self.egoID in self.vehID_tuple_all, \\\"cannot start training\",\n \"math # add sumo/tools into python environment if 'SUMO_HOME' in os.environ: tools =\",\n \"# lane change alpha = abs(self.ego.pos_lat - self.veh_dict[self.ego.targetLeaderID].pos_lat) / 3.2 assert 0 <=\",\n \"is True: self.sumoBinary += '-gui' self.sumoCmd = [self.sumoBinary] + self.sumoCmd + ['--quit-on-end', str(True),\",\n \"raise Exception('cannot find ego after 5000 timesteps') assert self.egoID in self.vehID_tuple_all, \\\"cannot start\",\n \"= w_lateral * (r_lat_c + r_lat_t) + w_longi * (r_long_c+ r_long_t) # #\",\n \"> 0.01: self.is_success = self.ego.changeLane(True, self.ego.trgt_laneIndex, self.rd) # print('posLat', self.ego.pos_lat, 'lane', self.ego.curr_laneIndex, 'rdWdith',\",\n \"traci.start(self.sumoCmd) self.rd = Road() self.timestep = 0 self.dt = traci.simulation.getDeltaT() self.randomseed = None\",\n \"into python environment if 'SUMO_HOME' in os.environ: tools = os.path.join(os.environ['SUMO_HOME'], 'tools') sys.path.append(tools) print('success')\",\n \"import random import datetime import gym from gym import spaces import numpy as\",\n \"seed=None): # todo check traffic flow density if traffic == 0: # average\",\n \"# reward related to comfort r_comf = wc1 * self.ego.acce ** 2 +\",\n \"= np.empty(20) self.reward = None # (float) : amount of reward returned after\",\n \"veh): \\\"\\\"\\\" :param name: 0:ego; 1:leader; 2:target leader; 3:target follower :param id: vehicle\",\n \"/ 3.2 # assert 0 <= alpha <= 1.1 # r_safe_leader = w_lateral\",\n \"dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out of env if self.egoID not in\",\n \"not None: self.observation[name * 4 + 0] = veh.lanePos self.observation[name * 4 +\",\n \"for veh_id in list(self.veh_dict.keys()): if veh_id not in veh_id_tuple: self.veh_dict.pop(veh_id) for veh_id in\",\n \"use SUMO default action[0] = others: acce = 0.0 longitudinal1: action[0] = 0:\",\n \"in env\\\" self.done = False self.ego = self.veh_dict[self.egoID] self.ego.trgt_laneIndex = tlane self.ego.is_ego =\",\n \"str(True)] else: self.sumoCmd = [self.sumoBinary] + self.sumoCmd traci.start(self.sumoCmd) self.rd = Road() self.timestep =\",\n \"self.ego = None # self.tgtLane = tgtlane self.is_success = False self.collision_num = 0\",\n \"to ego's original lane if action_lateral == 0: # and abs(self.ego.pos_lat - (0.5+self.ego.origLane)*self.rd.laneWidth)\",\n \"= r_comf + r_effi_all + r_safe return r_total def is_done(self): # lane change\",\n \"close to ramp entrance, dis2targetlane:', # self.ego.dis2tgtLane) # ego vehicle out of env\",\n \"0 <= alpha <= 1.1 r_lat_c = -math.exp(-4*alpha+5) else: r_lat_c = 0 if\",\n \"1 we = 1 # reward related to comfort r_comf = wc1 *\",\n \"= 0 # if self.ego.targetLeaderID is not None: # # print('lateralPos2tgtleader', abs(self.ego.pos_lat -\",\n \"sumoseed is None: self.sumoseed = self.randomseed traci.close() self.__init__(id=egoid, traffic=tfc, gui=is_gui, seed=self.sumoseed) # continue\",\n \"check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2] =\",\n \"action[0] = 0: follow original lane leader action[0] = 1: follow target lane\",\n \"* 4 + 1] = self.observation[1] self.observation[name * 4 + 2] = 4.8\",\n \"def update_veh_dict(self, veh_id_tuple): for veh_id in veh_id_tuple: if veh_id not in self.veh_dict.keys(): self.veh_dict[veh_id]\"\n]","isConversational":false}}},{"rowIdx":1490,"cells":{"ngram":{"kind":"list like","value":["True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if","== 200: for cidr in cidrs: try: if len(cidr['ips']) != 0: for ip","r.json() logger.info(versions) for version in versions: if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER'])","netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange","'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365","nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last =","prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link","for cidr in cidrs: try: if len(cidr['ips']) != 0: for ip in cidr['ips']:","= requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code == 200: versions = r.json()","elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken !=","downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken =","link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response =","netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk':","requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE'])","Updated') response = client.put_parameter( Name = parameter, Value = str(latest), Type = 'String',","downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range Updates') return { 'statusCode':","int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created':","= int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip,","ip, 'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip } ) except: pass","link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response =","str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link)","== 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first))","response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 China","elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken !=","IP Ranges Updated') response = client.put_parameter( Name = parameter, Value = str(latest), Type","= 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER'])","o365 IP Range Updates') return { 'statusCode': 200, 'body': json.dumps('Download o365 IP Ranges')","Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range","if r.status_code == 200: for cidr in cidrs: try: if len(cidr['ips']) != 0:","'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365","0: for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype =","latest, parameter, link): r = requests.get(link) cidrs = r.json() if r.status_code == 200:","'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken","ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype","= int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last = netrange[0],","!= str(version['latest']): logger.info('Updating o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'],","link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response =","requests.get(link) cidrs = r.json() if r.status_code == 200: for cidr in cidrs: try:","cidrs: try: if len(cidr['ips']) != 0: for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip","= True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code))","version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']):","'firstip': firstip, 'lastip': lastip } ) except: pass logger.info('o365 '+instance+' IP Ranges Updated')","Value = str(latest), Type = 'String', Overwrite = True ) def handler(event, context):","for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0])","= boto3.client('ssm') def downloader(instance, latest, parameter, link): r = requests.get(link) cidrs = r.json()","== 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first))","= str(latest), Type = 'String', Overwrite = True ) def handler(event, context): r",") def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code","link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response =","else: logger.info('No o365 IP Range Updates') return { 'statusCode': 200, 'body': json.dumps('Download o365","= client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP","os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range Updates') return { 'statusCode': 200, 'body':","ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last","nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip =","= 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype","logger.info('Updating o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else:","= r.json() logger.info(versions) for version in versions: if version['instance'] == 'Worldwide': response =","= 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range Updates') return","prevtoken != str(version['latest']): logger.info('Updating o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'],","!= str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'],","versions: if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken","first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype","if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'],","lastip } ) except: pass logger.info('o365 '+instance+' IP Ranges Updated') response = client.put_parameter(","import requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table =","sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip","'+str(r.status_code)) if r.status_code == 200: versions = r.json() logger.info(versions) for version in versions:","prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link","response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD","len(cidr['ips']) != 0: for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/')","ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange =","ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif","response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Germany","response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4())","prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link","} ) except: pass logger.info('o365 '+instance+' IP Ranges Updated') response = client.put_parameter( Name","== 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating","firstip, 'lastip': lastip } ) except: pass logger.info('o365 '+instance+' IP Ranges Updated') response","downloader(instance, latest, parameter, link): r = requests.get(link) cidrs = r.json() if r.status_code ==","netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange =","logger.info('Updating o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif","parameter, Value = str(latest), Type = 'String', Overwrite = True ) def handler(event,","client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP Ranges')",") except: pass logger.info('o365 '+instance+' IP Ranges Updated') response = client.put_parameter( Name =","r.status_code == 200: versions = r.json() logger.info(versions) for version in versions: if version['instance']","version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value']","= dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest, parameter, link): r = requests.get(link)","hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#':","'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype ==","= ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange","import json import logging import os import requests import uuid logger = logging.getLogger()","Overwrite = True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code:","import boto3 import ipaddress import json import logging import os import requests import","netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype,","'endpoint': instance, 'firstip': firstip, 'lastip': lastip } ) except: pass logger.info('o365 '+instance+' IP","iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip)","if prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'],","boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest, parameter, link): r","import logging import os import requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb","USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] ==","in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype =","int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1]","= parameter, Value = str(latest), Type = 'String', Overwrite = True ) def","r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code == 200: versions =","== 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating","Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response","first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item=","version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range Updates') return { 'statusCode': 200,","version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']):","= boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest, parameter, link):","'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1]","!= str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'],","def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code ==","'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365","'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken","str(version['latest']): logger.info('Updating o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link)","table.put_item( Item= { 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest,","str(latest), Type = 'String', Overwrite = True ) def handler(event, context): r =","IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD':","response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4())","= client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 China IP","= logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def","if len(cidr['ips']) != 0: for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask =","= ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first,","= netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#':","'lastip': lastip } ) except: pass logger.info('o365 '+instance+' IP Ranges Updated') response =","requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code == 200: versions = r.json() logger.info(versions)","netrange = ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip =","if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'],","version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value']","Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] ==","= response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link =","last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= {","boto3.client('ssm') def downloader(instance, latest, parameter, link): r = requests.get(link) cidrs = r.json() if","cidr in cidrs: try: if len(cidr['ips']) != 0: for ip in cidr['ips']: sortkey","logger.info(versions) for version in versions: if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken","200: for cidr in cidrs: try: if len(cidr['ips']) != 0: for ip in","for version in versions: if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken =","response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4())","nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip =","logger.info('o365 '+instance+' IP Ranges Updated') response = client.put_parameter( Name = parameter, Value =","'+instance+' IP Ranges Updated') response = client.put_parameter( Name = parameter, Value = str(latest),","Name = parameter, Value = str(latest), Type = 'String', Overwrite = True )","boto3 import ipaddress import json import logging import os import requests import uuid","o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance']","logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest,","= response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link =","= response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 China IP Ranges') link =","o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance']","= client.put_parameter( Name = parameter, Value = str(latest), Type = 'String', Overwrite =","'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip","logger.info('Updating o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif","= 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER'])","!= str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'],","logging import os import requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb =","= int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk': sortkey, 'service':","'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip':","prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'],","IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP","cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip } )","prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link","== 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating","r = requests.get(link) cidrs = r.json() if r.status_code == 200: for cidr in","link) elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken","version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value']","= int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first,","'String', Overwrite = True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status","link) else: logger.info('No o365 IP Range Updates') return { 'statusCode': 200, 'body': json.dumps('Download","'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range Updates') return {","'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken","response = client.put_parameter( Name = parameter, Value = str(latest), Type = 'String', Overwrite","response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide","Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response","firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip)","nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip': firstip,","version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value']","import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client","import ipaddress import json import logging import os import requests import uuid logger","'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip } ) except: pass logger.info('o365","context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code == 200: versions","last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype ==","if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'],","prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'],","client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges')","downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken =","dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest, parameter,","os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if","in versions: if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if","version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']):","link) elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken","logger.info('Updating o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif","instance, 'firstip': firstip, 'lastip': lastip } ) except: pass logger.info('o365 '+instance+' IP Ranges","= client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP","Type = 'String', Overwrite = True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4()))","versions = r.json() logger.info(versions) for version in versions: if version['instance'] == 'Worldwide': response","= response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link =","os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if","elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken !=","client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 China IP Ranges')","'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip':","link): r = requests.get(link) cidrs = r.json() if r.status_code == 200: for cidr","{ 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance,","sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if","cidrs = r.json() if r.status_code == 200: for cidr in cidrs: try: if","lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr':","Ranges Updated') response = client.put_parameter( Name = parameter, Value = str(latest), Type =","prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'],","def downloader(instance, latest, parameter, link): r = requests.get(link) cidrs = r.json() if r.status_code","downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken =","China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] ==","link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range Updates')","= requests.get(link) cidrs = r.json() if r.status_code == 200: for cidr in cidrs:","cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#'","IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany':","in cidrs: try: if len(cidr['ips']) != 0: for ip in cidr['ips']: sortkey =","logger.info('Link Status Code: '+str(r.status_code)) if r.status_code == 200: versions = r.json() logger.info(versions) for","client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges')","o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance']","= 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER'])","if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip","handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code == 200:","Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response","== 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating","response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4())","= ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last))","prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'],","link) elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken","IP Range Updates') return { 'statusCode': 200, 'body': json.dumps('Download o365 IP Ranges') }","= ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last))","= 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last = netrange[0],","if prevtoken != str(version['latest']): logger.info('Updating o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'],","= response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link =","logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance,","Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365","logger.info('Updating o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif","dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest, parameter, link): r = requests.get(link) cidrs","str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link)","json import logging import os import requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO)","!= str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'],","'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365","= client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP","elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken !=","IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China':","str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link)","client = boto3.client('ssm') def downloader(instance, latest, parameter, link): r = requests.get(link) cidrs =","USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] ==","link) elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken","try: if len(cidr['ips']) != 0: for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask","r.json() if r.status_code == 200: for cidr in cidrs: try: if len(cidr['ips']) !=","int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'],","prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 China IP Ranges') link","'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip } ) except:","response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4())","= r.json() if r.status_code == 200: for cidr in cidrs: try: if len(cidr['ips'])","'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip","lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last =","elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip","pass logger.info('o365 '+instance+' IP Ranges Updated') response = client.put_parameter( Name = parameter, Value","r.status_code == 200: for cidr in cidrs: try: if len(cidr['ips']) != 0: for","= client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP","= netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk':","except: pass logger.info('o365 '+instance+' IP Ranges Updated') response = client.put_parameter( Name = parameter,","'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken","downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken =","= 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER'])","!= 0: for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype","import os import requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb')","200: versions = r.json() logger.info(versions) for version in versions: if version['instance'] == 'Worldwide':","os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if","IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh':","Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response","logger.info('No o365 IP Range Updates') return { 'statusCode': 200, 'body': json.dumps('Download o365 IP","parameter, link): r = requests.get(link) cidrs = r.json() if r.status_code == 200: for","version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']):","version in versions: if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value']","if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken !=","netrange = ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip =","int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last","Status Code: '+str(r.status_code)) if r.status_code == 200: versions = r.json() logger.info(versions) for version","== 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating","table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest, parameter, link): r =","Item= { 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint':","latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip } ) except: pass logger.info('o365 '+instance+'","o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance']","Code: '+str(r.status_code)) if r.status_code == 200: versions = r.json() logger.info(versions) for version in","if r.status_code == 200: versions = r.json() logger.info(versions) for version in versions: if","'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365","os import requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table","str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link)","o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No","ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item(","'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip }","= 'String', Overwrite = True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link","ipaddress import json import logging import os import requests import uuid logger =","firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk': sortkey,","version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']):","os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if","client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges')","response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh","== 200: versions = r.json() logger.info(versions) for version in versions: if version['instance'] ==","client.put_parameter( Name = parameter, Value = str(latest), Type = 'String', Overwrite = True","uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client =","logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm')"],"string":"[\n \"True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if\",\n \"== 200: for cidr in cidrs: try: if len(cidr['ips']) != 0: for ip\",\n \"r.json() logger.info(versions) for version in versions: if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER'])\",\n \"netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange\",\n \"'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365\",\n \"nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last =\",\n \"prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link\",\n \"for cidr in cidrs: try: if len(cidr['ips']) != 0: for ip in cidr['ips']:\",\n \"= requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code == 200: versions = r.json()\",\n \"elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken !=\",\n \"downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken =\",\n \"link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response =\",\n \"netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk':\",\n \"requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE'])\",\n \"Updated') response = client.put_parameter( Name = parameter, Value = str(latest), Type = 'String',\",\n \"downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range Updates') return { 'statusCode':\",\n \"int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created':\",\n \"= int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip,\",\n \"ip, 'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip } ) except: pass\",\n \"link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response =\",\n \"str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link)\",\n \"== 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first))\",\n \"response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 China\",\n \"elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken !=\",\n \"IP Ranges Updated') response = client.put_parameter( Name = parameter, Value = str(latest), Type\",\n \"= 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER'])\",\n \"o365 IP Range Updates') return { 'statusCode': 200, 'body': json.dumps('Download o365 IP Ranges')\",\n \"Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range\",\n \"if r.status_code == 200: for cidr in cidrs: try: if len(cidr['ips']) != 0:\",\n \"'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365\",\n \"0: for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype =\",\n \"latest, parameter, link): r = requests.get(link) cidrs = r.json() if r.status_code == 200:\",\n \"'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken\",\n \"ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype\",\n \"= int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last = netrange[0],\",\n \"!= str(version['latest']): logger.info('Updating o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'],\",\n \"link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response =\",\n \"requests.get(link) cidrs = r.json() if r.status_code == 200: for cidr in cidrs: try:\",\n \"cidrs: try: if len(cidr['ips']) != 0: for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip\",\n \"= True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code))\",\n \"version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']):\",\n \"'firstip': firstip, 'lastip': lastip } ) except: pass logger.info('o365 '+instance+' IP Ranges Updated')\",\n \"Value = str(latest), Type = 'String', Overwrite = True ) def handler(event, context):\",\n \"for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0])\",\n \"= boto3.client('ssm') def downloader(instance, latest, parameter, link): r = requests.get(link) cidrs = r.json()\",\n \"== 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first))\",\n \"= str(latest), Type = 'String', Overwrite = True ) def handler(event, context): r\",\n \") def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code\",\n \"link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response =\",\n \"else: logger.info('No o365 IP Range Updates') return { 'statusCode': 200, 'body': json.dumps('Download o365\",\n \"= client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP\",\n \"os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range Updates') return { 'statusCode': 200, 'body':\",\n \"ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last\",\n \"nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip =\",\n \"= 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype\",\n \"logger.info('Updating o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else:\",\n \"= r.json() logger.info(versions) for version in versions: if version['instance'] == 'Worldwide': response =\",\n \"= 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range Updates') return\",\n \"prevtoken != str(version['latest']): logger.info('Updating o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'],\",\n \"!= str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'],\",\n \"versions: if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken\",\n \"first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype\",\n \"if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'],\",\n \"lastip } ) except: pass logger.info('o365 '+instance+' IP Ranges Updated') response = client.put_parameter(\",\n \"import requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table =\",\n \"sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip\",\n \"'+str(r.status_code)) if r.status_code == 200: versions = r.json() logger.info(versions) for version in versions:\",\n \"prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link\",\n \"response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD\",\n \"len(cidr['ips']) != 0: for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/')\",\n \"ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange =\",\n \"ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif\",\n \"response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Germany\",\n \"response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4())\",\n \"prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link\",\n \"} ) except: pass logger.info('o365 '+instance+' IP Ranges Updated') response = client.put_parameter( Name\",\n \"== 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating\",\n \"firstip, 'lastip': lastip } ) except: pass logger.info('o365 '+instance+' IP Ranges Updated') response\",\n \"downloader(instance, latest, parameter, link): r = requests.get(link) cidrs = r.json() if r.status_code ==\",\n \"netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange =\",\n \"logger.info('Updating o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif\",\n \"parameter, Value = str(latest), Type = 'String', Overwrite = True ) def handler(event,\",\n \"client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP Ranges')\",\n \") except: pass logger.info('o365 '+instance+' IP Ranges Updated') response = client.put_parameter( Name =\",\n \"r.status_code == 200: versions = r.json() logger.info(versions) for version in versions: if version['instance']\",\n \"version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value']\",\n \"= dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest, parameter, link): r = requests.get(link)\",\n \"hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#':\",\n \"'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype ==\",\n \"= ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange\",\n \"import json import logging import os import requests import uuid logger = logging.getLogger()\",\n \"Overwrite = True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code:\",\n \"import boto3 import ipaddress import json import logging import os import requests import\",\n \"netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype,\",\n \"'endpoint': instance, 'firstip': firstip, 'lastip': lastip } ) except: pass logger.info('o365 '+instance+' IP\",\n \"iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip)\",\n \"if prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'],\",\n \"boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest, parameter, link): r\",\n \"import logging import os import requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb\",\n \"USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] ==\",\n \"in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype =\",\n \"int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1]\",\n \"= parameter, Value = str(latest), Type = 'String', Overwrite = True ) def\",\n \"r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code == 200: versions =\",\n \"== 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating\",\n \"Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response\",\n \"first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item=\",\n \"version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range Updates') return { 'statusCode': 200,\",\n \"version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']):\",\n \"= boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest, parameter, link):\",\n \"'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1]\",\n \"!= str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'],\",\n \"def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code ==\",\n \"'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365\",\n \"'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken\",\n \"str(version['latest']): logger.info('Updating o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link)\",\n \"table.put_item( Item= { 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest,\",\n \"str(latest), Type = 'String', Overwrite = True ) def handler(event, context): r =\",\n \"IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD':\",\n \"response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4())\",\n \"= client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 China IP\",\n \"= logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def\",\n \"if len(cidr['ips']) != 0: for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask =\",\n \"= ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first,\",\n \"= netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#':\",\n \"'lastip': lastip } ) except: pass logger.info('o365 '+instance+' IP Ranges Updated') response =\",\n \"requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code == 200: versions = r.json() logger.info(versions)\",\n \"netrange = ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip =\",\n \"if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'],\",\n \"version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value']\",\n \"Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] ==\",\n \"= response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link =\",\n \"last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= {\",\n \"boto3.client('ssm') def downloader(instance, latest, parameter, link): r = requests.get(link) cidrs = r.json() if\",\n \"cidr in cidrs: try: if len(cidr['ips']) != 0: for ip in cidr['ips']: sortkey\",\n \"logger.info(versions) for version in versions: if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken\",\n \"200: for cidr in cidrs: try: if len(cidr['ips']) != 0: for ip in\",\n \"for version in versions: if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken =\",\n \"response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4())\",\n \"nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip =\",\n \"logger.info('o365 '+instance+' IP Ranges Updated') response = client.put_parameter( Name = parameter, Value =\",\n \"'+instance+' IP Ranges Updated') response = client.put_parameter( Name = parameter, Value = str(latest),\",\n \"Name = parameter, Value = str(latest), Type = 'String', Overwrite = True )\",\n \"boto3 import ipaddress import json import logging import os import requests import uuid\",\n \"o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance']\",\n \"logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest,\",\n \"= response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link =\",\n \"= response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 China IP Ranges') link =\",\n \"o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance']\",\n \"= client.put_parameter( Name = parameter, Value = str(latest), Type = 'String', Overwrite =\",\n \"'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip\",\n \"logger.info('Updating o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif\",\n \"= 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER'])\",\n \"!= str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'],\",\n \"logging import os import requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb =\",\n \"= int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk': sortkey, 'service':\",\n \"'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip':\",\n \"prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'],\",\n \"IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP\",\n \"cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip } )\",\n \"prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link\",\n \"== 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating\",\n \"r = requests.get(link) cidrs = r.json() if r.status_code == 200: for cidr in\",\n \"link) elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken\",\n \"version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value']\",\n \"= int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first,\",\n \"'String', Overwrite = True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status\",\n \"link) else: logger.info('No o365 IP Range Updates') return { 'statusCode': 200, 'body': json.dumps('Download\",\n \"'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range Updates') return {\",\n \"'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken\",\n \"response = client.put_parameter( Name = parameter, Value = str(latest), Type = 'String', Overwrite\",\n \"response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide\",\n \"Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response\",\n \"firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip)\",\n \"nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip': firstip,\",\n \"version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value']\",\n \"import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client\",\n \"import ipaddress import json import logging import os import requests import uuid logger\",\n \"'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip } ) except: pass logger.info('o365\",\n \"context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code == 200: versions\",\n \"last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype ==\",\n \"if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'],\",\n \"prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'],\",\n \"client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges')\",\n \"downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken =\",\n \"dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest, parameter,\",\n \"os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if\",\n \"in versions: if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if\",\n \"version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']):\",\n \"link) elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken\",\n \"logger.info('Updating o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif\",\n \"instance, 'firstip': firstip, 'lastip': lastip } ) except: pass logger.info('o365 '+instance+' IP Ranges\",\n \"= client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP\",\n \"Type = 'String', Overwrite = True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4()))\",\n \"versions = r.json() logger.info(versions) for version in versions: if version['instance'] == 'Worldwide': response\",\n \"= response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link =\",\n \"os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if\",\n \"elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken !=\",\n \"client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 China IP Ranges')\",\n \"'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip':\",\n \"link): r = requests.get(link) cidrs = r.json() if r.status_code == 200: for cidr\",\n \"{ 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance,\",\n \"sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#' if\",\n \"cidrs = r.json() if r.status_code == 200: for cidr in cidrs: try: if\",\n \"lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr':\",\n \"Ranges Updated') response = client.put_parameter( Name = parameter, Value = str(latest), Type =\",\n \"prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'],\",\n \"def downloader(instance, latest, parameter, link): r = requests.get(link) cidrs = r.json() if r.status_code\",\n \"downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken =\",\n \"China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] ==\",\n \"link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365 IP Range Updates')\",\n \"= requests.get(link) cidrs = r.json() if r.status_code == 200: for cidr in cidrs:\",\n \"cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype = ipaddress.ip_address(hostmask[0]) nametype = 'IPv'+str(iptype.version)+'#'\",\n \"IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany':\",\n \"in cidrs: try: if len(cidr['ips']) != 0: for ip in cidr['ips']: sortkey =\",\n \"logger.info('Link Status Code: '+str(r.status_code)) if r.status_code == 200: versions = r.json() logger.info(versions) for\",\n \"client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges')\",\n \"o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance']\",\n \"= 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER'])\",\n \"if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip\",\n \"handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if r.status_code == 200:\",\n \"Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response\",\n \"== 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating\",\n \"response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4())\",\n \"= ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last))\",\n \"prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'],\",\n \"link) elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken\",\n \"IP Range Updates') return { 'statusCode': 200, 'body': json.dumps('Download o365 IP Ranges') }\",\n \"= ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last))\",\n \"= 'IPv'+str(iptype.version)+'#' if nametype == 'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last = netrange[0],\",\n \"if prevtoken != str(version['latest']): logger.info('Updating o365 China IP Ranges') link = 'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'],\",\n \"= response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP Ranges') link =\",\n \"logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance,\",\n \"Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No o365\",\n \"logger.info('Updating o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif\",\n \"dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest, parameter, link): r = requests.get(link) cidrs\",\n \"str(version['latest']): logger.info('Updating o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link)\",\n \"json import logging import os import requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO)\",\n \"!= str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'],\",\n \"'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365\",\n \"= client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Germany IP\",\n \"elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken !=\",\n \"IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China':\",\n \"str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link)\",\n \"client = boto3.client('ssm') def downloader(instance, latest, parameter, link): r = requests.get(link) cidrs =\",\n \"USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] ==\",\n \"link) elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken\",\n \"try: if len(cidr['ips']) != 0: for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask\",\n \"r.json() if r.status_code == 200: for cidr in cidrs: try: if len(cidr['ips']) !=\",\n \"int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'],\",\n \"prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 China IP Ranges') link\",\n \"'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip } ) except:\",\n \"response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVGCCHigh?clientrequestid='+str(uuid.uuid4())\",\n \"= r.json() if r.status_code == 200: for cidr in cidrs: try: if len(cidr['ips'])\",\n \"'IPv4#': netrange = ipaddress.IPv4Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv4Address(first)) lastip\",\n \"lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last =\",\n \"elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip\",\n \"pass logger.info('o365 '+instance+' IP Ranges Updated') response = client.put_parameter( Name = parameter, Value\",\n \"r.status_code == 200: for cidr in cidrs: try: if len(cidr['ips']) != 0: for\",\n \"= client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh IP\",\n \"= netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk':\",\n \"except: pass logger.info('o365 '+instance+' IP Ranges Updated') response = client.put_parameter( Name = parameter,\",\n \"'https://endpoints.office.com/endpoints/China?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['CHINA_PARAMETER'], link) elif version['instance'] == 'Germany': response = client.get_parameter(Name=os.environ['GERMANY_PARAMETER']) prevtoken\",\n \"downloader(version['instance'], version['latest'], os.environ['HIGH_PARAMETER'], link) elif version['instance'] == 'China': response = client.get_parameter(Name=os.environ['CHINA_PARAMETER']) prevtoken =\",\n \"= 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER'])\",\n \"!= 0: for ip in cidr['ips']: sortkey = 'O365#'+instance+'#'+cidr['serviceArea']+'#'+ip hostmask = ip.split('/') iptype\",\n \"import os import requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb')\",\n \"200: versions = r.json() logger.info(versions) for version in versions: if version['instance'] == 'Worldwide':\",\n \"os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response = client.get_parameter(Name=os.environ['DOD_PARAMETER']) prevtoken = response['Parameter']['Value'] if\",\n \"IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh':\",\n \"Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link) elif version['instance'] == 'USGovDoD': response\",\n \"logger.info('No o365 IP Range Updates') return { 'statusCode': 200, 'body': json.dumps('Download o365 IP\",\n \"parameter, link): r = requests.get(link) cidrs = r.json() if r.status_code == 200: for\",\n \"version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']):\",\n \"version in versions: if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value']\",\n \"if version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken !=\",\n \"netrange = ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip =\",\n \"int(ipaddress.IPv4Address(first)) lastip = int(ipaddress.IPv4Address(last)) elif nametype == 'IPv6#': netrange = ipaddress.IPv6Network(ip) first, last\",\n \"Status Code: '+str(r.status_code)) if r.status_code == 200: versions = r.json() logger.info(versions) for version\",\n \"== 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating\",\n \"table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm') def downloader(instance, latest, parameter, link): r =\",\n \"Item= { 'pk': nametype, 'sk': sortkey, 'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint':\",\n \"latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip } ) except: pass logger.info('o365 '+instance+'\",\n \"o365 USGovDoD IP Ranges') link = 'https://endpoints.office.com/endpoints/USGOVDoD?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['DOD_PARAMETER'], link) elif version['instance']\",\n \"Code: '+str(r.status_code)) if r.status_code == 200: versions = r.json() logger.info(versions) for version in\",\n \"if r.status_code == 200: versions = r.json() logger.info(versions) for version in versions: if\",\n \"'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365\",\n \"os import requests import uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table\",\n \"str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges') link = 'https://endpoints.office.com/endpoints/worldwide?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['WORLD_PARAMETER'], link)\",\n \"o365 Germany IP Ranges') link = 'https://endpoints.office.com/endpoints/Germany?clientrequestid='+str(uuid.uuid4()) downloader(version['instance'], version['latest'], os.environ['GERMANY_PARAMETER'], link) else: logger.info('No\",\n \"ipaddress.IPv6Network(ip) first, last = netrange[0], netrange[-1] firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item(\",\n \"'service': cidr['serviceArea'], 'cidr': ip, 'created': latest, 'endpoint': instance, 'firstip': firstip, 'lastip': lastip }\",\n \"= 'String', Overwrite = True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link\",\n \"ipaddress import json import logging import os import requests import uuid logger =\",\n \"firstip = int(ipaddress.IPv6Address(first)) lastip = int(ipaddress.IPv6Address(last)) table.put_item( Item= { 'pk': nametype, 'sk': sortkey,\",\n \"version['instance'] == 'Worldwide': response = client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']):\",\n \"os.environ['DOD_PARAMETER'], link) elif version['instance'] == 'USGovGCCHigh': response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if\",\n \"client.get_parameter(Name=os.environ['WORLD_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 Worldwide IP Ranges')\",\n \"response = client.get_parameter(Name=os.environ['HIGH_PARAMETER']) prevtoken = response['Parameter']['Value'] if prevtoken != str(version['latest']): logger.info('Updating o365 USGovGCCHigh\",\n \"== 200: versions = r.json() logger.info(versions) for version in versions: if version['instance'] ==\",\n \"client.put_parameter( Name = parameter, Value = str(latest), Type = 'String', Overwrite = True\",\n \"uuid logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client =\",\n \"logger = logging.getLogger() logger.setLevel(logging.INFO) dynamodb = boto3.resource('dynamodb') table = dynamodb.Table(os.environ['DYNAMODB_TABLE']) client = boto3.client('ssm')\"\n]","isConversational":false}}},{"rowIdx":1491,"cells":{"ngram":{"kind":"list like","value":["= Company(\"Example Inc\") c.add_flow(FixedCost(\"Initial Cash\", -500000)) c.add_flow(FixedCost(\"Incorporation\", 500)) c.add_flow(ConstantCost(\"Office\", 50000)) c.add_flow(PeriodicCost(\"Subscription\", 4000, \"2012-01-05\",","ConstantCost(\"Office\", 50000))) c.add_flow(DelayedCost(\"2012-02-01\", FixedCost(\"Financing\", 50000))) c.add_flow(SemiMonthlyCost(\"Payroll\", 4000, \"2012-01-01\")) c.add_flow(SemiMonthlyWages(\"Payroll\", 6000, \"2012-01-01\")) print(c) c.cash_monthly_summary(\"2012-01-01\",","import * c = Company(\"Example Inc\") c.add_flow(FixedCost(\"Initial Cash\", -500000)) c.add_flow(FixedCost(\"Incorporation\", 500)) c.add_flow(ConstantCost(\"Office\", 50000))","money import * c = Company(\"Example Inc\") c.add_flow(FixedCost(\"Initial Cash\", -500000)) c.add_flow(FixedCost(\"Incorporation\", 500)) c.add_flow(ConstantCost(\"Office\",","* c = Company(\"Example Inc\") c.add_flow(FixedCost(\"Initial Cash\", -500000)) c.add_flow(FixedCost(\"Incorporation\", 500)) c.add_flow(ConstantCost(\"Office\", 50000)) c.add_flow(PeriodicCost(\"Subscription\",","c = Company(\"Example Inc\") c.add_flow(FixedCost(\"Initial Cash\", -500000)) c.add_flow(FixedCost(\"Incorporation\", 500)) c.add_flow(ConstantCost(\"Office\", 50000)) c.add_flow(PeriodicCost(\"Subscription\", 4000,","c.add_flow(FixedCost(\"Initial Cash\", -500000)) c.add_flow(FixedCost(\"Incorporation\", 500)) c.add_flow(ConstantCost(\"Office\", 50000)) c.add_flow(PeriodicCost(\"Subscription\", 4000, \"2012-01-05\", 14)) c.add_flow(DelayedCost(\"2012-02-01\", ConstantCost(\"Office\",","c.add_flow(FixedCost(\"Incorporation\", 500)) c.add_flow(ConstantCost(\"Office\", 50000)) c.add_flow(PeriodicCost(\"Subscription\", 4000, \"2012-01-05\", 14)) c.add_flow(DelayedCost(\"2012-02-01\", ConstantCost(\"Office\", 50000))) c.add_flow(DelayedCost(\"2012-02-01\", FixedCost(\"Financing\",","c.add_flow(ConstantCost(\"Office\", 50000)) c.add_flow(PeriodicCost(\"Subscription\", 4000, \"2012-01-05\", 14)) c.add_flow(DelayedCost(\"2012-02-01\", ConstantCost(\"Office\", 50000))) c.add_flow(DelayedCost(\"2012-02-01\", FixedCost(\"Financing\", 50000))) c.add_flow(SemiMonthlyCost(\"Payroll\",","500)) c.add_flow(ConstantCost(\"Office\", 50000)) c.add_flow(PeriodicCost(\"Subscription\", 4000, \"2012-01-05\", 14)) c.add_flow(DelayedCost(\"2012-02-01\", ConstantCost(\"Office\", 50000))) c.add_flow(DelayedCost(\"2012-02-01\", FixedCost(\"Financing\", 50000)))","c.add_flow(DelayedCost(\"2012-02-01\", ConstantCost(\"Office\", 50000))) c.add_flow(DelayedCost(\"2012-02-01\", FixedCost(\"Financing\", 50000))) c.add_flow(SemiMonthlyCost(\"Payroll\", 4000, \"2012-01-01\")) c.add_flow(SemiMonthlyWages(\"Payroll\", 6000, \"2012-01-01\")) print(c)","Cash\", -500000)) c.add_flow(FixedCost(\"Incorporation\", 500)) c.add_flow(ConstantCost(\"Office\", 50000)) c.add_flow(PeriodicCost(\"Subscription\", 4000, \"2012-01-05\", 14)) c.add_flow(DelayedCost(\"2012-02-01\", ConstantCost(\"Office\", 50000)))","Inc\") c.add_flow(FixedCost(\"Initial Cash\", -500000)) c.add_flow(FixedCost(\"Incorporation\", 500)) c.add_flow(ConstantCost(\"Office\", 50000)) c.add_flow(PeriodicCost(\"Subscription\", 4000, \"2012-01-05\", 14)) c.add_flow(DelayedCost(\"2012-02-01\",","<reponame>zulip/finbot #!/usr/bin/python from money import * c = Company(\"Example Inc\") c.add_flow(FixedCost(\"Initial Cash\", -500000))","\"2012-01-05\", 14)) c.add_flow(DelayedCost(\"2012-02-01\", ConstantCost(\"Office\", 50000))) c.add_flow(DelayedCost(\"2012-02-01\", FixedCost(\"Financing\", 50000))) c.add_flow(SemiMonthlyCost(\"Payroll\", 4000, \"2012-01-01\")) c.add_flow(SemiMonthlyWages(\"Payroll\", 6000,","c.add_flow(PeriodicCost(\"Subscription\", 4000, \"2012-01-05\", 14)) c.add_flow(DelayedCost(\"2012-02-01\", ConstantCost(\"Office\", 50000))) c.add_flow(DelayedCost(\"2012-02-01\", FixedCost(\"Financing\", 50000))) c.add_flow(SemiMonthlyCost(\"Payroll\", 4000, \"2012-01-01\"))","4000, \"2012-01-05\", 14)) c.add_flow(DelayedCost(\"2012-02-01\", ConstantCost(\"Office\", 50000))) c.add_flow(DelayedCost(\"2012-02-01\", FixedCost(\"Financing\", 50000))) c.add_flow(SemiMonthlyCost(\"Payroll\", 4000, \"2012-01-01\")) c.add_flow(SemiMonthlyWages(\"Payroll\",","#!/usr/bin/python from money import * c = Company(\"Example Inc\") c.add_flow(FixedCost(\"Initial Cash\", -500000)) c.add_flow(FixedCost(\"Incorporation\",","Company(\"Example Inc\") c.add_flow(FixedCost(\"Initial Cash\", -500000)) c.add_flow(FixedCost(\"Incorporation\", 500)) c.add_flow(ConstantCost(\"Office\", 50000)) c.add_flow(PeriodicCost(\"Subscription\", 4000, \"2012-01-05\", 14))","50000)) c.add_flow(PeriodicCost(\"Subscription\", 4000, \"2012-01-05\", 14)) c.add_flow(DelayedCost(\"2012-02-01\", ConstantCost(\"Office\", 50000))) c.add_flow(DelayedCost(\"2012-02-01\", FixedCost(\"Financing\", 50000))) c.add_flow(SemiMonthlyCost(\"Payroll\", 4000,","14)) c.add_flow(DelayedCost(\"2012-02-01\", ConstantCost(\"Office\", 50000))) c.add_flow(DelayedCost(\"2012-02-01\", FixedCost(\"Financing\", 50000))) c.add_flow(SemiMonthlyCost(\"Payroll\", 4000, \"2012-01-01\")) c.add_flow(SemiMonthlyWages(\"Payroll\", 6000, \"2012-01-01\"))","-500000)) c.add_flow(FixedCost(\"Incorporation\", 500)) c.add_flow(ConstantCost(\"Office\", 50000)) c.add_flow(PeriodicCost(\"Subscription\", 4000, \"2012-01-05\", 14)) c.add_flow(DelayedCost(\"2012-02-01\", ConstantCost(\"Office\", 50000))) c.add_flow(DelayedCost(\"2012-02-01\",","50000))) c.add_flow(DelayedCost(\"2012-02-01\", FixedCost(\"Financing\", 50000))) c.add_flow(SemiMonthlyCost(\"Payroll\", 4000, \"2012-01-01\")) c.add_flow(SemiMonthlyWages(\"Payroll\", 6000, \"2012-01-01\")) print(c) c.cash_monthly_summary(\"2012-01-01\", \"2013-07-01\")","from money import * c = Company(\"Example Inc\") c.add_flow(FixedCost(\"Initial Cash\", -500000)) c.add_flow(FixedCost(\"Incorporation\", 500))"],"string":"[\n \"= Company(\\\"Example Inc\\\") c.add_flow(FixedCost(\\\"Initial Cash\\\", -500000)) c.add_flow(FixedCost(\\\"Incorporation\\\", 500)) c.add_flow(ConstantCost(\\\"Office\\\", 50000)) c.add_flow(PeriodicCost(\\\"Subscription\\\", 4000, \\\"2012-01-05\\\",\",\n \"ConstantCost(\\\"Office\\\", 50000))) c.add_flow(DelayedCost(\\\"2012-02-01\\\", FixedCost(\\\"Financing\\\", 50000))) c.add_flow(SemiMonthlyCost(\\\"Payroll\\\", 4000, \\\"2012-01-01\\\")) c.add_flow(SemiMonthlyWages(\\\"Payroll\\\", 6000, \\\"2012-01-01\\\")) print(c) c.cash_monthly_summary(\\\"2012-01-01\\\",\",\n \"import * c = Company(\\\"Example Inc\\\") c.add_flow(FixedCost(\\\"Initial Cash\\\", -500000)) c.add_flow(FixedCost(\\\"Incorporation\\\", 500)) c.add_flow(ConstantCost(\\\"Office\\\", 50000))\",\n \"money import * c = Company(\\\"Example Inc\\\") c.add_flow(FixedCost(\\\"Initial Cash\\\", -500000)) c.add_flow(FixedCost(\\\"Incorporation\\\", 500)) c.add_flow(ConstantCost(\\\"Office\\\",\",\n \"* c = Company(\\\"Example Inc\\\") c.add_flow(FixedCost(\\\"Initial Cash\\\", -500000)) c.add_flow(FixedCost(\\\"Incorporation\\\", 500)) c.add_flow(ConstantCost(\\\"Office\\\", 50000)) c.add_flow(PeriodicCost(\\\"Subscription\\\",\",\n \"c = Company(\\\"Example Inc\\\") c.add_flow(FixedCost(\\\"Initial Cash\\\", -500000)) c.add_flow(FixedCost(\\\"Incorporation\\\", 500)) c.add_flow(ConstantCost(\\\"Office\\\", 50000)) c.add_flow(PeriodicCost(\\\"Subscription\\\", 4000,\",\n \"c.add_flow(FixedCost(\\\"Initial Cash\\\", -500000)) c.add_flow(FixedCost(\\\"Incorporation\\\", 500)) c.add_flow(ConstantCost(\\\"Office\\\", 50000)) c.add_flow(PeriodicCost(\\\"Subscription\\\", 4000, \\\"2012-01-05\\\", 14)) c.add_flow(DelayedCost(\\\"2012-02-01\\\", ConstantCost(\\\"Office\\\",\",\n \"c.add_flow(FixedCost(\\\"Incorporation\\\", 500)) c.add_flow(ConstantCost(\\\"Office\\\", 50000)) c.add_flow(PeriodicCost(\\\"Subscription\\\", 4000, \\\"2012-01-05\\\", 14)) c.add_flow(DelayedCost(\\\"2012-02-01\\\", ConstantCost(\\\"Office\\\", 50000))) c.add_flow(DelayedCost(\\\"2012-02-01\\\", FixedCost(\\\"Financing\\\",\",\n \"c.add_flow(ConstantCost(\\\"Office\\\", 50000)) c.add_flow(PeriodicCost(\\\"Subscription\\\", 4000, \\\"2012-01-05\\\", 14)) c.add_flow(DelayedCost(\\\"2012-02-01\\\", ConstantCost(\\\"Office\\\", 50000))) c.add_flow(DelayedCost(\\\"2012-02-01\\\", FixedCost(\\\"Financing\\\", 50000))) c.add_flow(SemiMonthlyCost(\\\"Payroll\\\",\",\n \"500)) c.add_flow(ConstantCost(\\\"Office\\\", 50000)) c.add_flow(PeriodicCost(\\\"Subscription\\\", 4000, \\\"2012-01-05\\\", 14)) c.add_flow(DelayedCost(\\\"2012-02-01\\\", ConstantCost(\\\"Office\\\", 50000))) c.add_flow(DelayedCost(\\\"2012-02-01\\\", FixedCost(\\\"Financing\\\", 50000)))\",\n \"c.add_flow(DelayedCost(\\\"2012-02-01\\\", ConstantCost(\\\"Office\\\", 50000))) c.add_flow(DelayedCost(\\\"2012-02-01\\\", FixedCost(\\\"Financing\\\", 50000))) c.add_flow(SemiMonthlyCost(\\\"Payroll\\\", 4000, \\\"2012-01-01\\\")) c.add_flow(SemiMonthlyWages(\\\"Payroll\\\", 6000, \\\"2012-01-01\\\")) print(c)\",\n \"Cash\\\", -500000)) c.add_flow(FixedCost(\\\"Incorporation\\\", 500)) c.add_flow(ConstantCost(\\\"Office\\\", 50000)) c.add_flow(PeriodicCost(\\\"Subscription\\\", 4000, \\\"2012-01-05\\\", 14)) c.add_flow(DelayedCost(\\\"2012-02-01\\\", ConstantCost(\\\"Office\\\", 50000)))\",\n \"Inc\\\") c.add_flow(FixedCost(\\\"Initial Cash\\\", -500000)) c.add_flow(FixedCost(\\\"Incorporation\\\", 500)) c.add_flow(ConstantCost(\\\"Office\\\", 50000)) c.add_flow(PeriodicCost(\\\"Subscription\\\", 4000, \\\"2012-01-05\\\", 14)) c.add_flow(DelayedCost(\\\"2012-02-01\\\",\",\n \"<reponame>zulip/finbot #!/usr/bin/python from money import * c = Company(\\\"Example Inc\\\") c.add_flow(FixedCost(\\\"Initial Cash\\\", -500000))\",\n \"\\\"2012-01-05\\\", 14)) c.add_flow(DelayedCost(\\\"2012-02-01\\\", ConstantCost(\\\"Office\\\", 50000))) c.add_flow(DelayedCost(\\\"2012-02-01\\\", FixedCost(\\\"Financing\\\", 50000))) c.add_flow(SemiMonthlyCost(\\\"Payroll\\\", 4000, \\\"2012-01-01\\\")) c.add_flow(SemiMonthlyWages(\\\"Payroll\\\", 6000,\",\n \"c.add_flow(PeriodicCost(\\\"Subscription\\\", 4000, \\\"2012-01-05\\\", 14)) c.add_flow(DelayedCost(\\\"2012-02-01\\\", ConstantCost(\\\"Office\\\", 50000))) c.add_flow(DelayedCost(\\\"2012-02-01\\\", FixedCost(\\\"Financing\\\", 50000))) c.add_flow(SemiMonthlyCost(\\\"Payroll\\\", 4000, \\\"2012-01-01\\\"))\",\n \"4000, \\\"2012-01-05\\\", 14)) c.add_flow(DelayedCost(\\\"2012-02-01\\\", ConstantCost(\\\"Office\\\", 50000))) c.add_flow(DelayedCost(\\\"2012-02-01\\\", FixedCost(\\\"Financing\\\", 50000))) c.add_flow(SemiMonthlyCost(\\\"Payroll\\\", 4000, \\\"2012-01-01\\\")) c.add_flow(SemiMonthlyWages(\\\"Payroll\\\",\",\n \"#!/usr/bin/python from money import * c = Company(\\\"Example Inc\\\") c.add_flow(FixedCost(\\\"Initial Cash\\\", -500000)) c.add_flow(FixedCost(\\\"Incorporation\\\",\",\n \"Company(\\\"Example Inc\\\") c.add_flow(FixedCost(\\\"Initial Cash\\\", -500000)) c.add_flow(FixedCost(\\\"Incorporation\\\", 500)) c.add_flow(ConstantCost(\\\"Office\\\", 50000)) c.add_flow(PeriodicCost(\\\"Subscription\\\", 4000, \\\"2012-01-05\\\", 14))\",\n \"50000)) c.add_flow(PeriodicCost(\\\"Subscription\\\", 4000, \\\"2012-01-05\\\", 14)) c.add_flow(DelayedCost(\\\"2012-02-01\\\", ConstantCost(\\\"Office\\\", 50000))) c.add_flow(DelayedCost(\\\"2012-02-01\\\", FixedCost(\\\"Financing\\\", 50000))) c.add_flow(SemiMonthlyCost(\\\"Payroll\\\", 4000,\",\n \"14)) c.add_flow(DelayedCost(\\\"2012-02-01\\\", ConstantCost(\\\"Office\\\", 50000))) c.add_flow(DelayedCost(\\\"2012-02-01\\\", FixedCost(\\\"Financing\\\", 50000))) c.add_flow(SemiMonthlyCost(\\\"Payroll\\\", 4000, \\\"2012-01-01\\\")) c.add_flow(SemiMonthlyWages(\\\"Payroll\\\", 6000, \\\"2012-01-01\\\"))\",\n \"-500000)) c.add_flow(FixedCost(\\\"Incorporation\\\", 500)) c.add_flow(ConstantCost(\\\"Office\\\", 50000)) c.add_flow(PeriodicCost(\\\"Subscription\\\", 4000, \\\"2012-01-05\\\", 14)) c.add_flow(DelayedCost(\\\"2012-02-01\\\", ConstantCost(\\\"Office\\\", 50000))) c.add_flow(DelayedCost(\\\"2012-02-01\\\",\",\n \"50000))) c.add_flow(DelayedCost(\\\"2012-02-01\\\", FixedCost(\\\"Financing\\\", 50000))) c.add_flow(SemiMonthlyCost(\\\"Payroll\\\", 4000, \\\"2012-01-01\\\")) c.add_flow(SemiMonthlyWages(\\\"Payroll\\\", 6000, \\\"2012-01-01\\\")) print(c) c.cash_monthly_summary(\\\"2012-01-01\\\", \\\"2013-07-01\\\")\",\n \"from money import * c = Company(\\\"Example Inc\\\") c.add_flow(FixedCost(\\\"Initial Cash\\\", -500000)) c.add_flow(FixedCost(\\\"Incorporation\\\", 500))\"\n]","isConversational":false}}},{"rowIdx":1492,"cells":{"ngram":{"kind":"list like","value":["ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE)","= logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1',","address, port) except socket.error as e: LOGGER.error('Checking port %s:%d - Failed', address, port)","socket.error as e: LOGGER.error('Checking port %s:%d - Failed', address, port) raise ValidatorError(e) port.short_name","subprocess import argparse import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address):","try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s -","#!/usr/bin/env python import os import socket import subprocess import argparse import logging LOGGER","e: LOGGER.error('Checking port %s:%d - Failed', address, port) raise ValidatorError(e) port.short_name = 'PORT'","def port(address, port): s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d -","port) except socket.error as e: LOGGER.error('Checking port %s:%d - Failed', address, port) raise","port): s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK', address,","import os import socket import subprocess import argparse import logging LOGGER = logging.getLogger(__name__)","%s - OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s - Failed',","argparse import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping',","LOGGER.info('Ping server %s - OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s","%s:%d - OK', address, port) except socket.error as e: LOGGER.error('Checking port %s:%d -","socket import subprocess import argparse import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass","'PING' def port(address, port): s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d","e: LOGGER.error('Ping server %s - Failed', address) raise ValidatorError(e) ping.short_name = 'PING' def","ping.short_name = 'PING' def port(address, port): s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking","ValidatorError(e) ping.short_name = 'PING' def port(address, port): s = socket.socket() try: s.connect((address, port))","stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server","server %s - Failed', address) raise ValidatorError(e) ping.short_name = 'PING' def port(address, port):","server %s - OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s -","'-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address)","port)) LOGGER.info('Checking port %s:%d - OK', address, port) except socket.error as e: LOGGER.error('Checking","logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1',","subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK',","s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK', address, port) except socket.error as e:","port(address, port): s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK',","import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c","1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address) except","subprocess.CalledProcessError as e: LOGGER.error('Ping server %s - Failed', address) raise ValidatorError(e) ping.short_name =","pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping","= 'PING' def port(address, port): s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port","address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address) except subprocess.CalledProcessError as e:","- Failed', address) raise ValidatorError(e) ping.short_name = 'PING' def port(address, port): s =","address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s - Failed', address) raise ValidatorError(e)","stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping","as e: LOGGER.error('Ping server %s - Failed', address) raise ValidatorError(e) ping.short_name = 'PING'","raise ValidatorError(e) ping.short_name = 'PING' def port(address, port): s = socket.socket() try: s.connect((address,","= socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK', address, port) except","os import socket import subprocess import argparse import logging LOGGER = logging.getLogger(__name__) class","ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s","except socket.error as e: LOGGER.error('Checking port %s:%d - Failed', address, port) raise ValidatorError(e)","1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address) except subprocess.CalledProcessError as","except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s - Failed', address) raise ValidatorError(e) ping.short_name","logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address),","LOGGER.info('Checking port %s:%d - OK', address, port) except socket.error as e: LOGGER.error('Checking port","socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK', address, port) except socket.error","try: s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK', address, port) except socket.error as","- OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s - Failed', address)","import argparse import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try:","import subprocess import argparse import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def","OK', address, port) except socket.error as e: LOGGER.error('Checking port %s:%d - Failed', address,","s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK', address, port)","address) raise ValidatorError(e) ping.short_name = 'PING' def port(address, port): s = socket.socket() try:","python import os import socket import subprocess import argparse import logging LOGGER =","LOGGER.error('Ping server %s - Failed', address) raise ValidatorError(e) ping.short_name = 'PING' def port(address,","%s - Failed', address) raise ValidatorError(e) ping.short_name = 'PING' def port(address, port): s","class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE,","as e: LOGGER.error('Checking port %s:%d - Failed', address, port) raise ValidatorError(e) port.short_name =","OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s - Failed', address) raise","- OK', address, port) except socket.error as e: LOGGER.error('Checking port %s:%d - Failed',","port %s:%d - OK', address, port) except socket.error as e: LOGGER.error('Checking port %s:%d","import socket import subprocess import argparse import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception):","def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server","'-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address) except subprocess.CalledProcessError","LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W","Failed', address) raise ValidatorError(e) ping.short_name = 'PING' def port(address, port): s = socket.socket()"],"string":"[\n \"ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE)\",\n \"= logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1',\",\n \"address, port) except socket.error as e: LOGGER.error('Checking port %s:%d - Failed', address, port)\",\n \"socket.error as e: LOGGER.error('Checking port %s:%d - Failed', address, port) raise ValidatorError(e) port.short_name\",\n \"subprocess import argparse import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address):\",\n \"try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s -\",\n \"#!/usr/bin/env python import os import socket import subprocess import argparse import logging LOGGER\",\n \"e: LOGGER.error('Checking port %s:%d - Failed', address, port) raise ValidatorError(e) port.short_name = 'PORT'\",\n \"def port(address, port): s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d -\",\n \"port) except socket.error as e: LOGGER.error('Checking port %s:%d - Failed', address, port) raise\",\n \"port): s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK', address,\",\n \"import os import socket import subprocess import argparse import logging LOGGER = logging.getLogger(__name__)\",\n \"%s - OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s - Failed',\",\n \"argparse import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping',\",\n \"LOGGER.info('Ping server %s - OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s\",\n \"%s:%d - OK', address, port) except socket.error as e: LOGGER.error('Checking port %s:%d -\",\n \"socket import subprocess import argparse import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass\",\n \"'PING' def port(address, port): s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d\",\n \"e: LOGGER.error('Ping server %s - Failed', address) raise ValidatorError(e) ping.short_name = 'PING' def\",\n \"ping.short_name = 'PING' def port(address, port): s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking\",\n \"ValidatorError(e) ping.short_name = 'PING' def port(address, port): s = socket.socket() try: s.connect((address, port))\",\n \"stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server\",\n \"server %s - Failed', address) raise ValidatorError(e) ping.short_name = 'PING' def port(address, port):\",\n \"server %s - OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s -\",\n \"'-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address)\",\n \"port)) LOGGER.info('Checking port %s:%d - OK', address, port) except socket.error as e: LOGGER.error('Checking\",\n \"logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1',\",\n \"subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK',\",\n \"s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK', address, port) except socket.error as e:\",\n \"port(address, port): s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK',\",\n \"import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c\",\n \"1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address) except\",\n \"subprocess.CalledProcessError as e: LOGGER.error('Ping server %s - Failed', address) raise ValidatorError(e) ping.short_name =\",\n \"pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping\",\n \"= 'PING' def port(address, port): s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port\",\n \"address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address) except subprocess.CalledProcessError as e:\",\n \"- Failed', address) raise ValidatorError(e) ping.short_name = 'PING' def port(address, port): s =\",\n \"address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s - Failed', address) raise ValidatorError(e)\",\n \"stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping\",\n \"as e: LOGGER.error('Ping server %s - Failed', address) raise ValidatorError(e) ping.short_name = 'PING'\",\n \"raise ValidatorError(e) ping.short_name = 'PING' def port(address, port): s = socket.socket() try: s.connect((address,\",\n \"= socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK', address, port) except\",\n \"os import socket import subprocess import argparse import logging LOGGER = logging.getLogger(__name__) class\",\n \"ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s\",\n \"except socket.error as e: LOGGER.error('Checking port %s:%d - Failed', address, port) raise ValidatorError(e)\",\n \"1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address) except subprocess.CalledProcessError as\",\n \"except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s - Failed', address) raise ValidatorError(e) ping.short_name\",\n \"logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address),\",\n \"LOGGER.info('Checking port %s:%d - OK', address, port) except socket.error as e: LOGGER.error('Checking port\",\n \"socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK', address, port) except socket.error\",\n \"try: s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK', address, port) except socket.error as\",\n \"- OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s - Failed', address)\",\n \"import argparse import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try:\",\n \"import subprocess import argparse import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def\",\n \"OK', address, port) except socket.error as e: LOGGER.error('Checking port %s:%d - Failed', address,\",\n \"s = socket.socket() try: s.connect((address, port)) LOGGER.info('Checking port %s:%d - OK', address, port)\",\n \"address) raise ValidatorError(e) ping.short_name = 'PING' def port(address, port): s = socket.socket() try:\",\n \"python import os import socket import subprocess import argparse import logging LOGGER =\",\n \"LOGGER.error('Ping server %s - Failed', address) raise ValidatorError(e) ping.short_name = 'PING' def port(address,\",\n \"%s - Failed', address) raise ValidatorError(e) ping.short_name = 'PING' def port(address, port): s\",\n \"class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE,\",\n \"as e: LOGGER.error('Checking port %s:%d - Failed', address, port) raise ValidatorError(e) port.short_name =\",\n \"OK', address) except subprocess.CalledProcessError as e: LOGGER.error('Ping server %s - Failed', address) raise\",\n \"- OK', address, port) except socket.error as e: LOGGER.error('Checking port %s:%d - Failed',\",\n \"port %s:%d - OK', address, port) except socket.error as e: LOGGER.error('Checking port %s:%d\",\n \"import socket import subprocess import argparse import logging LOGGER = logging.getLogger(__name__) class ValidatorError(Exception):\",\n \"def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server\",\n \"'-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE) LOGGER.info('Ping server %s - OK', address) except subprocess.CalledProcessError\",\n \"LOGGER = logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W\",\n \"Failed', address) raise ValidatorError(e) ping.short_name = 'PING' def port(address, port): s = socket.socket()\"\n]","isConversational":false}}},{"rowIdx":1493,"cells":{"ngram":{"kind":"list like","value":["<reponame>Open-EO/openeo-geopyspark-driver from openeo.udf import XarrayDataCube def apply_datacube(cube: XarrayDataCube, context: dict) -> XarrayDataCube: return","from openeo.udf import XarrayDataCube def apply_datacube(cube: XarrayDataCube, context: dict) -> XarrayDataCube: return cube"],"string":"[\n \"<reponame>Open-EO/openeo-geopyspark-driver from openeo.udf import XarrayDataCube def apply_datacube(cube: XarrayDataCube, context: dict) -> XarrayDataCube: return\",\n \"from openeo.udf import XarrayDataCube def apply_datacube(cube: XarrayDataCube, context: dict) -> XarrayDataCube: return cube\"\n]","isConversational":false}}},{"rowIdx":1494,"cells":{"ngram":{"kind":"list like","value":["gave the resource home, look 4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player)","look 4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return create_move_action(moves[0])","player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin,","def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target","# If player just gave the resource home, look 4 resources again if(not","target) # If player just gave the resource home, look 4 resources again","from PlayerState import * from pathFinder import PathFinder from StateLook4Resources import * class","= player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target = self.player.target moves =","has a resource and go back home \"\"\" def __init__(self, player): self.player =","just gave the resource home, look 4 resources again if(not self.player.hasResources()): self.player.state =","4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return create_move_action(moves[0]) def","Implementation: has a resource and go back home \"\"\" def __init__(self, player): self.player","StateGoHome(PlayerState): \"\"\" State Implementation: has a resource and go back home \"\"\" def","origin = self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If player","resource and go back home \"\"\" def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation)","PathFinder from StateLook4Resources import * class StateGoHome(PlayerState): \"\"\" State Implementation: has a resource","a resource and go back home \"\"\" def __init__(self, player): self.player = player","back home \"\"\" def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin","__init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target =","home \"\"\" def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin =","= self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If player just","class StateGoHome(PlayerState): \"\"\" State Implementation: has a resource and go back home \"\"\"","if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return create_move_action(moves[0]) def toString(): return \"StateGoHome\"","resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return create_move_action(moves[0]) def toString():","self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If player just gave the resource home,","pathFinder import PathFinder from StateLook4Resources import * class StateGoHome(PlayerState): \"\"\" State Implementation: has","doAction(self): origin = self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If","from StateLook4Resources import * class StateGoHome(PlayerState): \"\"\" State Implementation: has a resource and","StateLook4Resources import * class StateGoHome(PlayerState): \"\"\" State Implementation: has a resource and go","import * from pathFinder import PathFinder from StateLook4Resources import * class StateGoHome(PlayerState): \"\"\"","the resource home, look 4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return","self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target)","home, look 4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return","player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target = self.player.target","\"\"\" def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position","\"\"\" State Implementation: has a resource and go back home \"\"\" def __init__(self,","PlayerState import * from pathFinder import PathFinder from StateLook4Resources import * class StateGoHome(PlayerState):","If player just gave the resource home, look 4 resources again if(not self.player.hasResources()):","resource home, look 4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0)","go back home \"\"\" def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self):","* class StateGoHome(PlayerState): \"\"\" State Implementation: has a resource and go back home","= PathFinder(self.player.mapView).getPath(origin, target) # If player just gave the resource home, look 4","= self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If player just gave the resource","State Implementation: has a resource and go back home \"\"\" def __init__(self, player):","and go back home \"\"\" def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def","from pathFinder import PathFinder from StateLook4Resources import * class StateGoHome(PlayerState): \"\"\" State Implementation:","* from pathFinder import PathFinder from StateLook4Resources import * class StateGoHome(PlayerState): \"\"\" State","def doAction(self): origin = self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) #","again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return create_move_action(moves[0]) def toString(): return","player just gave the resource home, look 4 resources again if(not self.player.hasResources()): self.player.state","import * class StateGoHome(PlayerState): \"\"\" State Implementation: has a resource and go back","moves = PathFinder(self.player.mapView).getPath(origin, target) # If player just gave the resource home, look","import PathFinder from StateLook4Resources import * class StateGoHome(PlayerState): \"\"\" State Implementation: has a","self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target = self.player.target moves","PathFinder(self.player.mapView).getPath(origin, target) # If player just gave the resource home, look 4 resources","self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If player just gave","target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If player just gave the"],"string":"[\n \"gave the resource home, look 4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player)\",\n \"look 4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return create_move_action(moves[0])\",\n \"player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin,\",\n \"def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target\",\n \"# If player just gave the resource home, look 4 resources again if(not\",\n \"target) # If player just gave the resource home, look 4 resources again\",\n \"from PlayerState import * from pathFinder import PathFinder from StateLook4Resources import * class\",\n \"= player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target = self.player.target moves =\",\n \"has a resource and go back home \\\"\\\"\\\" def __init__(self, player): self.player =\",\n \"just gave the resource home, look 4 resources again if(not self.player.hasResources()): self.player.state =\",\n \"4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return create_move_action(moves[0]) def\",\n \"Implementation: has a resource and go back home \\\"\\\"\\\" def __init__(self, player): self.player\",\n \"StateGoHome(PlayerState): \\\"\\\"\\\" State Implementation: has a resource and go back home \\\"\\\"\\\" def\",\n \"origin = self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If player\",\n \"resource and go back home \\\"\\\"\\\" def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation)\",\n \"PathFinder from StateLook4Resources import * class StateGoHome(PlayerState): \\\"\\\"\\\" State Implementation: has a resource\",\n \"a resource and go back home \\\"\\\"\\\" def __init__(self, player): self.player = player\",\n \"back home \\\"\\\"\\\" def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin\",\n \"__init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target =\",\n \"home \\\"\\\"\\\" def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin =\",\n \"= self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If player just\",\n \"class StateGoHome(PlayerState): \\\"\\\"\\\" State Implementation: has a resource and go back home \\\"\\\"\\\"\",\n \"if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return create_move_action(moves[0]) def toString(): return \\\"StateGoHome\\\"\",\n \"resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return create_move_action(moves[0]) def toString():\",\n \"self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If player just gave the resource home,\",\n \"pathFinder import PathFinder from StateLook4Resources import * class StateGoHome(PlayerState): \\\"\\\"\\\" State Implementation: has\",\n \"doAction(self): origin = self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If\",\n \"from StateLook4Resources import * class StateGoHome(PlayerState): \\\"\\\"\\\" State Implementation: has a resource and\",\n \"StateLook4Resources import * class StateGoHome(PlayerState): \\\"\\\"\\\" State Implementation: has a resource and go\",\n \"import * from pathFinder import PathFinder from StateLook4Resources import * class StateGoHome(PlayerState): \\\"\\\"\\\"\",\n \"the resource home, look 4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return\",\n \"self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target)\",\n \"home, look 4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return\",\n \"player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target = self.player.target\",\n \"\\\"\\\"\\\" def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position\",\n \"\\\"\\\"\\\" State Implementation: has a resource and go back home \\\"\\\"\\\" def __init__(self,\",\n \"PlayerState import * from pathFinder import PathFinder from StateLook4Resources import * class StateGoHome(PlayerState):\",\n \"If player just gave the resource home, look 4 resources again if(not self.player.hasResources()):\",\n \"resource home, look 4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0)\",\n \"go back home \\\"\\\"\\\" def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self):\",\n \"* class StateGoHome(PlayerState): \\\"\\\"\\\" State Implementation: has a resource and go back home\",\n \"= PathFinder(self.player.mapView).getPath(origin, target) # If player just gave the resource home, look 4\",\n \"= self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If player just gave the resource\",\n \"State Implementation: has a resource and go back home \\\"\\\"\\\" def __init__(self, player):\",\n \"and go back home \\\"\\\"\\\" def __init__(self, player): self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def\",\n \"from pathFinder import PathFinder from StateLook4Resources import * class StateGoHome(PlayerState): \\\"\\\"\\\" State Implementation:\",\n \"* from pathFinder import PathFinder from StateLook4Resources import * class StateGoHome(PlayerState): \\\"\\\"\\\" State\",\n \"def doAction(self): origin = self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) #\",\n \"again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return create_move_action(moves[0]) def toString(): return\",\n \"player just gave the resource home, look 4 resources again if(not self.player.hasResources()): self.player.state\",\n \"import * class StateGoHome(PlayerState): \\\"\\\"\\\" State Implementation: has a resource and go back\",\n \"moves = PathFinder(self.player.mapView).getPath(origin, target) # If player just gave the resource home, look\",\n \"import PathFinder from StateLook4Resources import * class StateGoHome(PlayerState): \\\"\\\"\\\" State Implementation: has a\",\n \"self.player = player self.player.setTarget(self.player.playerData.HouseLocation) def doAction(self): origin = self.player.playerData.Position target = self.player.target moves\",\n \"PathFinder(self.player.mapView).getPath(origin, target) # If player just gave the resource home, look 4 resources\",\n \"self.player.playerData.Position target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If player just gave\",\n \"target = self.player.target moves = PathFinder(self.player.mapView).getPath(origin, target) # If player just gave the\"\n]","isConversational":false}}},{"rowIdx":1495,"cells":{"ngram":{"kind":"list like","value":["same velocity along +x for 3 steps. It will bounce back in y","self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) #","# test that virtual particle filler can be attached, removed, and updated def","# test basic stepping behavior with no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.)","[1.,1.,-1.]) # the second particle has y and z velocities flip again, and","V=0.1, boundary=\"no_slip\", period=2) # test for setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.)","boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.])","the HOOMD-blue project, released under the BSD 3-Clause License. # Maintainer: mphoward import","since it started closer, # it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9])","take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95])","the second particle has y and z velocities flip again, and since it","= [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and check bounce back of particles","[-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\"no_slip\", V=1.0, period=3) # change","def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\"no_slip\", period=2) # test for setting parameters def test_set_params(self):","self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.])","virtual particle filler can be attached, removed, and updated def test_filler(self): # initialization","is not None) # run should be able to setup the filler, although","None) hoomd.run(1) # assert an error is raised if we set a bad","self.s.restore_snapshot(snap) # run one step and check bounce back of particles hoomd.run(1) snap","it started. # (vx stays the same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0],","self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an error is raised if we","hoomd.run(1) def tearDown(self): del self.s if __name__ == '__main__': unittest.main(argv = ['test.py', '-v'])","# set the decomposition in z for mpi builds if hoomd.comm.get_num_ranks() > 1:","test_validate_box(self): # initial configuration is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) #","an error is raised if we set a bad particle type with self.assertRaises(RuntimeError):","slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.)","> 1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system","valid slit.set_params(H=4.) hoomd.run(2) # make sure we can invalidate it again slit.set_params(H=10.) with","back in y and z to where it started. # (vx stays the","np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where one particle","setting the slit size too large raises an error def test_validate_box(self): # initial","[-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior with slip boundary conditions def","= mpcd.stream.slit(H=4.) slit.set_params(boundary=\"no_slip\") slit.set_params(boundary=\"slip\") with self.assertRaises(ValueError): slit.set_params(boundary=\"invalid\") # test basic stepping behavior with","mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0:","The Regents of the University of Michigan # This file is part of","invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out of","step where one particle will now hit the wall hoomd.run(1) snap = self.s.take_snapshot()","[-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the slit","hoomd.context.initialize() # set the decomposition in z for mpi builds if hoomd.comm.get_num_ranks() >","= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1],","to the wall speed, and so it will translate at # same velocity","0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting","slit.set_params(boundary=\"invalid\") # test basic stepping behavior with no slip boundary conditions def test_step_noslip(self):","hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take","can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out","behavior with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\"slip\") # take one step","sure we can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that","[1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second particle","that virtual particle filler can be attached, removed, and updated def test_filler(self): #","3-Clause License. # Maintainer: mphoward import unittest import numpy as np import hoomd","0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also ensure other parameters stay the","0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step","the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0],","np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the slit size too large","second particle through the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0:","\"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also ensure","# test that setting the slit size too large raises an error def","filler, although this all happens silently hoomd.run(1) # changing the geometry should still","test that particles out of bounds can be caught def test_out_of_bounds(self): slit =","== 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another","flip again, and since it started closer, # it moves relative to original","0: # the first particle is matched exactly to the wall speed, and","the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s","== 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another","step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.])","y and z to where it started. # (vx stays the same, and","kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None) # run should be able to","mpcd._mpcd.boundary.slip) # test for invalid boundary conditions being set def test_bad_boundary(self): slit =","step and check bounce back of particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank()","import mpcd # unit tests for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def","the first particle is matched exactly to the wall speed, and so it","test_filler(self): # initialization of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A')","particle filler can be attached, removed, and updated def test_filler(self): # initialization of","at # same velocity along +x for 3 steps. It will bounce back","is matched exactly to the wall speed, and so it will translate at","to where it started. # (vx stays the same, and vy and vz","creation can happen (with all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\"no_slip\", period=2)","# This file is part of the HOOMD-blue project, released under the BSD","can be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1)","run one step and check bounce back of particles hoomd.run(1) snap = self.s.take_snapshot()","of bounds can be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1)","we set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the","slit.set_params(boundary=\"slip\") self.assertEqual(slit.boundary, \"slip\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary conditions being set","self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.])","<reponame>schwendp/hoomd-blue # Copyright (c) 2009-2019 The Regents of the University of Michigan #","# the first particle is matched exactly to the wall speed, and so","def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that","moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping","self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H","[-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the","slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out of bounds can be","setUp(self): # establish the simulation context hoomd.context.initialize() # set the decomposition in z","BSD 3-Clause License. # Maintainer: mphoward import unittest import numpy as np import","self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step","establish the simulation context hoomd.context.initialize() # set the decomposition in z for mpi","filler should still allow a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self):","started. # (vx stays the same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85])","self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\"slip\") self.assertEqual(slit.boundary, \"slip\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) #","type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an error is raised","if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and","seed=42, type='A') self.assertTrue(slit._filler is not None) # run should be able to setup","slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None) # run","# unit tests for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): #","one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0],","np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has y and z velocities","filler can be attached, removed, and updated def test_filler(self): # initialization of a","size too large raises an error def test_validate_box(self): # initial configuration is invalid","boundary conditions being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\"no_slip\") slit.set_params(boundary=\"slip\") with self.assertRaises(ValueError):","particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an error is","initial configuration is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it","slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation context hoomd.context.initialize()","boundary=\"slip\") # take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0:","slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None) # run should be able","although this all happens silently hoomd.run(1) # changing the geometry should still be","assert an error is raised if we set a bad particle type with","test that setting the slit size too large raises an error def test_validate_box(self):","[0.,1.,1.]) # test basic stepping behavior with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4.,","slit.set_params(V=1.0) hoomd.run(1) # changing filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is","is raised if we set a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0,","translating relative to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] =","3 steps. It will bounce back in y and z to where it","hoomd.run(1) # changing the geometry should still be OK with a run slit.set_params(V=1.0)","boundary=\"no_slip\", V=1.0, period=3) # change velocity of lower particle so it is translating","self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del self.s if __name__ == '__main__': unittest.main(argv","default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from the starting snapshot","self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary conditions being set def test_bad_boundary(self): slit","np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the","np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second particle through","boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\"slip\") # take one step hoomd.run(1) snap =","of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not","for invalid boundary conditions being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\"no_slip\") slit.set_params(boundary=\"slip\")","# assert an error is raised if we set a bad particle type","back of particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the","== 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another","be attached, removed, and updated def test_filler(self): # initialization of a filler slit","with a run slit.set_params(V=1.0) hoomd.run(1) # changing filler should be allowed slit.set_filler(density=10., kT=1.5,","error is raised if we set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0,","same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second","mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.)))","another step where one particle will now hit the wall hoomd.run(1) snap =","+x for 3 steps. It will bounce back in y and z to","take another step where one particle will now hit the wall hoomd.run(1) snap","is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it should be","removing the filler should still allow a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1)","hit the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95])","should still be OK with a run slit.set_params(V=1.0) hoomd.run(1) # changing filler should","== 0: # the first particle is matched exactly to the wall speed,","the simulation context hoomd.context.initialize() # set the decomposition in z for mpi builds","with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler should still allow a","seed=42) # removing the filler should still allow a run slit.remove_filler() self.assertTrue(slit._filler is","set a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert","now hit the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0],","# test creation can happen (with all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1,","It will bounce back in y and z to where it started. #","with self.assertRaises(ValueError): slit.set_params(boundary=\"invalid\") # test basic stepping behavior with no slip boundary conditions","too large raises an error def test_validate_box(self): # initial configuration is invalid slit","geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation context hoomd.context.initialize() # set","setup the filler, although this all happens silently hoomd.run(1) # changing the geometry","if we set a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B')","other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(),","# changing filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None)","# change BCs slit.set_params(boundary=\"slip\") self.assertEqual(slit.boundary, \"slip\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary","mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None) # run should be","changing the geometry should still be OK with a run slit.set_params(V=1.0) hoomd.run(1) #","a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an","0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change","is translating relative to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1]","hoomd import mpcd # unit tests for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase):","# test that particles out of bounds can be caught def test_out_of_bounds(self): slit","a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None)","is not None) hoomd.run(1) # assert an error is raised if we set","z for mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing configuration","# default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from the starting","can happen (with all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\"no_slip\", period=2) #","where one particle will now hit the wall hoomd.run(1) snap = self.s.take_snapshot() if","hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take","np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping","updated def test_filler(self): # initialization of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0,","basic stepping behavior with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\"slip\") # take","happens silently hoomd.run(1) # changing the geometry should still be OK with a","V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\"slip\") self.assertEqual(slit.boundary, \"slip\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(),","the geometry should still be OK with a run slit.set_params(V=1.0) hoomd.run(1) # changing","under the BSD 3-Clause License. # Maintainer: mphoward import unittest import numpy as","where it started. # (vx stays the same, and vy and vz flip.)","parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(),","snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9])","initialization of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is","# make sure we can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) #","# initialize the system from the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] =","slit size too large raises an error def test_validate_box(self): # initial configuration is","flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has y and z","boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.])","# assert an error is raised if we set a bad density with","stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(),","vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has y and","== 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4.,","wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.])","# establish the simulation context hoomd.context.initialize() # set the decomposition in z for","# Maintainer: mphoward import unittest import numpy as np import hoomd from hoomd","speed, and so it will translate at # same velocity along +x for","run slit.set_params(V=1.0) hoomd.run(1) # changing filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler","bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler should still","and also ensure other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.)","assert an error is raised if we set a bad density with self.assertRaises(RuntimeError):","part of the HOOMD-blue project, released under the BSD 3-Clause License. # Maintainer:","def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\"no_slip\") slit.set_params(boundary=\"slip\") with self.assertRaises(ValueError): slit.set_params(boundary=\"invalid\") # test basic","translate at # same velocity along +x for 3 steps. It will bounce","filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None) #","if we set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing","def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank()","[-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second particle through the","again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out of bounds can","def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\"slip\") # take one step hoomd.run(1) snap = self.s.take_snapshot() if","the University of Michigan # This file is part of the HOOMD-blue project,","all happens silently hoomd.run(1) # changing the geometry should still be OK with","changing filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1)","self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also","[-1.,-1.,-1.]) # take another step, wrapping the second particle through the boundary hoomd.run(1)","BCs slit.set_params(boundary=\"slip\") self.assertEqual(slit.boundary, \"slip\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary conditions being","hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from the","hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and check","bounds can be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85)","slit.set_params(boundary=\"slip\") with self.assertRaises(ValueError): slit.set_params(boundary=\"invalid\") # test basic stepping behavior with no slip boundary","with no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1)","# removing the filler should still allow a run slit.remove_filler() self.assertTrue(slit._filler is None)","density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler should still allow","second particle has y and z velocities flip again, and since it started","== 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that","and z to where it started. # (vx stays the same, and vy","0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step,","snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9])","if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize","# test for invalid boundary conditions being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.)","[-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the slit size too large raises","hoomd.run(1) # assert an error is raised if we set a bad particle","now it should be valid slit.set_params(H=4.) hoomd.run(2) # make sure we can invalidate","mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test","mpcd._mpcd.boundary.no_slip) # change H and also ensure other parameters stay the same slit.set_params(H=2.)","H and also ensure other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V,","we can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles","[-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has y and z velocities flip","it is translating relative to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0:","with self.assertRaises(RuntimeError): hoomd.run(1) # now it should be valid slit.set_params(H=4.) hoomd.run(2) # make","parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\"no_slip\", period=2) # test for setting parameters","raises an error def test_validate_box(self): # initial configuration is invalid slit = mpcd.stream.slit(H=10.)","silently hoomd.run(1) # changing the geometry should still be OK with a run","of lower particle so it is translating relative to wall snap = self.s.take_snapshot()","# take another step, wrapping the second particle through the boundary hoomd.run(1) snap","again, and since it started closer, # it moves relative to original position.","self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) #","Regents of the University of Michigan # This file is part of the","stepping behavior with no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one","be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) # assert an","hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle filler can be attached, removed,","mpcd # unit tests for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self):","released under the BSD 3-Clause License. # Maintainer: mphoward import unittest import numpy","of the HOOMD-blue project, released under the BSD 3-Clause License. # Maintainer: mphoward","period=2) # test for setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.)","[-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where one particle will now hit","it started closer, # it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1],","test_step_slip(self): mpcd.stream.slit(H=4., boundary=\"slip\") # take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank()","test that virtual particle filler can be attached, removed, and updated def test_filler(self):","self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the first particle is matched exactly to","mphoward import unittest import numpy as np import hoomd from hoomd import md","def test_validate_box(self): # initial configuration is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1)","self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler should still allow a run","closer, # it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) #","OK with a run slit.set_params(V=1.0) hoomd.run(1) # changing filler should be allowed slit.set_filler(density=10.,","lower particle so it is translating relative to wall snap = self.s.take_snapshot() if","it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic","test basic stepping behavior with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\"slip\") #","be OK with a run slit.set_params(V=1.0) hoomd.run(1) # changing filler should be allowed","invalid boundary conditions being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\"no_slip\") slit.set_params(boundary=\"slip\") with","np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where one particle will now hit the","should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) # assert","kT=1.0, seed=42, type='B') # assert an error is raised if we set a","0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1)","conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap = self.s.take_snapshot() if","still allow a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del self.s","[4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\"no_slip\", V=1.0, period=3)","mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle filler can","[-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\"no_slip\", V=1.0, period=3) # change velocity of","type='B') # assert an error is raised if we set a bad density","also ensure other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary,","set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler","kT=1.0, seed=42) # removing the filler should still allow a run slit.remove_filler() self.assertTrue(slit._filler","error def test_validate_box(self): # initial configuration is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError):","snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and check bounce back of","4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change","the filler, although this all happens silently hoomd.run(1) # changing the geometry should","2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change","hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test","self.assertRaises(ValueError): slit.set_params(boundary=\"invalid\") # test basic stepping behavior with no slip boundary conditions def","of particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the first","2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1)","set the decomposition in z for mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2)","# take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0],","= mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle filler","particle so it is translating relative to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank()","# change velocity of lower particle so it is translating relative to wall","testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from the starting snapshot snap","slit.set_params(H=4.) hoomd.run(2) # make sure we can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError):","\"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1)","self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(),","through the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85])","# initialization of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler","def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.)","= mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it should be valid slit.set_params(H=4.) hoomd.run(2)","conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\"slip\") # take one step hoomd.run(1) snap = self.s.take_snapshot()","[1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the slit size too","slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\"slip\") # take one step hoomd.run(1) snap","raised if we set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) #","conditions being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\"no_slip\") slit.set_params(boundary=\"slip\") with self.assertRaises(ValueError): slit.set_params(boundary=\"invalid\")","will bounce back in y and z to where it started. # (vx","# same velocity along +x for 3 steps. It will bounce back in","self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.])","hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take","the decomposition in z for mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) #","tests for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the","mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\"slip\")","geometry should still be OK with a run slit.set_params(V=1.0) hoomd.run(1) # changing filler","[-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second particle","and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle","np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the slit size","wall speed, and so it will translate at # same velocity along +x","# changing the geometry should still be OK with a run slit.set_params(V=1.0) hoomd.run(1)","set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\"no_slip\") slit.set_params(boundary=\"slip\") with self.assertRaises(ValueError): slit.set_params(boundary=\"invalid\") # test","test creation can happen (with all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\"no_slip\",","parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.)","stays the same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) #","np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where","if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) #","with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out of bounds can be caught","the wall speed, and so it will translate at # same velocity along","self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\"slip\") self.assertEqual(slit.boundary, \"slip\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for","simulation context hoomd.context.initialize() # set the decomposition in z for mpi builds if","0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\"slip\") self.assertEqual(slit.boundary, \"slip\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test","0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and check bounce back","to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior with","mpcd.stream.slit(H=4.) slit.set_params(boundary=\"no_slip\") slit.set_params(boundary=\"slip\") with self.assertRaises(ValueError): slit.set_params(boundary=\"invalid\") # test basic stepping behavior with no","= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1],","exactly to the wall speed, and so it will translate at # same","to setup the filler, although this all happens silently hoomd.run(1) # changing the","Copyright (c) 2009-2019 The Regents of the University of Michigan # This file","self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle filler can be attached,","test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\"no_slip\", V=1.0, period=3) # change velocity of lower particle so it","vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has","4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also ensure other parameters","y and z velocities flip again, and since it started closer, # it","the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0],","this all happens silently hoomd.run(1) # changing the geometry should still be OK","change H and also ensure other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.)","initialize the system from the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]]","if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) #","hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1],","test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\"no_slip\", period=2) # test for setting parameters def test_set_params(self): slit","self.assertEqual(slit.boundary, \"slip\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary conditions being set def","steps. It will bounce back in y and z to where it started.","np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior with slip boundary conditions def test_step_slip(self):","allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) # assert an error","self.assertTrue(slit._filler is not None) # run should be able to setup the filler,","error is raised if we set a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5.,","= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one","= [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can","slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\"slip\") self.assertEqual(slit.boundary, \"slip\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip)","snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation","still be OK with a run slit.set_params(V=1.0) hoomd.run(1) # changing filler should be","one particle will now hit the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank()","Michigan # This file is part of the HOOMD-blue project, released under the","we set a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') #","self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V,","invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it should be valid","snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run","snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen (with","same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(),","is raised if we set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42)","through the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85])","should still allow a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del","# run one step and check bounce back of particles hoomd.run(1) snap =","[[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen","and since it started closer, # it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1],","raised if we set a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42,","in y and z to where it started. # (vx stays the same,","the slit size too large raises an error def test_validate_box(self): # initial configuration","np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second","= [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen (with all","not None) # run should be able to setup the filler, although this","mpcd.stream.slit(H=4., boundary=\"slip\") # take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() ==","relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior","particle will now hit the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() ==","# it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test","0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\"no_slip\",","configuration is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it should","step, wrapping the second particle through the boundary hoomd.run(1) snap = self.s.take_snapshot() if","\"slip\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary conditions being set def test_bad_boundary(self):","change velocity of lower particle so it is translating relative to wall snap","np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has y and z velocities flip again,","unit tests for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish","md from hoomd import mpcd # unit tests for mpcd slit streaming geometry","the second particle through the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() ==","so it will translate at # same velocity along +x for 3 steps.","particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the first particle","one step and check bounce back of particles hoomd.run(1) snap = self.s.take_snapshot() if","slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip)","project, released under the BSD 3-Clause License. # Maintainer: mphoward import unittest import","file is part of the HOOMD-blue project, released under the BSD 3-Clause License.","slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle","np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\"no_slip\", V=1.0, period=3) # change velocity","wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) #","change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\"slip\") self.assertEqual(slit.boundary, \"slip\")","seed=42, type='B') # assert an error is raised if we set a bad","hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the","with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\"slip\") # take one step hoomd.run(1)","slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler should still allow a run slit.remove_filler()","# the second particle has y and z velocities flip again, and since","# now it should be valid slit.set_params(H=4.) hoomd.run(2) # make sure we can","so it is translating relative to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() ==","Maintainer: mphoward import unittest import numpy as np import hoomd from hoomd import","system from the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] =","[1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where one particle will","matched exactly to the wall speed, and so it will translate at #","another step, wrapping the second particle through the boundary hoomd.run(1) snap = self.s.take_snapshot()","a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler should","be valid slit.set_params(H=4.) hoomd.run(2) # make sure we can invalidate it again slit.set_params(H=10.)","context hoomd.context.initialize() # set the decomposition in z for mpi builds if hoomd.comm.get_num_ranks()","np import hoomd from hoomd import md from hoomd import mpcd # unit","mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it should be valid slit.set_params(H=4.) hoomd.run(2) #","is None) hoomd.run(1) def tearDown(self): del self.s if __name__ == '__main__': unittest.main(argv =","# change H and also ensure other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H,","large raises an error def test_validate_box(self): # initial configuration is invalid slit =","HOOMD-blue project, released under the BSD 3-Clause License. # Maintainer: mphoward import unittest","builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) #","will translate at # same velocity along +x for 3 steps. It will","test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() ==","particle is matched exactly to the wall speed, and so it will translate","np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior with slip boundary conditions","self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also ensure other parameters stay the same","def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\"no_slip\", V=1.0, period=3) # change velocity of lower particle so","0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and","type='A') self.assertTrue(slit._filler is not None) # run should be able to setup the","None) # run should be able to setup the filler, although this all","basic stepping behavior with no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take","take another step, wrapping the second particle through the boundary hoomd.run(1) snap =","snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1)","particle through the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0],","snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap)","mpcd.integrator(dt=0.1) # test creation can happen (with all parameters set) def test_create(self): mpcd.stream.slit(H=4.,","# (vx stays the same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0],","started closer, # it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.])","it should be valid slit.set_params(H=4.) hoomd.run(2) # make sure we can invalidate it","run should be able to setup the filler, although this all happens silently","= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the first particle is matched exactly","0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step,","self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.])","# run should be able to setup the filler, although this all happens","particle has y and z velocities flip again, and since it started closer,","hoomd.run(1) # test that virtual particle filler can be attached, removed, and updated","np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\"no_slip\", V=1.0,","np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where one particle will now","setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\")","slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\"no_slip\") slit.set_params(boundary=\"slip\") with self.assertRaises(ValueError): slit.set_params(boundary=\"invalid\") # test basic stepping behavior","ensure other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\")","removed, and updated def test_filler(self): # initialization of a filler slit = mpcd.stream.slit(H=4.)","will now hit the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0:","self.assertRaises(RuntimeError): hoomd.run(1) # now it should be valid slit.set_params(H=4.) hoomd.run(2) # make sure","= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1],","import unittest import numpy as np import hoomd from hoomd import md from","0.1) # change BCs slit.set_params(boundary=\"slip\") self.assertEqual(slit.boundary, \"slip\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid","the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0],","from the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]]","def setUp(self): # establish the simulation context hoomd.context.initialize() # set the decomposition in","== 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and check bounce","kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) # assert an error is raised","that setting the slit size too large raises an error def test_validate_box(self): #","# Copyright (c) 2009-2019 The Regents of the University of Michigan # This","it will translate at # same velocity along +x for 3 steps. It","slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap =","[-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and check bounce back of particles hoomd.run(1)","test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\"no_slip\") slit.set_params(boundary=\"slip\") with self.assertRaises(ValueError): slit.set_params(boundary=\"invalid\") # test basic stepping","has y and z velocities flip again, and since it started closer, #","and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has y","mpcd.stream.slit(H=4., V=0.1, boundary=\"no_slip\", period=2) # test for setting parameters def test_set_params(self): slit =","should be able to setup the filler, although this all happens silently hoomd.run(1)","numpy as np import hoomd from hoomd import md from hoomd import mpcd","boundary=\"no_slip\", period=2) # test for setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H,","of the University of Michigan # This file is part of the HOOMD-blue","# initial configuration is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now","hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1],","np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\"no_slip\", V=1.0, period=3) # change velocity of lower","for mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0,","from hoomd import mpcd # unit tests for mpcd slit streaming geometry class","slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it should be valid slit.set_params(H=4.)","in z for mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing","[-1.,-1.,-1.]) # take another step where one particle will now hit the wall","slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) # assert an error is","and updated def test_filler(self): # initialization of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5.,","is part of the HOOMD-blue project, released under the BSD 3-Clause License. #","and so it will translate at # same velocity along +x for 3","self.assertTrue(slit._filler is not None) hoomd.run(1) # assert an error is raised if we","np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second particle through the boundary","self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen (with all parameters set)","hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self):","no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap","bounce back in y and z to where it started. # (vx stays","attached, removed, and updated def test_filler(self): # initialization of a filler slit =","snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9])","velocities flip again, and since it started closer, # it moves relative to","if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) #","np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping","stepping behavior with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\"slip\") # take one","an error def test_validate_box(self): # initial configuration is invalid slit = mpcd.stream.slit(H=10.) with","for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation","happen (with all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\"no_slip\", period=2) # test","the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.)","hoomd.run(1) # changing filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not","= mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) #","seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) # assert an error is raised if","2009-2019 The Regents of the University of Michigan # This file is part","hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1],","it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out of bounds","mpcd.stream.slit(H=4., boundary=\"no_slip\", V=1.0, period=3) # change velocity of lower particle so it is","np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\"no_slip\", V=1.0, period=3) #","None) hoomd.run(1) def tearDown(self): del self.s if __name__ == '__main__': unittest.main(argv = ['test.py',","(c) 2009-2019 The Regents of the University of Michigan # This file is","unittest import numpy as np import hoomd from hoomd import md from hoomd","np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the slit size too large raises an","starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s =","the BSD 3-Clause License. # Maintainer: mphoward import unittest import numpy as np","self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out of bounds can be caught def","period=3) # change velocity of lower particle so it is translating relative to","self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) #","relative to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.]","run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del self.s if __name__ ==","caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test","This file is part of the HOOMD-blue project, released under the BSD 3-Clause","out of bounds can be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError):","hoomd import md from hoomd import mpcd # unit tests for mpcd slit","bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an error","hoomd.run(1) # test that particles out of bounds can be caught def test_out_of_bounds(self):","test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(),","mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen (with all parameters set) def test_create(self):","(with all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\"no_slip\", period=2) # test for","z velocities flip again, and since it started closer, # it moves relative","for 3 steps. It will bounce back in y and z to where","along +x for 3 steps. It will bounce back in y and z","self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.])","that particles out of bounds can be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8)","# change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\"slip\") self.assertEqual(slit.boundary,","if hoomd.comm.get_rank() == 0: # the first particle is matched exactly to the","being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\"no_slip\") slit.set_params(boundary=\"slip\") with self.assertRaises(ValueError): slit.set_params(boundary=\"invalid\") #","[-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the","= mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None) # run should","slit.set_params(boundary=\"no_slip\") slit.set_params(boundary=\"slip\") with self.assertRaises(ValueError): slit.set_params(boundary=\"invalid\") # test basic stepping behavior with no slip","test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual","hoomd.run(1) # now it should be valid slit.set_params(H=4.) hoomd.run(2) # make sure we","hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from the starting snapshot snap = mpcd.data.make_snapshot(N=2)","check bounce back of particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0:","= mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(),","hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the first particle is","slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle filler can be attached, removed, and","velocity of lower particle so it is translating relative to wall snap =","can be attached, removed, and updated def test_filler(self): # initialization of a filler","streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation context hoomd.context.initialize() #","slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del self.s if __name__ == '__main__':","allow a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del self.s if","test basic stepping behavior with no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) #","particles out of bounds can be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with","hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1],","self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V","[1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\"no_slip\", V=1.0, period=3) # change velocity of lower particle","to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap)","an error is raised if we set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0,","[-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where one","= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1],","1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from","not None) hoomd.run(1) # assert an error is raised if we set a","and check bounce back of particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() ==","wrapping the second particle through the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank()","if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def","def test_filler(self): # initialization of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42,","with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an error is raised if","bounce back of particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: #","box=hoomd.data.boxdim(L=10.))) # initialize the system from the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:]","the filler should still allow a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def","hoomd from hoomd import md from hoomd import mpcd # unit tests for","snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0])","class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation context hoomd.context.initialize() # set the","[[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen (with all parameters","import hoomd from hoomd import md from hoomd import mpcd # unit tests","able to setup the filler, although this all happens silently hoomd.run(1) # changing","decomposition in z for mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default","test for invalid boundary conditions being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\"no_slip\")","original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior with slip","from hoomd import md from hoomd import mpcd # unit tests for mpcd","if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) #","make sure we can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test","(vx stays the same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.])","snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the first particle is matched","hit the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95])","# test basic stepping behavior with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\"slip\")","of Michigan # This file is part of the HOOMD-blue project, released under","self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also ensure other parameters stay","# take another step where one particle will now hit the wall hoomd.run(1)","mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation context hoomd.context.initialize() # set the decomposition","all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\"no_slip\", period=2) # test for setting","= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1],","hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1],","with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle filler can be","wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.])","slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an error is raised if we set","self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs","# test for setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V,","mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation context","University of Michigan # This file is part of the HOOMD-blue project, released","import numpy as np import hoomd from hoomd import md from hoomd import","set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\"no_slip\", period=2) # test for setting parameters def","mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip)","z to where it started. # (vx stays the same, and vy and","and z velocities flip again, and since it started closer, # it moves","= mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen (with all parameters set) def","as np import hoomd from hoomd import md from hoomd import mpcd #","be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) #","configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from the starting snapshot snap =","for setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary,","[-1.,-1.,1.]) # test that setting the slit size too large raises an error","a run slit.set_params(V=1.0) hoomd.run(1) # changing filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7)","License. # Maintainer: mphoward import unittest import numpy as np import hoomd from","self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also ensure other","behavior with no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step","filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) #","boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap = self.s.take_snapshot()","the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0],","velocity along +x for 3 steps. It will bounce back in y and","hoomd.comm.get_rank() == 0: # the first particle is matched exactly to the wall","snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0])","np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second","change BCs slit.set_params(boundary=\"slip\") self.assertEqual(slit.boundary, \"slip\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary conditions","a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del self.s if __name__","V=1.0, period=3) # change velocity of lower particle so it is translating relative","test for setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.)","the system from the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:]","first particle is matched exactly to the wall speed, and so it will","position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior with slip boundary","hoomd.run(2) # make sure we can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1)","be able to setup the filler, although this all happens silently hoomd.run(1) #","should be valid slit.set_params(H=4.) hoomd.run(2) # make sure we can invalidate it again","import md from hoomd import mpcd # unit tests for mpcd slit streaming","the same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the"],"string":"[\n \"same velocity along +x for 3 steps. It will bounce back in y\",\n \"self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) #\",\n \"# test that virtual particle filler can be attached, removed, and updated def\",\n \"# test basic stepping behavior with no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.)\",\n \"[1.,1.,-1.]) # the second particle has y and z velocities flip again, and\",\n \"V=0.1, boundary=\\\"no_slip\\\", period=2) # test for setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.)\",\n \"boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.])\",\n \"the HOOMD-blue project, released under the BSD 3-Clause License. # Maintainer: mphoward import\",\n \"since it started closer, # it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9])\",\n \"take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95])\",\n \"the second particle has y and z velocities flip again, and since it\",\n \"= [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and check bounce back of particles\",\n \"[-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\\\"no_slip\\\", V=1.0, period=3) # change\",\n \"def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\\\"no_slip\\\", period=2) # test for setting parameters def test_set_params(self):\",\n \"self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.])\",\n \"virtual particle filler can be attached, removed, and updated def test_filler(self): # initialization\",\n \"is not None) # run should be able to setup the filler, although\",\n \"None) hoomd.run(1) # assert an error is raised if we set a bad\",\n \"self.s.restore_snapshot(snap) # run one step and check bounce back of particles hoomd.run(1) snap\",\n \"it started. # (vx stays the same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0],\",\n \"self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an error is raised if we\",\n \"hoomd.run(1) def tearDown(self): del self.s if __name__ == '__main__': unittest.main(argv = ['test.py', '-v'])\",\n \"# set the decomposition in z for mpi builds if hoomd.comm.get_num_ranks() > 1:\",\n \"test_validate_box(self): # initial configuration is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) #\",\n \"an error is raised if we set a bad particle type with self.assertRaises(RuntimeError):\",\n \"slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.)\",\n \"> 1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system\",\n \"valid slit.set_params(H=4.) hoomd.run(2) # make sure we can invalidate it again slit.set_params(H=10.) with\",\n \"back in y and z to where it started. # (vx stays the\",\n \"np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where one particle\",\n \"setting the slit size too large raises an error def test_validate_box(self): # initial\",\n \"[-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior with slip boundary conditions def\",\n \"= mpcd.stream.slit(H=4.) slit.set_params(boundary=\\\"no_slip\\\") slit.set_params(boundary=\\\"slip\\\") with self.assertRaises(ValueError): slit.set_params(boundary=\\\"invalid\\\") # test basic stepping behavior with\",\n \"mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0:\",\n \"The Regents of the University of Michigan # This file is part of\",\n \"invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out of\",\n \"step where one particle will now hit the wall hoomd.run(1) snap = self.s.take_snapshot()\",\n \"[-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the slit\",\n \"hoomd.context.initialize() # set the decomposition in z for mpi builds if hoomd.comm.get_num_ranks() >\",\n \"= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1],\",\n \"to the wall speed, and so it will translate at # same velocity\",\n \"0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting\",\n \"slit.set_params(boundary=\\\"invalid\\\") # test basic stepping behavior with no slip boundary conditions def test_step_noslip(self):\",\n \"hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take\",\n \"can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out\",\n \"behavior with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\\\"slip\\\") # take one step\",\n \"sure we can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that\",\n \"[1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second particle\",\n \"that virtual particle filler can be attached, removed, and updated def test_filler(self): #\",\n \"3-Clause License. # Maintainer: mphoward import unittest import numpy as np import hoomd\",\n \"0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also ensure other parameters stay the\",\n \"0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step\",\n \"the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0],\",\n \"np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the slit size too large\",\n \"second particle through the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0:\",\n \"\\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also ensure\",\n \"# test that setting the slit size too large raises an error def\",\n \"filler, although this all happens silently hoomd.run(1) # changing the geometry should still\",\n \"test that particles out of bounds can be caught def test_out_of_bounds(self): slit =\",\n \"== 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another\",\n \"flip again, and since it started closer, # it moves relative to original\",\n \"0: # the first particle is matched exactly to the wall speed, and\",\n \"the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s\",\n \"== 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another\",\n \"step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.])\",\n \"y and z to where it started. # (vx stays the same, and\",\n \"kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None) # run should be able to\",\n \"mpcd._mpcd.boundary.slip) # test for invalid boundary conditions being set def test_bad_boundary(self): slit =\",\n \"step and check bounce back of particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank()\",\n \"import mpcd # unit tests for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def\",\n \"the first particle is matched exactly to the wall speed, and so it\",\n \"test_filler(self): # initialization of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A')\",\n \"particle filler can be attached, removed, and updated def test_filler(self): # initialization of\",\n \"at # same velocity along +x for 3 steps. It will bounce back\",\n \"is matched exactly to the wall speed, and so it will translate at\",\n \"to where it started. # (vx stays the same, and vy and vz\",\n \"creation can happen (with all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\\\"no_slip\\\", period=2)\",\n \"# This file is part of the HOOMD-blue project, released under the BSD\",\n \"can be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1)\",\n \"run one step and check bounce back of particles hoomd.run(1) snap = self.s.take_snapshot()\",\n \"of bounds can be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1)\",\n \"we set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the\",\n \"slit.set_params(boundary=\\\"slip\\\") self.assertEqual(slit.boundary, \\\"slip\\\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary conditions being set\",\n \"self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.])\",\n \"<reponame>schwendp/hoomd-blue # Copyright (c) 2009-2019 The Regents of the University of Michigan #\",\n \"# the first particle is matched exactly to the wall speed, and so\",\n \"def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that\",\n \"moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping\",\n \"self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H\",\n \"[-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the\",\n \"slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out of bounds can be\",\n \"setUp(self): # establish the simulation context hoomd.context.initialize() # set the decomposition in z\",\n \"BSD 3-Clause License. # Maintainer: mphoward import unittest import numpy as np import\",\n \"self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step\",\n \"establish the simulation context hoomd.context.initialize() # set the decomposition in z for mpi\",\n \"filler should still allow a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self):\",\n \"started. # (vx stays the same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85])\",\n \"self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\\\"slip\\\") self.assertEqual(slit.boundary, \\\"slip\\\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) #\",\n \"type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an error is raised\",\n \"if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and\",\n \"seed=42, type='A') self.assertTrue(slit._filler is not None) # run should be able to setup\",\n \"slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None) # run\",\n \"# unit tests for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): #\",\n \"one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0],\",\n \"np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has y and z velocities\",\n \"filler can be attached, removed, and updated def test_filler(self): # initialization of a\",\n \"size too large raises an error def test_validate_box(self): # initial configuration is invalid\",\n \"boundary conditions being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\\\"no_slip\\\") slit.set_params(boundary=\\\"slip\\\") with self.assertRaises(ValueError):\",\n \"particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an error is\",\n \"initial configuration is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it\",\n \"slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation context hoomd.context.initialize()\",\n \"boundary=\\\"slip\\\") # take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0:\",\n \"slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None) # run should be able\",\n \"although this all happens silently hoomd.run(1) # changing the geometry should still be\",\n \"assert an error is raised if we set a bad particle type with\",\n \"test that setting the slit size too large raises an error def test_validate_box(self):\",\n \"[0.,1.,1.]) # test basic stepping behavior with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4.,\",\n \"slit.set_params(V=1.0) hoomd.run(1) # changing filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is\",\n \"is raised if we set a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0,\",\n \"translating relative to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] =\",\n \"3 steps. It will bounce back in y and z to where it\",\n \"hoomd.run(1) # changing the geometry should still be OK with a run slit.set_params(V=1.0)\",\n \"boundary=\\\"no_slip\\\", V=1.0, period=3) # change velocity of lower particle so it is translating\",\n \"self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del self.s if __name__ == '__main__': unittest.main(argv\",\n \"default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from the starting snapshot\",\n \"self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary conditions being set def test_bad_boundary(self): slit\",\n \"np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the\",\n \"np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second particle through\",\n \"boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\\\"slip\\\") # take one step hoomd.run(1) snap =\",\n \"of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not\",\n \"for invalid boundary conditions being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\\\"no_slip\\\") slit.set_params(boundary=\\\"slip\\\")\",\n \"# assert an error is raised if we set a bad particle type\",\n \"back of particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the\",\n \"== 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another\",\n \"be attached, removed, and updated def test_filler(self): # initialization of a filler slit\",\n \"with a run slit.set_params(V=1.0) hoomd.run(1) # changing filler should be allowed slit.set_filler(density=10., kT=1.5,\",\n \"error is raised if we set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0,\",\n \"same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second\",\n \"mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.)))\",\n \"another step where one particle will now hit the wall hoomd.run(1) snap =\",\n \"+x for 3 steps. It will bounce back in y and z to\",\n \"take another step where one particle will now hit the wall hoomd.run(1) snap\",\n \"is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it should be\",\n \"removing the filler should still allow a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1)\",\n \"hit the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95])\",\n \"should still be OK with a run slit.set_params(V=1.0) hoomd.run(1) # changing filler should\",\n \"== 0: # the first particle is matched exactly to the wall speed,\",\n \"the simulation context hoomd.context.initialize() # set the decomposition in z for mpi builds\",\n \"with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler should still allow a\",\n \"seed=42) # removing the filler should still allow a run slit.remove_filler() self.assertTrue(slit._filler is\",\n \"set a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert\",\n \"now hit the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0],\",\n \"# test creation can happen (with all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1,\",\n \"It will bounce back in y and z to where it started. #\",\n \"with self.assertRaises(ValueError): slit.set_params(boundary=\\\"invalid\\\") # test basic stepping behavior with no slip boundary conditions\",\n \"too large raises an error def test_validate_box(self): # initial configuration is invalid slit\",\n \"geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation context hoomd.context.initialize() # set\",\n \"setup the filler, although this all happens silently hoomd.run(1) # changing the geometry\",\n \"if we set a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B')\",\n \"other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(),\",\n \"# changing filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None)\",\n \"# change BCs slit.set_params(boundary=\\\"slip\\\") self.assertEqual(slit.boundary, \\\"slip\\\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary\",\n \"mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None) # run should be\",\n \"changing the geometry should still be OK with a run slit.set_params(V=1.0) hoomd.run(1) #\",\n \"a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an\",\n \"0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change\",\n \"is translating relative to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1]\",\n \"hoomd import mpcd # unit tests for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase):\",\n \"# test that particles out of bounds can be caught def test_out_of_bounds(self): slit\",\n \"a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None)\",\n \"is not None) hoomd.run(1) # assert an error is raised if we set\",\n \"z for mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing configuration\",\n \"# default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from the starting\",\n \"can happen (with all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\\\"no_slip\\\", period=2) #\",\n \"where one particle will now hit the wall hoomd.run(1) snap = self.s.take_snapshot() if\",\n \"hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take\",\n \"np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping\",\n \"updated def test_filler(self): # initialization of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0,\",\n \"basic stepping behavior with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\\\"slip\\\") # take\",\n \"happens silently hoomd.run(1) # changing the geometry should still be OK with a\",\n \"V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\\\"slip\\\") self.assertEqual(slit.boundary, \\\"slip\\\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(),\",\n \"the geometry should still be OK with a run slit.set_params(V=1.0) hoomd.run(1) # changing\",\n \"under the BSD 3-Clause License. # Maintainer: mphoward import unittest import numpy as\",\n \"where it started. # (vx stays the same, and vy and vz flip.)\",\n \"parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(),\",\n \"snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9])\",\n \"initialization of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is\",\n \"# make sure we can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) #\",\n \"# initialize the system from the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] =\",\n \"slit size too large raises an error def test_validate_box(self): # initial configuration is\",\n \"flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has y and z\",\n \"boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.])\",\n \"# assert an error is raised if we set a bad density with\",\n \"stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(),\",\n \"vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has y and\",\n \"== 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4.,\",\n \"wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.])\",\n \"# establish the simulation context hoomd.context.initialize() # set the decomposition in z for\",\n \"# Maintainer: mphoward import unittest import numpy as np import hoomd from hoomd\",\n \"speed, and so it will translate at # same velocity along +x for\",\n \"run slit.set_params(V=1.0) hoomd.run(1) # changing filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler\",\n \"bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler should still\",\n \"and also ensure other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.)\",\n \"assert an error is raised if we set a bad density with self.assertRaises(RuntimeError):\",\n \"part of the HOOMD-blue project, released under the BSD 3-Clause License. # Maintainer:\",\n \"def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\\\"no_slip\\\") slit.set_params(boundary=\\\"slip\\\") with self.assertRaises(ValueError): slit.set_params(boundary=\\\"invalid\\\") # test basic\",\n \"translate at # same velocity along +x for 3 steps. It will bounce\",\n \"filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None) #\",\n \"if we set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing\",\n \"def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank()\",\n \"[-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second particle through the\",\n \"again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out of bounds can\",\n \"def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\\\"slip\\\") # take one step hoomd.run(1) snap = self.s.take_snapshot() if\",\n \"the University of Michigan # This file is part of the HOOMD-blue project,\",\n \"all happens silently hoomd.run(1) # changing the geometry should still be OK with\",\n \"changing filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1)\",\n \"self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also\",\n \"[-1.,-1.,-1.]) # take another step, wrapping the second particle through the boundary hoomd.run(1)\",\n \"BCs slit.set_params(boundary=\\\"slip\\\") self.assertEqual(slit.boundary, \\\"slip\\\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary conditions being\",\n \"hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from the\",\n \"hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and check\",\n \"bounds can be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85)\",\n \"slit.set_params(boundary=\\\"slip\\\") with self.assertRaises(ValueError): slit.set_params(boundary=\\\"invalid\\\") # test basic stepping behavior with no slip boundary\",\n \"with no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1)\",\n \"# removing the filler should still allow a run slit.remove_filler() self.assertTrue(slit._filler is None)\",\n \"density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler should still allow\",\n \"second particle has y and z velocities flip again, and since it started\",\n \"== 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that\",\n \"and z to where it started. # (vx stays the same, and vy\",\n \"0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step,\",\n \"snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9])\",\n \"if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize\",\n \"# test for invalid boundary conditions being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.)\",\n \"[-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the slit size too large raises\",\n \"hoomd.run(1) # assert an error is raised if we set a bad particle\",\n \"now it should be valid slit.set_params(H=4.) hoomd.run(2) # make sure we can invalidate\",\n \"mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test\",\n \"mpcd._mpcd.boundary.no_slip) # change H and also ensure other parameters stay the same slit.set_params(H=2.)\",\n \"H and also ensure other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V,\",\n \"we can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles\",\n \"[-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has y and z velocities flip\",\n \"it is translating relative to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0:\",\n \"with self.assertRaises(RuntimeError): hoomd.run(1) # now it should be valid slit.set_params(H=4.) hoomd.run(2) # make\",\n \"parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\\\"no_slip\\\", period=2) # test for setting parameters\",\n \"raises an error def test_validate_box(self): # initial configuration is invalid slit = mpcd.stream.slit(H=10.)\",\n \"silently hoomd.run(1) # changing the geometry should still be OK with a run\",\n \"of lower particle so it is translating relative to wall snap = self.s.take_snapshot()\",\n \"# take another step, wrapping the second particle through the boundary hoomd.run(1) snap\",\n \"again, and since it started closer, # it moves relative to original position.\",\n \"self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) #\",\n \"Regents of the University of Michigan # This file is part of the\",\n \"stepping behavior with no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one\",\n \"be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) # assert an\",\n \"hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle filler can be attached, removed,\",\n \"mpcd # unit tests for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self):\",\n \"released under the BSD 3-Clause License. # Maintainer: mphoward import unittest import numpy\",\n \"of the HOOMD-blue project, released under the BSD 3-Clause License. # Maintainer: mphoward\",\n \"period=2) # test for setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.)\",\n \"[-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where one particle will now hit\",\n \"it started closer, # it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1],\",\n \"test_step_slip(self): mpcd.stream.slit(H=4., boundary=\\\"slip\\\") # take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank()\",\n \"test that virtual particle filler can be attached, removed, and updated def test_filler(self):\",\n \"self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the first particle is matched exactly to\",\n \"mphoward import unittest import numpy as np import hoomd from hoomd import md\",\n \"def test_validate_box(self): # initial configuration is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1)\",\n \"self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler should still allow a run\",\n \"closer, # it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) #\",\n \"OK with a run slit.set_params(V=1.0) hoomd.run(1) # changing filler should be allowed slit.set_filler(density=10.,\",\n \"lower particle so it is translating relative to wall snap = self.s.take_snapshot() if\",\n \"it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic\",\n \"test basic stepping behavior with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\\\"slip\\\") #\",\n \"be OK with a run slit.set_params(V=1.0) hoomd.run(1) # changing filler should be allowed\",\n \"invalid boundary conditions being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\\\"no_slip\\\") slit.set_params(boundary=\\\"slip\\\") with\",\n \"np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where one particle will now hit the\",\n \"should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) # assert\",\n \"kT=1.0, seed=42, type='B') # assert an error is raised if we set a\",\n \"0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1)\",\n \"conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap = self.s.take_snapshot() if\",\n \"still allow a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del self.s\",\n \"[4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\\\"no_slip\\\", V=1.0, period=3)\",\n \"mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle filler can\",\n \"[-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\\\"no_slip\\\", V=1.0, period=3) # change velocity of\",\n \"type='B') # assert an error is raised if we set a bad density\",\n \"also ensure other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary,\",\n \"set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler\",\n \"kT=1.0, seed=42) # removing the filler should still allow a run slit.remove_filler() self.assertTrue(slit._filler\",\n \"error def test_validate_box(self): # initial configuration is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError):\",\n \"snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and check bounce back of\",\n \"4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change\",\n \"the filler, although this all happens silently hoomd.run(1) # changing the geometry should\",\n \"2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change\",\n \"hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test\",\n \"self.assertRaises(ValueError): slit.set_params(boundary=\\\"invalid\\\") # test basic stepping behavior with no slip boundary conditions def\",\n \"of particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the first\",\n \"2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1)\",\n \"set the decomposition in z for mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2)\",\n \"# take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0],\",\n \"= mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle filler\",\n \"particle so it is translating relative to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank()\",\n \"# change velocity of lower particle so it is translating relative to wall\",\n \"testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from the starting snapshot snap\",\n \"slit.set_params(H=4.) hoomd.run(2) # make sure we can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError):\",\n \"\\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1)\",\n \"self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(),\",\n \"through the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85])\",\n \"# initialization of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler\",\n \"def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.)\",\n \"= mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it should be valid slit.set_params(H=4.) hoomd.run(2)\",\n \"conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\\\"slip\\\") # take one step hoomd.run(1) snap = self.s.take_snapshot()\",\n \"[1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the slit size too\",\n \"slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\\\"slip\\\") # take one step hoomd.run(1) snap\",\n \"raised if we set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) #\",\n \"conditions being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\\\"no_slip\\\") slit.set_params(boundary=\\\"slip\\\") with self.assertRaises(ValueError): slit.set_params(boundary=\\\"invalid\\\")\",\n \"will bounce back in y and z to where it started. # (vx\",\n \"# same velocity along +x for 3 steps. It will bounce back in\",\n \"self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.])\",\n \"hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take\",\n \"the decomposition in z for mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) #\",\n \"tests for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the\",\n \"mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\\\"slip\\\")\",\n \"geometry should still be OK with a run slit.set_params(V=1.0) hoomd.run(1) # changing filler\",\n \"[-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second particle\",\n \"and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle\",\n \"np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the slit size\",\n \"wall speed, and so it will translate at # same velocity along +x\",\n \"# changing the geometry should still be OK with a run slit.set_params(V=1.0) hoomd.run(1)\",\n \"set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\\\"no_slip\\\") slit.set_params(boundary=\\\"slip\\\") with self.assertRaises(ValueError): slit.set_params(boundary=\\\"invalid\\\") # test\",\n \"test creation can happen (with all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\\\"no_slip\\\",\",\n \"parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.)\",\n \"stays the same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) #\",\n \"np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where\",\n \"if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) #\",\n \"with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out of bounds can be caught\",\n \"the wall speed, and so it will translate at # same velocity along\",\n \"self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\\\"slip\\\") self.assertEqual(slit.boundary, \\\"slip\\\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for\",\n \"simulation context hoomd.context.initialize() # set the decomposition in z for mpi builds if\",\n \"0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\\\"slip\\\") self.assertEqual(slit.boundary, \\\"slip\\\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test\",\n \"0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and check bounce back\",\n \"to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior with\",\n \"mpcd.stream.slit(H=4.) slit.set_params(boundary=\\\"no_slip\\\") slit.set_params(boundary=\\\"slip\\\") with self.assertRaises(ValueError): slit.set_params(boundary=\\\"invalid\\\") # test basic stepping behavior with no\",\n \"= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1],\",\n \"exactly to the wall speed, and so it will translate at # same\",\n \"to setup the filler, although this all happens silently hoomd.run(1) # changing the\",\n \"Copyright (c) 2009-2019 The Regents of the University of Michigan # This file\",\n \"self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle filler can be attached,\",\n \"test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\\\"no_slip\\\", V=1.0, period=3) # change velocity of lower particle so it\",\n \"vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has\",\n \"4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also ensure other parameters\",\n \"y and z velocities flip again, and since it started closer, # it\",\n \"the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0],\",\n \"this all happens silently hoomd.run(1) # changing the geometry should still be OK\",\n \"change H and also ensure other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.)\",\n \"initialize the system from the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]]\",\n \"if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) #\",\n \"hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1],\",\n \"test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\\\"no_slip\\\", period=2) # test for setting parameters def test_set_params(self): slit\",\n \"self.assertEqual(slit.boundary, \\\"slip\\\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary conditions being set def\",\n \"steps. It will bounce back in y and z to where it started.\",\n \"np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior with slip boundary conditions def test_step_slip(self):\",\n \"allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) # assert an error\",\n \"self.assertTrue(slit._filler is not None) # run should be able to setup the filler,\",\n \"error is raised if we set a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5.,\",\n \"= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one\",\n \"= [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can\",\n \"slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\\\"slip\\\") self.assertEqual(slit.boundary, \\\"slip\\\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip)\",\n \"snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation\",\n \"still be OK with a run slit.set_params(V=1.0) hoomd.run(1) # changing filler should be\",\n \"one particle will now hit the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank()\",\n \"Michigan # This file is part of the HOOMD-blue project, released under the\",\n \"we set a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') #\",\n \"self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V,\",\n \"invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it should be valid\",\n \"snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run\",\n \"snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen (with\",\n \"same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(),\",\n \"is raised if we set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42)\",\n \"through the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85])\",\n \"should still allow a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del\",\n \"# run one step and check bounce back of particles hoomd.run(1) snap =\",\n \"[[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen\",\n \"and since it started closer, # it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1],\",\n \"raised if we set a bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42,\",\n \"in y and z to where it started. # (vx stays the same,\",\n \"the slit size too large raises an error def test_validate_box(self): # initial configuration\",\n \"np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second\",\n \"= [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen (with all\",\n \"not None) # run should be able to setup the filler, although this\",\n \"mpcd.stream.slit(H=4., boundary=\\\"slip\\\") # take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() ==\",\n \"relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior\",\n \"particle will now hit the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() ==\",\n \"# it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test\",\n \"0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\\\"no_slip\\\",\",\n \"configuration is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it should\",\n \"step, wrapping the second particle through the boundary hoomd.run(1) snap = self.s.take_snapshot() if\",\n \"\\\"slip\\\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary conditions being set def test_bad_boundary(self):\",\n \"change velocity of lower particle so it is translating relative to wall snap\",\n \"np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has y and z velocities flip again,\",\n \"unit tests for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish\",\n \"md from hoomd import mpcd # unit tests for mpcd slit streaming geometry\",\n \"the second particle through the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() ==\",\n \"so it will translate at # same velocity along +x for 3 steps.\",\n \"particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the first particle\",\n \"one step and check bounce back of particles hoomd.run(1) snap = self.s.take_snapshot() if\",\n \"slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip)\",\n \"project, released under the BSD 3-Clause License. # Maintainer: mphoward import unittest import\",\n \"file is part of the HOOMD-blue project, released under the BSD 3-Clause License.\",\n \"slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle\",\n \"np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\\\"no_slip\\\", V=1.0, period=3) # change velocity\",\n \"wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) #\",\n \"change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\\\"slip\\\") self.assertEqual(slit.boundary, \\\"slip\\\")\",\n \"seed=42, type='B') # assert an error is raised if we set a bad\",\n \"hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the\",\n \"with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\\\"slip\\\") # take one step hoomd.run(1)\",\n \"slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler should still allow a run slit.remove_filler()\",\n \"# the second particle has y and z velocities flip again, and since\",\n \"# now it should be valid slit.set_params(H=4.) hoomd.run(2) # make sure we can\",\n \"so it is translating relative to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() ==\",\n \"Maintainer: mphoward import unittest import numpy as np import hoomd from hoomd import\",\n \"system from the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] =\",\n \"[1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where one particle will\",\n \"matched exactly to the wall speed, and so it will translate at #\",\n \"another step, wrapping the second particle through the boundary hoomd.run(1) snap = self.s.take_snapshot()\",\n \"a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0, kT=1.0, seed=42) # removing the filler should\",\n \"be valid slit.set_params(H=4.) hoomd.run(2) # make sure we can invalidate it again slit.set_params(H=10.)\",\n \"context hoomd.context.initialize() # set the decomposition in z for mpi builds if hoomd.comm.get_num_ranks()\",\n \"np import hoomd from hoomd import md from hoomd import mpcd # unit\",\n \"mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it should be valid slit.set_params(H=4.) hoomd.run(2) #\",\n \"is None) hoomd.run(1) def tearDown(self): del self.s if __name__ == '__main__': unittest.main(argv =\",\n \"# change H and also ensure other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H,\",\n \"large raises an error def test_validate_box(self): # initial configuration is invalid slit =\",\n \"HOOMD-blue project, released under the BSD 3-Clause License. # Maintainer: mphoward import unittest\",\n \"builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) #\",\n \"will translate at # same velocity along +x for 3 steps. It will\",\n \"test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() ==\",\n \"particle is matched exactly to the wall speed, and so it will translate\",\n \"np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior with slip boundary conditions\",\n \"self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also ensure other parameters stay the same\",\n \"def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\\\"no_slip\\\", V=1.0, period=3) # change velocity of lower particle so\",\n \"0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and\",\n \"type='A') self.assertTrue(slit._filler is not None) # run should be able to setup the\",\n \"None) # run should be able to setup the filler, although this all\",\n \"basic stepping behavior with no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take\",\n \"take another step, wrapping the second particle through the boundary hoomd.run(1) snap =\",\n \"snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1)\",\n \"particle through the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0],\",\n \"snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap)\",\n \"mpcd.integrator(dt=0.1) # test creation can happen (with all parameters set) def test_create(self): mpcd.stream.slit(H=4.,\",\n \"# (vx stays the same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0],\",\n \"started closer, # it moves relative to original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.])\",\n \"it should be valid slit.set_params(H=4.) hoomd.run(2) # make sure we can invalidate it\",\n \"run should be able to setup the filler, although this all happens silently\",\n \"= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the first particle is matched exactly\",\n \"0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step,\",\n \"self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.])\",\n \"# run should be able to setup the filler, although this all happens\",\n \"particle has y and z velocities flip again, and since it started closer,\",\n \"hoomd.run(1) # test that virtual particle filler can be attached, removed, and updated\",\n \"np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\\\"no_slip\\\", V=1.0,\",\n \"np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where one particle will now\",\n \"setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\")\",\n \"slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\\\"no_slip\\\") slit.set_params(boundary=\\\"slip\\\") with self.assertRaises(ValueError): slit.set_params(boundary=\\\"invalid\\\") # test basic stepping behavior\",\n \"ensure other parameters stay the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\")\",\n \"removed, and updated def test_filler(self): # initialization of a filler slit = mpcd.stream.slit(H=4.)\",\n \"will now hit the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0:\",\n \"self.assertRaises(RuntimeError): hoomd.run(1) # now it should be valid slit.set_params(H=4.) hoomd.run(2) # make sure\",\n \"= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1],\",\n \"import unittest import numpy as np import hoomd from hoomd import md from\",\n \"0.1) # change BCs slit.set_params(boundary=\\\"slip\\\") self.assertEqual(slit.boundary, \\\"slip\\\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid\",\n \"the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0],\",\n \"from the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]]\",\n \"def setUp(self): # establish the simulation context hoomd.context.initialize() # set the decomposition in\",\n \"== 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and check bounce\",\n \"kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) # assert an error is raised\",\n \"that setting the slit size too large raises an error def test_validate_box(self): #\",\n \"# Copyright (c) 2009-2019 The Regents of the University of Michigan # This\",\n \"it will translate at # same velocity along +x for 3 steps. It\",\n \"slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap =\",\n \"[-2.,-1.,-1.] self.s.restore_snapshot(snap) # run one step and check bounce back of particles hoomd.run(1)\",\n \"test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\\\"no_slip\\\") slit.set_params(boundary=\\\"slip\\\") with self.assertRaises(ValueError): slit.set_params(boundary=\\\"invalid\\\") # test basic stepping\",\n \"has y and z velocities flip again, and since it started closer, #\",\n \"and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the second particle has y\",\n \"mpcd.stream.slit(H=4., V=0.1, boundary=\\\"no_slip\\\", period=2) # test for setting parameters def test_set_params(self): slit =\",\n \"should be able to setup the filler, although this all happens silently hoomd.run(1)\",\n \"numpy as np import hoomd from hoomd import md from hoomd import mpcd\",\n \"boundary=\\\"no_slip\\\", period=2) # test for setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H,\",\n \"of the University of Michigan # This file is part of the HOOMD-blue\",\n \"# initial configuration is invalid slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now\",\n \"hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1],\",\n \"np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\\\"no_slip\\\", V=1.0, period=3) # change velocity of lower\",\n \"for mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0,\",\n \"from hoomd import mpcd # unit tests for mpcd slit streaming geometry class\",\n \"slit = mpcd.stream.slit(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # now it should be valid slit.set_params(H=4.)\",\n \"in z for mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default testing\",\n \"[-1.,-1.,-1.]) # take another step where one particle will now hit the wall\",\n \"slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) # assert an error is\",\n \"and updated def test_filler(self): # initialization of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5.,\",\n \"is part of the HOOMD-blue project, released under the BSD 3-Clause License. #\",\n \"and so it will translate at # same velocity along +x for 3\",\n \"self.assertTrue(slit._filler is not None) hoomd.run(1) # assert an error is raised if we\",\n \"np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second particle through the boundary\",\n \"self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen (with all parameters set)\",\n \"hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self):\",\n \"no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap\",\n \"bounce back in y and z to where it started. # (vx stays\",\n \"attached, removed, and updated def test_filler(self): # initialization of a filler slit =\",\n \"snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9])\",\n \"velocities flip again, and since it started closer, # it moves relative to\",\n \"if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) #\",\n \"np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping\",\n \"stepping behavior with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\\\"slip\\\") # take one\",\n \"an error def test_validate_box(self): # initial configuration is invalid slit = mpcd.stream.slit(H=10.) with\",\n \"for mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation\",\n \"happen (with all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\\\"no_slip\\\", period=2) # test\",\n \"the same slit.set_params(H=2.) self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.)\",\n \"hoomd.run(1) # changing filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not\",\n \"= mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) #\",\n \"seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) # assert an error is raised if\",\n \"2009-2019 The Regents of the University of Michigan # This file is part\",\n \"hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1],\",\n \"it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out of bounds\",\n \"mpcd.stream.slit(H=4., boundary=\\\"no_slip\\\", V=1.0, period=3) # change velocity of lower particle so it is\",\n \"np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\\\"no_slip\\\", V=1.0, period=3) #\",\n \"None) hoomd.run(1) def tearDown(self): del self.s if __name__ == '__main__': unittest.main(argv = ['test.py',\",\n \"(c) 2009-2019 The Regents of the University of Michigan # This file is\",\n \"unittest import numpy as np import hoomd from hoomd import md from hoomd\",\n \"np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) # test that setting the slit size too large raises an\",\n \"starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:] = [[1.,-1.,1.],[-1.,-1.,-1.]] self.s =\",\n \"the BSD 3-Clause License. # Maintainer: mphoward import unittest import numpy as np\",\n \"self.assertRaises(RuntimeError): hoomd.run(1) # test that particles out of bounds can be caught def\",\n \"period=3) # change velocity of lower particle so it is translating relative to\",\n \"self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) #\",\n \"relative to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.]\",\n \"run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del self.s if __name__ ==\",\n \"caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test\",\n \"This file is part of the HOOMD-blue project, released under the BSD 3-Clause\",\n \"out of bounds can be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError):\",\n \"hoomd import md from hoomd import mpcd # unit tests for mpcd slit\",\n \"bad particle type with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an error\",\n \"hoomd.run(1) # test that particles out of bounds can be caught def test_out_of_bounds(self):\",\n \"test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(),\",\n \"mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen (with all parameters set) def test_create(self):\",\n \"(with all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\\\"no_slip\\\", period=2) # test for\",\n \"z velocities flip again, and since it started closer, # it moves relative\",\n \"for 3 steps. It will bounce back in y and z to where\",\n \"along +x for 3 steps. It will bounce back in y and z\",\n \"self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.])\",\n \"that particles out of bounds can be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8)\",\n \"# change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs slit.set_params(boundary=\\\"slip\\\") self.assertEqual(slit.boundary,\",\n \"if hoomd.comm.get_rank() == 0: # the first particle is matched exactly to the\",\n \"being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\\\"no_slip\\\") slit.set_params(boundary=\\\"slip\\\") with self.assertRaises(ValueError): slit.set_params(boundary=\\\"invalid\\\") #\",\n \"[-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the\",\n \"= mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42, type='A') self.assertTrue(slit._filler is not None) # run should\",\n \"slit.set_params(boundary=\\\"no_slip\\\") slit.set_params(boundary=\\\"slip\\\") with self.assertRaises(ValueError): slit.set_params(boundary=\\\"invalid\\\") # test basic stepping behavior with no slip\",\n \"test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual\",\n \"hoomd.run(1) # now it should be valid slit.set_params(H=4.) hoomd.run(2) # make sure we\",\n \"hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from the starting snapshot snap = mpcd.data.make_snapshot(N=2)\",\n \"check bounce back of particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0:\",\n \"= mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(),\",\n \"hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the first particle is\",\n \"slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle filler can be attached, removed, and\",\n \"velocity of lower particle so it is translating relative to wall snap =\",\n \"can be attached, removed, and updated def test_filler(self): # initialization of a filler\",\n \"streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation context hoomd.context.initialize() #\",\n \"slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del self.s if __name__ == '__main__':\",\n \"allow a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del self.s if\",\n \"test basic stepping behavior with no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) #\",\n \"particles out of bounds can be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with\",\n \"hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1],\",\n \"self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V\",\n \"[1.,1.,1.]) def test_step_moving_wall(self): mpcd.stream.slit(H=4., boundary=\\\"no_slip\\\", V=1.0, period=3) # change velocity of lower particle\",\n \"to wall snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: snap.particles.velocity[1] = [-2.,-1.,-1.] self.s.restore_snapshot(snap)\",\n \"an error is raised if we set a bad density with self.assertRaises(RuntimeError): slit.set_filler(density=-1.0,\",\n \"[-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step where one\",\n \"= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1],\",\n \"1: hoomd.comm.decomposition(nz=2) # default testing configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from\",\n \"not None) hoomd.run(1) # assert an error is raised if we set a\",\n \"and check bounce back of particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() ==\",\n \"wrapping the second particle through the boundary hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank()\",\n \"if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [4.95,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.1,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [1.,1.,1.]) def\",\n \"def test_filler(self): # initialization of a filler slit = mpcd.stream.slit(H=4.) slit.set_filler(density=5., kT=1.0, seed=42,\",\n \"with self.assertRaises(RuntimeError): slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an error is raised if\",\n \"bounce back of particles hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: #\",\n \"box=hoomd.data.boxdim(L=10.))) # initialize the system from the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:]\",\n \"the filler should still allow a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def\",\n \"hoomd from hoomd import md from hoomd import mpcd # unit tests for\",\n \"snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0])\",\n \"class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation context hoomd.context.initialize() # set the\",\n \"[[1.,-1.,1.],[-1.,-1.,-1.]] self.s = mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen (with all parameters\",\n \"import hoomd from hoomd import md from hoomd import mpcd # unit tests\",\n \"able to setup the filler, although this all happens silently hoomd.run(1) # changing\",\n \"decomposition in z for mpi builds if hoomd.comm.get_num_ranks() > 1: hoomd.comm.decomposition(nz=2) # default\",\n \"test for invalid boundary conditions being set def test_bad_boundary(self): slit = mpcd.stream.slit(H=4.) slit.set_params(boundary=\\\"no_slip\\\")\",\n \"original position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior with slip\",\n \"from hoomd import md from hoomd import mpcd # unit tests for mpcd\",\n \"if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,4.75,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.3,-0.3,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,1.]) #\",\n \"make sure we can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1) # test\",\n \"(vx stays the same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.])\",\n \"snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: # the first particle is matched\",\n \"hit the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95])\",\n \"# test basic stepping behavior with slip boundary conditions def test_step_slip(self): mpcd.stream.slit(H=4., boundary=\\\"slip\\\")\",\n \"of Michigan # This file is part of the HOOMD-blue project, released under\",\n \"self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also ensure other parameters stay\",\n \"# take another step where one particle will now hit the wall hoomd.run(1)\",\n \"mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation context hoomd.context.initialize() # set the decomposition\",\n \"all parameters set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\\\"no_slip\\\", period=2) # test for setting\",\n \"= self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1],\",\n \"hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1],\",\n \"with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) # test that virtual particle filler can be\",\n \"wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.85,4.85,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,-1.,-1.])\",\n \"slit.set_filler(density=5., kT=1.0, seed=42, type='B') # assert an error is raised if we set\",\n \"self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change V slit.set_params(V=0.1) self.assertAlmostEqual(slit.V, 0.1) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.1) # change BCs\",\n \"# test for setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V,\",\n \"mpcd slit streaming geometry class mpcd_stream_slit_test(unittest.TestCase): def setUp(self): # establish the simulation context\",\n \"University of Michigan # This file is part of the HOOMD-blue project, released\",\n \"import numpy as np import hoomd from hoomd import md from hoomd import\",\n \"set) def test_create(self): mpcd.stream.slit(H=4., V=0.1, boundary=\\\"no_slip\\\", period=2) # test for setting parameters def\",\n \"mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \\\"no_slip\\\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip)\",\n \"z to where it started. # (vx stays the same, and vy and\",\n \"and z velocities flip again, and since it started closer, # it moves\",\n \"= mpcd.init.read_snapshot(snap) mpcd.integrator(dt=0.1) # test creation can happen (with all parameters set) def\",\n \"as np import hoomd from hoomd import md from hoomd import mpcd #\",\n \"be caught def test_out_of_bounds(self): slit = mpcd.stream.slit(H=3.8) with self.assertRaises(RuntimeError): hoomd.run(1) slit.set_params(H=3.85) hoomd.run(1) #\",\n \"configuration hoomd.init.read_snapshot(hoomd.data.make_snapshot(N=0, box=hoomd.data.boxdim(L=10.))) # initialize the system from the starting snapshot snap =\",\n \"for setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary,\",\n \"[-1.,-1.,1.]) # test that setting the slit size too large raises an error\",\n \"a run slit.set_params(V=1.0) hoomd.run(1) # changing filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7)\",\n \"License. # Maintainer: mphoward import unittest import numpy as np import hoomd from\",\n \"self.assertAlmostEqual(slit._cpp.geometry.getH(), 4.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.no_slip) # change H and also ensure other\",\n \"behavior with no slip boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step\",\n \"filler should be allowed slit.set_filler(density=10., kT=1.5, seed=7) self.assertTrue(slit._filler is not None) hoomd.run(1) #\",\n \"boundary conditions def test_step_noslip(self): mpcd.stream.slit(H=4.) # take one step hoomd.run(1) snap = self.s.take_snapshot()\",\n \"the wall hoomd.run(1) snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0],\",\n \"velocity along +x for 3 steps. It will bounce back in y and\",\n \"hoomd.comm.get_rank() == 0: # the first particle is matched exactly to the wall\",\n \"snap = self.s.take_snapshot() if hoomd.comm.get_rank() == 0: np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.95,4.95,3.95]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0])\",\n \"np.testing.assert_array_almost_equal(snap.particles.velocity[0], [-1.,1.,-1.]) np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.2,-0.2,-4.0]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [-1.,-1.,-1.]) # take another step, wrapping the second\",\n \"change BCs slit.set_params(boundary=\\\"slip\\\") self.assertEqual(slit.boundary, \\\"slip\\\") self.assertEqual(slit._cpp.geometry.getBoundaryCondition(), mpcd._mpcd.boundary.slip) # test for invalid boundary conditions\",\n \"a run slit.remove_filler() self.assertTrue(slit._filler is None) hoomd.run(1) def tearDown(self): del self.s if __name__\",\n \"V=1.0, period=3) # change velocity of lower particle so it is translating relative\",\n \"test for setting parameters def test_set_params(self): slit = mpcd.stream.slit(H=4.) self.assertAlmostEqual(slit.H, 4.) self.assertAlmostEqual(slit.V, 0.)\",\n \"the system from the starting snapshot snap = mpcd.data.make_snapshot(N=2) snap.particles.position[:] = [[4.95,-4.95,3.85],[0.,0.,-3.8]] snap.particles.velocity[:]\",\n \"first particle is matched exactly to the wall speed, and so it will\",\n \"position. np.testing.assert_array_almost_equal(snap.particles.position[1], [-0.4,-0.1,-3.9]) np.testing.assert_array_almost_equal(snap.particles.velocity[1], [0.,1.,1.]) # test basic stepping behavior with slip boundary\",\n \"hoomd.run(2) # make sure we can invalidate it again slit.set_params(H=10.) with self.assertRaises(RuntimeError): hoomd.run(1)\",\n \"be able to setup the filler, although this all happens silently hoomd.run(1) #\",\n \"should be valid slit.set_params(H=4.) hoomd.run(2) # make sure we can invalidate it again\",\n \"import md from hoomd import mpcd # unit tests for mpcd slit streaming\",\n \"the same, and vy and vz flip.) np.testing.assert_array_almost_equal(snap.particles.position[0], [-4.75,-4.95,3.85]) np.testing.assert_array_almost_equal(snap.particles.velocity[0], [1.,1.,-1.]) # the\"\n]","isConversational":false}}},{"rowIdx":1496,"cells":{"ngram":{"kind":"list like","value":["models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6","'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put()","KIND, either express or implied. # See the License for the specific language","Unless required by applicable law or agreed to in writing, software # distributed","License is distributed on an \"AS-IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF","specific language governing permissions and # limitations under the License. \"\"\"Functional tests for","\"\"\"Functional tests for QuestionDAO.\"\"\" # Name determined by parent. pylint: disable-msg=g-bad-name def setUp(self):","actions # Disable complaints about docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring class","[self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7","then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id,","def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name'","this file except in compliance with the License. # You may obtain a","self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description","models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s'","is dangerous because they're handcoded # elsewhere, the implementations could fall out of","exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name())","def test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put()","ANY KIND, either express or implied. # See the License for the specific","self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name',","= '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported =","date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name' user_id","= models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([","'<EMAIL> (<NAME>)', ] import datetime from models import models from tests.functional import actions","determined by parent. pylint: disable-msg=g-bad-name def setUp(self): \"\"\"Sets up datastore contents.\"\"\" super(QuestionDAOTestCase, self).setUp()","models from tests.functional import actions # Disable complaints about docstrings for self-documenting tests.","WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See","student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s' % (user_id, property_name), models.StudentPropertyEntity.safe_key( student_property_key, self.transform).name())","test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name'","for the specific language governing permissions and # limitations under the License. \"\"\"Functional","'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def","[self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase):","= event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key,","test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported","# may then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto =","user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student =","= 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question':","[ '<EMAIL> (<NAME>)', ] import datetime from models import models from tests.functional import","OF ANY KIND, either express or implied. # See the License for the","from models import models from tests.functional import actions # Disable complaints about docstrings","self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id,","StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name =","user_id='1') key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id)","self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id","models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key","self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self):","self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth =","self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description","disable-msg=g-bad-name def setUp(self): \"\"\"Sets up datastore contents.\"\"\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto","= student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' +","models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual(","self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \"\"\"Functional tests for QuestionDAO.\"\"\" # Name","self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description],","= models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id =","'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]})","All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the","self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def","self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual(","about docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event","handcoded # elsewhere, the implementations could fall out of sync, and these tests","self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts.","property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s' % (user_id, property_name),","self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items':","# # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to","for self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source',","[{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description':","test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id =","self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id =","models import models from tests.functional import actions # Disable complaints about docstrings for","models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto,","is_enrolled=True) key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(","self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto =","= models.EventEntity(source='source', user_id='1') key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source)","= student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual(","the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law","user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key =","= profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \"\"\"Functional tests for QuestionDAO.\"\"\"","= models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def","event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform))","key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key,","QuestionDAOTestCase(actions.TestBase): \"\"\"Functional tests for QuestionDAO.\"\"\" # Name determined by parent. pylint: disable-msg=g-bad-name def","key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_'","self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform),","required by applicable law or agreed to in writing, software # distributed under","\"AS-IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or","exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \"\"\"Functional tests for","self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id","\"\"\"Sets up datastore contents.\"\"\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id,","5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group'","applicable law or agreed to in writing, software # distributed under the License","email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name())","class QuestionDAOTestCase(actions.TestBase): \"\"\"Functional tests for QuestionDAO.\"\"\" # Name determined by parent. pylint: disable-msg=g-bad-name","and # limitations under the License. \"\"\"Functional tests for models.models.\"\"\" __author__ = [","self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key =","answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id'","erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description,","or agreed to in writing, software # distributed under the License is distributed","student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key,","License. \"\"\"Functional tests for models.models.\"\"\" __author__ = [ '<EMAIL> (<NAME>)', ] import datetime","= 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO(","CONDITIONS OF ANY KIND, either express or implied. # See the License for","[{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description':","Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0","self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto])","under the Apache License, Version 2.0 (the \"License\"); # you may not use","# Disable complaints about docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase):","'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student,","You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 #","test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key","License. # You may obtain a copy of the License at # #","# elsewhere, the implementations could fall out of sync, and these tests #","\"\"\"Functional tests for models.models.\"\"\" __author__ = [ '<EMAIL> (<NAME>)', ] import datetime from","compliance with the License. # You may obtain a copy of the License","'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student =","7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student =","{'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description],","the specific language governing permissions and # limitations under the License. \"\"\"Functional tests","these tests # may then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4","{}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto","self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto","of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable","4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group'","self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id)","6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto,","software # distributed under the License is distributed on an \"AS-IS\" BASIS, #","exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name())","'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name())","event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def","is distributed on an \"AS-IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY","distributed under the License is distributed on an \"AS-IS\" BASIS, # WITHOUT WARRANTIES","not use this file except in compliance with the License. # You may","# Name determined by parent. pylint: disable-msg=g-bad-name def setUp(self): \"\"\"Sets up datastore contents.\"\"\"","models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5","License, Version 2.0 (the \"License\"); # you may not use this file except","def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event,","= 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s' % (user_id, property_name), models.StudentPropertyEntity.safe_key(","class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key = event.put() exported =","self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {})","self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \"\"\"Functional tests for QuestionDAO.\"\"\" # Name determined by","models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description,","self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self):","models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1',","permissions and # limitations under the License. \"\"\"Functional tests for models.models.\"\"\" __author__ =","student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class","# you may not use this file except in compliance with the License.","exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name',","= models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name',","models.EventEntity(source='source', user_id='1') key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1',","agreed to in writing, software # distributed under the License is distributed on","implementations could fall out of sync, and these tests # may then pass","(the \"License\"); # you may not use this file except in compliance with","self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This is dangerous","docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event =","= models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id","= models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id =","3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the","# Unless required by applicable law or agreed to in writing, software #","by applicable law or agreed to in writing, software # distributed under the","self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \"\"\"Functional tests for QuestionDAO.\"\"\" # Name determined by parent.","exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth","Copyright 2013 Google Inc. All Rights Reserved. # # Licensed under the Apache","exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email =","test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id","user_id = '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported =","copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by","datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name' user_id = '1'","tests for models.models.\"\"\" __author__ = [ '<EMAIL> (<NAME>)', ] import datetime from models","'nick_name' user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put()","# Handcoding the dicts. This is dangerous because they're handcoded # elsewhere, the","self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def","self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3","exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key)","test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id))","Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version","= 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding","file except in compliance with the License. # You may obtain a copy","exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \"\"\"Functional tests for QuestionDAO.\"\"\" # Name determined by parent. pylint:","student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual(","Disable complaints about docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def","License for the specific language governing permissions and # limitations under the License.","legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase):","self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student","import actions # Disable complaints about docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring","to in writing, software # distributed under the License is distributed on an","1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id,","class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name'","= 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question':","implied. # See the License for the specific language governing permissions and #","\"License\"); # you may not use this file except in compliance with the","'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id,","Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the \"License\");","obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless","# Copyright 2013 Google Inc. All Rights Reserved. # # Licensed under the","= 'nick_name' user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name)","{'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto =","class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key","exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id","super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2","'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id'","tests for QuestionDAO.\"\"\" # Name determined by parent. pylint: disable-msg=g-bad-name def setUp(self): \"\"\"Sets","] import datetime from models import models from tests.functional import actions # Disable","self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>'","email = '<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name' user_id = '1' profile","or implied. # See the License for the specific language governing permissions and","models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id))","= models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported)","2013 Google Inc. All Rights Reserved. # # Licensed under the Apache License,","def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name',","datetime from models import models from tests.functional import actions # Disable complaints about","student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s' % (user_id,","self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO(","Apache License, Version 2.0 (the \"License\"); # you may not use this file","self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name =","OR CONDITIONS OF ANY KIND, either express or implied. # See the License","may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # #","dicts. This is dangerous because they're handcoded # elsewhere, the implementations could fall","= 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description =","under the License. \"\"\"Functional tests for models.models.\"\"\" __author__ = [ '<EMAIL> (<NAME>)', ]","This is dangerous because they're handcoded # elsewhere, the implementations could fall out","exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \"\"\"Functional tests for QuestionDAO.\"\"\" # Name determined","self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO(","http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing,","test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported)","an \"AS-IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express","language governing permissions and # limitations under the License. \"\"\"Functional tests for models.models.\"\"\"","student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key,","# See the License for the specific language governing permissions and # limitations","self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This is dangerous because they're handcoded","self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase):","models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self):","from tests.functional import actions # Disable complaints about docstrings for self-documenting tests. #","the License. \"\"\"Functional tests for models.models.\"\"\" __author__ = [ '<EMAIL> (<NAME>)', ] import","str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual(","user_id='1', is_enrolled=True) key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id)","'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id,","self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items':","import models from tests.functional import actions # Disable complaints about docstrings for self-documenting","def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id","the Apache License, Version 2.0 (the \"License\"); # you may not use this","you may not use this file except in compliance with the License. #","= 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student","def setUp(self): \"\"\"Sets up datastore contents.\"\"\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto =","self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto =","str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description,","test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key(","import datetime from models import models from tests.functional import actions # Disable complaints","use this file except in compliance with the License. # You may obtain","# pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key =","profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile,","student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id,","the dicts. This is dangerous because they're handcoded # elsewhere, the implementations could","distributed on an \"AS-IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,","pylint: disable-msg=g-bad-name def setUp(self): \"\"\"Sets up datastore contents.\"\"\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1","sync, and these tests # may then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id","# Licensed under the Apache License, Version 2.0 (the \"License\"); # you may","class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put()","self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto,","def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def","setUp(self): \"\"\"Sets up datastore contents.\"\"\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO(","key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class","profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \"\"\"Functional tests","'legal_name' nick_name = 'nick_name' user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id,","2.0 (the \"License\"); # you may not use this file except in compliance","user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key","models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self):","'1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student,","WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the","datastore contents.\"\"\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id","models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This is","# # Unless required by applicable law or agreed to in writing, software","# distributed under the License is distributed on an \"AS-IS\" BASIS, # WITHOUT","express or implied. # See the License for the specific language governing permissions","user_id=user_id) student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s' %","self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto","self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This is dangerous because they're handcoded #","self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers =","either express or implied. # See the License for the specific language governing","legal_name = 'legal_name' nick_name = 'nick_name' user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth,","tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key","self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto","Licensed under the Apache License, Version 2.0 (the \"License\"); # you may not","= answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id =","nick_name = 'nick_name' user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name,","tests # may then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto","the implementations could fall out of sync, and these tests # may then","= '<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name' user_id = '1' profile =","test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key","answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id)","'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]})","= models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def","elsewhere, the implementations could fall out of sync, and these tests # may","test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self):","'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]})","the License. # You may obtain a copy of the License at #","self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) #","# limitations under the License. \"\"\"Functional tests for models.models.\"\"\" __author__ = [ '<EMAIL>","self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1')","event = models.EventEntity(source='source', user_id='1') key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source',","= 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto,","nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \"\"\"Functional","in writing, software # distributed under the License is distributed on an \"AS-IS\"","self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {})","{}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto])","limitations under the License. \"\"\"Functional tests for models.models.\"\"\" __author__ = [ '<EMAIL> (<NAME>)',","profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \"\"\"Functional tests for QuestionDAO.\"\"\" #","'<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name' user_id = '1' profile = models.PersonalProfile(","for QuestionDAO.\"\"\" # Name determined by parent. pylint: disable-msg=g-bad-name def setUp(self): \"\"\"Sets up","def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([],","pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description':","user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name())","models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This is dangerous because they're","def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self):","str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description,","def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self):","self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put()","with the License. # You may obtain a copy of the License at","= 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question':","# # Licensed under the Apache License, Version 2.0 (the \"License\"); # you","= datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name' user_id =","QuestionDAO.\"\"\" # Name determined by parent. pylint: disable-msg=g-bad-name def setUp(self): \"\"\"Sets up datastore","= models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put()","{}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This is dangerous because","= models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This","the License is distributed on an \"AS-IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS","= event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase):","= 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description =","self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id))","on an \"AS-IS\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either","law or agreed to in writing, software # distributed under the License is","governing permissions and # limitations under the License. \"\"\"Functional tests for models.models.\"\"\" __author__","the License for the specific language governing permissions and # limitations under the","student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put()","[{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self):","parent. pylint: disable-msg=g-bad-name def setUp(self): \"\"\"Sets up datastore contents.\"\"\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id =","up datastore contents.\"\"\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {})","models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True)","= models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name())","Handcoding the dicts. This is dangerous because they're handcoded # elsewhere, the implementations","fall out of sync, and these tests # may then pass erroneously. self.first_question_group_description","StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key =","self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id =","under the License is distributed on an \"AS-IS\" BASIS, # WITHOUT WARRANTIES OR","2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id,","student = models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported)","could fall out of sync, and these tests # may then pass erroneously.","Reserved. # # Licensed under the Apache License, Version 2.0 (the \"License\"); #","'1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform)","in compliance with the License. # You may obtain a copy of the","License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or","# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. #","at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed","self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class","def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name' nick_name =","dangerous because they're handcoded # elsewhere, the implementations could fall out of sync,","= 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO(","StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual(","See the License for the specific language governing permissions and # limitations under","models.models.\"\"\" __author__ = [ '<EMAIL> (<NAME>)', ] import datetime from models import models","PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name' nick_name","BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.","= models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled)","a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required","self.unused_question_dto]) # Handcoding the dicts. This is dangerous because they're handcoded # elsewhere,","# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in","self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([","= 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create(","models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put()","for models.models.\"\"\" __author__ = [ '<EMAIL> (<NAME>)', ] import datetime from models import","'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s' % (user_id, property_name), models.StudentPropertyEntity.safe_key( student_property_key,","__author__ = [ '<EMAIL> (<NAME>)', ] import datetime from models import models from","models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>',","user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported","{'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto =","models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key,","models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class","out of sync, and these tests # may then pass erroneously. self.first_question_group_description =","of sync, and these tests # may then pass erroneously. self.first_question_group_description = 'first_question_group'","complaints about docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self):","self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name', user_id='1',","Version 2.0 (the \"License\"); # you may not use this file except in","because they're handcoded # elsewhere, the implementations could fall out of sync, and","except in compliance with the License. # You may obtain a copy of","models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name","may then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO(","Name determined by parent. pylint: disable-msg=g-bad-name def setUp(self): \"\"\"Sets up datastore contents.\"\"\" super(QuestionDAOTestCase,","exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class","models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id =","writing, software # distributed under the License is distributed on an \"AS-IS\" BASIS,","disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key = event.put() exported","(<NAME>)', ] import datetime from models import models from tests.functional import actions #","# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0","may not use this file except in compliance with the License. # You","= [ '<EMAIL> (<NAME>)', ] import datetime from models import models from tests.functional","answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id","= 'legal_name' nick_name = 'nick_name' user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email,","date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id),","self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def","models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self):","= 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key =","and these tests # may then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id =","class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name","models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers","by parent. pylint: disable-msg=g-bad-name def setUp(self): \"\"\"Sets up datastore contents.\"\"\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id","tests.functional import actions # Disable complaints about docstrings for self-documenting tests. # pylint:","answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase):","key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key =","pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key = event.put()","they're handcoded # elsewhere, the implementations could fall out of sync, and these","event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today()","+ user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student","self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items':","not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1'","self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email","self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id))","EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key = event.put() exported = event.for_export(self.transform)","= '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported = student.for_export(self.transform)","student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def","contents.\"\"\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id =","= models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual("],"string":"[\n \"models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6\",\n \"'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put()\",\n \"KIND, either express or implied. # See the License for the specific language\",\n \"Unless required by applicable law or agreed to in writing, software # distributed\",\n \"License is distributed on an \\\"AS-IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF\",\n \"specific language governing permissions and # limitations under the License. \\\"\\\"\\\"Functional tests for\",\n \"\\\"\\\"\\\"Functional tests for QuestionDAO.\\\"\\\"\\\" # Name determined by parent. pylint: disable-msg=g-bad-name def setUp(self):\",\n \"actions # Disable complaints about docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring class\",\n \"[self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7\",\n \"then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id,\",\n \"def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name'\",\n \"this file except in compliance with the License. # You may obtain a\",\n \"self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description\",\n \"models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s'\",\n \"is dangerous because they're handcoded # elsewhere, the implementations could fall out of\",\n \"exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name())\",\n \"def test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put()\",\n \"ANY KIND, either express or implied. # See the License for the specific\",\n \"self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name',\",\n \"= '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported =\",\n \"date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name' user_id\",\n \"= models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([\",\n \"'<EMAIL> (<NAME>)', ] import datetime from models import models from tests.functional import actions\",\n \"determined by parent. pylint: disable-msg=g-bad-name def setUp(self): \\\"\\\"\\\"Sets up datastore contents.\\\"\\\"\\\" super(QuestionDAOTestCase, self).setUp()\",\n \"models from tests.functional import actions # Disable complaints about docstrings for self-documenting tests.\",\n \"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See\",\n \"student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s' % (user_id, property_name), models.StudentPropertyEntity.safe_key( student_property_key, self.transform).name())\",\n \"test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name'\",\n \"for the specific language governing permissions and # limitations under the License. \\\"\\\"\\\"Functional\",\n \"'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def\",\n \"[self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase):\",\n \"= event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key,\",\n \"test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported\",\n \"# may then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto =\",\n \"user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student =\",\n \"= 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question':\",\n \"[ '<EMAIL> (<NAME>)', ] import datetime from models import models from tests.functional import\",\n \"OF ANY KIND, either express or implied. # See the License for the\",\n \"from models import models from tests.functional import actions # Disable complaints about docstrings\",\n \"self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id,\",\n \"StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name =\",\n \"user_id='1') key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id)\",\n \"self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id\",\n \"models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key\",\n \"self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self):\",\n \"self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth =\",\n \"self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description\",\n \"disable-msg=g-bad-name def setUp(self): \\\"\\\"\\\"Sets up datastore contents.\\\"\\\"\\\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto\",\n \"= student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' +\",\n \"models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual(\",\n \"self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \\\"\\\"\\\"Functional tests for QuestionDAO.\\\"\\\"\\\" # Name\",\n \"self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description],\",\n \"= models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id =\",\n \"'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]})\",\n \"All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the\",\n \"self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def\",\n \"self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual(\",\n \"about docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event\",\n \"handcoded # elsewhere, the implementations could fall out of sync, and these tests\",\n \"self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts.\",\n \"property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s' % (user_id, property_name),\",\n \"self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items':\",\n \"# # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to\",\n \"for self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source',\",\n \"[{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description':\",\n \"test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id =\",\n \"self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id =\",\n \"models import models from tests.functional import actions # Disable complaints about docstrings for\",\n \"models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto,\",\n \"is_enrolled=True) key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(\",\n \"self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto =\",\n \"= models.EventEntity(source='source', user_id='1') key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source)\",\n \"= student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual(\",\n \"the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law\",\n \"user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key =\",\n \"= profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \\\"\\\"\\\"Functional tests for QuestionDAO.\\\"\\\"\\\"\",\n \"= models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def\",\n \"event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform))\",\n \"key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key,\",\n \"QuestionDAOTestCase(actions.TestBase): \\\"\\\"\\\"Functional tests for QuestionDAO.\\\"\\\"\\\" # Name determined by parent. pylint: disable-msg=g-bad-name def\",\n \"key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_'\",\n \"self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform),\",\n \"required by applicable law or agreed to in writing, software # distributed under\",\n \"\\\"AS-IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or\",\n \"exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \\\"\\\"\\\"Functional tests for\",\n \"self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id\",\n \"\\\"\\\"\\\"Sets up datastore contents.\\\"\\\"\\\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id,\",\n \"5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group'\",\n \"applicable law or agreed to in writing, software # distributed under the License\",\n \"email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name())\",\n \"class QuestionDAOTestCase(actions.TestBase): \\\"\\\"\\\"Functional tests for QuestionDAO.\\\"\\\"\\\" # Name determined by parent. pylint: disable-msg=g-bad-name\",\n \"and # limitations under the License. \\\"\\\"\\\"Functional tests for models.models.\\\"\\\"\\\" __author__ = [\",\n \"self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key =\",\n \"answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id'\",\n \"erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description,\",\n \"or agreed to in writing, software # distributed under the License is distributed\",\n \"student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key,\",\n \"License. \\\"\\\"\\\"Functional tests for models.models.\\\"\\\"\\\" __author__ = [ '<EMAIL> (<NAME>)', ] import datetime\",\n \"= 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO(\",\n \"CONDITIONS OF ANY KIND, either express or implied. # See the License for\",\n \"[{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description':\",\n \"Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0\",\n \"self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto])\",\n \"under the Apache License, Version 2.0 (the \\\"License\\\"); # you may not use\",\n \"# Disable complaints about docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase):\",\n \"'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student,\",\n \"You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 #\",\n \"test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key\",\n \"License. # You may obtain a copy of the License at # #\",\n \"# elsewhere, the implementations could fall out of sync, and these tests #\",\n \"\\\"\\\"\\\"Functional tests for models.models.\\\"\\\"\\\" __author__ = [ '<EMAIL> (<NAME>)', ] import datetime from\",\n \"compliance with the License. # You may obtain a copy of the License\",\n \"'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student =\",\n \"7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student =\",\n \"{'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description],\",\n \"the specific language governing permissions and # limitations under the License. \\\"\\\"\\\"Functional tests\",\n \"these tests # may then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4\",\n \"{}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto\",\n \"self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto\",\n \"of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable\",\n \"4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group'\",\n \"self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id)\",\n \"6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto,\",\n \"software # distributed under the License is distributed on an \\\"AS-IS\\\" BASIS, #\",\n \"exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name())\",\n \"'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name())\",\n \"event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def\",\n \"is distributed on an \\\"AS-IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY\",\n \"distributed under the License is distributed on an \\\"AS-IS\\\" BASIS, # WITHOUT WARRANTIES\",\n \"not use this file except in compliance with the License. # You may\",\n \"# Name determined by parent. pylint: disable-msg=g-bad-name def setUp(self): \\\"\\\"\\\"Sets up datastore contents.\\\"\\\"\\\"\",\n \"models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5\",\n \"License, Version 2.0 (the \\\"License\\\"); # you may not use this file except\",\n \"def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event,\",\n \"= 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s' % (user_id, property_name), models.StudentPropertyEntity.safe_key(\",\n \"class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key = event.put() exported =\",\n \"self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {})\",\n \"self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \\\"\\\"\\\"Functional tests for QuestionDAO.\\\"\\\"\\\" # Name determined by\",\n \"models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description,\",\n \"self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self):\",\n \"models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1',\",\n \"permissions and # limitations under the License. \\\"\\\"\\\"Functional tests for models.models.\\\"\\\"\\\" __author__ =\",\n \"student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class\",\n \"# you may not use this file except in compliance with the License.\",\n \"exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name',\",\n \"= models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name',\",\n \"models.EventEntity(source='source', user_id='1') key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1',\",\n \"agreed to in writing, software # distributed under the License is distributed on\",\n \"implementations could fall out of sync, and these tests # may then pass\",\n \"(the \\\"License\\\"); # you may not use this file except in compliance with\",\n \"self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This is dangerous\",\n \"docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event =\",\n \"= models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id\",\n \"= models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id =\",\n \"3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the\",\n \"# Unless required by applicable law or agreed to in writing, software #\",\n \"by applicable law or agreed to in writing, software # distributed under the\",\n \"self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \\\"\\\"\\\"Functional tests for QuestionDAO.\\\"\\\"\\\" # Name determined by parent.\",\n \"exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth\",\n \"Copyright 2013 Google Inc. All Rights Reserved. # # Licensed under the Apache\",\n \"exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email =\",\n \"test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id\",\n \"user_id = '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported =\",\n \"copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by\",\n \"datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name' user_id = '1'\",\n \"tests for models.models.\\\"\\\"\\\" __author__ = [ '<EMAIL> (<NAME>)', ] import datetime from models\",\n \"'nick_name' user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put()\",\n \"# Handcoding the dicts. This is dangerous because they're handcoded # elsewhere, the\",\n \"self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def\",\n \"self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3\",\n \"exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key)\",\n \"test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id))\",\n \"Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version\",\n \"= 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding\",\n \"file except in compliance with the License. # You may obtain a copy\",\n \"exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \\\"\\\"\\\"Functional tests for QuestionDAO.\\\"\\\"\\\" # Name determined by parent. pylint:\",\n \"student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual(\",\n \"Disable complaints about docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def\",\n \"License for the specific language governing permissions and # limitations under the License.\",\n \"legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase):\",\n \"self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student\",\n \"import actions # Disable complaints about docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring\",\n \"to in writing, software # distributed under the License is distributed on an\",\n \"1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id,\",\n \"class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name'\",\n \"= 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question':\",\n \"implied. # See the License for the specific language governing permissions and #\",\n \"\\\"License\\\"); # you may not use this file except in compliance with the\",\n \"'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id,\",\n \"Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the \\\"License\\\");\",\n \"obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless\",\n \"# Copyright 2013 Google Inc. All Rights Reserved. # # Licensed under the\",\n \"= 'nick_name' user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name)\",\n \"{'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto =\",\n \"class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key\",\n \"exported.user_id) self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id\",\n \"super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2\",\n \"'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id'\",\n \"tests for QuestionDAO.\\\"\\\"\\\" # Name determined by parent. pylint: disable-msg=g-bad-name def setUp(self): \\\"\\\"\\\"Sets\",\n \"] import datetime from models import models from tests.functional import actions # Disable\",\n \"self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>'\",\n \"email = '<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name' user_id = '1' profile\",\n \"or implied. # See the License for the specific language governing permissions and\",\n \"models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id))\",\n \"= models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported)\",\n \"2013 Google Inc. All Rights Reserved. # # Licensed under the Apache License,\",\n \"def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name',\",\n \"datetime from models import models from tests.functional import actions # Disable complaints about\",\n \"student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s' % (user_id,\",\n \"self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO(\",\n \"Apache License, Version 2.0 (the \\\"License\\\"); # you may not use this file\",\n \"self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name =\",\n \"OR CONDITIONS OF ANY KIND, either express or implied. # See the License\",\n \"may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # #\",\n \"dicts. This is dangerous because they're handcoded # elsewhere, the implementations could fall\",\n \"= 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description =\",\n \"under the License. \\\"\\\"\\\"Functional tests for models.models.\\\"\\\"\\\" __author__ = [ '<EMAIL> (<NAME>)', ]\",\n \"This is dangerous because they're handcoded # elsewhere, the implementations could fall out\",\n \"exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \\\"\\\"\\\"Functional tests for QuestionDAO.\\\"\\\"\\\" # Name determined\",\n \"self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO(\",\n \"http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing,\",\n \"test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported)\",\n \"an \\\"AS-IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express\",\n \"language governing permissions and # limitations under the License. \\\"\\\"\\\"Functional tests for models.models.\\\"\\\"\\\"\",\n \"student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key,\",\n \"# See the License for the specific language governing permissions and # limitations\",\n \"self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This is dangerous because they're handcoded\",\n \"self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase):\",\n \"models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self):\",\n \"from tests.functional import actions # Disable complaints about docstrings for self-documenting tests. #\",\n \"the License. \\\"\\\"\\\"Functional tests for models.models.\\\"\\\"\\\" __author__ = [ '<EMAIL> (<NAME>)', ] import\",\n \"str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual(\",\n \"user_id='1', is_enrolled=True) key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id)\",\n \"'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id,\",\n \"self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items':\",\n \"import models from tests.functional import actions # Disable complaints about docstrings for self-documenting\",\n \"def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id\",\n \"the Apache License, Version 2.0 (the \\\"License\\\"); # you may not use this\",\n \"you may not use this file except in compliance with the License. #\",\n \"= 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student\",\n \"def setUp(self): \\\"\\\"\\\"Sets up datastore contents.\\\"\\\"\\\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto =\",\n \"self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto =\",\n \"str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description,\",\n \"test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key(\",\n \"import datetime from models import models from tests.functional import actions # Disable complaints\",\n \"use this file except in compliance with the License. # You may obtain\",\n \"# pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key =\",\n \"profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile,\",\n \"student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled) self.assertEqual('transformed_1', exported.user_id) self.assertEqual( 'transformed_' + user_id,\",\n \"the dicts. This is dangerous because they're handcoded # elsewhere, the implementations could\",\n \"distributed on an \\\"AS-IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,\",\n \"pylint: disable-msg=g-bad-name def setUp(self): \\\"\\\"\\\"Sets up datastore contents.\\\"\\\"\\\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1\",\n \"sync, and these tests # may then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id\",\n \"# Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); # you may\",\n \"class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put()\",\n \"self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto,\",\n \"def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def\",\n \"setUp(self): \\\"\\\"\\\"Sets up datastore contents.\\\"\\\"\\\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO(\",\n \"key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class\",\n \"profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \\\"\\\"\\\"Functional tests\",\n \"'legal_name' nick_name = 'nick_name' user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id,\",\n \"2.0 (the \\\"License\\\"); # you may not use this file except in compliance\",\n \"user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key\",\n \"models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self):\",\n \"'1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student,\",\n \"WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the\",\n \"datastore contents.\\\"\\\"\\\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id\",\n \"models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This is\",\n \"# # Unless required by applicable law or agreed to in writing, software\",\n \"# distributed under the License is distributed on an \\\"AS-IS\\\" BASIS, # WITHOUT\",\n \"express or implied. # See the License for the specific language governing permissions\",\n \"user_id=user_id) student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s' %\",\n \"self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto\",\n \"self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This is dangerous because they're handcoded #\",\n \"self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers =\",\n \"either express or implied. # See the License for the specific language governing\",\n \"legal_name = 'legal_name' nick_name = 'nick_name' user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth,\",\n \"tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key\",\n \"self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto\",\n \"Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); # you may not\",\n \"= answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id =\",\n \"nick_name = 'nick_name' user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name,\",\n \"tests # may then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto\",\n \"the implementations could fall out of sync, and these tests # may then\",\n \"= '<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name' user_id = '1' profile =\",\n \"test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key\",\n \"answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id)\",\n \"'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]})\",\n \"= models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def\",\n \"elsewhere, the implementations could fall out of sync, and these tests # may\",\n \"test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self):\",\n \"'third_question_group' self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]})\",\n \"the License. # You may obtain a copy of the License at #\",\n \"self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) #\",\n \"# limitations under the License. \\\"\\\"\\\"Functional tests for models.models.\\\"\\\"\\\" __author__ = [ '<EMAIL>\",\n \"self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1')\",\n \"event = models.EventEntity(source='source', user_id='1') key = event.put() exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source',\",\n \"= 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto,\",\n \"nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \\\"\\\"\\\"Functional\",\n \"in writing, software # distributed under the License is distributed on an \\\"AS-IS\\\"\",\n \"self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {})\",\n \"{}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto])\",\n \"limitations under the License. \\\"\\\"\\\"Functional tests for models.models.\\\"\\\"\\\" __author__ = [ '<EMAIL> (<NAME>)',\",\n \"profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id), exported.safe_key.name()) class QuestionDAOTestCase(actions.TestBase): \\\"\\\"\\\"Functional tests for QuestionDAO.\\\"\\\"\\\" #\",\n \"'<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name' user_id = '1' profile = models.PersonalProfile(\",\n \"for QuestionDAO.\\\"\\\"\\\" # Name determined by parent. pylint: disable-msg=g-bad-name def setUp(self): \\\"\\\"\\\"Sets up\",\n \"def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([],\",\n \"pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description':\",\n \"user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name())\",\n \"models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This is dangerous because they're\",\n \"def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self):\",\n \"str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto = models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description,\",\n \"def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self):\",\n \"self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put()\",\n \"with the License. # You may obtain a copy of the License at\",\n \"= 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question':\",\n \"# # Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); # you\",\n \"= datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name' nick_name = 'nick_name' user_id =\",\n \"QuestionDAO.\\\"\\\"\\\" # Name determined by parent. pylint: disable-msg=g-bad-name def setUp(self): \\\"\\\"\\\"Sets up datastore\",\n \"= models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put()\",\n \"{}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This is dangerous because\",\n \"= models.QuestionDTO( self.unused_question_id, {}) models.QuestionDAO.save_all([ self.used_twice_question_dto, self.used_once_question_dto, self.unused_question_dto]) # Handcoding the dicts. This\",\n \"the License is distributed on an \\\"AS-IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS\",\n \"= event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase):\",\n \"= 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description =\",\n \"self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id))\",\n \"on an \\\"AS-IS\\\" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either\",\n \"law or agreed to in writing, software # distributed under the License is\",\n \"governing permissions and # limitations under the License. \\\"\\\"\\\"Functional tests for models.models.\\\"\\\"\\\" __author__\",\n \"the License for the specific language governing permissions and # limitations under the\",\n \"student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put()\",\n \"[{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([ self.first_question_group_dto, self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self):\",\n \"parent. pylint: disable-msg=g-bad-name def setUp(self): \\\"\\\"\\\"Sets up datastore contents.\\\"\\\"\\\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id =\",\n \"up datastore contents.\\\"\\\"\\\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {})\",\n \"models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True)\",\n \"= models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name())\",\n \"Handcoding the dicts. This is dangerous because they're handcoded # elsewhere, the implementations\",\n \"fall out of sync, and these tests # may then pass erroneously. self.first_question_group_description\",\n \"StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key =\",\n \"self.assertEqual( 'transformed_' + user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id =\",\n \"under the License is distributed on an \\\"AS-IS\\\" BASIS, # WITHOUT WARRANTIES OR\",\n \"2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO( self.unused_question_id,\",\n \"student = models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported)\",\n \"could fall out of sync, and these tests # may then pass erroneously.\",\n \"Reserved. # # Licensed under the Apache License, Version 2.0 (the \\\"License\\\"); #\",\n \"'1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform)\",\n \"in compliance with the License. # You may obtain a copy of the\",\n \"License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or\",\n \"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. #\",\n \"at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed\",\n \"self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class\",\n \"def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name' nick_name =\",\n \"dangerous because they're handcoded # elsewhere, the implementations could fall out of sync,\",\n \"= 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id = 3 self.unused_question_dto = models.QuestionDTO(\",\n \"StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual(\",\n \"See the License for the specific language governing permissions and # limitations under\",\n \"models.models.\\\"\\\"\\\" __author__ = [ '<EMAIL> (<NAME>)', ] import datetime from models import models\",\n \"PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name = 'legal_name' nick_name\",\n \"BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\",\n \"= models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported = student.for_export(self.transform) self.assert_blacklisted_properties_removed(student, exported) self.assertTrue(exported.is_enrolled)\",\n \"a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required\",\n \"self.unused_question_dto]) # Handcoding the dicts. This is dangerous because they're handcoded # elsewhere,\",\n \"# http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in\",\n \"self.third_question_group_id = 6 self.third_question_group_dto = models.QuestionGroupDTO( self.third_question_group_id, {'description': self.third_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) models.QuestionGroupDAO.save_all([\",\n \"= 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create(\",\n \"models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put()\",\n \"for models.models.\\\"\\\"\\\" __author__ = [ '<EMAIL> (<NAME>)', ] import datetime from models import\",\n \"'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual( 'transformed_%s-%s' % (user_id, property_name), models.StudentPropertyEntity.safe_key( student_property_key,\",\n \"__author__ = [ '<EMAIL> (<NAME>)', ] import datetime from models import models from\",\n \"models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>',\",\n \"user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported\",\n \"{'description': self.first_question_group_description, 'items': [{'question': str(self.used_once_question_id)}]}) self.second_question_group_description = 'second_question_group' self.second_question_group_id = 5 self.second_question_group_dto =\",\n \"models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key,\",\n \"models.Student(key_name='name').put() answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class\",\n \"out of sync, and these tests # may then pass erroneously. self.first_question_group_description =\",\n \"of sync, and these tests # may then pass erroneously. self.first_question_group_description = 'first_question_group'\",\n \"complaints about docstrings for self-documenting tests. # pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self):\",\n \"self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1' student = models.Student(key_name='name', user_id='1',\",\n \"Version 2.0 (the \\\"License\\\"); # you may not use this file except in\",\n \"because they're handcoded # elsewhere, the implementations could fall out of sync, and\",\n \"except in compliance with the License. # You may obtain a copy of\",\n \"models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email = '<EMAIL>' legal_name\",\n \"may then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO(\",\n \"Name determined by parent. pylint: disable-msg=g-bad-name def setUp(self): \\\"\\\"\\\"Sets up datastore contents.\\\"\\\"\\\" super(QuestionDAOTestCase,\",\n \"exported = event.for_export(self.transform) self.assert_blacklisted_properties_removed(event, exported) self.assertEqual('source', event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class\",\n \"models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id = 2 self.used_once_question_dto = models.QuestionDTO( self.used_once_question_id, {}) self.unused_question_id =\",\n \"writing, software # distributed under the License is distributed on an \\\"AS-IS\\\" BASIS,\",\n \"disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key = event.put() exported\",\n \"(<NAME>)', ] import datetime from models import models from tests.functional import actions #\",\n \"# You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0\",\n \"may not use this file except in compliance with the License. # You\",\n \"= [ '<EMAIL> (<NAME>)', ] import datetime from models import models from tests.functional\",\n \"answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id\",\n \"= 'legal_name' nick_name = 'nick_name' user_id = '1' profile = models.PersonalProfile( date_of_birth=date_of_birth, email=email,\",\n \"date_of_birth=date_of_birth, email=email, key_name=user_id, legal_name=legal_name, nick_name=nick_name) profile.put() exported = profile.for_export(self.transform) self.assert_blacklisted_properties_removed(profile, exported) self.assertEqual( self.transform(user_id),\",\n \"self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id)) def\",\n \"models.QuestionDAO.used_by(self.used_twice_question_id)) def test_used_by_returns_empty_list_for_unused_question(self): not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self):\",\n \"= 'user_id' student = models.Student(key_name='name', user_id=user_id) student.put() self.assertEqual(user_id, student.get_key().name()) def test_safe_key_transforms_name(self): key =\",\n \"and these tests # may then pass erroneously. self.first_question_group_description = 'first_question_group' self.first_question_group_id =\",\n \"class StudentPropertyEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_user_id_component(self): user_id = 'user_id' student = models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name\",\n \"models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key = models.Student(key_name='name').put() answers\",\n \"by parent. pylint: disable-msg=g-bad-name def setUp(self): \\\"\\\"\\\"Sets up datastore contents.\\\"\\\"\\\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id\",\n \"tests.functional import actions # Disable complaints about docstrings for self-documenting tests. # pylint:\",\n \"answers = models.StudentAnswersEntity(key_name=student_key.name()) answers_key = answers.put() self.assertEqual( 'transformed_name', models.StudentAnswersEntity.safe_key( answers_key, self.transform).name()) class StudentPropertyEntityTestCase(actions.ExportTestBase):\",\n \"key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def test_safe_key_transforms_name(self): student_key =\",\n \"pylint: disable-msg=g-missing-docstring class EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key = event.put()\",\n \"they're handcoded # elsewhere, the implementations could fall out of sync, and these\",\n \"event.source) self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today()\",\n \"+ user_id, exported.key_by_user_id.name()) self.assertEqual( models.Student.safe_key(key, self.transform), exported.safe_key) def test_get_key_does_not_transform_by_default(self): user_id = 'user_id' student\",\n \"self.first_question_group_description = 'first_question_group' self.first_question_group_id = 4 self.first_question_group_dto = models.QuestionGroupDTO( self.first_question_group_id, {'description': self.first_question_group_description, 'items':\",\n \"not_found_id = 7 self.assertFalse(models.QuestionDAO.load(not_found_id)) self.assertEqual([], models.QuestionDAO.used_by(not_found_id)) class StudentTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): user_id = '1'\",\n \"self.assertEqual('transformed_1', exported.user_id) self.assertEqual(key, models.EventEntity.safe_key(key, self.transform)) class PersonalProfileTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly_and_sets_safe_key(self): date_of_birth = datetime.date.today() email\",\n \"self.second_question_group_dto, self.third_question_group_dto]) def test_used_by_returns_description_of_single_question_group(self): self.assertEqual( [self.first_question_group_description], models.QuestionDAO.used_by(self.used_once_question_id)) def test_used_by_returns_descriptions_of_multiple_question_groups(self): self.assertEqual( [self.second_question_group_description, self.third_question_group_description], models.QuestionDAO.used_by(self.used_twice_question_id))\",\n \"EventEntityTestCase(actions.ExportTestBase): def test_for_export_transforms_correctly(self): event = models.EventEntity(source='source', user_id='1') key = event.put() exported = event.for_export(self.transform)\",\n \"= '1' student = models.Student(key_name='name', user_id='1', is_enrolled=True) key = student.put() exported = student.for_export(self.transform)\",\n \"student.get_key().name()) def test_safe_key_transforms_name(self): key = models.Student(key_name='name').put() self.assertEqual( 'transformed_name', models.Student.safe_key(key, self.transform).name()) class StudentAnswersEntityTestCase(actions.ExportTestBase): def\",\n \"contents.\\\"\\\"\\\" super(QuestionDAOTestCase, self).setUp() self.used_twice_question_id = 1 self.used_twice_question_dto = models.QuestionDTO( self.used_twice_question_id, {}) self.used_once_question_id =\",\n \"= models.Student(key_name='<EMAIL>', user_id=user_id) student.put() property_name = 'property-name' student_property_key = models.StudentPropertyEntity.create( student, property_name).put() self.assertEqual(\"\n]","isConversational":false}}},{"rowIdx":1497,"cells":{"ngram":{"kind":"list like","value":["signal to. Must be more than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional):","of the phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float()","int = 100, center: bool = False, norm_vars: bool = False, ) ->","amin)) top_db (float or None, optional): Minimum negative cut-off in decibels. A reasonable","etc. If None, then the complex spectrum is returned instead. normalized (bool): Whether","= quantization_channels - 1.0 if not x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu,","the first pass of decoding -- not the final version of the features,","torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs def create_fb_matrix( n_freqs: int, f_min: float,","((x_mu) / mu) * 2 - 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) *","Frequencies in Hz mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default:","on Acoustics, Speech and Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049.","specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n, n + 1, 1,","waveform.shape[0] dtype = waveform.dtype device = waveform.device last_window_start = last_window_end = -1 cur_sum","be uniformly sampled from [0, mask_param] mask_value (float): Value to assign to the","(float): If power equals 1, will compute DB to power. If 0.5, will","STFT spectrogram of dimension (..., freq, frames) where freq is ``n_fft // 2","(fb matrix) of size (``n_freqs``, ``n_mels``) meaning number of frequencies to highlight/apply to","(bool, default = false) norm_vars (bool, optional): If true, normalize variance to one.","= torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device)","the same number of frames. (default: True) Returns: Tensor: Pitch feature. Shape: ``(batch,","# twice sum of integer squared denom = n * (n + 1)","so that the number of frames is the file size divided by the","pitch extraction. A non-critical parameter; the frame at which we recompute some of","import Optional, Tuple import torch from torch import Tensor from torchaudio._internal import module_utils","\"DB_to_amplitude\", \"compute_deltas\", \"compute_kaldi_pitch\", \"create_fb_matrix\", \"create_dct\", \"compute_deltas\", \"detect_pitch_frequency\", \"DB_to_amplitude\", \"mu_law_encoding\", \"mu_law_decoding\", \"complex_norm\", \"angle\", \"magphase\",","either magnitude-only or complex. Args: waveform (Tensor): Tensor of audio of dimension (...,",") # Update our phase estimates angles = rebuilt if momentum: angles =","= angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0,","dimension (..., freq, time) Example >>> specgram = torch.randn(1, 40, 1000) >>> delta","True, compression: Optional[float] = None, encoding: Optional[str] = None, bits_per_sample: Optional[int] = None,","deltas at time :math:`t`, :math:`c_t` is the spectrogram coeffcients at time :math:`t`, :math:`N`",") return fb def create_dct( n_mfcc: int, n_mels: int, norm: Optional[str] ) ->","``[channel, time]`` else ``[time, channel]``. \"\"\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first,","= \"htk\", ) -> Tensor: r\"\"\"Create a frequency bin conversion matrix. Args: n_freqs","def mu_law_encoding( x: Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Encode signal based on","the angle of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(...,","window_start + cmn_window else: window_start = t - cmn_window window_end = t +","spectrogram from the power/amplitude scale to the decibel scale. The output of each","shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate,","freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs def create_fb_matrix(",") -> Tensor: r\"\"\" Apply a mask along ``axis``. Mask will be applied","x_db def DB_to_amplitude( x: Tensor, ref: float, power: float ) -> Tensor: r\"\"\"Turn","power (float): Power of the norm. (Default: `1.0`). Returns: Tensor: Power of the","https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor ) -> Tensor: r\"\"\"Compute","mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu)","for lag in range(1, lags + 1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[...,","1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) # create","hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack batch spec_f","mels = min_log_mel + math.log(freq / min_log_hz) / logstep return mels def _mel_to_hz(mels:","of `(..., freq, time, complex=2)` rate (float): Speed-up factor phase_advance (Tensor): Expected phase","is defined as the weighted average of the frequency values, weighted by their","\"compute_kaldi_pitch\", \"create_fb_matrix\", \"create_dct\", \"compute_deltas\", \"detect_pitch_frequency\", \"DB_to_amplitude\", \"mu_law_encoding\", \"mu_law_decoding\", \"complex_norm\", \"angle\", \"magphase\", \"phase_vocoder\", 'mask_along_axis',",">>> specgram = torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram) >>> delta2 =","``uniform(0, max_v - v)``. All examples will have the same mask interval. Args:","int = 5, mode: str = \"replicate\" ) -> Tensor: r\"\"\"Compute delta coefficients","0'.format(momentum) if normalized: warnings.warn( \"The argument normalized is not used in Griffin-Lim, \"","= 0 if center: window_start = t - cmn_window // 2 window_end =","window (Tensor): Window tensor that is applied/multiplied to each frame/window n_fft (int): Size","result would be ``A * create_fb_matrix(A.size(-1), ...)``. \"\"\" if norm is not None","1025, 512 >>> # (channel, freq, time, complex=2) >>> complex_specgrams = torch.randn(2, freq,","freqs = f_min + f_sp * mels # And now the nonlinear scale","false, the incomplete frames near the ending edge won't be snipped, so that","-1) return values def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float = 10","complex spectrum is returned instead. normalized (bool): Whether to normalize by magnitude after","Only relevant for compatibility with online pitch extraction. A non-critical parameter; the frame","is the file size divided by the frame-shift. This makes different types of","decibel scale. The output of each tensor in a batch depends on the","masked will be uniformly sampled from [0, mask_param] mask_value (float): Value to assign","(mels[log_t] - min_log_mel)) return freqs def create_fb_matrix( n_freqs: int, f_min: float, f_max: float,","Output tensor in decibel scale \"\"\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db","> 0: # TODO add \"with torch.no_grad():\" back when JIT supports it waveform","Reference which the output will be scaled by. power (float): If power equals","freq, 300, 2) >>> rate = 1.3 # Speed up by 30% >>>","EPSILON = 10 ** (-9) freq = sample_rate / (EPSILON + indices.to(torch.float)) #","initialize the phase batch, freq, frames = specgram.size() if rand_init: angles = 2","Tensor of audio of dimension (..., time) pad (int): Two sided padding of","# Compute Phase Accum phase = phase + phase_advance phase = torch.cat([phase_0, phase[...,","the number of filterbanks. Each column is a filterbank so that assuming there","dct *= math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int","hop between STFT windows win_length (int): Window size power (float or None): Exponent","= (-1.0 * slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:,","CMN computation (int, default = 600) min_cmn_window (int, optional): Minimum CMN window used","above 1 may not converge. length (int or None): Array length of the","Tensor: Input after mu-law decoding \"\"\" mu = quantization_channels - 1.0 if not","optional): Highest frequency that can be detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor","window hops (n_frame). \"\"\" if pad > 0: # TODO add \"with torch.no_grad():\"","frame_to_add if norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames = window_end - window_start","r\"\"\" Compute the spectral centroid for each channel along the time axis. The","recompute_frame (int, optional): Only relevant for compatibility with online pitch extraction. A non-critical","-2, -1)) - top_db).view(-1, 1, 1, 1)) # Repack batch x_db = x_db.reshape(shape)","the last dimension corresponds to pitch and NCCF. Reference: - A pitch extraction","Returns: freqs (Tensor): Mels converted in Hz \"\"\" if mel_scale not in ['slaney',","(default: 1000) resample_frequency (float, optional): Frequency that we down-sample the signal to. Must","Returns: Tensor: Output tensor in decibel scale \"\"\" x_db = multiplier * torch.log10(torch.clamp(x,","in power/amplitude scale. \"\"\" return ref * torch.pow(torch.pow(10.0, 0.1 * x), power) def","0 if last_window_start == -1: input_part = waveform[:, window_start: window_end - window_start, :]","(frame_to_add ** 2) window_frames = window_end - window_start last_window_start = window_start last_window_end =","the file size divided by the frame-shift. This makes different types of features","of dimension (..., frame) \"\"\" input_shape = waveform.shape num_frames, num_feats = input_shape[-2:] waveform","\\times \\text{hop\\_length}`. Default: ``True`` pad_mode (string, optional): controls the padding method used when","frequency that can be detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor of freq","or \"slaney\".') if mel_scale == \"htk\": return 2595.0 * math.log10(1.0 + (freq /","x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1, 1)) # Repack","torch.cat(output_lag, -1) return nccf def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh:","Invert with our current estimate of the phases inverse = torch.istft(specgram * angles,","freq, time) sample_rate (int): The sample rate of the waveform (Hz) frame_time (float,","librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided,","= specgram.size() if rand_init: angles = 2 * math.pi * torch.rand(batch, freq, frames)","norm_vars: if window_frames == 1: cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats, dtype=dtype,","mask_start) & (mask < mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams def","based on mu-law companding. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This","\" \"please use `normalized=False`.\") # pack batch shape = specgram.size() specgram = specgram.reshape([-1]","n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft(","(pad, pad), \"constant\") # pack batch shape = waveform.size() waveform = waveform.reshape(-1, shape[-1])","form `(batch, channel, freq, time)`. multiplier (float): Use 10. for power and 20.","= f_pts[1:] - f_pts[:-1] # (n_mels + 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1)","previous iterate to 0 rebuilt = torch.tensor(0.) for _ in range(n_iter): # Store",">= mask_start) & (mask < mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams","freq_low: int ) -> Tensor: r\"\"\" Compute Normalized Cross-Correlation Function (NCCF). .. math::","first half of lags, then the latter is taken. \"\"\" lag_min = int(math.ceil(sample_rate","win_length (int, optional): The window length for median smoothing (in number of frames)","number of window hops (n_frame). \"\"\" if pad > 0: # TODO add","2) # create overlapping triangles zero = torch.zeros(1) down_slopes = (-1.0 * slopes[:,","= (win_length - 1) // 2 # twice sum of integer squared denom","r\"\"\"Create a spectrogram or a batch of spectrograms from a raw audio signal.","sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width,","extraction. A non-critical parameter; the frame at which we recompute some of the","rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True,","``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio of dimension (..., freq, time) win_length","* torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) #","last dimension corresponds to pitch and NCCF. Reference: - A pitch extraction algorithm","over the given window. \"\"\" # Centered windowed pad_length = (win_length - 1)","x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu return x",") -> Tensor: r\"\"\"Compute the norm of complex tensor input. Args: complex_tensor (Tensor):","0) simulate_first_pass_online (bool, optional): If true, the function will output features that correspond","int, n_mels: int, norm: Optional[str] ) -> Tensor: r\"\"\"Create a DCT transformation matrix","0 recovers the original Griffin-Lim method. Values near 1 can lead to faster","also ```channels_first```. sample_rate (int): Sample rate of the audio waveform. format (str): File","indices = _median_smoothing(indices, win_length) # Convert indices to frequency EPSILON = 10 **","pad_length = (win_length - 1) // 2 # \"replicate\" padding in any dimension","median smoothing to the 1D tensor over the given window. \"\"\" # Centered","0.1) lowpass_cutoff (float, optional): Cutoff frequency for LowPass filter (Hz) (default: 1000) resample_frequency","- cmn_window window_end = t + 1 if window_start < 0: window_end -=","sample_rate, channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes,","waveform (Tensor): The input waveform of shape `(..., time)`. sample_rate (float): Sample rate","/= window.pow(2.).sum().sqrt() if power is not None: if power == 1.0: return spec_f.abs()","p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 - angle_0 -","= specgram.dtype # pack batch shape = specgram.size() specgram = specgram.reshape(1, -1, shape[-1])","is the default. (default: False) Relevant if ``frames_per_chunk > 0``. recompute_frame (int, optional):","size (``n_freqs``, ``n_mels``) meaning number of frequencies to highlight/apply to x the number","from [0, mask_param] mask_value (float): Value to assign to the masked columns axis","The transformation matrix, to be right-multiplied to row-wise data of size (``n_mels``, ``n_mfcc``).","which is the default. (default: False) Relevant if ``frames_per_chunk > 0``. recompute_frame (int,","this warning, \" \"please use `normalized=False`.\") # pack batch shape = specgram.size() specgram","torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1, :] else:","p)) # Compute lags output_lag = [] for lag in range(1, lags +","normalized depending on norm. Args: n_mfcc (int): Number of mfc coefficients to retain","momentum: float, length: Optional[int], rand_init: bool ) -> Tensor: r\"\"\"Compute waveform from a","int, format: str, channels_first: bool = True, compression: Optional[float] = None, encoding: Optional[str]","of (..., time), where time equals the ``length`` parameter if given. \"\"\" assert","freq of dimension (..., frame) \"\"\" # pack batch shape = list(waveform.size()) waveform","of `(..., )` \"\"\" # Replace by torch.norm once issue is fixed #","mel band (area normalization). (Default: ``None``) mel_scale (str, optional): Scale to use: ``htk``","1. Args: x (Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor:","recompute_frame: int = 500, snip_edges: bool = True, ) -> torch.Tensor: \"\"\"Extract pitch","Exponent for the magnitude spectrogram, (must be > 0) e.g., 1 for energy,","= specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) * mask_param min_value","# TODO add \"with torch.no_grad():\" back when JIT supports it waveform = torch.nn.functional.pad(waveform,","2.0 else: assert norm == \"ortho\" dct[0] *= 1.0 / math.sqrt(2.0) dct *=","Per batch example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask","padding method used when :attr:`center` is ``True``. Default: ``\"reflect\"`` onesided (bool, optional): controls","recovery process. momentum (float): The momentum parameter for fast Griffin-Lim. Setting this to","= waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor, multiplier: float, amin:","bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max,","& (mask < mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams def mask_along_axis(","def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float = 0.99 )","= 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep = math.log(6.4) /","= 0, frames_per_chunk: int = 0, simulate_first_pass_online: bool = False, recompute_frame: int =","complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams: Tensor, rate:","a filterbank so that assuming there is a matrix A of size (...,","n), mode=mode) kernel = torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1)","(new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long())","to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: mels (float): Frequency in Mels","applied result would be ``A * create_fb_matrix(A.size(-1), ...)``. \"\"\" if norm is not","``n_fft``) power (float): Exponent for the magnitude spectrogram, (must be > 0) e.g.,","complex_tensor: Tensor, power: float = 1.0 ) -> Tensor: r\"\"\"Compute the norm of","\"htk\" or \"slaney\".') if mel_scale == \"htk\": return 700.0 * (10.0**(mels / 2595.0)","mfc coefficients to retain n_mels (int): Number of mel filterbanks norm (str or","mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. Args: specgrams (Tensor): Real spectrograms","* (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert","CMN window used at start of decoding (adds latency only at start). Only","= input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype","device = waveform.device last_window_start = last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype,","or None) Returns: Tensor: The transformation matrix, to be right-multiplied to row-wise data","assert norm == \"ortho\" dct[0] *= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 /","\"replicate\" padding in any dimension indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\"constant\", value=0.","freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length /","size Returns: Tensor: Dimension (..., time) \"\"\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft,","decibels. A reasonable number is 80. (Default: ``None``) Returns: Tensor: Output tensor in","norm is not None and norm != \"slaney\": raise ValueError(\"norm must be one","in hertz f_diff = f_pts[1:] - f_pts[:-1] # (n_mels + 1) slopes =","\"\"\" if axis != 2 and axis != 3: raise ValueError('Only Frequency and","detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor of freq of dimension (..., frame)","+= torch.cumsum(input_part ** 2, 1)[:, -1, :] else: if window_start > last_window_start: frame_to_remove","variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform =","the decibel scale to the power/amplitude scale. Args: x (Tensor): Input tensor before","phase_acc = torch.cumsum(phase, -1) mag = alphas * norm_1 + (1 - alphas)","= mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch","the frame at which we recompute some of the forward pointers, after revising","torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented, _ =","float = 0.99 ) -> Tuple[Tensor, Tensor]: \"\"\" Take value from first if","phase def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor ) -> Tensor: r\"\"\"Given","dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value) #","n_fft: int, hop_length: int, win_length: int, power: Optional[float], normalized: bool, center: bool =","Expand batch shape = x_db.size() packed_channels = shape[-3] if x_db.dim() > 2 else","= torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True,","_hz_to_mel(freq: float, mel_scale: str = \"htk\") -> float: r\"\"\"Convert Hz to Mels. Args:","using normalized cross-correlation function and median smoothing. Args: waveform (Tensor): Tensor of audio","if ``frames_per_chunk > 0``. (default: 500) snip_edges (bool, optional): If this is set","f_diff = f_pts[1:] - f_pts[:-1] # (n_mels + 1) slopes = f_pts.unsqueeze(0) -","Relevant if ``frames_per_chunk > 0``. recompute_frame (int, optional): Only relevant for compatibility with","_median_smoothing(indices, win_length) # Convert indices to frequency EPSILON = 10 ** (-9) freq","will be applied from indices ``[v_0, v_0 + v)``, where ``v`` is sampled","Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \"\"\" shape = waveform.shape waveform","the nonlinear scale min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp","1`` bins hop_length (int): Length of hop between STFT windows. ( Default: ``win_length","will compute DB to amplitude. Returns: Tensor: Output tensor in power/amplitude scale. \"\"\"","1`` and ``n_fft`` is the number of Fourier bins, and time is the","shape[-1]) assert win_length >= 3 n = (win_length - 1) // 2 #","(Tensor): Mel frequencies mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default:","n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack batch","that we allow pitch tracking to introduce into the feature processing (affects output","Args: specgram (Tensor): A magnitude-only STFT spectrogram of dimension (..., freq, frames) where","<NAME>, <NAME> and <NAME> 2014 IEEE International Conference on Acoustics, Speech and Signal","min_f0: float = 50, max_f0: float = 400, soft_min_f0: float = 10.0, penalty_factor:","= waveform.dtype device = waveform.device last_window_start = last_window_end = -1 cur_sum = torch.zeros(num_channels,","``n_fft`` is the number of Fourier bins, and time is the number of","/ min_log_hz) / logstep return mels def _mel_to_hz(mels: Tensor, mel_scale: str = \"htk\")","int, window: Tensor, n_fft: int, hop_length: int, win_length: int, power: Optional[float], normalized: bool,","n_mels) up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero,","is not None and norm == \"slaney\": # Slaney-style mel is scaled to","n + 1) / 3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel =","If false, window is to the left. (bool, default = false) norm_vars (bool,","modifying pitch by a factor of ``rate``. Args: complex_specgrams (Tensor): Dimension of `(...,","audio waveform pad (int): Two sided padding of signal window (Tensor): Window tensor","torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu + 1) / 2 *","transform,\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor): A","unpack batch output = output.reshape(shape) return output def _compute_nccf( waveform: Tensor, sample_rate: int,","Pitch feature. Shape: ``(batch, frames 2)`` where the last dimension corresponds to pitch","(int): Window size Returns: Tensor: Dimension (..., time) \"\"\" specgram = spectrogram(waveform, pad=pad,","int ) -> Tensor: r\"\"\" Apply median smoothing to the 1D tensor over","(float): Frequency in Mels \"\"\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale","# Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins, freq,","and norm != \"slaney\": raise ValueError(\"norm must be one of None or 'slaney'\")","(2 * n + 1) / 3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode)","soft_min_f0 (float, optional): Minimum f0, applied in soft way, must not exceed min-f0","pack batch shape = list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform,","batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor, cmn_window:","None, bits_per_sample: Optional[int] = None, ) -> Tensor: r\"\"\" Apply codecs as a","(Hz) n_mels (int): Number of mel filterbanks sample_rate (int): Sample rate of the","between 0 and quantization_channels - 1 and returns a signal scaled between -1","amplitude. Returns: Tensor: Output tensor in power/amplitude scale. \"\"\" return ref * torch.pow(torch.pow(10.0,","at which we recompute some of the forward pointers, after revising our estimate","== 1: cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance","power/amplitude scale. \"\"\" return ref * torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq:",") -> Tensor: r\"\"\"Encode signal based on mu-law companding. For more info see","Tensor: Tensor of freq of dimension (..., frame) \"\"\" # pack batch shape","among all the lags is very close to the first half of lags,","def _hz_to_mel(freq: float, mel_scale: str = \"htk\") -> float: r\"\"\"Convert Hz to Mels.","Tensor): The magnitude and phase of the complex tensor \"\"\" mag = complex_norm(complex_tensor,","fb def create_dct( n_mfcc: int, n_mels: int, norm: Optional[str] ) -> Tensor: r\"\"\"Create","Returns: Tensor: Masked spectrograms of dimensions (batch, channel, freq, time) \"\"\" if axis","list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor, cmn_window: int = 600, min_cmn_window: int","with online pitch extraction. A non-critical parameter; the frame at which we recompute","and returns a signal scaled between -1 and 1. Args: x_mu (Tensor): Input","(Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law","spectrogram coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of","cmn_window // 2 window_end = window_start + cmn_window else: window_start = t -","(affects output only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int,","unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor,","norm_vars: bool = False, ) -> Tensor: r\"\"\" Apply sliding-window cepstral mean (and","Tensor, power: float = 1.0 ) -> Tensor: r\"\"\"Compute the norm of complex","freq, time) win_length (int, optional): The window length used for computing delta (Default:","quiet frames (default: 7000) lowpass_filter_width (int, optional): Integer that determines filter width of","waveform (Tensor): Tensor of audio of dimension (..., freq, time) cmn_window (int, optional):","float = 25.0, frame_shift: float = 10.0, min_f0: float = 50, max_f0: float","filter (Hz) (default: 1000) resample_frequency (float, optional): Frequency that we down-sample the signal","= \"htk\") -> float: r\"\"\"Convert Hz to Mels. Args: freqs (float): Frequencies in","-> Tensor: r\"\"\"Create a spectrogram or a batch of spectrograms from a raw","# (n_mels + 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels +","true, normalize variance to one. (bool, default = false) Returns: Tensor: Tensor of",":math:`b_i` is the beginning of frame :math:`i`, :math:`E(j)` is the energy :math:`\\sum_{n=j}^{j+N-1} w^2(n)`.","when :attr:`center` is ``True``. Default: ``\"reflect\"`` onesided (bool, optional): controls whether to return","on norm. Args: n_mfcc (int): Number of mfc coefficients to retain n_mels (int):","= torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu","Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law decoding","+ N-1} w(n) w(m+n)}{\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\phi_i(m)` is the NCCF at frame :math:`i`","Take value from first if bigger than a multiplicative factor of the second,","min-f0 (default: 10.0) penalty_factor (float, optional): Cost factor for FO change. (default: 0.1)","norm. Args: n_mfcc (int): Number of mfc coefficients to retain n_mels (int): Number","assert mask_end - mask_start < mask_param if axis == 1: specgram[:, mask_start:mask_end] =","512 >>> # (channel, freq, time, complex=2) >>> complex_specgrams = torch.randn(2, freq, 300,","b[0] indices = mask * a[1] + ~mask * b[1] return values, indices","not None: if power == 1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def","def griffinlim( specgram: Tensor, window: Tensor, n_fft: int, hop_length: int, win_length: int, power:","number is 80. (Default: ``None``) Returns: Tensor: Output tensor in decibel scale \"\"\"","the given window. \"\"\" # Centered windowed pad_length = (win_length - 1) //","expected output. rand_init (bool): Initializes phase randomly if True, to zero otherwise. Returns:","time) sample_rate (int): The sample rate of the waveform (Hz) frame_time (float, optional):","channel]``. compression (float): Used for formats other than WAV. For mor details see","row-wise data of size (``n_mels``, ``n_mfcc``). \"\"\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k","filter banks (fb matrix) of size (``n_freqs``, ``n_mels``) meaning number of frequencies to","optional): whether to pad :attr:`waveform` on both sides so that the :math:`t`-th frame","specgram.size() if rand_init: angles = 2 * math.pi * torch.rand(batch, freq, frames) else:","2595.0) - 1.0) # Fill in the linear scale f_min = 0.0 f_sp","(``n_mels``, ``n_mfcc``). \"\"\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct =","multiplier: float, amin: float, db_multiplier: float, top_db: Optional[float] = None ) -> Tensor:","magnitude and phase of the complex tensor \"\"\" mag = complex_norm(complex_tensor, power) phase","math.pi)) # Compute Phase Accum phase = phase + phase_advance phase = torch.cat([phase_0,","mask_param (int): Number of columns to be masked will be uniformly sampled from","\"\"\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power: float =","\"mu_law_encoding\", \"mu_law_decoding\", \"complex_norm\", \"angle\", \"magphase\", \"phase_vocoder\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \"spectral_centroid\", \"apply_codec\", ] def","2 # twice sum of integer squared denom = n * (n +","for running average CMN computation (int, default = 600) min_cmn_window (int, optional): Minimum","torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats))","will output features that correspond to what an online decoder would see in","* mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value) # Create","= false) norm_vars (bool, optional): If true, normalize variance to one. (bool, default","power: float, normalized: bool, n_iter: int, momentum: float, length: Optional[int], rand_init: bool )","int ) -> Tensor: r\"\"\" Compute Normalized Cross-Correlation Function (NCCF). .. math:: \\phi_i(m)",">>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with 231 == ceil(300","num_channels = waveform.shape[0] dtype = waveform.dtype device = waveform.device last_window_start = last_window_end =","(win_length - 1) // 2 # twice sum of integer squared denom =","Otherwise, they have dimension ``[time, channel]``. compression (float): Used for formats other than","waveform norm (Optional[str]): If 'slaney', divide the triangular mel weights by the width","= None ) -> Tensor: r\"\"\"Turn a spectrogram from the power/amplitude scale to",") -> Tensor: r\"\"\"Create a spectrogram or a batch of spectrograms from a","/ float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int ) -> Tensor:","num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels,","= 0 window_end = 0 if center: window_start = t - cmn_window //","= compute_deltas(delta) \"\"\" device = specgram.device dtype = specgram.dtype # pack batch shape","be one of \"htk\" or \"slaney\".') if mel_scale == \"htk\": return 2595.0 *","hop_length (int): Length of hop between STFT windows win_length (int): Window size Returns:","frames 2)`` where the last dimension corresponds to pitch and NCCF. Reference: -","(float): Minimum frequency (Hz) f_max (float): Maximum frequency (Hz) n_mels (int): Number of","Tensor, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, power: Optional[float],","frames = specgram.size() if rand_init: angles = 2 * math.pi * torch.rand(batch, freq,","in the first pass of decoding -- not the final version of the","start of decoding (adds latency only at start). Only applicable if center ==","phase = phase + phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc =","_ = torch.median(roll, -1) return values def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time:","resample_frequency (float, optional): Frequency that we down-sample the signal to. Must be more","(bool): Whether to normalize by magnitude after stft center (bool, optional): whether to",":math:`c_t` is the spectrogram coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram","signal encoded with values from 0 to quantization_channels - 1. Args: x (Tensor):","200.0 / 3 freqs = f_min + f_sp * mels # And now","Tensor: r\"\"\" Apply a mask along ``axis``. Mask will be applied from indices","= torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag = [] for lag in",":py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding for the supported formats. For more","complex_tensor (Tensor): Tensor shape of `(..., complex=2)` Return: Tensor: Angle of a complex","last_window_end = window_end cmn_waveform[:, t, :] = waveform[:, t, :] - cur_sum /","Tensor, sample_rate: int, format: str, channels_first: bool = True, compression: Optional[float] = None,","signal energy. Relevant if ``frames_per_chunk > 0``. (default: 500) snip_edges (bool, optional): If","float ) -> Tensor: r\"\"\"Turn a tensor from the decibel scale to the","v_0 + v)``, where ``v`` is sampled from ``uniform(0, mask_param)``, and ``v_0`` from","the lags is very close to the first half of lags, then the","one mel filterbank has all zero values. \" f\"The value for `n_mels` ({n_mels})","is the NCCF at frame :math:`i` with lag :math:`m`, :math:`w` is the waveform,","effects=[[\"rate\", f\"{sample_rate}\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float,","of dimension (..., freq, time) cmn_window (int, optional): Window in frames for running","(Default: ``5``) mode (str, optional): Mode parameter passed to padding (Default: ``\"replicate\"``) Returns:","onesided (bool, optional): controls whether to return half of results to avoid redundancy.","def spectral_centroid( waveform: Tensor, sample_rate: int, pad: int, window: Tensor, n_fft: int, hop_length:","1) upsample_filter_width (int, optional): Integer that determines filter width when upsampling NCCF. (default:","= int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames","hop_length = 1025, 512 >>> # (channel, freq, time, complex=2) >>> complex_specgrams =","range(1, lags + 1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2","from modified short-time Fourier transform,\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984.","Dimension of `(..., freq, time, complex=2)` rate (float): Speed-up factor phase_advance (Tensor): Expected","(default: 0) frames_per_chunk (int, optional): The number of frames used for energy normalization.","least one mel filterbank has all zero values. \" f\"The value for `n_mels`","phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag = alphas * norm_1 +","our estimate of the signal energy. Relevant if ``frames_per_chunk > 0``. (default: 500)","[1]. This function computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor):",">>> phase_advance = torch.linspace( >>> 0, math.pi * hop_length, freq)[..., None] >>> x","int, power: float, normalized: bool, n_iter: int, momentum: float, length: Optional[int], rand_init: bool","= waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames = ( (s1 * s2).sum(-1)","angles - tprev.mul_(momentum / (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the","pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1)","our current estimate of the phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length,","complex tensor. Shape of `(..., )` \"\"\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def","5, max_frames_latency: int = 0, frames_per_chunk: int = 0, simulate_first_pass_online: bool = False,","> t: window_end = max(t + 1, min_cmn_window) if window_end > num_frames: window_start","NCCF. (default: 5) max_frames_latency (int, optional): Maximum number of frames of latency that","A magnitude-only STFT spectrogram of dimension (..., freq, frames) where freq is ``n_fft","centered median smoothing, and convert to frequency. Note: If the max among all","Length of hop between STFT windows win_length (int): Window size Returns: Tensor: Dimension","-> Tensor: r\"\"\" Apply codecs as a form of augmentation. Args: waveform (Tensor):","Kaldi. Args: waveform (Tensor): The input waveform of shape `(..., time)`. sample_rate (float):","optional): Minimum negative cut-off in decibels. A reasonable number is 80. (Default: ``None``)","Tensor of audio of dimension (..., freq, time) win_length (int, optional): The window","second, elementwise. \"\"\" mask = (a[0] > thresh * b[0]) values = mask","batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if power","(a[0] > thresh * b[0]) values = mask * a[0] + ~mask *","waveform = torch.nn.functional.pad(waveform, (pad, pad), \"constant\") # pack batch shape = waveform.size() waveform","t, :] = waveform[:, t, :] - cur_sum / window_frames if norm_vars: if","(Tensor): Input tensor before being converted to power/amplitude scale. ref (float): Reference which","a frequency bin conversion matrix. Args: n_freqs (int): Number of frequencies to highlight/apply","waveform from a linear scale magnitude spectrogram using the Griffin-Lim transformation. Implementation ported",":math:`d_t` is the deltas at time :math:`t`, :math:`c_t` is the spectrogram coeffcients at","return output def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float, freq_low: int )","/ window_frames if norm_vars: if window_frames == 1: cmn_waveform[:, t, :] = torch.zeros(","> 1 can be unstable'.format(momentum) assert momentum >= 0, 'momentum={} < 0'.format(momentum) if","Speed-up factor phase_advance (Tensor): Expected phase advance in each bin. Dimension of (freq,","of audio of dimension (..., freq, time) sample_rate (int): The sample rate of","output of each tensor in a batch depends on the maximum value of","sample_rate: float, frame_length: float = 25.0, frame_shift: float = 10.0, min_f0: float =","in python.\" In Proceedings of the 14th python in science conference, pp. 18-25.","1) // 2 # \"replicate\" padding in any dimension indices = torch.nn.functional.pad( indices,","Log10(max(reference value and amin)) top_db (float or None, optional): Minimum negative cut-off in","= mask_value else: raise ValueError('Only Frequency and Time masking are supported') # unpack","encoding, bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\"rate\", f\"{sample_rate}\"]], channels_first=channels_first, format=format)","windows win_length (int): Window size Returns: Tensor: Dimension (..., time) \"\"\" specgram =","4000, delta_pitch: float = 0.005, nccf_ballast: float = 7000, lowpass_filter_width: int = 1,","for `n_freqs` ({n_freqs}) may be set too low.\" ) return fb def create_dct(","= None, mel_scale: str = \"htk\", ) -> Tensor: r\"\"\"Create a frequency bin","at frame :math:`i` with lag :math:`m`, :math:`w` is the waveform, :math:`N` is the","all zero values. \" f\"The value for `n_mels` ({n_mels}) may be set too","1 for energy, 2 for power, etc. If None, then the complex spectrum","in ['slaney', 'htk']: raise ValueError('mel_scale should be one of \"htk\" or \"slaney\".') if","freq, time) Example >>> specgram = torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram)","time) cmn_window (int, optional): Window in frames for running average CMN computation (int,","specgram: Tensor, window: Tensor, n_fft: int, hop_length: int, win_length: int, power: float, normalized:","int, win_length: int, power: float, normalized: bool, n_iter: int, momentum: float, length: Optional[int],","str = \"htk\") -> Tensor: \"\"\"Convert mel bin numbers to frequencies. Args: mels","= True, ) -> torch.Tensor: \"\"\"Extract pitch based on method described in [1].","this to 0 recovers the original Griffin-Lim method. Values near 1 can lead","scale \"\"\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier","float = 10 ** (-2), win_length: int = 30, freq_low: int = 85,","x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with 231 == ceil(300 /","(-2), win_length: int = 30, freq_low: int = 85, freq_high: int = 3400,","1, 1)) # Repack batch x_db = x_db.reshape(shape) return x_db def DB_to_amplitude( x:","if power == 1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram:","torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu =","faster convergence, but above 1 may not converge. length (int or None): Array","version of the features, which is the default. (default: False) Relevant if ``frames_per_chunk","-- not the final version of the features, which is the default. (default:","torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack batch output = output.reshape(shape) return output","running average CMN computation (int, default = 600) min_cmn_window (int, optional): Minimum CMN","complex=2)` power (float): Power of the norm. (Default: `1.0`) Returns: (Tensor, Tensor): The","Reference: - A pitch extraction algorithm tuned for automatic speech recognition <NAME>, <NAME>,","# pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value =","dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack batch","= false) Returns: Tensor: Tensor of freq of dimension (..., frame) \"\"\" input_shape","input and output Tensor have dimension ``[channel, time]``. Otherwise, they have dimension ``[time,","s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size,","is returned instead. normalized (bool): Whether to normalize by magnitude after stft center","see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values between 0","returns a signal scaled between -1 and 1. Args: x_mu (Tensor): Input tensor","value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert mask_end - mask_start","None) Returns: Tensor: The transformation matrix, to be right-multiplied to row-wise data of","torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 - angle_0 - phase_advance phase = phase","FO change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency for LowPass filter (Hz)","integer squared denom = n * (n + 1) * (2 * n","format (str): File format. channels_first (bool): When True, both the input and output","input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float): Power of","(batch, channel, freq, time) mask_param (int): Number of columns to be masked will","-> Tensor: r\"\"\" Apply sliding-window cepstral mean (and optionally variance) normalization per utterance.","described in [1]. This function computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args:","Frequency that we down-sample the signal to. Must be more than twice lowpass-cutoff.",">>> delta2 = compute_deltas(delta) \"\"\" device = specgram.device dtype = specgram.dtype # pack","- tprev.mul_(momentum / (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final","(int, optional): Integer that determines filter width of lowpass filter, more gives sharper","lags output_lag = [] for lag in range(1, lags + 1): s1 =","pad_mode (string, optional): controls the padding method used when :attr:`center` is ``True``. Default:","waveform.shape waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0,","Normalized Cross-Correlation Function (NCCF). .. math:: \\phi_i(m) = \\frac{\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\sqrt{E(b_i)","Fill in the linear scale f_min = 0.0 f_sp = 200.0 / 3","assuming there is a matrix A of size (..., ``n_freqs``), the applied result","= 0.1, lowpass_cutoff: float = 1000, resample_frequency: float = 4000, delta_pitch: float =","scale. Input should take the form `(..., freq, time)`. Batched inputs should include","be set too low.\" ) return fb def create_dct( n_mfcc: int, n_mels: int,","converted in Hz \"\"\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should","Returns: (Tensor, Tensor): The magnitude and phase of the complex tensor \"\"\" mag","`librosa`. * [1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \"librosa:","audio of dimension (..., freq, time) sample_rate (int): The sample rate of the","specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float, axis:","math import warnings from typing import Optional, Tuple import torch from torch import","f_sp logstep = math.log(6.4) / 27.0 log_t = (mels >= min_log_mel) freqs[log_t] =","frame :math:`i` with lag :math:`m`, :math:`w` is the waveform, :math:`N` is the length","upsample_filter_width (int, optional): Integer that determines filter width when upsampling NCCF. (default: 5)","linear part f_min = 0.0 f_sp = 200.0 / 3 mels = (freq",":] output_frames = ( (s1 * s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2)","is not None: # Expand batch shape = x_db.size() packed_channels = shape[-3] if","IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (pp. 1-4),","part f_min = 0.0 f_sp = 200.0 / 3 mels = (freq -",".. math:: \\phi_i(m) = \\frac{\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\phi_i(m)` is","the energy :math:`\\sum_{n=j}^{j+N-1} w^2(n)`. \"\"\" EPSILON = 10 ** (-9) # Number of","``[time, channel]``. \"\"\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding,","after revising our estimate of the signal energy. Relevant if ``frames_per_chunk > 0``.","list(shape[-2:])) value = torch.rand(1) * mask_param min_value = torch.rand(1) * (specgram.size(axis) - value)","NCCF, apply centered median smoothing, and convert to frequency. Note: If the max","= torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not None and norm == \"slaney\":","spectral centroid is defined as the weighted average of the frequency values, weighted","input with values between 0 and quantization_channels - 1 and returns a signal","phase_0 = angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0,","window: Tensor, n_fft: int, hop_length: int, win_length: int, power: float, normalized: bool, n_iter:","values, indices def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int ) -> Tensor:","device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def","of iteration for phase recovery process. momentum (float): The momentum parameter for fast","* hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape #","complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas","(Tensor): Tensor of audio of dimension (..., freq, time) win_length (int, optional): The","= min_value[..., None, None] mask_end = (min_value + value)[..., None, None] mask =","dct = torch.cos(math.pi / float(n_mels) * (n + 0.5) * k) # size","** 2) / (window_frames ** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :]",":] = waveform[:, t, :] - cur_sum / window_frames if norm_vars: if window_frames","Mels. Args: freqs (float): Frequencies in Hz mel_scale (str, optional): Scale to use:","each frame/window n_fft (int): Size of FFT hop_length (int): Length of hop between","axis: int ) -> Tensor: r\"\"\" Apply a mask along ``axis``. Mask will","mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: mels","specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor, win_length: int","n_iter (int): Number of iteration for phase recovery process. momentum (float): The momentum","= 5, mode: str = \"replicate\" ) -> Tensor: r\"\"\"Compute delta coefficients of","convert to frequency. Note: If the max among all the lags is very","values def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float = 10 ** (-2),","smoothing (in number of frames) (Default: ``30``). freq_low (int, optional): Lowest frequency that","normalized: bool, center: bool = True, pad_mode: str = \"reflect\", onesided: bool =","* a[1] + ~mask * b[1] return values, indices def _find_max_per_frame( nccf: Tensor,","* power) def angle( complex_tensor: Tensor ) -> Tensor: r\"\"\"Compute the angle of","is set to false, the incomplete frames near the ending edge won't be","Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \"\"\" shape = waveform.shape waveform = waveform.reshape(-1,","compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float = 25.0, frame_shift: float = 10.0,","frames_per_chunk (int, optional): The number of frames used for energy normalization. (default: 0)","time]``. Otherwise, they have dimension ``[time, channel]``. compression (float): Used for formats other","complex=2)` power (float): Power of the norm. (Default: `1.0`). Returns: Tensor: Power of","mask_param if axis == 1: specgram[:, mask_start:mask_end] = mask_value elif axis == 2:","if normalized: warnings.warn( \"The argument normalized is not used in Griffin-Lim, \" \"and","= torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\ .to(dtype=specgram.dtype, device=specgram.device) specgram","freqs (float): Frequencies in Hz mel_scale (str, optional): Scale to use: ``htk`` or","For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has","to assign to the masked columns axis (int): Axis to apply masking on","frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames","if norm_vars: cur_sumsq -= (frame_to_remove ** 2) if window_end > last_window_end: frame_to_add =","= 1, upsample_filter_width: int = 5, max_frames_latency: int = 0, frames_per_chunk: int =","point in hertz f_diff = f_pts[1:] - f_pts[:-1] # (n_mels + 1) slopes","Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float): Power of the","phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with 231 == ceil(300 / 1.3) torch.Size([2,","phase batch, freq, frames = specgram.size() if rand_init: angles = 2 * math.pi","t: window_end = max(t + 1, min_cmn_window) if window_end > num_frames: window_start -=","angles = angles - tprev.mul_(momentum / (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) #","Minimum negative cut-off in decibels. A reasonable number is 80. (Default: ``None``) Returns:","complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float, axis: int","the mel band (area normalization). (Default: ``None``) mel_scale (str, optional): Scale to use:","rate of `waveform`. frame_length (float, optional): Frame length in milliseconds. (default: 25.0) frame_shift","mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert mask_end - mask_start <","complex_specgrams (Tensor): Dimension of `(..., freq, time, complex=2)` rate (float): Speed-up factor phase_advance","# Replace by torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 *","Initializes phase randomly if True, to zero otherwise. Returns: torch.Tensor: waveform of (...,","# Fill in the log-scale part min_log_hz = 1000.0 min_log_mel = (min_log_hz -","spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if power is","2``) win_length (int): Window size. (Default: ``n_fft``) power (float): Exponent for the magnitude","math:: d_t = \\frac{\\sum_{n=1}^{\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\sum_{n=1}^{\\text{N}} n^2} where :math:`d_t` is","compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\"rate\", f\"{sample_rate}\"]],","f_min) / f_sp logstep = math.log(6.4) / 27.0 log_t = (mels >= min_log_mel)","+ math.log(freq / min_log_hz) / logstep return mels def _mel_to_hz(mels: Tensor, mel_scale: str","online decoder would see in the first pass of decoding -- not the","the phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() #","imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def","Tensor: r\"\"\"Compute waveform from a linear scale magnitude spectrogram using the Griffin-Lim transformation.","x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu) * 2 -","2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 =","number of frames is the file size divided by the frame-shift. This makes","\"\"\" if norm is not None and norm != \"slaney\": raise ValueError(\"norm must","(str or None): Norm to use (either 'ortho' or None) Returns: Tensor: The","has ``[channel, time]`` else ``[time, channel]``. \"\"\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate,","torch from torch import Tensor from torchaudio._internal import module_utils as _mod_utils import torchaudio","of decoding (adds latency only at start). Only applicable if center == false,","= num_frames if window_start < 0: window_start = 0 if last_window_start == -1:","have dimension ``[time, channel]``. compression (float): Used for formats other than WAV. For","real_stretch = mag * torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch,","of channels Returns: Tensor: Input after mu-law decoding \"\"\" mu = quantization_channels -",".to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate to 0","= window_start + cmn_window else: window_start = t - cmn_window window_end = t","algorithm tuned for automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME>","1, min_cmn_window) if window_end > num_frames: window_start -= (window_end - num_frames) window_end =","= torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size],","optional): Minimum CMN window used at start of decoding (adds latency only at","win_length: int, ) -> Tensor: r\"\"\" Compute the spectral centroid for each channel","True, to zero otherwise. Returns: torch.Tensor: waveform of (..., time), where time equals",":num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames = (","Note: If the max among all the lags is very close to the","int = 0, simulate_first_pass_online: bool = False, recompute_frame: int = 500, snip_edges: bool","// 2 # \"replicate\" padding in any dimension indices = torch.nn.functional.pad( indices, (pad_length,","(default: 400.0) soft_min_f0 (float, optional): Minimum f0, applied in soft way, must not","the forward pointers, after revising our estimate of the signal energy. Relevant if","features, which is the default. (default: False) Relevant if ``frames_per_chunk > 0``. recompute_frame","used in Griffin-Lim, \" \"and will be removed in v0.9.0 release. To suppress","If 'slaney', divide the triangular mel weights by the width of the mel","def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float = 10 ** (-2), win_length:","optional): Duration of a frame (Default: ``10 ** (-2)``). win_length (int, optional): The","this is set to false, the incomplete frames near the ending edge won't","int, win_length: int, ) -> Tensor: r\"\"\" Compute the spectral centroid for each","freq, frames) where freq is ``n_fft // 2 + 1``. window (Tensor): Window",">>> freq, hop_length = 1025, 512 >>> # (channel, freq, time, complex=2) >>>","else ``[time, channel]``. \"\"\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format,","<NAME>, \"Signal estimation from modified short-time Fourier transform,\" IEEE Trans. ASSP, vol.32, no.2,","length=length) # unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB(","None and norm == \"slaney\": # Slaney-style mel is scaled to be approx","0 to quantization_channels - 1. Args: x (Tensor): Input tensor quantization_channels (int): Number","device=device, dtype=dtype) # Per batch example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >=","power (float): Exponent for the magnitude spectrogram, (must be > 0) e.g., 1","torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for","window_end = max(t + 1, min_cmn_window) if window_end > num_frames: window_start -= (window_end","= max(t + 1, min_cmn_window) if window_end > num_frames: window_start -= (window_end -","f0, applied in soft way, must not exceed min-f0 (default: 10.0) penalty_factor (float,","= lags + num_of_frames * frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0, p))","spectrogram or a batch of spectrograms from a raw audio signal. The spectrogram","torch.linspace(0, sample_rate // 2, n_freqs) # calculate mel freq bins m_min = _hz_to_mel(f_min,","Real spectrograms (batch, channel, freq, time) mask_param (int): Number of columns to be","(float): Frequencies in Hz mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``.","win_length: int ) -> Tensor: r\"\"\" Apply median smoothing to the 1D tensor","(default: 4000) delta_pitch( float, optional): Smallest relative change in pitch that our algorithm","spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor, n_fft: int,","mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor: r\"\"\"",") # unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /=","(bool): Whether to normalize by magnitude after stft. n_iter (int): Number of iteration","griffinlim( specgram: Tensor, window: Tensor, n_fft: int, hop_length: int, win_length: int, power: float,","and 1 and returns a signal encoded with values from 0 to quantization_channels","1.3 # Speed up by 30% >>> phase_advance = torch.linspace( >>> 0, math.pi","where time equals the ``length`` parameter if given. \"\"\" assert momentum < 1,","Default: ``True`` Returns: Tensor: Dimension (..., freq, time), freq is ``n_fft // 2","3 -> time) Returns: Tensor: Masked spectrograms of dimensions (batch, channel, freq, time)","For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal","+ ~mask * b[1] return values, indices def _find_max_per_frame( nccf: Tensor, sample_rate: int,","is not None and norm != \"slaney\": raise ValueError(\"norm must be one of","to Mels. Args: freqs (float): Frequencies in Hz mel_scale (str, optional): Scale to","num_frames, num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype device = waveform.device last_window_start =","the function will output features that correspond to what an online decoder would","return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power: float = 1.0","channels Returns: Tensor: Input after mu-law decoding \"\"\" mu = quantization_channels - 1.0","= torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value) # Create broadcastable mask mask_start","# size (n_mfcc, n_mels) if norm is None: dct *= 2.0 else: assert","channel dimension and have the form `(batch, channel, freq, time)`. multiplier (float): Use","apply masking on (2 -> frequency, 3 -> time) Returns: Tensor: Masked spectrograms",") -> Tensor: r\"\"\"Compute the angle of complex tensor input. Args: complex_tensor (Tensor):","n_freqs) # calculate mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max,","Tensor]: r\"\"\"Separate a complex-valued spectrogram with shape `(..., 2)` into its magnitude and","specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor, win_length: int = 5, mode: str","/ mu) * 2 - 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu))","power/amplitude scale. ref (float): Reference which the output will be scaled by. power","the features, which is the default. (default: False) Relevant if ``frames_per_chunk > 0``.","time is the number of window hops (n_frame). \"\"\" if pad > 0:","(-2)``). win_length (int, optional): The window length for median smoothing (in number of","of frames) (Default: ``30``). freq_low (int, optional): Lowest frequency that can be detected","list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices","def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor:","if given. \"\"\" assert momentum < 1, 'momentum={} > 1 can be unstable'.format(momentum)","/ power) # randomly initialize the phase batch, freq, frames = specgram.size() if","2 else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3,","device=device) for t in range(num_frames): window_start = 0 window_end = 0 if center:","A pitch extraction algorithm tuned for automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>,","= math.log(6.4) / 27.0 log_t = (mels >= min_log_mel) freqs[log_t] = min_log_hz *","torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) )","0.99 ) -> Tuple[Tensor, Tensor]: \"\"\" Take value from first if bigger than","\"phase_vocoder\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \"spectral_centroid\", \"apply_codec\", ] def spectrogram( waveform: Tensor, pad: int,","(default: 10.0) min_f0 (float, optional): Minimum F0 to search for (Hz) (default: 50.0)","= None, encoding: Optional[str] = None, bits_per_sample: Optional[int] = None, ) -> Tensor:","variance -= ((cur_sum ** 2) / (window_frames ** 2)) variance = torch.pow(variance, -0.5)","TODO add \"with torch.no_grad():\" back when JIT supports it waveform = torch.nn.functional.pad(waveform, (pad,","must be one of None or 'slaney'\") # freq bins # Equivalent filterbank","in milliseconds. (default: 10.0) min_f0 (float, optional): Minimum F0 to search for (Hz)","``[channel, time]``. Otherwise, they have dimension ``[time, channel]``. compression (float): Used for formats","(Default: `1.0`). Returns: Tensor: Power of the normed input tensor. Shape of `(...,","= specgram.pow(1 / power) # randomly initialize the phase batch, freq, frames =","latency that we allow pitch tracking to introduce into the feature processing (affects","= cur_sumsq variance = variance / window_frames variance -= ((cur_sum ** 2) /","mels def _mel_to_hz(mels: Tensor, mel_scale: str = \"htk\") -> Tensor: \"\"\"Convert mel bin","norm: Optional[str] = None, mel_scale: str = \"htk\", ) -> Tensor: r\"\"\"Create a","None or 'slaney'\") # freq bins # Equivalent filterbank construction by Librosa all_freqs","(Default: `1.0`) Returns: (Tensor, Tensor): The magnitude and phase of the complex tensor","device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1, :]) #","`(..., complex=2)` power (float): Power of the norm. (Default: `1.0`) Returns: (Tensor, Tensor):","from ``uniform(0, max_v - v)``. Args: specgrams (Tensor): Real spectrograms (batch, channel, freq,",") -> torch.Tensor: \"\"\"Extract pitch based on method described in [1]. This function","if power is not None: if power == 1.0: return spec_f.abs() return spec_f.abs().pow(power)","optional): The number of frames used for energy normalization. (default: 0) simulate_first_pass_online (bool,","Input should take the form `(..., freq, time)`. Batched inputs should include a","weighted by their magnitude. Args: waveform (Tensor): Tensor of audio of dimension (...,","torchaudio._internal import module_utils as _mod_utils import torchaudio __all__ = [ \"spectrogram\", \"griffinlim\", \"amplitude_to_DB\",","x_mu: Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Decode mu-law encoded signal. For more","specgram: Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor: r\"\"\" Apply","transformation matrix, to be right-multiplied to row-wise data of size (``n_mels``, ``n_mfcc``). \"\"\"","the deltas at time :math:`t`, :math:`c_t` is the spectrogram coeffcients at time :math:`t`,","shape = specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert win_length >= 3 n","= torch.nn.functional.pad( indices, (pad_length, 0), mode=\"constant\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length *","upsampling NCCF. (default: 5) max_frames_latency (int, optional): Maximum number of frames of latency","win_length >= 3 n = (win_length - 1) // 2 # twice sum","torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) * (n + 0.5) * k) #","= waveform[:, last_window_end, :] cur_sum += frame_to_add if norm_vars: cur_sumsq += (frame_to_add **","else: assert norm == \"ortho\" dct[0] *= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0","tensor, and so may return different values for an audio clip split into","frame/window n_fft (int): Size of FFT hop_length (int): Length of hop between STFT","# unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt()","Returns: Tensor: Power of the normed input tensor. Shape of `(..., )` \"\"\"","dimension (..., freq, time) win_length (int, optional): The window length used for computing","= False, norm_vars: bool = False, ) -> Tensor: r\"\"\" Apply sliding-window cepstral","if not center: if window_end > t: window_end = max(t + 1, min_cmn_window)","smoothing to the 1D tensor over the given window. \"\"\" # Centered windowed","\" \"and will be removed in v0.9.0 release. To suppress this warning, \"","DB_to_amplitude( x: Tensor, ref: float, power: float ) -> Tensor: r\"\"\"Turn a tensor","will be removed in v0.9.0 release. To suppress this warning, \" \"please use","num_feats)) if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform:","10.0, penalty_factor: float = 0.1, lowpass_cutoff: float = 1000, resample_frequency: float = 4000,","average of the frequency values, weighted by their magnitude. Args: waveform (Tensor): Tensor","\\frac{\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\phi_i(m)` is the NCCF at frame","feature processing (affects output only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0)","F0 to search for (Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum f0, applied","controls whether to return half of results to avoid redundancy. Default: ``True`` Returns:","(c_{t+n} - c_{t-n})}{2 \\sum_{n=1}^{\\text{N}} n^2} where :math:`d_t` is the deltas at time :math:`t`,","-1) return nccf def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float","= specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float,","Tensor: r\"\"\"Turn a tensor from the decibel scale to the power/amplitude scale. Args:","(..., time) \"\"\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False)","spectral centroid for each channel along the time axis. The spectral centroid is","Highest frequency that can be detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor of","complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins, freq, 2) complex_specgrams_0 =","30, freq_low: int = 85, freq_high: int = 3400, ) -> Tensor: r\"\"\"Detect","frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk,","converge. length (int or None): Array length of the expected output. rand_init (bool):","= torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 - angle_0 - phase_advance phase =","0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Decode","value of that tensor, and so may return different values for an audio","mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) #","waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p = lags + num_of_frames * frame_size","length used for computing delta (Default: ``5``) mode (str, optional): Mode parameter passed","shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1, 1)) #","/ 1.3) torch.Size([2, 1025, 231, 2]) \"\"\" # pack batch shape = complex_specgrams.size()","def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int ) -> Tensor: r\"\"\" For","Dimension of (freq, 1) Returns: Tensor: Complex Specgrams Stretch with dimension of `(...,","of deltas of dimension (..., freq, time) Example >>> specgram = torch.randn(1, 40,","True, pad_mode: str = \"reflect\", onesided: bool = True ) -> Tensor: r\"\"\"Create","= x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x))","\"At least one mel filterbank has all zero values. \" f\"The value for","length: Optional[int], rand_init: bool ) -> Tensor: r\"\"\"Compute waveform from a linear scale","- all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) # create overlapping triangles zero =","Returns: Tensor: Tensor of freq of dimension (..., frame) \"\"\" # pack batch","else: if window_start > last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum -= frame_to_remove","If 0.5, will compute DB to amplitude. Returns: Tensor: Output tensor in power/amplitude","as the weighted average of the frequency values, weighted by their magnitude. Args:","indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length) # Convert indices to","channels_first (bool): When True, both the input and output Tensor have dimension ``[channel,","* (mels[log_t] - min_log_mel)) return freqs def create_fb_matrix( n_freqs: int, f_min: float, f_max:","lowpass_filter_width: int = 1, upsample_filter_width: int = 5, max_frames_latency: int = 0, frames_per_chunk:","warnings.warn( \"At least one mel filterbank has all zero values. \" f\"The value",":math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio of dimension (..., freq,","use (either 'ortho' or None) Returns: Tensor: The transformation matrix, to be right-multiplied","of \"htk\" or \"slaney\".') if mel_scale == \"htk\": return 700.0 * (10.0**(mels /","audio of dimension (..., freq, time) win_length (int, optional): The window length used","kernel = torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output =","- 1 and returns a signal scaled between -1 and 1. Args: x_mu","waveform, :math:`N` is the length of a frame, :math:`b_i` is the beginning of","Smallest relative change in pitch that our algorithm measures. (default: 0.005) nccf_ballast (float,","complex_specgrams = torch.randn(2, freq, 300, 2) >>> rate = 1.3 # Speed up","bool = False, ) -> Tensor: r\"\"\" Apply sliding-window cepstral mean (and optionally","each stft freq point in hertz f_diff = f_pts[1:] - f_pts[:-1] # (n_mels","(..., frame) \"\"\" input_shape = waveform.shape num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1,","tensor in decibel scale \"\"\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -=","x (Tensor): Input tensor before being converted to power/amplitude scale. ref (float): Reference","to avoid redundancy. Default: ``True`` Returns: Tensor: Dimension (..., freq, time), freq is","*= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \"At least one mel filterbank has","frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag =","a batch of spectrograms from a raw audio signal. The spectrogram can be","torch.cos(math.pi / float(n_mels) * (n + 0.5) * k) # size (n_mfcc, n_mels)","logstep = math.log(6.4) / 27.0 log_t = (mels >= min_log_mel) freqs[log_t] = min_log_hz","indices += 1 return indices def _median_smoothing( indices: Tensor, win_length: int ) ->","method described in [1]. This function computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi.","x the number of filterbanks. Each column is a filterbank so that assuming","augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\"rate\", f\"{sample_rate}\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def","Window tensor that is applied/multiplied to each frame/window n_fft (int): Size of FFT,","None, ) -> Tensor: r\"\"\" Apply codecs as a form of augmentation. Args:","mask * a[1] + ~mask * b[1] return values, indices def _find_max_per_frame( nccf:","str = \"reflect\", onesided: bool = True ) -> Tensor: r\"\"\"Create a spectrogram","of Fourier bins, and time is the number of window hops (n_frame). \"\"\"","when JIT supports it waveform = torch.nn.functional.pad(waveform, (pad, pad), \"constant\") # pack batch","1 can lead to faster convergence, but above 1 may not converge. length","filterbanks sample_rate (int): Sample rate of the audio waveform norm (Optional[str]): If 'slaney',","lowpass_cutoff: float = 1000, resample_frequency: float = 4000, delta_pitch: float = 0.005, nccf_ballast:","float, db_multiplier: float, top_db: Optional[float] = None ) -> Tensor: r\"\"\"Turn a spectrogram","and norm == \"slaney\": # Slaney-style mel is scaled to be approx constant","* mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int )","indices to frequency EPSILON = 10 ** (-9) freq = sample_rate / (EPSILON","with shape (``n_mels``, ``n_mfcc``), normalized depending on norm. Args: n_mfcc (int): Number of","or None): Array length of the expected output. rand_init (bool): Initializes phase randomly","Mask will be applied from indices ``[v_0, v_0 + v)``, where ``v`` is","2 window_end = window_start + cmn_window else: window_start = t - cmn_window window_end","waveform[:, last_window_start, :] cur_sum -= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove ** 2)","not center: if window_end > t: window_end = max(t + 1, min_cmn_window) if","window is to the left. (bool, default = false) norm_vars (bool, optional): If","// 2 + 1``. window (Tensor): Window tensor that is applied/multiplied to each","penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, )","'mask_along_axis_iid', 'sliding_window_cmn', \"spectral_centroid\", \"apply_codec\", ] def spectrogram( waveform: Tensor, pad: int, window: Tensor,","to normalize by magnitude after stft center (bool, optional): whether to pad :attr:`waveform`","2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox()","min_log_mel = (min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0 if","of filterbanks. Each column is a filterbank so that assuming there is a","each tensor in a batch depends on the maximum value of that tensor,","x = ((x_mu) / mu) * 2 - 1.0 x = torch.sign(x) *","`(..., )` \"\"\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power:","zero otherwise. Returns: torch.Tensor: waveform of (..., time), where time equals the ``length``","(Default: ``None``) mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``)","(must be > 0) e.g., 1 for energy, 2 for power, etc. normalized","mel filterbanks norm (str or None): Norm to use (either 'ortho' or None)","stft center (bool, optional): whether to pad :attr:`waveform` on both sides so that","pitch tracking to introduce into the feature processing (affects output only if ``frames_per_chunk","pp. 18-25. 2015. * [2] <NAME>., <NAME>., & <NAME>. \"A fast Griffin-Lim algorithm,\"","tensor from the decibel scale to the power/amplitude scale. Args: x (Tensor): Input","Hz mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns:",":-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag = alphas * norm_1 + (1","if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1, :] else: if window_start","win_length (int): Window size Returns: Tensor: Dimension (..., time) \"\"\" specgram = spectrogram(waveform,","decoding -- not the final version of the features, which is the default.","frames) (Default: ``30``). freq_low (int, optional): Lowest frequency that can be detected (Hz)","\\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate to","is taken. \"\"\" lag_min = int(math.ceil(sample_rate / freq_high)) # Find near enough max","num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype device = waveform.device last_window_start = last_window_end","in decibels. A reasonable number is 80. (Default: ``None``) Returns: Tensor: Output tensor","(int, optional): Changes the bit depth for the supported formats. For more details","float = 1000, resample_frequency: float = 4000, delta_pitch: float = 0.005, nccf_ballast: float","float(n_mels) * (n + 0.5) * k) # size (n_mfcc, n_mels) if norm","triangular mel weights by the width of the mel band (area normalization). (Default:","alphas * norm_1 + (1 - alphas) * norm_0 real_stretch = mag *","for (Hz) (default: 50.0) max_f0 (float, optional): Maximum F0 to search for (Hz)","returns a signal encoded with values from 0 to quantization_channels - 1. Args:","Args: specgram (Tensor): Tensor of audio of dimension (..., freq, time) win_length (int,","2]) # (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps","ValueError(\"norm must be one of None or 'slaney'\") # freq bins # Equivalent","torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast,","sample_rate: int, freq_high: int ) -> Tensor: r\"\"\" For each frame, take the","(1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates waveform","min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs def create_fb_matrix( n_freqs: int,","return specgram def compute_deltas( specgram: Tensor, win_length: int = 5, mode: str =","Whether to normalize by magnitude after stft. n_iter (int): Number of iteration for","to faster convergence, but above 1 may not converge. length (int or None):","of the expected output. rand_init (bool): Initializes phase randomly if True, to zero","types of features give the same number of frames. (default: True) Returns: Tensor:","Axis to apply masking on (1 -> frequency, 2 -> time) Returns: Tensor:","r\"\"\"Given a STFT tensor, speed up in time without modifying pitch by a","Tensor, ref: float, power: float ) -> Tensor: r\"\"\"Turn a tensor from the","zero = torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2]) / f_diff[:-1] # (n_freqs,","Args: mels (Tensor): Mel frequencies mel_scale (str, optional): Scale to use: ``htk`` or","return values, indices def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int ) ->","of frames used for energy normalization. (default: 0) simulate_first_pass_online (bool, optional): If true,","of the forward pointers, after revising our estimate of the signal energy. Relevant","before being converted to decibel scale. Input should take the form `(..., freq,","the feature processing (affects output only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default:","`n_mels` ({n_mels}) may be set too high. \" f\"Or, the value for `n_freqs`","``n_fft // 2 + 1`` and ``n_fft`` is the number of Fourier bins,","the linear scale f_min = 0.0 f_sp = 200.0 / 3 freqs =","specgrams.size(axis), device=device, dtype=dtype) # Per batch example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask","variance = variance / window_frames variance -= ((cur_sum ** 2) / (window_frames **","from Kaldi. Args: waveform (Tensor): The input waveform of shape `(..., time)`. sample_rate","= torch.tensor(0.) for _ in range(n_iter): # Store the previous iterate tprev =","\"\"\" # Centered windowed pad_length = (win_length - 1) // 2 # \"replicate\"","and <NAME> 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),","spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True,","be scaled by. power (float): If power equals 1, will compute DB to","best = _combine_max(half, best) indices = best[1] # Add back minimal lag indices","frequency, 3 -> time) Returns: Tensor: Masked spectrograms of dimensions (batch, channel, freq,","Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Decode mu-law encoded signal. For more info","1)) # Repack batch x_db = x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor,","w(m+n)}{\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\phi_i(m)` is the NCCF at frame :math:`i` with lag :math:`m`,","frame, :math:`b_i` is the beginning of frame :math:`i`, :math:`E(j)` is the energy :math:`\\sum_{n=j}^{j+N-1}","= waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype device = waveform.device","of hop between STFT windows. ( Default: ``win_length // 2``) win_length (int): Window","optional): If true, normalize variance to one. (bool, default = false) Returns: Tensor:","complex=2)` rate (float): Speed-up factor phase_advance (Tensor): Expected phase advance in each bin.","< mask_param if axis == 1: specgram[:, mask_start:mask_end] = mask_value elif axis ==","complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 =",":math:`\\sum_{n=j}^{j+N-1} w^2(n)`. \"\"\" EPSILON = 10 ** (-9) # Number of lags to","10.0) min_f0 (float, optional): Minimum F0 to search for (Hz) (default: 50.0) max_f0","// 2 + 1`` bins hop_length (int): Length of hop between STFT windows.","and ``n_fft`` is the number of Fourier bins, and time is the number","to Audio and Acoustics (pp. 1-4), Oct. 2013. * [3] <NAME> and <NAME>,","(..., freq, time) cmn_window (int, optional): Window in frames for running average CMN","Tensor: Output tensor in power/amplitude scale. \"\"\" return ref * torch.pow(torch.pow(10.0, 0.1 *","= 3400, ) -> Tensor: r\"\"\"Detect pitch frequency. It is implemented using normalized","(int): Axis to apply masking on (1 -> frequency, 2 -> time) Returns:","// 2 half = torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best) indices =","(bool): When True, both the input and output Tensor have dimension ``[channel, time]``.","+ value)[..., None, None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch","\"slaney\".') if mel_scale == \"htk\": return 700.0 * (10.0**(mels / 2595.0) - 1.0)","axis != 3: raise ValueError('Only Frequency and Time masking are supported') device =","power == 1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor,","to x the number of filterbanks. Each column is a filterbank so that","smoothing, and convert to frequency. Note: If the max among all the lags","will be uniformly sampled from [0, mask_param] mask_value (float): Value to assign to","waveform[:, last_window_end, :] cur_sum += frame_to_add if norm_vars: cur_sumsq += (frame_to_add ** 2)","return_complex=True, ) ) # Update our phase estimates angles = rebuilt if momentum:","frame_time: float, freq_low: int ) -> Tensor: r\"\"\" Compute Normalized Cross-Correlation Function (NCCF).","# default values are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length,","optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter","a form of augmentation. Args: waveform (Tensor): Audio data. Must be 2 dimensional.","randomly initialize the phase batch, freq, frames = specgram.size() if rand_init: angles =","Two sided padding of signal window (Tensor): Window tensor that is applied/multiplied to","\" f\"Or, the value for `n_freqs` ({n_freqs}) may be set too low.\" )","scaled by. power (float): If power equals 1, will compute DB to power.","complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float,","Length of hop between STFT windows. ( Default: ``win_length // 2``) win_length (int):","multiplier * db_multiplier if top_db is not None: # Expand batch shape =","float = 1.0 ) -> Tuple[Tensor, Tensor]: r\"\"\"Separate a complex-valued spectrogram with shape","last_window_start, :] cur_sum -= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove ** 2) if","frame_shift (float, optional): Frame shift in milliseconds. (default: 10.0) min_f0 (float, optional): Minimum","`Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values between 0 and quantization_channels","Expected phase advance in each bin. Dimension of (freq, 1) Returns: Tensor: Complex","Repack batch x_db = x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor, ref: float,","amin (float): Number to clamp ``x`` db_multiplier (float): Log10(max(reference value and amin)) top_db","* (n + 1) * (2 * n + 1) / 3 specgram","``True`` pad_mode (string, optional): controls the padding method used when :attr:`center` is ``True``.","t, :] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance = cur_sumsq variance","the highest value of NCCF, apply centered median smoothing, and convert to frequency.","= specgram.reshape(1, -1, shape[-1]) assert win_length >= 3 n = (win_length - 1)","Find near enough max that is smallest best = torch.max(nccf[..., lag_min:], -1) half_size","optional): The window length used for computing delta (Default: ``5``) mode (str, optional):","window_end = t + 1 if window_start < 0: window_end -= window_start window_start","magnitude and phase. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float):","= int(math.ceil(sample_rate / freq_high)) # Find near enough max that is smallest best","bins, and time is the number of window hops (n_frame). \"\"\" if pad","be > 0) e.g., 1 for energy, 2 for power, etc. If None,","specgram = specgram.reshape(1, -1, shape[-1]) assert win_length >= 3 n = (win_length -","angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates waveform = torch.istft(specgram *","f_sp logstep = math.log(6.4) / 27.0 if freq >= min_log_hz: mels = min_log_mel","r\"\"\" Apply a mask along ``axis``. Mask will be applied from indices ``[v_0,","applicable if center == false, ignored if center==true (int, default = 100) center","\"\"\"Extract pitch based on method described in [1]. This function computes the equivalent","torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] +","1 empirical calibration offset indices += 1 return indices def _median_smoothing( indices: Tensor,","dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1)","1 and returns a signal encoded with values from 0 to quantization_channels -","(int, optional): The window length used for computing delta (Default: ``5``) mode (str,","bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\"rate\", f\"{sample_rate}\"]], channels_first=channels_first, format=format) return","Number of iteration for phase recovery process. momentum (float): The momentum parameter for","release. To suppress this warning, \" \"please use `normalized=False`.\") # pack batch shape","will be scaled by. power (float): If power equals 1, will compute DB","\\phi_i(m) = \\frac{\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\phi_i(m)` is the NCCF","= torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack batch output = output.reshape(shape) return","(Hz) (Default: ``85``). freq_high (int, optional): Highest frequency that can be detected (Hz)","float, top_db: Optional[float] = None ) -> Tensor: r\"\"\"Turn a spectrogram from the","int, norm: Optional[str] ) -> Tensor: r\"\"\"Create a DCT transformation matrix with shape","to introduce into the feature processing (affects output only if ``frames_per_chunk > 0``","is None: dct *= 2.0 else: assert norm == \"ortho\" dct[0] *= 1.0","defined as the weighted average of the frequency values, weighted by their magnitude.","delta (Default: ``5``) mode (str, optional): Mode parameter passed to padding (Default: ``\"replicate\"``)","be approx constant energy per channel enorm = 2.0 / (f_pts[2:n_mels + 2]","upsample_filter_width: int = 5, max_frames_latency: int = 0, frames_per_chunk: int = 0, simulate_first_pass_online:","_mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between each mel point and each stft","= complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1","(Default: ``10 ** (-2)``). win_length (int, optional): The window length for median smoothing","low.\" ) return fb def create_dct( n_mfcc: int, n_mels: int, norm: Optional[str] )","be snipped, so that the number of frames is the file size divided","torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes","spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False,","* torch.log1p(mu)) - 1.0) / mu return x def complex_norm( complex_tensor: Tensor, power:",":math:`E(j)` is the energy :math:`\\sum_{n=j}^{j+N-1} w^2(n)`. \"\"\" EPSILON = 10 ** (-9) #","<NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE International Conference on Acoustics, Speech","specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate to 0 rebuilt = torch.tensor(0.) for","# calculate the difference between each mel point and each stft freq point",") -> Tensor: r\"\"\"Given a STFT tensor, speed up in time without modifying","of dimensions (batch, channel, freq, time) \"\"\" if axis != 2 and axis","rand_init: bool ) -> Tensor: r\"\"\"Compute waveform from a linear scale magnitude spectrogram","that tensor, and so may return different values for an audio clip split","f_pts[:-1] # (n_mels + 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels","should be one of \"htk\" or \"slaney\".') if mel_scale == \"htk\": return 2595.0","\"with torch.no_grad():\" back when JIT supports it waveform = torch.nn.functional.pad(waveform, (pad, pad), \"constant\")","return values def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float = 10 **","Optional[int], rand_init: bool ) -> Tensor: r\"\"\"Compute waveform from a linear scale magnitude","waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor, multiplier: float, amin: float,","= torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best) indices = best[1] # Add","For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding for the","if axis != 2 and axis != 3: raise ValueError('Only Frequency and Time","frame_size, frame_size)[..., :num_of_frames, :] output_frames = ( (s1 * s2).sum(-1) / (EPSILON +","angles = 2 * math.pi * torch.rand(batch, freq, frames) else: angles = torch.zeros(batch,","None): Array length of the expected output. rand_init (bool): Initializes phase randomly if","int, norm: Optional[str] = None, mel_scale: str = \"htk\", ) -> Tensor: r\"\"\"Create","``n_mels``) meaning number of frequencies to highlight/apply to x the number of filterbanks.","the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has been scaled to","in milliseconds. (default: 25.0) frame_shift (float, optional): Frame shift in milliseconds. (default: 10.0)","value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) *","mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding for the supported","``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels converted in Hz \"\"\" if mel_scale","method used when :attr:`center` is ``True``. Default: ``\"reflect\"`` onesided (bool, optional): controls whether","cmn_waveform[:, t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape)","n^2} where :math:`d_t` is the deltas at time :math:`t`, :math:`c_t` is the spectrogram","-> Tensor: r\"\"\"Turn a spectrogram from the power/amplitude scale to the decibel scale.","\"htk\" or \"slaney\".') if mel_scale == \"htk\": return 2595.0 * math.log10(1.0 + (freq","\"\"\"Convert mel bin numbers to frequencies. Args: mels (Tensor): Mel frequencies mel_scale (str,","phase + phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1)","to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels converted in","of mel filterbanks sample_rate (int): Sample rate of the audio waveform norm (Optional[str]):","device=device, dtype=dtype) * (specgrams.size(axis) - value) # Create broadcastable mask mask_start = min_value[...,","(in number of frames) (Default: ``30``). freq_low (int, optional): Lowest frequency that can","of freq of dimension (..., frame) \"\"\" input_shape = waveform.shape num_frames, num_feats =","int = 5, max_frames_latency: int = 0, frames_per_chunk: int = 0, simulate_first_pass_online: bool","dtype = waveform.dtype device = waveform.device last_window_start = last_window_end = -1 cur_sum =","torch.linspace(m_min, m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference","divide the triangular mel weights by the width of the mel band (area","``v_0`` from ``uniform(0, max_v - v)``. All examples will have the same mask","Sample rate of `waveform`. frame_length (float, optional): Frame length in milliseconds. (default: 25.0)","waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate,","-= (window_end - num_frames) window_end = num_frames if window_start < 0: window_start =","frame_to_add = waveform[:, last_window_end, :] cur_sum += frame_to_add if norm_vars: cur_sumsq += (frame_to_add","int = 500, snip_edges: bool = True, ) -> torch.Tensor: \"\"\"Extract pitch based","if window_start > last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum -= frame_to_remove if","power equals 1, will compute DB to power. If 0.5, will compute DB","# unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB( x:","batch shape = specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert win_length >= 3","meaning number of frequencies to highlight/apply to x the number of filterbanks. Each","from first if bigger than a multiplicative factor of the second, elementwise. \"\"\"","than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding","is applied/multiplied to each frame/window n_fft (int): Size of FFT hop_length (int): Length","that is applied/multiplied to each frame/window n_fft (int): Size of FFT, creates ``n_fft","channels Returns: Tensor: Input after mu-law encoding \"\"\" mu = quantization_channels - 1.0",") -> Tuple[Tensor, Tensor]: r\"\"\"Separate a complex-valued spectrogram with shape `(..., 2)` into","# Speed up by 30% >>> phase_advance = torch.linspace( >>> 0, math.pi *","Audio data. Must be 2 dimensional. See also ```channels_first```. sample_rate (int): Sample rate","to quantization_channels - 1. Args: x (Tensor): Input tensor quantization_channels (int): Number of","& <NAME>. \"A fast Griffin-Lim algorithm,\" IEEE Workshop on Applications of Signal Processing","= 400, soft_min_f0: float = 10.0, penalty_factor: float = 0.1, lowpass_cutoff: float =","computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The input waveform","where ``v`` is sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v -","= torch.nn.functional.pad(waveform, (pad, pad), \"constant\") # pack batch shape = waveform.size() waveform =","700.0)) # Fill in the linear part f_min = 0.0 f_sp = 200.0","None and norm != \"slaney\": raise ValueError(\"norm must be one of None or","norm. (Default: `1.0`). Returns: Tensor: Power of the normed input tensor. Shape of","(float): Number to clamp ``x`` db_multiplier (float): Log10(max(reference value and amin)) top_db (float","masking on (1 -> frequency, 2 -> time) Returns: Tensor: Masked spectrogram of","Add back minimal lag indices += lag_min # Add 1 empirical calibration offset","Convert indices to frequency EPSILON = 10 ** (-9) freq = sample_rate /","normalized (bool): Whether to normalize by magnitude after stft center (bool, optional): whether","last_window_start = last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq =","sample rate of the waveform (Hz) frame_time (float, optional): Duration of a frame","method. Values near 1 can lead to faster convergence, but above 1 may","waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p = lags + num_of_frames","\"\"\" input_shape = waveform.shape num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats)","``channels_first=True``, it has ``[channel, time]`` else ``[time, channel]``. \"\"\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes,","norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch =","the ending edge won't be snipped, so that the number of frames is","(int): Number of columns to be masked will be uniformly sampled from [0,","= 1025, 512 >>> # (channel, freq, time, complex=2) >>> complex_specgrams = torch.randn(2,","return dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Encode signal","start). Only applicable if center == false, ignored if center==true (int, default =","Tensor shape of `(..., complex=2)` Return: Tensor: Angle of a complex tensor. Shape","Griffin-Lim. Setting this to 0 recovers the original Griffin-Lim method. Values near 1","and 20. for amplitude amin (float): Number to clamp ``x`` db_multiplier (float): Log10(max(reference","> last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum -= frame_to_remove if norm_vars: cur_sumsq","freq is ``n_fft // 2 + 1`` and ``n_fft`` is the number of","x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) -","math.log(6.4) / 27.0 log_t = (mels >= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep","0]) def magphase( complex_tensor: Tensor, power: float = 1.0 ) -> Tuple[Tensor, Tensor]:","ValueError('Only Frequency and Time masking are supported') device = specgrams.device dtype = specgrams.dtype","To suppress this warning, \" \"please use `normalized=False`.\") # pack batch shape =","window_end > num_frames: window_start -= (window_end - num_frames) window_end = num_frames if window_start","- c_{t-n})}{2 \\sum_{n=1}^{\\text{N}} n^2} where :math:`d_t` is the deltas at time :math:`t`, :math:`c_t`","0.).any(): warnings.warn( \"At least one mel filterbank has all zero values. \" f\"The","of dimension (..., frame) \"\"\" # pack batch shape = list(waveform.size()) waveform =","mask * a[0] + ~mask * b[0] indices = mask * a[1] +","(int, optional): Integer that determines filter width when upsampling NCCF. (default: 5) max_frames_latency","= 0.0 f_sp = 200.0 / 3 mels = (freq - f_min) /","in each bin. Dimension of (freq, 1) Returns: Tensor: Complex Specgrams Stretch with","0.0 f_sp = 200.0 / 3 mels = (freq - f_min) / f_sp","Slaney-style mel is scaled to be approx constant energy per channel enorm =","1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor,","s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames = ( (s1 *","format. channels_first (bool): When True, both the input and output Tensor have dimension","+ value.long()).squeeze() assert mask_end - mask_start < mask_param if axis == 1: specgram[:,","Tensor: r\"\"\" For each frame, take the highest value of NCCF, apply centered","pointers, after revising our estimate of the signal energy. Relevant if ``frames_per_chunk >","coding: utf-8 -*- import io import math import warnings from typing import Optional,","# Fill in the linear scale f_min = 0.0 f_sp = 200.0 /","near 1 can lead to faster convergence, but above 1 may not converge.","amin: float, db_multiplier: float, top_db: Optional[float] = None ) -> Tensor: r\"\"\"Turn a","m_pts = torch.linspace(m_min, m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate","cur_sum += frame_to_add if norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames = window_end","Frequency and Time masking are supported') device = specgrams.device dtype = specgrams.dtype value","< mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram: Tensor,","rate (float): Speed-up factor phase_advance (Tensor): Expected phase advance in each bin. Dimension","= 10 ** (-9) # Number of lags to check lags = int(math.ceil(sample_rate","logstep = math.log(6.4) / 27.0 if freq >= min_log_hz: mels = min_log_mel +","Audio and Acoustics (pp. 1-4), Oct. 2013. * [3] <NAME> and <NAME>, \"Signal","= 0, simulate_first_pass_online: bool = False, recompute_frame: int = 500, snip_edges: bool =","waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag = [] for","of each tensor in a batch depends on the maximum value of that","600) min_cmn_window (int, optional): Minimum CMN window used at start of decoding (adds","complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor ) -> Tensor: r\"\"\"Compute the angle","window used at start of decoding (adds latency only at start). Only applicable","convergence, but above 1 may not converge. length (int or None): Array length","rebuilt = torch.tensor(0.) for _ in range(n_iter): # Store the previous iterate tprev","0) e.g., 1 for energy, 2 for power, etc. normalized (bool): Whether to","Return the final phase estimates waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length,","return different values for an audio clip split into snippets vs. a full","lowpass_cutoff (float, optional): Cutoff frequency for LowPass filter (Hz) (default: 1000) resample_frequency (float,","filter, more gives sharper filter. (default: 1) upsample_filter_width (int, optional): Integer that determines","= specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor, win_length: int =","1.0 ) -> Tuple[Tensor, Tensor]: r\"\"\"Separate a complex-valued spectrogram with shape `(..., 2)`","Sample rate of the audio waveform norm (Optional[str]): If 'slaney', divide the triangular","on the maximum value of that tensor, and so may return different values","function and median smoothing. Args: waveform (Tensor): Tensor of audio of dimension (...,","to frequency. Note: If the max among all the lags is very close","mask_value elif axis == 2: specgram[:, :, mask_start:mask_end] = mask_value else: raise ValueError('Only","spectral_centroid( waveform: Tensor, sample_rate: int, pad: int, window: Tensor, n_fft: int, hop_length: int,","our phase estimates angles = rebuilt if momentum: angles = angles - tprev.mul_(momentum","http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) *","to 0 rebuilt = torch.tensor(0.) for _ in range(n_iter): # Store the previous","def spectrogram( waveform: Tensor, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length:","(Tensor): Window tensor that is applied/multiplied to each frame/window n_fft (int): Size of","in [1]. This function computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform","= (win_length - 1) // 2 # \"replicate\" padding in any dimension indices","frame_length: float = 25.0, frame_shift: float = 10.0, min_f0: float = 50, max_f0:","freq_high (int, optional): Highest frequency that can be detected (Hz) (Default: ``3400``). Returns:","= 1000, resample_frequency: float = 4000, delta_pitch: float = 0.005, nccf_ballast: float =","freq_high)) # Find near enough max that is smallest best = torch.max(nccf[..., lag_min:],","value = torch.rand(1) * mask_param min_value = torch.rand(1) * (specgram.size(axis) - value) mask_start","= torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu + 1)","mel is scaled to be approx constant energy per channel enorm = 2.0","def _mel_to_hz(mels: Tensor, mel_scale: str = \"htk\") -> Tensor: \"\"\"Convert mel bin numbers","# Compute lags output_lag = [] for lag in range(1, lags + 1):","calculate mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts","-> torch.Tensor: \"\"\"Extract pitch based on method described in [1]. This function computes","(bool, optional): If true, normalize variance to one. (bool, default = false) Returns:","frames near the ending edge won't be snipped, so that the number of","have the form `(batch, channel, freq, time)`. multiplier (float): Use 10. for power","dim=-1) phase_acc = torch.cumsum(phase, -1) mag = alphas * norm_1 + (1 -","+ n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim)","shape of `(..., complex=2)` Return: Tensor: Angle of a complex tensor. Shape of","range(n_iter): # Store the previous iterate tprev = rebuilt # Invert with our","Value to assign to the masked columns axis (int): Axis to apply masking","t - cmn_window // 2 window_end = window_start + cmn_window else: window_start =","10.0, min_f0: float = 50, max_f0: float = 400, soft_min_f0: float = 10.0,",") -> Tensor: r\"\"\" Compute the spectral centroid for each channel along the","should be one of \"htk\" or \"slaney\".') if mel_scale == \"htk\": return 700.0","(Tensor): Real spectrograms (batch, channel, freq, time) mask_param (int): Number of columns to","(Hz) frame_time (float, optional): Duration of a frame (Default: ``10 ** (-2)``). win_length","1-4), Oct. 2013. * [3] <NAME> and <NAME>, \"Signal estimation from modified short-time","= x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1,","values, weighted by their magnitude. Args: waveform (Tensor): Tensor of audio of dimension","1) / 2 * mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor,","of latency that we allow pitch tracking to introduce into the feature processing","* mels # And now the nonlinear scale min_log_hz = 1000.0 min_log_mel =","* torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs def create_fb_matrix( n_freqs: int, f_min:","(and optionally variance) normalization per utterance. Args: waveform (Tensor): Tensor of audio of","= torch.rand(1) * (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() +","torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for t in range(num_frames): window_start = 0","= waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0,","({n_freqs}) may be set too low.\" ) return fb def create_dct( n_mfcc: int,","0, 2]) # (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2,","mask_value: float, axis: int ) -> Tensor: r\"\"\" Apply a mask along ``axis``.","float, axis: int ) -> Tensor: r\"\"\" Apply a mask along ``axis``. Mask","edge won't be snipped, so that the number of frames is the file","last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum += frame_to_add if norm_vars: cur_sumsq +=","spectrogram of dimension (..., freq, frames) where freq is ``n_fft // 2 +","(window_end - num_frames) window_end = num_frames if window_start < 0: window_start = 0","+ spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if power is not None: if","may be set too low.\" ) return fb def create_dct( n_mfcc: int, n_mels:","import math import warnings from typing import Optional, Tuple import torch from torch","NCCF for quiet frames (default: 7000) lowpass_filter_width (int, optional): Integer that determines filter","to decibel scale. Input should take the form `(..., freq, time)`. Batched inputs","batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2),","= 0 if not center: if window_end > t: window_end = max(t +","waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width,","signal scaled between -1 and 1. Args: x_mu (Tensor): Input tensor quantization_channels (int):",")` \"\"\" # Replace by torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return","freq, frames = specgram.size() if rand_init: angles = 2 * math.pi * torch.rand(batch,","spectrogram of dimensions (channel, freq, time) \"\"\" # pack batch shape = specgram.size()","the encoding for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int,","time) Returns: Tensor: Masked spectrogram of dimensions (channel, freq, time) \"\"\" # pack","(bool, default = false) Returns: Tensor: Tensor of freq of dimension (..., frame)","is the spectrogram coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor):","And initialize the previous iterate to 0 rebuilt = torch.tensor(0.) for _ in","time)`. Batched inputs should include a channel dimension and have the form `(batch,","Tensor: Output tensor in decibel scale \"\"\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin))","tensor. Shape of `(..., )` \"\"\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase(","x_db.dim() > 2 else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db =","'slaney', divide the triangular mel weights by the width of the mel band","freq, hop_length = 1025, 512 >>> # (channel, freq, time, complex=2) >>> complex_specgrams","waveform.reshape(-1, shape[-1]) # default values are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform,","freq point in hertz f_diff = f_pts[1:] - f_pts[:-1] # (n_mels + 1)","= torch.median(roll, -1) return values def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float","return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor ) -> Tensor: r\"\"\"Compute the","spectrogram( waveform: Tensor, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int,","waveform = waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype device =","channel, freq, time)`. multiplier (float): Use 10. for power and 20. for amplitude","spectrogram with shape `(..., 2)` into its magnitude and phase. Args: complex_tensor (Tensor):","time) mask_param (int): Number of columns to be masked will be uniformly sampled","Compute the spectral centroid for each channel along the time axis. The spectral","supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``,","specgram (Tensor): Tensor of audio of dimension (..., freq, time) win_length (int, optional):","n = (win_length - 1) // 2 # twice sum of integer squared","iterate tprev = rebuilt # Invert with our current estimate of the phases","phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor ) -> Tensor: r\"\"\"Given a STFT","of dimension (..., freq, time) Example >>> specgram = torch.randn(1, 40, 1000) >>>","very close to the first half of lags, then the latter is taken.","# Find near enough max that is smallest best = torch.max(nccf[..., lag_min:], -1)","best) indices = best[1] # Add back minimal lag indices += lag_min #","num_frames) window_end = num_frames if window_start < 0: window_start = 0 if last_window_start","torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size], -1)","int ) -> Tensor: r\"\"\" Apply a mask along ``axis``. Mask will be","(..., ``n_freqs``), the applied result would be ``A * create_fb_matrix(A.size(-1), ...)``. \"\"\" if","= specgram.device dtype = specgram.dtype # pack batch shape = specgram.size() specgram =","Args: x (Tensor): Input tensor before being converted to power/amplitude scale. ref (float):","Cutoff frequency for LowPass filter (Hz) (default: 1000) resample_frequency (float, optional): Frequency that","torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq: float, mel_scale: str = \"htk\") ->","\"griffinlim\", \"amplitude_to_DB\", \"DB_to_amplitude\", \"compute_deltas\", \"compute_kaldi_pitch\", \"create_fb_matrix\", \"create_dct\", \"compute_deltas\", \"detect_pitch_frequency\", \"DB_to_amplitude\", \"mu_law_encoding\", \"mu_law_decoding\", \"complex_norm\",","hop between STFT windows. ( Default: ``win_length // 2``) win_length (int): Window size.","smallest best = torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] // 2 half =","Frequency in Mels \"\"\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should","Whether to normalize by magnitude after stft center (bool, optional): whether to pad","_find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int ) -> Tensor: r\"\"\" For each","optional): Minimum f0, applied in soft way, must not exceed min-f0 (default: 10.0)","snipped, so that the number of frames is the file size divided by","batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 /","of shape `(..., time)`. sample_rate (float): Sample rate of `waveform`. frame_length (float, optional):","phase = angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance:","frame_shift: float = 10.0, min_f0: float = 50, max_f0: float = 400, soft_min_f0:","= (min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0 if freq","a spectrogram: .. math:: d_t = \\frac{\\sum_{n=1}^{\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\sum_{n=1}^{\\text{N}} n^2}","audio of dimension (..., freq, time) cmn_window (int, optional): Window in frames for","the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If","mu-law decoding \"\"\" mu = quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu =","onesided=onesided, return_complex=True, ) # unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized:","before being converted to power/amplitude scale. ref (float): Reference which the output will","-> Tensor: r\"\"\"Compute delta coefficients of a tensor, usually a spectrogram: .. math::","Triangular filter banks (fb matrix) of size (``n_freqs``, ``n_mels``) meaning number of frequencies","= _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts,","waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag = [] for lag","1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom #","signal. The spectrogram can be either magnitude-only or complex. Args: waveform (Tensor): Tensor","frame-shift. This makes different types of features give the same number of frames.","spectrograms of dimensions (batch, channel, freq, time) \"\"\" if axis != 2 and","* frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag","then the latter is taken. \"\"\" lag_min = int(math.ceil(sample_rate / freq_high)) # Find","import Tensor from torchaudio._internal import module_utils as _mod_utils import torchaudio __all__ = [","= 100, center: bool = False, norm_vars: bool = False, ) -> Tensor:","None, encoding: Optional[str] = None, bits_per_sample: Optional[int] = None, ) -> Tensor: r\"\"\"","``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter banks (fb matrix) of size (``n_freqs``,","(..., time) pad (int): Two sided padding of signal window (Tensor): Window tensor","Returns: Tensor: Complex Specgrams Stretch with dimension of `(..., freq, ceil(time/rate), complex=2)` Example","extraction algorithm tuned for automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and","float = 7000, lowpass_filter_width: int = 1, upsample_filter_width: int = 5, max_frames_latency: int","hop_length: int, win_length: int, power: Optional[float], normalized: bool, center: bool = True, pad_mode:","power: float = 1.0 ) -> Tensor: r\"\"\"Compute the norm of complex tensor","(1 -> frequency, 2 -> time) Returns: Tensor: Masked spectrogram of dimensions (channel,","-> Tensor: r\"\"\"Encode signal based on mu-law companding. For more info see the","(win_length - 1) // 2 # \"replicate\" padding in any dimension indices =","'htk']: raise ValueError('mel_scale should be one of \"htk\" or \"slaney\".') if mel_scale ==","x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu","0 rebuilt = torch.tensor(0.) for _ in range(n_iter): # Store the previous iterate","input waveform of shape `(..., time)`. sample_rate (float): Sample rate of `waveform`. frame_length","(float, optional): Frame shift in milliseconds. (default: 10.0) min_f0 (float, optional): Minimum F0","norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 - angle_0 - phase_advance phase","calculate the difference between each mel point and each stft freq point in","100, center: bool = False, norm_vars: bool = False, ) -> Tensor: r\"\"\"","beginning of frame :math:`i`, :math:`E(j)` is the energy :math:`\\sum_{n=j}^{j+N-1} w^2(n)`. \"\"\" EPSILON =","snip_edges: bool = True, ) -> torch.Tensor: \"\"\"Extract pitch based on method described","of dimension (..., time) pad (int): Two sided padding of signal window (Tensor):","= (freq - f_min) / f_sp # Fill in the log-scale part min_log_hz","to frequencies. Args: mels (Tensor): Mel frequencies mel_scale (str, optional): Scale to use:","be unstable'.format(momentum) assert momentum >= 0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \"The","= torch.cat(output_lag, -1) return nccf def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor],","-0.5) cmn_waveform[:, t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if","= x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu) * 2","dimension and have the form `(batch, channel, freq, time)`. multiplier (float): Use 10.","= 500, snip_edges: bool = True, ) -> torch.Tensor: \"\"\"Extract pitch based on","cur_sum -= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove ** 2) if window_end >","momentum: angles = angles - tprev.mul_(momentum / (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles))","waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor, multiplier: float,","300, 2) >>> rate = 1.3 # Speed up by 30% >>> phase_advance","of `(..., freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length = 1025, 512 >>>","\"A fast Griffin-Lim algorithm,\" IEEE Workshop on Applications of Signal Processing to Audio","% 1.0 phase_0 = angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams,","* (n + 0.5) * k) # size (n_mfcc, n_mels) if norm is","cepstral mean (and optionally variance) normalization per utterance. Args: waveform (Tensor): Tensor of","n_mels (int): Number of mel filterbanks norm (str or None): Norm to use","window_start < 0: window_start = 0 if last_window_start == -1: input_part = waveform[:,","and axis != 3: raise ValueError('Only Frequency and Time masking are supported') device","spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate //","that determines filter width when upsampling NCCF. (default: 5) max_frames_latency (int, optional): Maximum","def magphase( complex_tensor: Tensor, power: float = 1.0 ) -> Tuple[Tensor, Tensor]: r\"\"\"Separate","the complex tensor \"\"\" mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag,","= 1.0 ) -> Tuple[Tensor, Tensor]: r\"\"\"Separate a complex-valued spectrogram with shape `(...,","top_db: Optional[float] = None ) -> Tensor: r\"\"\"Turn a spectrogram from the power/amplitude","bins hop_length (int): Length of hop between STFT windows. ( Default: ``win_length //","-> Tuple[Tensor, Tensor]: r\"\"\"Separate a complex-valued spectrogram with shape `(..., 2)` into its","batch example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask <","waveform = waveform.reshape(-1, shape[-1]) # default values are consistent with librosa.core.spectrum._spectrogram spec_f =","channel along the time axis. The spectral centroid is defined as the weighted","frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length) # Convert","1000, resample_frequency: float = 4000, delta_pitch: float = 0.005, nccf_ballast: float = 7000,","\"htk\": return 700.0 * (10.0**(mels / 2595.0) - 1.0) # Fill in the","sample_rate // 2, n_freqs) # calculate mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale)","Time masking are supported') device = specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2],","torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1],","once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor:","Returns: Tensor: Dimension (..., freq, time), freq is ``n_fft // 2 + 1``","tensor quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law decoding \"\"\"","= nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best)","norm_vars (bool, optional): If true, normalize variance to one. (bool, default = false)","= cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int, pad: int, window:","(Tensor): Input spectrogram(s) before being converted to decibel scale. Input should take the","@_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float = 25.0, frame_shift: float","(bool, optional): If this is set to false, the incomplete frames near the","delta_pitch: float = 0.005, nccf_ballast: float = 7000, lowpass_filter_width: int = 1, upsample_filter_width:","a frame, :math:`b_i` is the beginning of frame :math:`i`, :math:`E(j)` is the energy","the default. (default: False) Relevant if ``frames_per_chunk > 0``. recompute_frame (int, optional): Only","Window size. (Default: ``n_fft``) power (float): Exponent for the magnitude spectrogram, (must be","0 and quantization_channels - 1 and returns a signal scaled between -1 and","False, recompute_frame: int = 500, snip_edges: bool = True, ) -> torch.Tensor: \"\"\"Extract","Fourier transform,\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor):","Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \"librosa: Audio and music signal","x_mu = ((x_mu + 1) / 2 * mu + 0.5).to(torch.int64) return x_mu","first if bigger than a multiplicative factor of the second, elementwise. \"\"\" mask","of \"htk\" or \"slaney\".') if mel_scale == \"htk\": return 2595.0 * math.log10(1.0 +","Tensor: r\"\"\"Create a frequency bin conversion matrix. Args: n_freqs (int): Number of frequencies","specgram (Tensor): Real spectrogram (channel, freq, time) mask_param (int): Number of columns to","_combine_max(half, best) indices = best[1] # Add back minimal lag indices += lag_min","info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has been","batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) *","dim=-1) phase = angle_1 - angle_0 - phase_advance phase = phase - 2","- A pitch extraction algorithm tuned for automatic speech recognition <NAME>, <NAME>, <NAME>,","which the output will be scaled by. power (float): If power equals 1,","(str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: mels (float):","(f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn(","(int): Axis to apply masking on (2 -> frequency, 3 -> time) Returns:","return freqs def create_fb_matrix( n_freqs: int, f_min: float, f_max: float, n_mels: int, sample_rate:","int, win_length: int, power: Optional[float], normalized: bool, center: bool = True, pad_mode: str","but above 1 may not converge. length (int or None): Array length of","frame_size)[..., :num_of_frames, :] output_frames = ( (s1 * s2).sum(-1) / (EPSILON + torch.norm(s1,","size (``n_mels``, ``n_mfcc``). \"\"\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct",") -> Tensor: r\"\"\"Detect pitch frequency. It is implemented using normalized cross-correlation function","filterbank construction by Librosa all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) # calculate","= complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device,","DCT transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized depending on norm. Args: n_mfcc","(float): Used for formats other than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding","// 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim)","be one of None or 'slaney'\") # freq bins # Equivalent filterbank construction","num_of_frames * frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute lags","taken. \"\"\" lag_min = int(math.ceil(sample_rate / freq_high)) # Find near enough max that","details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has ``[channel, time]``","int, hop_length: int, win_length: int, power: Optional[float], normalized: bool, center: bool = True,","== 2: specgram[:, :, mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency and Time",":pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1) values,","mel_scale=mel_scale) # calculate the difference between each mel point and each stft freq","dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid(","Args: specgrams (Tensor): Real spectrograms (batch, channel, freq, time) mask_param (int): Number of","from `librosa`. * [1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>.","- f_min) / f_sp logstep = math.log(6.4) / 27.0 if freq >= min_log_hz:","norm of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)`","to power/amplitude scale. ref (float): Reference which the output will be scaled by.","Compute lags output_lag = [] for lag in range(1, lags + 1): s1","Array length of the expected output. rand_init (bool): Initializes phase randomly if True,","= min_log_mel + math.log(freq / min_log_hz) / logstep return mels def _mel_to_hz(mels: Tensor,","and ``v_0`` from ``uniform(0, max_v - v)``. All examples will have the same","set to false, the incomplete frames near the ending edge won't be snipped,","WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding for","= torch.linspace(m_min, m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the","use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels converted in Hz","signal window (Tensor): Window tensor that is applied/multiplied to each frame/window n_fft (int):","shape of `(..., complex=2)` power (float): Power of the norm. (Default: `1.0`). Returns:","torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle(","window_end - window_start, :] cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part","DB to power. If 0.5, will compute DB to amplitude. Returns: Tensor: Output","supported') device = specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) *","2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \"\"\" shape = waveform.shape waveform = waveform.reshape(-1, shape[-1])","the final phase estimates waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window,","= spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate","mel_scale: str = \"htk\") -> float: r\"\"\"Convert Hz to Mels. Args: freqs (float):","27.0 log_t = (mels >= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t]","more gives sharper filter. (default: 1) upsample_filter_width (int, optional): Integer that determines filter","alphas) * norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc)","size (..., ``n_freqs``), the applied result would be ``A * create_fb_matrix(A.size(-1), ...)``. \"\"\"","_compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length)","torch.rand(1) * mask_param min_value = torch.rand(1) * (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze()",") -> Tensor: r\"\"\" Apply median smoothing to the 1D tensor over the","encoding for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional):","value=0. ) indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1,","magnitude-only or complex. Args: waveform (Tensor): Tensor of audio of dimension (..., time)","as _mod_utils import torchaudio __all__ = [ \"spectrogram\", \"griffinlim\", \"amplitude_to_DB\", \"DB_to_amplitude\", \"compute_deltas\", \"compute_kaldi_pitch\",","And now the nonlinear scale min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min)","of size (..., ``n_freqs``), the applied result would be ``A * create_fb_matrix(A.size(-1), ...)``.","n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not None and norm","magnitude after stft center (bool, optional): whether to pad :attr:`waveform` on both sides","up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes,","- phase_advance phase = phase - 2 * math.pi * torch.round(phase / (2","2:] / f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm","def compute_deltas( specgram: Tensor, win_length: int = 5, mode: str = \"replicate\" )","if center==true (int, default = 100) center (bool, optional): If true, use a","dimension (..., frame) \"\"\" input_shape = waveform.shape num_frames, num_feats = input_shape[-2:] waveform =","// 2 + 1`` and ``n_fft`` is the number of Fourier bins, and","a multiplicative factor of the second, elementwise. \"\"\" mask = (a[0] > thresh","batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param:","+ list(shape[-2:])) value = torch.rand(1) * mask_param min_value = torch.rand(1) * (specgram.size(axis) -","<NAME>, <NAME>, <NAME>, and <NAME>. \"librosa: Audio and music signal analysis in python.\"","'momentum={} > 1 can be unstable'.format(momentum) assert momentum >= 0, 'momentum={} < 0'.format(momentum)","(Hz) f_max (float): Maximum frequency (Hz) n_mels (int): Number of mel filterbanks sample_rate","Tensor ) -> Tensor: r\"\"\"Given a STFT tensor, speed up in time without","we recompute some of the forward pointers, after revising our estimate of the","time]`` else ``[time, channel]``. \"\"\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression,","2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int, pad:","Real spectrogram (channel, freq, time) mask_param (int): Number of columns to be masked","complex-valued spectrogram with shape `(..., 2)` into its magnitude and phase. Args: complex_tensor","optional): If true, use a window centered on the current frame (to the","- cur_sum / window_frames if norm_vars: if window_frames == 1: cmn_waveform[:, t, :]","construction by Librosa all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) # calculate mel","(n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not None and","Args: x_mu (Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input","n (c_{t+n} - c_{t-n})}{2 \\sum_{n=1}^{\\text{N}} n^2} where :math:`d_t` is the deltas at time","-1) half_size = nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size], -1) best =","torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) #","- f_min) / f_sp # Fill in the log-scale part min_log_hz = 1000.0","frames is the file size divided by the frame-shift. This makes different types","process. momentum (float): The momentum parameter for fast Griffin-Lim. Setting this to 0","0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \"The argument normalized is not used","of integer squared denom = n * (n + 1) * (2 *","'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \"The argument normalized is not used in","window: Tensor, n_fft: int, hop_length: int, win_length: int, ) -> Tensor: r\"\"\" Compute","1984. Args: specgram (Tensor): A magnitude-only STFT spectrogram of dimension (..., freq, frames)","(Optional[str]): If 'slaney', divide the triangular mel weights by the width of the","n_fft: int, hop_length: int, win_length: int, ) -> Tensor: r\"\"\" Compute the spectral","mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels + 2) f_pts","search for (Hz) (default: 50.0) max_f0 (float, optional): Maximum F0 to search for","is centered at time :math:`t \\times \\text{hop\\_length}`. Default: ``True`` pad_mode (string, optional): controls","of hop between STFT windows win_length (int): Window size power (float or None):","different values for an audio clip split into snippets vs. a full clip.","scale min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep =","angle( complex_tensor: Tensor ) -> Tensor: r\"\"\"Compute the angle of complex tensor input.","It is implemented using normalized cross-correlation function and median smoothing. Args: waveform (Tensor):","if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor,","min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online,","1: specgram[:, mask_start:mask_end] = mask_value elif axis == 2: specgram[:, :, mask_start:mask_end] =","bool = True, compression: Optional[float] = None, encoding: Optional[str] = None, bits_per_sample: Optional[int]","conversion matrix. Args: n_freqs (int): Number of frequencies to highlight/apply f_min (float): Minimum","5) max_frames_latency (int, optional): Maximum number of frames of latency that we allow","and NCCF. Reference: - A pitch extraction algorithm tuned for automatic speech recognition","freq, time) \"\"\" if axis != 2 and axis != 3: raise ValueError('Only","linear scale f_min = 0.0 f_sp = 200.0 / 3 freqs = f_min","filterbanks norm (str or None): Norm to use (either 'ortho' or None) Returns:","(to the extent possible, modulo end effects). If false, window is to the","from a raw audio signal. The spectrogram can be either magnitude-only or complex.","``x`` db_multiplier (float): Log10(max(reference value and amin)) top_db (float or None, optional): Minimum","/ 3 mels = (freq - f_min) / f_sp # Fill in the","STFT tensor, speed up in time without modifying pitch by a factor of","Applications of Signal Processing to Audio and Acoustics (pp. 1-4), Oct. 2013. *","(Tensor, Tensor): The magnitude and phase of the complex tensor \"\"\" mag =","def angle( complex_tensor: Tensor ) -> Tensor: r\"\"\"Compute the angle of complex tensor","2) if window_end > last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum += frame_to_add","n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:])","top_db).view(-1, 1, 1, 1)) # Repack batch x_db = x_db.reshape(shape) return x_db def","db_multiplier: float, top_db: Optional[float] = None ) -> Tensor: r\"\"\"Turn a spectrogram from","num_feats, dtype=dtype, device=device) for t in range(num_frames): window_start = 0 window_end = 0","= t - cmn_window // 2 window_end = window_start + cmn_window else: window_start","info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values between","their magnitude. Args: waveform (Tensor): Tensor of audio of dimension (..., time) sample_rate","`(..., )` \"\"\" # Replace by torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279","* a[0] + ~mask * b[0] indices = mask * a[1] + ~mask","= int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p","indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\"constant\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length","torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\"rate\", f\"{sample_rate}\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor,","freqs = torch.linspace(0, sample_rate // 2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1))","if norm is not None and norm != \"slaney\": raise ValueError(\"norm must be","take the highest value of NCCF, apply centered median smoothing, and convert to","(specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert mask_end","dimension (..., frame) \"\"\" # pack batch shape = list(waveform.size()) waveform = waveform.reshape([-1]","- 1.0) # Fill in the linear scale f_min = 0.0 f_sp =","+ (1 - alphas) * norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch =","If true, the function will output features that correspond to what an online","of the features, which is the default. (default: False) Relevant if ``frames_per_chunk >","reasonable number is 80. (Default: ``None``) Returns: Tensor: Output tensor in decibel scale","mu-law encoding \"\"\" mu = quantization_channels - 1.0 if not x.is_floating_point(): x =","sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. All examples","in Hz mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``)","advance in each bin. Dimension of (freq, 1) Returns: Tensor: Complex Specgrams Stretch",") -> Tensor: r\"\"\" Compute Normalized Cross-Correlation Function (NCCF). .. math:: \\phi_i(m) =","= f_min + f_sp * mels # And now the nonlinear scale min_log_hz","Speech and Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \"\"\" shape","used when :attr:`center` is ``True``. Default: ``\"reflect\"`` onesided (bool, optional): controls whether to","instead. normalized (bool): Whether to normalize by magnitude after stft center (bool, optional):","1, 1, 1)) # Repack batch x_db = x_db.reshape(shape) return x_db def DB_to_amplitude(","Input after mu-law decoding \"\"\" mu = quantization_channels - 1.0 if not x_mu.is_floating_point():","-> time) Returns: Tensor: Masked spectrograms of dimensions (batch, channel, freq, time) \"\"\"","Tensor shape of `(..., complex=2)` power (float): Power of the norm. (Default: `1.0`).","= \"htk\") -> Tensor: \"\"\"Convert mel bin numbers to frequencies. Args: mels (Tensor):","on mu-law companding. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm","None, None] mask_end = (min_value + value)[..., None, None] mask = torch.arange(0, specgrams.size(axis),","apply centered median smoothing, and convert to frequency. Note: If the max among","estimate of the signal energy. Relevant if ``frames_per_chunk > 0``. (default: 500) snip_edges","IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor): A magnitude-only","= 4000, delta_pitch: float = 0.005, nccf_ballast: float = 7000, lowpass_filter_width: int =","for _ in range(n_iter): # Store the previous iterate tprev = rebuilt #","Args: specgram (Tensor): Real spectrogram (channel, freq, time) mask_param (int): Number of columns","of the frequency values, weighted by their magnitude. Args: waveform (Tensor): Tensor of","= None, bits_per_sample: Optional[int] = None, ) -> Tensor: r\"\"\" Apply codecs as","f_pts[1:] - f_pts[:-1] # (n_mels + 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) #","> 0``. (default: 500) snip_edges (bool, optional): If this is set to false,","/ f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is","None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with 231 ==","= mask_value elif axis == 2: specgram[:, :, mask_start:mask_end] = mask_value else: raise","sided padding of signal window (Tensor): Window tensor that is applied/multiplied to each","== -1: input_part = waveform[:, window_start: window_end - window_start, :] cur_sum += torch.sum(input_part,","spectrogram using the Griffin-Lim transformation. Implementation ported from `librosa`. * [1] McFee, Brian,","length (int or None): Array length of the expected output. rand_init (bool): Initializes","current estimate of the phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length,","(EPSILON + indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq","<NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE International Conference on Acoustics, Speech and","(..., frame) \"\"\" # pack batch shape = list(waveform.size()) waveform = waveform.reshape([-1] +","(Hz) (default: 50.0) max_f0 (float, optional): Maximum F0 to search for (Hz) (default:","* slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:, 2:] /","= angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor","on both sides so that the :math:`t`-th frame is centered at time :math:`t","Tensor of deltas of dimension (..., freq, time) Example >>> specgram = torch.randn(1,","being converted to power/amplitude scale. ref (float): Reference which the output will be","nccf: Tensor, sample_rate: int, freq_high: int ) -> Tensor: r\"\"\" For each frame,","frequencies mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns:","= _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length) # Convert indices to frequency","raise ValueError(\"norm must be one of None or 'slaney'\") # freq bins #","set too high. \" f\"Or, the value for `n_freqs` ({n_freqs}) may be set","one of \"htk\" or \"slaney\".') if mel_scale == \"htk\": return 700.0 * (10.0**(mels","+ num_of_frames * frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute","false) Returns: Tensor: Tensor of freq of dimension (..., frame) \"\"\" input_shape =","specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int, format: str, channels_first: bool =","torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack","(int, optional): Only relevant for compatibility with online pitch extraction. A non-critical parameter;","for (Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum f0, applied in soft way,","= mag * torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch],","for fast Griffin-Lim. Setting this to 0 recovers the original Griffin-Lim method. Values","nccf_ballast: float = 7000, lowpass_filter_width: int = 1, upsample_filter_width: int = 5, max_frames_latency:","if last_window_start == -1: input_part = waveform[:, window_start: window_end - window_start, :] cur_sum","sides so that the :math:`t`-th frame is centered at time :math:`t \\times \\text{hop\\_length}`.","approx constant energy per channel enorm = 2.0 / (f_pts[2:n_mels + 2] -","- 1.0 if not x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu","norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1","mode=\"constant\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll =","waveform.dtype device = waveform.device last_window_start = last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats,","the audio waveform pad (int): Two sided padding of signal window (Tensor): Window","should include a channel dimension and have the form `(batch, channel, freq, time)`.","decoder would see in the first pass of decoding -- not the final","bool = True, pad_mode: str = \"reflect\", onesided: bool = True ) ->","Number of lags to check lags = int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate","= 1.0 ) -> Tensor: r\"\"\"Compute the norm of complex tensor input. Args:","-> float: r\"\"\"Convert Hz to Mels. Args: freqs (float): Frequencies in Hz mel_scale","details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit depth for the supported","window_frames == 1: cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else:","int, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, ) ->","each frame, take the highest value of NCCF, apply centered median smoothing, and","+ 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) #","on (2 -> frequency, 3 -> time) Returns: Tensor: Masked spectrograms of dimensions","float, phase_advance: Tensor ) -> Tensor: r\"\"\"Given a STFT tensor, speed up in","torch.round(phase / (2 * math.pi)) # Compute Phase Accum phase = phase +","output_lag = [] for lag in range(1, lags + 1): s1 = waveform[...,","1) if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1, :] else: if","give the same number of frames. (default: True) Returns: Tensor: Pitch feature. Shape:","< 0: window_start = 0 if last_window_start == -1: input_part = waveform[:, window_start:","etc. normalized (bool): Whether to normalize by magnitude after stft. n_iter (int): Number","= phase - 2 * math.pi * torch.round(phase / (2 * math.pi)) #","231, 2]) \"\"\" # pack batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] +","factor reduces NCCF for quiet frames (default: 7000) lowpass_filter_width (int, optional): Integer that","ending edge won't be snipped, so that the number of frames is the","Apply median smoothing to the 1D tensor over the given window. \"\"\" #","Masked spectrograms of dimensions (batch, channel, freq, time) \"\"\" if axis != 2","frame, take the highest value of NCCF, apply centered median smoothing, and convert","up by 30% >>> phase_advance = torch.linspace( >>> 0, math.pi * hop_length, freq)[...,","python.\" In Proceedings of the 14th python in science conference, pp. 18-25. 2015.","scale to the power/amplitude scale. Args: x (Tensor): Input tensor before being converted","false, ignored if center==true (int, default = 100) center (bool, optional): If true,","waveform (Tensor): Audio data. Must be 2 dimensional. See also ```channels_first```. sample_rate (int):","``n_fft // 2 + 1``. window (Tensor): Window tensor that is applied/multiplied to","columns axis (int): Axis to apply masking on (2 -> frequency, 3 ->","default = 100) center (bool, optional): If true, use a window centered on","bigger than a multiplicative factor of the second, elementwise. \"\"\" mask = (a[0]","frame_time: float = 10 ** (-2), win_length: int = 30, freq_low: int =","f_max: float, n_mels: int, sample_rate: int, norm: Optional[str] = None, mel_scale: str =","(default: 500) snip_edges (bool, optional): If this is set to false, the incomplete","- 2 * math.pi * torch.round(phase / (2 * math.pi)) # Compute Phase","frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames =","that the :math:`t`-th frame is centered at time :math:`t \\times \\text{hop\\_length}`. Default: ``True``","+ list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor, cmn_window: int = 600, min_cmn_window:","waveform def amplitude_to_DB( x: Tensor, multiplier: float, amin: float, db_multiplier: float, top_db: Optional[float]","normalized=False, onesided=onesided, return_complex=True, ) # unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if","Minimum frequency (Hz) f_max (float): Maximum frequency (Hz) n_mels (int): Number of mel","size (n_mfcc, n_mels) if norm is None: dct *= 2.0 else: assert norm","\"\"\" mu = quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu","``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. Args: specgrams (Tensor): Real","a batch depends on the maximum value of that tensor, and so may","(int, optional): Highest frequency that can be detected (Hz) (Default: ``3400``). Returns: Tensor:","for t in range(num_frames): window_start = 0 window_end = 0 if center: window_start","if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu)","it has ``[channel, time]`` else ``[time, channel]``. \"\"\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform,","This makes different types of features give the same number of frames. (default:","final phase estimates waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length)","return 2595.0 * math.log10(1.0 + (freq / 700.0)) # Fill in the linear","energy, 2 for power, etc. normalized (bool): Whether to normalize by magnitude after","Tensor: r\"\"\"Encode signal based on mu-law companding. For more info see the `Wikipedia","norm. (Default: `1.0`) Returns: (Tensor, Tensor): The magnitude and phase of the complex","= sample_rate / (EPSILON + indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1] +","uniformly sampled from [0, mask_param] mask_value (float): Value to assign to the masked","too high. \" f\"Or, the value for `n_freqs` ({n_freqs}) may be set too","- 1. Args: x (Tensor): Input tensor quantization_channels (int): Number of channels Returns:","in range(1, lags + 1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :]","Accum phase = phase + phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc","to each frame/window n_fft (int): Size of FFT hop_length (int): Length of hop","x.shape # with 231 == ceil(300 / 1.3) torch.Size([2, 1025, 231, 2]) \"\"\"","columns axis (int): Axis to apply masking on (1 -> frequency, 2 ->","axis != 2 and axis != 3: raise ValueError('Only Frequency and Time masking","half of lags, then the latter is taken. \"\"\" lag_min = int(math.ceil(sample_rate /","** (-2)``). win_length (int, optional): The window length for median smoothing (in number","torch.cumsum(input_part ** 2, 1)[:, -1, :] else: if window_start > last_window_start: frame_to_remove =","n_mels + 2) # create overlapping triangles zero = torch.zeros(1) down_slopes = (-1.0","the audio waveform norm (Optional[str]): If 'slaney', divide the triangular mel weights by","= complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 =","or a batch of spectrograms from a raw audio signal. The spectrogram can","None, None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch example masking","torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance = cur_sumsq variance = variance /","= variance / window_frames variance -= ((cur_sum ** 2) / (window_frames ** 2))","format: str, channels_first: bool = True, compression: Optional[float] = None, encoding: Optional[str] =","kernel, groups=specgram.shape[1]) / denom # unpack batch output = output.reshape(shape) return output def","0.005, nccf_ballast: float = 7000, lowpass_filter_width: int = 1, upsample_filter_width: int = 5,","F0 to search for (Hz) (default: 50.0) max_f0 (float, optional): Maximum F0 to","frequency. It is implemented using normalized cross-correlation function and median smoothing. Args: waveform","(float): The momentum parameter for fast Griffin-Lim. Setting this to 0 recovers the","n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate // 2, steps=1 +","of the 14th python in science conference, pp. 18-25. 2015. * [2] <NAME>.,","may return different values for an audio clip split into snippets vs. a","time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1)","# pack batch shape = specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert win_length","x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Decode mu-law encoded","simulate_first_pass_online (bool, optional): If true, the function will output features that correspond to","specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int, format: str, channels_first:","def create_dct( n_mfcc: int, n_mels: int, norm: Optional[str] ) -> Tensor: r\"\"\"Create a","waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames = ( (s1 * s2).sum(-1) /","2) >>> rate = 1.3 # Speed up by 30% >>> phase_advance =","(float): Reference which the output will be scaled by. power (float): If power","simulate_first_pass_online: bool = False, recompute_frame: int = 500, snip_edges: bool = True, )","for energy, 2 for power, etc. If None, then the complex spectrum is","Optional[str] = None, mel_scale: str = \"htk\", ) -> Tensor: r\"\"\"Create a frequency","m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels","* norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch","indices.unfold(-1, win_length, 1) values, _ = torch.median(roll, -1) return values def detect_pitch_frequency( waveform:","waveform: Tensor, sample_rate: int, frame_time: float = 10 ** (-2), win_length: int =","the maximum value of that tensor, and so may return different values for","DB to amplitude. Returns: Tensor: Output tensor in power/amplitude scale. \"\"\" return ref","for an audio clip split into snippets vs. a full clip. Args: x","fast Griffin-Lim algorithm,\" IEEE Workshop on Applications of Signal Processing to Audio and","of the audio waveform pad (int): Two sided padding of signal window (Tensor):","float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Encode","<NAME>. \"librosa: Audio and music signal analysis in python.\" In Proceedings of the","/ (EPSILON + indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return","def apply_codec( waveform: Tensor, sample_rate: int, format: str, channels_first: bool = True, compression:","Returns: Tensor: Pitch feature. Shape: ``(batch, frames 2)`` where the last dimension corresponds","v)``. All examples will have the same mask interval. Args: specgram (Tensor): Real","indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn(","from torch import Tensor from torchaudio._internal import module_utils as _mod_utils import torchaudio __all__","angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2])","(int): Sample rate of the audio waveform pad (int): Two sided padding of","`(..., freq, time)`. Batched inputs should include a channel dimension and have the","20. for amplitude amin (float): Number to clamp ``x`` db_multiplier (float): Log10(max(reference value","be more than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest relative change","mels # And now the nonlinear scale min_log_hz = 1000.0 min_log_mel = (min_log_hz","* torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq: float, mel_scale: str = \"htk\")","norm (str or None): Norm to use (either 'ortho' or None) Returns: Tensor:","data of size (``n_mels``, ``n_mfcc``). \"\"\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k =","of hop between STFT windows win_length (int): Window size Returns: Tensor: Dimension (...,","may not converge. length (int or None): Array length of the expected output.","tprev = rebuilt # Invert with our current estimate of the phases inverse","parameter for fast Griffin-Lim. Setting this to 0 recovers the original Griffin-Lim method.","* n + 1) / 3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel","can lead to faster convergence, but above 1 may not converge. length (int","variance to one. (bool, default = false) Returns: Tensor: Tensor of freq of","mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram: Tensor, mask_param: int,","angle_0 - phase_advance phase = phase - 2 * math.pi * torch.round(phase /","the signal to. Must be more than twice lowpass-cutoff. (default: 4000) delta_pitch( float,","torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier if top_db is not None: #","= torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram","pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) # Update our phase estimates angles =","if axis == 1: specgram[:, mask_start:mask_end] = mask_value elif axis == 2: specgram[:,","are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center,","\"magphase\", \"phase_vocoder\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \"spectral_centroid\", \"apply_codec\", ] def spectrogram( waveform: Tensor, pad:","* angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch waveform = waveform.reshape(shape[:-2]","whether to return half of results to avoid redundancy. Default: ``True`` Returns: Tensor:","channel, freq, time) \"\"\" if axis != 2 and axis != 3: raise","indices, (pad_length, 0), mode=\"constant\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)],","than a multiplicative factor of the second, elementwise. \"\"\" mask = (a[0] >","the signal has been scaled to between -1 and 1 and returns a","is not used in Griffin-Lim, \" \"and will be removed in v0.9.0 release.","(int): Number of channels Returns: Tensor: Input after mu-law encoding \"\"\" mu =","a spectrogram from the power/amplitude scale to the decibel scale. The output of","normalize by magnitude after stft center (bool, optional): whether to pad :attr:`waveform` on","mels = (freq - f_min) / f_sp # Fill in the log-scale part","down_slopes = (-1.0 * slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes =","ValueError('Only Frequency and Time masking are supported') # unpack batch specgram = specgram.reshape(shape[:-2]",".. math:: d_t = \\frac{\\sum_{n=1}^{\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\sum_{n=1}^{\\text{N}} n^2} where :math:`d_t`","Tensor: r\"\"\"Turn a spectrogram from the power/amplitude scale to the decibel scale. The","``True``. Default: ``\"reflect\"`` onesided (bool, optional): controls whether to return half of results","decibel scale to the power/amplitude scale. Args: x (Tensor): Input tensor before being","torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch","if x_db.dim() > 2 else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db","range(num_frames): window_start = 0 window_end = 0 if center: window_start = t -","+ cmn_window else: window_start = t - cmn_window window_end = t + 1","torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best) indices = best[1] # Add back","mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be one of \"htk\" or","+ 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between each mel","and <NAME>, \"Signal estimation from modified short-time Fourier transform,\" IEEE Trans. ASSP, vol.32,","and Time masking are supported') # unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:])","parameter passed to padding (Default: ``\"replicate\"``) Returns: Tensor: Tensor of deltas of dimension","set too low.\" ) return fb def create_dct( n_mfcc: int, n_mels: int, norm:","lag_min:], -1) half_size = nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size], -1) best","frequencies to highlight/apply to x the number of filterbanks. Each column is a","optionally variance) normalization per utterance. Args: waveform (Tensor): Tensor of audio of dimension","(float, optional): Duration of a frame (Default: ``10 ** (-2)``). win_length (int, optional):","float, mel_scale: str = \"htk\") -> float: r\"\"\"Convert Hz to Mels. Args: freqs","+ 1`` bins hop_length (int): Length of hop between STFT windows. ( Default:","filterbanks. Each column is a filterbank so that assuming there is a matrix","0, math.pi * hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>>","frame_size)) p = lags + num_of_frames * frame_size - waveform_length waveform = torch.nn.functional.pad(waveform,","centroid for each channel along the time axis. The spectral centroid is defined","if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be one of \"htk\"","in Griffin-Lim, \" \"and will be removed in v0.9.0 release. To suppress this","length of a frame, :math:`b_i` is the beginning of frame :math:`i`, :math:`E(j)` is","Norm to use (either 'ortho' or None) Returns: Tensor: The transformation matrix, to",":math:`m`, :math:`w` is the waveform, :math:`N` is the length of a frame, :math:`b_i`","t + 1 if window_start < 0: window_end -= window_start window_start = 0","rebuilt if momentum: angles = angles - tprev.mul_(momentum / (1 + momentum)) angles","= complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas =","device = specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param","the max among all the lags is very close to the first half","indices = mask * a[1] + ~mask * b[1] return values, indices def","torch.Size([2, 1025, 231, 2]) \"\"\" # pack batch shape = complex_specgrams.size() complex_specgrams =","tprev.mul_(momentum / (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase","# unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas( specgram:","Only applicable if center == false, ignored if center==true (int, default = 100)","parameter; the frame at which we recompute some of the forward pointers, after","Minimum CMN window used at start of decoding (adds latency only at start).","\"librosa: Audio and music signal analysis in python.\" In Proceedings of the 14th","r\"\"\"Compute the angle of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of","f_sp * mels # And now the nonlinear scale min_log_hz = 1000.0 min_log_mel","number of frames used for energy normalization. (default: 0) simulate_first_pass_online (bool, optional): If","int, power: Optional[float], normalized: bool, center: bool = True, pad_mode: str = \"reflect\",","Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has been scaled to between -1","normalized: spec_f /= window.pow(2.).sum().sqrt() if power is not None: if power == 1.0:","2 for power, etc. If None, then the complex spectrum is returned instead.","None, mel_scale: str = \"htk\", ) -> Tensor: r\"\"\"Create a frequency bin conversion","too low.\" ) return fb def create_dct( n_mfcc: int, n_mels: int, norm: Optional[str]","= waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf,","= 0.005, nccf_ballast: float = 7000, lowpass_filter_width: int = 1, upsample_filter_width: int =","1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0","the NCCF at frame :math:`i` with lag :math:`m`, :math:`w` is the waveform, :math:`N`","this factor reduces NCCF for quiet frames (default: 7000) lowpass_filter_width (int, optional): Integer","sample_rate (int): The sample rate of the waveform (Hz) frame_time (float, optional): Duration","= (min_value.long() + value.long()).squeeze() assert mask_end - mask_start < mask_param if axis ==","<NAME>., <NAME>., & <NAME>. \"A fast Griffin-Lim algorithm,\" IEEE Workshop on Applications of","channel]``. \"\"\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample","`(batch, channel, freq, time)`. multiplier (float): Use 10. for power and 20. for","of a frame (Default: ``10 ** (-2)``). win_length (int, optional): The window length","based on method described in [1]. This function computes the equivalent of `compute-kaldi-pitch-feats`","see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has ``[channel, time]`` else","if not x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x)","the audio waveform. format (str): File format. channels_first (bool): When True, both the","revising our estimate of the signal energy. Relevant if ``frames_per_chunk > 0``. (default:","50, max_f0: float = 400, soft_min_f0: float = 10.0, penalty_factor: float = 0.1,","+ specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor, win_length: int = 5, mode:","10.1109/ICASSP.2014.6854049. \"\"\" shape = waveform.shape waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform,","encoded with values from 0 to quantization_channels - 1. Args: x (Tensor): Input","device=device) else: variance = cur_sumsq variance = variance / window_frames variance -= ((cur_sum","penalty_factor (float, optional): Cost factor for FO change. (default: 0.1) lowpass_cutoff (float, optional):","(default: 0) simulate_first_pass_online (bool, optional): If true, the function will output features that","lags, then the latter is taken. \"\"\" lag_min = int(math.ceil(sample_rate / freq_high)) #","to false, the incomplete frames near the ending edge won't be snipped, so","of the signal energy. Relevant if ``frames_per_chunk > 0``. (default: 500) snip_edges (bool,","frames) else: angles = torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\","mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor: r\"\"\"","> 0``. recompute_frame (int, optional): Only relevant for compatibility with online pitch extraction.","norm == \"slaney\": # Slaney-style mel is scaled to be approx constant energy","(frame_to_remove ** 2) if window_end > last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum","packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1,","Apply a mask along ``axis``. Mask will be applied from indices ``[v_0, v_0","0.1 * x), power) def _hz_to_mel(freq: float, mel_scale: str = \"htk\") -> float:","momentum (float): The momentum parameter for fast Griffin-Lim. Setting this to 0 recovers","up_slopes)) if norm is not None and norm == \"slaney\": # Slaney-style mel","freq, time)`. Batched inputs should include a channel dimension and have the form","torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag = [] for lag in range(1,","LowPass filter (Hz) (default: 1000) resample_frequency (float, optional): Frequency that we down-sample the","features that correspond to what an online decoder would see in the first","max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result = result.reshape(shape[:-1] + result.shape[-2:]) return result","bool = True ) -> Tensor: r\"\"\"Create a spectrogram or a batch of","0, 0, 2]) # (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 =","r\"\"\"Convert Hz to Mels. Args: freqs (float): Frequencies in Hz mel_scale (str, optional):","and median smoothing. Args: waveform (Tensor): Tensor of audio of dimension (..., freq,","without modifying pitch by a factor of ``rate``. Args: complex_specgrams (Tensor): Dimension of","Dimension (..., freq, time), freq is ``n_fft // 2 + 1`` and ``n_fft``","Default: ``True`` pad_mode (string, optional): controls the padding method used when :attr:`center` is","output will be scaled by. power (float): If power equals 1, will compute","at time :math:`t \\times \\text{hop\\_length}`. Default: ``True`` pad_mode (string, optional): controls the padding","The window length for median smoothing (in number of frames) (Default: ``30``). freq_low","(int): Number of iteration for phase recovery process. momentum (float): The momentum parameter","`1.0`) Returns: (Tensor, Tensor): The magnitude and phase of the complex tensor \"\"\"","Lowest frequency that can be detected (Hz) (Default: ``85``). freq_high (int, optional): Highest","bit depth for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor:","estimation from modified short-time Fourier transform,\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr.","torch.log1p(mu)) - 1.0) / mu return x def complex_norm( complex_tensor: Tensor, power: float","= freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor, cmn_window: int =","both the input and output Tensor have dimension ``[channel, time]``. Otherwise, they have","ported from `librosa`. * [1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and","mu = quantization_channels - 1.0 if not x.is_floating_point(): x = x.to(torch.float) mu =","quantization_channels: int ) -> Tensor: r\"\"\"Decode mu-law encoded signal. For more info see","from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. All examples will","freq, time, complex=2)` rate (float): Speed-up factor phase_advance (Tensor): Expected phase advance in","being converted to decibel scale. Input should take the form `(..., freq, time)`.","n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between each","= angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase","mel point and each stft freq point in hertz f_diff = f_pts[1:] -","apply_codec( waveform: Tensor, sample_rate: int, format: str, channels_first: bool = True, compression: Optional[float]","\" f\"The value for `n_mels` ({n_mels}) may be set too high. \" f\"Or,","been scaled to between -1 and 1 and returns a signal encoded with","power: Optional[float], normalized: bool, center: bool = True, pad_mode: str = \"reflect\", onesided:","= specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end), mask_value) specgrams =","window. \"\"\" # Centered windowed pad_length = (win_length - 1) // 2 #","+ 1) / 3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n,","freq_low (int, optional): Lowest frequency that can be detected (Hz) (Default: ``85``). freq_high","m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between","for formats other than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional):","max_frames_latency (int, optional): Maximum number of frames of latency that we allow pitch","whether to pad :attr:`waveform` on both sides so that the :math:`t`-th frame is","mask along ``axis``. Mask will be applied from indices ``[v_0, v_0 + v)``,","batch depends on the maximum value of that tensor, and so may return","[indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1) values, _ = torch.median(roll, -1)","batch of spectrograms from a raw audio signal. The spectrogram can be either","None): Norm to use (either 'ortho' or None) Returns: Tensor: The transformation matrix,","torch.Tensor: waveform of (..., time), where time equals the ``length`` parameter if given.","dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu","length for median smoothing (in number of frames) (Default: ``30``). freq_low (int, optional):","See also ```channels_first```. sample_rate (int): Sample rate of the audio waveform. format (str):","Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law encoding","waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default values are consistent with librosa.core.spectrum._spectrogram spec_f","Args: complex_specgrams (Tensor): Dimension of `(..., freq, time, complex=2)` rate (float): Speed-up factor","50.0) max_f0 (float, optional): Maximum F0 to search for (Hz) (default: 400.0) soft_min_f0","Tensor, sample_rate: int, frame_time: float = 10 ** (-2), win_length: int = 30,","-= ((cur_sum ** 2) / (window_frames ** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:,","the same mask interval. Args: specgram (Tensor): Real spectrogram (channel, freq, time) mask_param","freq_low: int = 85, freq_high: int = 3400, ) -> Tensor: r\"\"\"Detect pitch","r\"\"\"Compute the norm of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of","search for (Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum f0, applied in soft","float, f_max: float, n_mels: int, sample_rate: int, norm: Optional[str] = None, mel_scale: str","f\"Or, the value for `n_freqs` ({n_freqs}) may be set too low.\" ) return","(x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1, 1)) # Repack batch x_db =","optional): If this is set to false, the incomplete frames near the ending","is the number of window hops (n_frame). \"\"\" if pad > 0: #","+ v)``, where ``v`` is sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0,","bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0)","float, frame_length: float = 25.0, frame_shift: float = 10.0, min_f0: float = 50,","+ f_sp * mels # And now the nonlinear scale min_log_hz = 1000.0","mask interval. Args: specgram (Tensor): Real spectrogram (channel, freq, time) mask_param (int): Number","7000, lowpass_filter_width: int = 1, upsample_filter_width: int = 5, max_frames_latency: int = 0,","(channel, freq, time) \"\"\" # pack batch shape = specgram.size() specgram = specgram.reshape([-1]","-1) return specgrams def mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float, axis: int","shape = waveform.shape waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length,","log_t = (mels >= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] -","`Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has been scaled to between","delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result = result.reshape(shape[:-1]","window_end -= window_start window_start = 0 if not center: if window_end > t:",") ) # Update our phase estimates angles = rebuilt if momentum: angles","# (n_freqs, n_mels) up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) fb","torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag = alphas * norm_1","for median smoothing (in number of frames) (Default: ``30``). freq_low (int, optional): Lowest","incomplete frames near the ending edge won't be snipped, so that the number","/ 27.0 if freq >= min_log_hz: mels = min_log_mel + math.log(freq / min_log_hz)","max_frames_latency: int = 0, frames_per_chunk: int = 0, simulate_first_pass_online: bool = False, recompute_frame:","int, window: Tensor, n_fft: int, hop_length: int, win_length: int, ) -> Tensor: r\"\"\"","2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \"At least","= t - cmn_window window_end = t + 1 if window_start < 0:","of `(..., complex=2)` power (float): Power of the norm. (Default: `1.0`) Returns: (Tensor,","mask_param: int, mask_value: float, axis: int ) -> Tensor: r\"\"\" Apply a mask","* torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3]","where :math:`d_t` is the deltas at time :math:`t`, :math:`c_t` is the spectrogram coeffcients","quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law decoding \"\"\" mu","of the audio waveform norm (Optional[str]): If 'slaney', divide the triangular mel weights","to the masked columns axis (int): Axis to apply masking on (1 ->","Args: freqs (float): Frequencies in Hz mel_scale (str, optional): Scale to use: ``htk``","dimension (..., time) sample_rate (int): Sample rate of the audio waveform pad (int):","(default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency for LowPass filter (Hz) (default: 1000)","*= 2.0 else: assert norm == \"ortho\" dct[0] *= 1.0 / math.sqrt(2.0) dct","str = \"replicate\" ) -> Tensor: r\"\"\"Compute delta coefficients of a tensor, usually","to highlight/apply f_min (float): Minimum frequency (Hz) f_max (float): Maximum frequency (Hz) n_mels","3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n, n + 1,","hop_length: int, win_length: int, power: float, normalized: bool, n_iter: int, momentum: float, length:","= torch.rand(1) * mask_param min_value = torch.rand(1) * (specgram.size(axis) - value) mask_start =","enough max that is smallest best = torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1]","number of frames. (default: True) Returns: Tensor: Pitch feature. Shape: ``(batch, frames 2)``","f_sp # Fill in the log-scale part min_log_hz = 1000.0 min_log_mel = (min_log_hz","effects). If false, window is to the left. (bool, default = false) norm_vars","nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result = result.reshape(shape[:-1] +","n_fft (int): Size of FFT, creates ``n_fft // 2 + 1`` bins hop_length","cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int, pad: int,","can be either magnitude-only or complex. Args: waveform (Tensor): Tensor of audio of","to pad :attr:`waveform` on both sides so that the :math:`t`-th frame is centered","values for an audio clip split into snippets vs. a full clip. Args:","of results to avoid redundancy. Default: ``True`` Returns: Tensor: Dimension (..., freq, time),","window_start: window_end - window_start, :] cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq +=","= torch.linspace(0, sample_rate // 2, n_freqs) # calculate mel freq bins m_min =","normalized: bool, n_iter: int, momentum: float, length: Optional[int], rand_init: bool ) -> Tensor:","phase randomly if True, to zero otherwise. Returns: torch.Tensor: waveform of (..., time),","import io import math import warnings from typing import Optional, Tuple import torch","- 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu","complex=2)` Return: Tensor: Angle of a complex tensor. Shape of `(..., )` \"\"\"","10.0) penalty_factor (float, optional): Cost factor for FO change. (default: 0.1) lowpass_cutoff (float,","\"create_fb_matrix\", \"create_dct\", \"compute_deltas\", \"detect_pitch_frequency\", \"DB_to_amplitude\", \"mu_law_encoding\", \"mu_law_decoding\", \"complex_norm\", \"angle\", \"magphase\", \"phase_vocoder\", 'mask_along_axis', 'mask_along_axis_iid',","angles.sin()], dim=-1) \\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous","(Tensor): Real spectrogram (channel, freq, time) mask_param (int): Number of columns to be","(Default: ``\"replicate\"``) Returns: Tensor: Tensor of deltas of dimension (..., freq, time) Example","a spectrogram or a batch of spectrograms from a raw audio signal. The","to return half of results to avoid redundancy. Default: ``True`` Returns: Tensor: Dimension","Returns: Tensor: The transformation matrix, to be right-multiplied to row-wise data of size","bin conversion matrix. Args: n_freqs (int): Number of frequencies to highlight/apply f_min (float):","makes different types of features give the same number of frames. (default: True)",">= 3 n = (win_length - 1) // 2 # twice sum of","torch.min(down_slopes, up_slopes)) if norm is not None and norm == \"slaney\": # Slaney-style","enorm = 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if","v)``. Args: specgrams (Tensor): Real spectrograms (batch, channel, freq, time) mask_param (int): Number","torchaudio __all__ = [ \"spectrogram\", \"griffinlim\", \"amplitude_to_DB\", \"DB_to_amplitude\", \"compute_deltas\", \"compute_kaldi_pitch\", \"create_fb_matrix\", \"create_dct\", \"compute_deltas\",","quantization_channels - 1 and returns a signal scaled between -1 and 1. Args:","can be detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor of freq of dimension","for FO change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency for LowPass filter","mel filterbank has all zero values. \" f\"The value for `n_mels` ({n_mels}) may","rate of the audio waveform norm (Optional[str]): If 'slaney', divide the triangular mel","logstep return mels def _mel_to_hz(mels: Tensor, mel_scale: str = \"htk\") -> Tensor: \"\"\"Convert","n_mfcc (int): Number of mfc coefficients to retain n_mels (int): Number of mel","* math.pi * torch.rand(batch, freq, frames) else: angles = torch.zeros(batch, freq, frames) angles","Tensor: r\"\"\"Create a DCT transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized depending on","phase_advance phase = phase - 2 * math.pi * torch.round(phase / (2 *","typing import Optional, Tuple import torch from torch import Tensor from torchaudio._internal import","audio of dimension (..., time) pad (int): Two sided padding of signal window","1) // 2 # twice sum of integer squared denom = n *","0``. (default: 500) snip_edges (bool, optional): If this is set to false, the","= 600) min_cmn_window (int, optional): Minimum CMN window used at start of decoding","/ freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length","waveform: Tensor, sample_rate: int, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length:","spectrogram(s) before being converted to decibel scale. Input should take the form `(...,","= True, pad_mode: str = \"reflect\", onesided: bool = True ) -> Tensor:","not x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) *","* [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1) values, _ = torch.median(roll,","can be unstable'.format(momentum) assert momentum >= 0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn(","(float): Use 10. for power and 20. for amplitude amin (float): Number to","torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1, 1)) # Repack batch x_db","from indices ``[v_0, v_0 + v)``, where ``v`` is sampled from ``uniform(0, mask_param)``,","# unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform:","tensor in power/amplitude scale. \"\"\" return ref * torch.pow(torch.pow(10.0, 0.1 * x), power)","\"create_dct\", \"compute_deltas\", \"detect_pitch_frequency\", \"DB_to_amplitude\", \"mu_law_encoding\", \"mu_law_decoding\", \"complex_norm\", \"angle\", \"magphase\", \"phase_vocoder\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn',",":py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit depth for the supported formats. For","magnitude spectrogram using the Griffin-Lim transformation. Implementation ported from `librosa`. * [1] McFee,","torch.Tensor, sample_rate: float, frame_length: float = 25.0, frame_shift: float = 10.0, min_f0: float","= torch.cos(math.pi / float(n_mels) * (n + 0.5) * k) # size (n_mfcc,","True) Returns: Tensor: Pitch feature. Shape: ``(batch, frames 2)`` where the last dimension","2595.0 * math.log10(1.0 + (freq / 700.0)) # Fill in the linear part","window_start = 0 if last_window_start == -1: input_part = waveform[:, window_start: window_end -","``win_length // 2``) win_length (int): Window size. (Default: ``n_fft``) power (float): Exponent for","f_sp = 200.0 / 3 freqs = f_min + f_sp * mels #","compute_deltas(delta) \"\"\" device = specgram.device dtype = specgram.dtype # pack batch shape =","> thresh * b[0]) values = mask * a[0] + ~mask * b[0]","= list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low)","mask mask_start = min_value[..., None, None] mask_end = (min_value + value)[..., None, None]","= t + 1 if window_start < 0: window_end -= window_start window_start =","(NCCF). .. math:: \\phi_i(m) = \\frac{\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\phi_i(m)`","= x_db.size() packed_channels = shape[-3] if x_db.dim() > 2 else 1 x_db =","if window_start < 0: window_end -= window_start window_start = 0 if not center:","center: if window_end > t: window_end = max(t + 1, min_cmn_window) if window_end","2) window_frames = window_end - window_start last_window_start = window_start last_window_end = window_end cmn_waveform[:,","inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the","is the deltas at time :math:`t`, :math:`c_t` is the spectrogram coeffcients at time","bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\"rate\", f\"{sample_rate}\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi()","r\"\"\"Turn a tensor from the decibel scale to the power/amplitude scale. Args: x","2) / (window_frames ** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :] *=","more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit depth for the","= 5, max_frames_latency: int = 0, frames_per_chunk: int = 0, simulate_first_pass_online: bool =","torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\ .to(dtype=specgram.dtype, device=specgram.device) specgram =","complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps","int ) -> Tensor: r\"\"\"Decode mu-law encoded signal. For more info see the","initialize the previous iterate to 0 rebuilt = torch.tensor(0.) for _ in range(n_iter):","amplitude_to_DB( x: Tensor, multiplier: float, amin: float, db_multiplier: float, top_db: Optional[float] = None","a raw audio signal. The spectrogram can be either magnitude-only or complex. Args:","return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Decode mu-law","torch.cumsum(phase, -1) mag = alphas * norm_1 + (1 - alphas) * norm_0","-1, shape[-1]) assert win_length >= 3 n = (win_length - 1) // 2","processing (affects output only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk","if norm is not None and norm == \"slaney\": # Slaney-style mel is","or None): Exponent for the magnitude spectrogram, (must be > 0) e.g., 1","see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has been scaled","[ \"spectrogram\", \"griffinlim\", \"amplitude_to_DB\", \"DB_to_amplitude\", \"compute_deltas\", \"compute_kaldi_pitch\", \"create_fb_matrix\", \"create_dct\", \"compute_deltas\", \"detect_pitch_frequency\", \"DB_to_amplitude\", \"mu_law_encoding\",","Args: waveform (Tensor): Tensor of audio of dimension (..., time) pad (int): Two","Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter banks","mask_value else: raise ValueError('Only Frequency and Time masking are supported') # unpack batch","specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert win_length >= 3 n = (win_length","Function (NCCF). .. math:: \\phi_i(m) = \\frac{\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\sqrt{E(b_i) E(m+b_i)}}, where","/ (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) )","is applied/multiplied to each frame/window n_fft (int): Size of FFT, creates ``n_fft //","offset indices += 1 return indices def _median_smoothing( indices: Tensor, win_length: int )","dimension corresponds to pitch and NCCF. Reference: - A pitch extraction algorithm tuned","if window_start < 0: window_start = 0 if last_window_start == -1: input_part =","vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor): A magnitude-only STFT spectrogram of","between STFT windows win_length (int): Window size Returns: Tensor: Dimension (..., time) \"\"\"","mel filterbanks sample_rate (int): Sample rate of the audio waveform norm (Optional[str]): If","Tensor]: \"\"\" Take value from first if bigger than a multiplicative factor of","pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1","roll = indices.unfold(-1, win_length, 1) values, _ = torch.median(roll, -1) return values def","of `(..., )` \"\"\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor,","Input spectrogram(s) before being converted to decibel scale. Input should take the form","pitch based on method described in [1]. This function computes the equivalent of","``n_mfcc``), normalized depending on norm. Args: n_mfcc (int): Number of mfc coefficients to","fast Griffin-Lim. Setting this to 0 recovers the original Griffin-Lim method. Values near","clip split into snippets vs. a full clip. Args: x (Tensor): Input spectrogram(s)","(int): Number of mel filterbanks norm (str or None): Norm to use (either","torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, )","Masked spectrogram of dimensions (channel, freq, time) \"\"\" # pack batch shape =","Tensor: r\"\"\" Compute Normalized Cross-Correlation Function (NCCF). .. math:: \\phi_i(m) = \\frac{\\sum_{n=b_i}^{b_i +","Tensor, win_length: int ) -> Tensor: r\"\"\" Apply median smoothing to the 1D",") -> Tensor: r\"\"\" Apply sliding-window cepstral mean (and optionally variance) normalization per","- num_frames) window_end = num_frames if window_start < 0: window_start = 0 if","of frames is the file size divided by the frame-shift. This makes different","each channel along the time axis. The spectral centroid is defined as the",":math:`t`, :math:`c_t` is the spectrogram coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args:","r\"\"\" Apply codecs as a form of augmentation. Args: waveform (Tensor): Audio data.","torch.Tensor: \"\"\"Extract pitch based on method described in [1]. This function computes the","example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end),","lags to check lags = int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate * frame_time))","waveform.shape num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0]","freq is ``n_fft // 2 + 1``. window (Tensor): Window tensor that is","energy. Relevant if ``frames_per_chunk > 0``. (default: 500) snip_edges (bool, optional): If this","Returns: mels (float): Frequency in Mels \"\"\" if mel_scale not in ['slaney', 'htk']:","= waveform.shape waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift,","pass of decoding -- not the final version of the features, which is","time :math:`t \\times \\text{hop\\_length}`. Default: ``True`` pad_mode (string, optional): controls the padding method","/ 2595.0) - 1.0) # Fill in the linear scale f_min = 0.0","in v0.9.0 release. To suppress this warning, \" \"please use `normalized=False`.\") # pack","not in ['slaney', 'htk']: raise ValueError('mel_scale should be one of \"htk\" or \"slaney\".')","False, ) -> Tensor: r\"\"\" Apply sliding-window cepstral mean (and optionally variance) normalization","Tensor: r\"\"\" Apply median smoothing to the 1D tensor over the given window.","win_length) # Convert indices to frequency EPSILON = 10 ** (-9) freq =","= torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1, 1)) # Repack batch","is the length of a frame, :math:`b_i` is the beginning of frame :math:`i`,","p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf def _combine_max( a:","freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform:",") -> Tensor: r\"\"\"Compute delta coefficients of a tensor, usually a spectrogram: ..","of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power","-> Tensor: r\"\"\" Apply a mask along ``axis``. Mask will be applied from",") -> Tuple[Tensor, Tensor]: \"\"\" Take value from first if bigger than a","# Fill in the linear part f_min = 0.0 f_sp = 200.0 /","channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float","of the normed input tensor. Shape of `(..., )` \"\"\" # Replace by","-> Tuple[Tensor, Tensor]: \"\"\" Take value from first if bigger than a multiplicative","r\"\"\"Encode signal based on mu-law companding. For more info see the `Wikipedia Entry","(default: True) Returns: Tensor: Pitch feature. Shape: ``(batch, frames 2)`` where the last","+ 1) / 2 * mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu:","Power of the normed input tensor. Shape of `(..., )` \"\"\" # Replace","All examples will have the same mask interval. Args: specgram (Tensor): Real spectrogram","x: Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Encode signal based on mu-law companding.","mask_start:mask_end] = mask_value elif axis == 2: specgram[:, :, mask_start:mask_end] = mask_value else:","output.reshape(shape) return output def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float, freq_low: int","each bin. Dimension of (freq, 1) Returns: Tensor: Complex Specgrams Stretch with dimension","torch.log1p(mu) x_mu = ((x_mu + 1) / 2 * mu + 0.5).to(torch.int64) return","= _median_smoothing(indices, win_length) # Convert indices to frequency EPSILON = 10 ** (-9)","1, will compute DB to power. If 0.5, will compute DB to amplitude.","Window size Returns: Tensor: Dimension (..., time) \"\"\" specgram = spectrogram(waveform, pad=pad, window=window,","specgrams = specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram: Tensor, mask_param: int, mask_value:","specgrams (Tensor): Real spectrograms (batch, channel, freq, time) mask_param (int): Number of columns","normalized=False) freqs = torch.linspace(0, sample_rate // 2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1,","assert momentum < 1, 'momentum={} > 1 can be unstable'.format(momentum) assert momentum >=","(Hz) (default: 1000) resample_frequency (float, optional): Frequency that we down-sample the signal to.","complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` Return: Tensor:","int, ) -> Tensor: r\"\"\" Compute the spectral centroid for each channel along","optional): Frame length in milliseconds. (default: 25.0) frame_shift (float, optional): Frame shift in","0 if not center: if window_end > t: window_end = max(t + 1,","the 1D tensor over the given window. \"\"\" # Centered windowed pad_length =","column is a filterbank so that assuming there is a matrix A of","the expected output. rand_init (bool): Initializes phase randomly if True, to zero otherwise.","int = 600, min_cmn_window: int = 100, center: bool = False, norm_vars: bool","mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs","_median_smoothing( indices: Tensor, win_length: int ) -> Tensor: r\"\"\" Apply median smoothing to","n_mels: int, norm: Optional[str] ) -> Tensor: r\"\"\"Create a DCT transformation matrix with","is sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. Args:","top_db (float or None, optional): Minimum negative cut-off in decibels. A reasonable number","= (min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0 log_t =","return x_db def DB_to_amplitude( x: Tensor, ref: float, power: float ) -> Tensor:","Relevant if ``frames_per_chunk > 0``. (default: 500) snip_edges (bool, optional): If this is","must not exceed min-f0 (default: 10.0) penalty_factor (float, optional): Cost factor for FO","(int): Length of hop between STFT windows. ( Default: ``win_length // 2``) win_length","f_min) / f_sp logstep = math.log(6.4) / 27.0 if freq >= min_log_hz: mels","500) snip_edges (bool, optional): If this is set to false, the incomplete frames","-1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device)","raise ValueError('mel_scale should be one of \"htk\" or \"slaney\".') if mel_scale == \"htk\":","factor phase_advance (Tensor): Expected phase advance in each bin. Dimension of (freq, 1)","= 0.0 f_sp = 200.0 / 3 freqs = f_min + f_sp *","freq_high: int ) -> Tensor: r\"\"\" For each frame, take the highest value","value of NCCF, apply centered median smoothing, and convert to frequency. Note: If","the norm. (Default: `1.0`) Returns: (Tensor, Tensor): The magnitude and phase of the","frame (to the extent possible, modulo end effects). If false, window is to","banks (fb matrix) of size (``n_freqs``, ``n_mels``) meaning number of frequencies to highlight/apply","waveform (Tensor): Tensor of audio of dimension (..., time) pad (int): Two sided","axis. The spectral centroid is defined as the weighted average of the frequency","in Mels \"\"\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be","Returns: Tensor: Output tensor in power/amplitude scale. \"\"\" return ref * torch.pow(torch.pow(10.0, 0.1","2 # \"replicate\" padding in any dimension indices = torch.nn.functional.pad( indices, (pad_length, 0),","\"slaney\": raise ValueError(\"norm must be one of None or 'slaney'\") # freq bins","detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float = 10 ** (-2), win_length: int","to padding (Default: ``\"replicate\"``) Returns: Tensor: Tensor of deltas of dimension (..., freq,","stft freq point in hertz f_diff = f_pts[1:] - f_pts[:-1] # (n_mels +","complex_tensor: Tensor, power: float = 1.0 ) -> Tuple[Tensor, Tensor]: r\"\"\"Separate a complex-valued","specgram (Tensor): A magnitude-only STFT spectrogram of dimension (..., freq, frames) where freq","2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs","(str): File format. channels_first (bool): When True, both the input and output Tensor","broadcastable mask mask_start = min_value[..., None, None] mask_end = (min_value + value)[..., None,","lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames = ( (s1 * s2).sum(-1) / (EPSILON","each mel point and each stft freq point in hertz f_diff = f_pts[1:]","from ``uniform(0, max_v - v)``. All examples will have the same mask interval.","the previous iterate tprev = rebuilt # Invert with our current estimate of","output. rand_init (bool): Initializes phase randomly if True, to zero otherwise. Returns: torch.Tensor:","# create overlapping triangles zero = torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2])","use a window centered on the current frame (to the extent possible, modulo","200.0 / 3 mels = (freq - f_min) / f_sp # Fill in","700.0 * (10.0**(mels / 2595.0) - 1.0) # Fill in the linear scale","format, encoding, bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\"rate\", f\"{sample_rate}\"]], channels_first=channels_first,","tensor that is applied/multiplied to each frame/window n_fft (int): Size of FFT, creates","int = 30, freq_low: int = 85, freq_high: int = 3400, ) ->","Number of frequencies to highlight/apply f_min (float): Minimum frequency (Hz) f_max (float): Maximum","snippets vs. a full clip. Args: x (Tensor): Input spectrogram(s) before being converted","+ (freq / 700.0)) # Fill in the linear part f_min = 0.0","shape (``n_mels``, ``n_mfcc``), normalized depending on norm. Args: n_mfcc (int): Number of mfc","torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 - angle_0","window_start > last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum -= frame_to_remove if norm_vars:","tensor in a batch depends on the maximum value of that tensor, and","Power of the norm. (Default: `1.0`) Returns: (Tensor, Tensor): The magnitude and phase","int = 1, upsample_filter_width: int = 5, max_frames_latency: int = 0, frames_per_chunk: int","lag_min:half_size], -1) best = _combine_max(half, best) indices = best[1] # Add back minimal","``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels converted in Hz \"\"\"","Tensor: Pitch feature. Shape: ``(batch, frames 2)`` where the last dimension corresponds to","2)`` where the last dimension corresponds to pitch and NCCF. Reference: - A",">= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs","that determines filter width of lowpass filter, more gives sharper filter. (default: 1)","= torch.stack([angles.cos(), angles.sin()], dim=-1) \\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize","\"\"\" device = specgram.device dtype = specgram.dtype # pack batch shape = specgram.size()","would see in the first pass of decoding -- not the final version","optional): Frequency that we down-sample the signal to. Must be more than twice","pitch frequency. It is implemented using normalized cross-correlation function and median smoothing. Args:","of columns to be masked will be uniformly sampled from [0, mask_param] mask_value","original Griffin-Lim method. Values near 1 can lead to faster convergence, but above","return mag, phase def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor ) ->","w(n) w(m+n)}{\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\phi_i(m)` is the NCCF at frame :math:`i` with lag",") indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length,","McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \"librosa: Audio and music","waveform[:, window_start: window_end - window_start, :] cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq","phase estimates waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) #","f_min = 0.0 f_sp = 200.0 / 3 freqs = f_min + f_sp","Tensor ) -> Tensor: r\"\"\"Compute the angle of complex tensor input. Args: complex_tensor","+ momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates waveform =","triangles zero = torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2]) / f_diff[:-1] #","``htk``) Returns: mels (float): Frequency in Mels \"\"\" if mel_scale not in ['slaney',","magphase( complex_tensor: Tensor, power: float = 1.0 ) -> Tuple[Tensor, Tensor]: r\"\"\"Separate a","1025, 231, 2]) \"\"\" # pack batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1]","mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch =","pad_mode: str = \"reflect\", onesided: bool = True ) -> Tensor: r\"\"\"Create a","mask_end = (min_value + value)[..., None, None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype)","raise ValueError('Only Frequency and Time masking are supported') # unpack batch specgram =","num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for t","waveform of (..., time), where time equals the ``length`` parameter if given. \"\"\"","(Default: ``htk``) Returns: mels (float): Frequency in Mels \"\"\" if mel_scale not in","Size of FFT, creates ``n_fft // 2 + 1`` bins hop_length (int): Length","pitch extraction algorithm tuned for automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME>","** 2) window_frames = window_end - window_start last_window_start = window_start last_window_end = window_end","rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1, :])","to one. (bool, default = false) Returns: Tensor: Tensor of freq of dimension","= torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n, n + 1, 1, device=device,","the previous iterate to 0 rebuilt = torch.tensor(0.) for _ in range(n_iter): #","Griffin-Lim, \" \"and will be removed in v0.9.0 release. To suppress this warning,","windows. ( Default: ``win_length // 2``) win_length (int): Window size. (Default: ``n_fft``) power","specgram[:, :, mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency and Time masking are","1.0) # Fill in the linear scale f_min = 0.0 f_sp = 200.0","device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value)","/ f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs,","N-1} w(n) w(m+n)}{\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\phi_i(m)` is the NCCF at frame :math:`i` with","(int): The sample rate of the waveform (Hz) frame_time (float, optional): Duration of","overlapping triangles zero = torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2]) / f_diff[:-1]","and Acoustics (pp. 1-4), Oct. 2013. * [3] <NAME> and <NAME>, \"Signal estimation","torch.linspace(0, sample_rate // 2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim =","Minimum f0, applied in soft way, must not exceed min-f0 (default: 10.0) penalty_factor","or complex. Args: waveform (Tensor): Tensor of audio of dimension (..., time) pad","\"\"\" shape = waveform.shape waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate,","output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack batch output = output.reshape(shape)","the frame-shift. This makes different types of features give the same number of","25.0, frame_shift: float = 10.0, min_f0: float = 50, max_f0: float = 400,","Tensor, sample_rate: int, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int,","win_length (int): Window size power (float or None): Exponent for the magnitude spectrogram,","and have the form `(batch, channel, freq, time)`. multiplier (float): Use 10. for","cut-off in decibels. A reasonable number is 80. (Default: ``None``) Returns: Tensor: Output","quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype)","io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented, _","the masked columns axis (int): Axis to apply masking on (1 -> frequency,","lags = int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1]","Tensor], thresh: float = 0.99 ) -> Tuple[Tensor, Tensor]: \"\"\" Take value from","Window in frames for running average CMN computation (int, default = 600) min_cmn_window","to the 1D tensor over the given window. \"\"\" # Centered windowed pad_length","= torch.cumsum(phase, -1) mag = alphas * norm_1 + (1 - alphas) *","r\"\"\" Apply sliding-window cepstral mean (and optionally variance) normalization per utterance. Args: waveform","(int, optional): Window in frames for running average CMN computation (int, default =","min_f0 (float, optional): Minimum F0 to search for (Hz) (default: 50.0) max_f0 (float,","true, use a window centered on the current frame (to the extent possible,","* (2 * n + 1) / 3 specgram = torch.nn.functional.pad(specgram, (n, n),","(torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu return x def complex_norm( complex_tensor: Tensor,","freq = sample_rate / (EPSILON + indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1]","= io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented,","non-critical parameter; the frame at which we recompute some of the forward pointers,","!= 3: raise ValueError('Only Frequency and Time masking are supported') device = specgrams.device","float = 0.1, lowpass_cutoff: float = 1000, resample_frequency: float = 4000, delta_pitch: float","= 10 ** (-9) freq = sample_rate / (EPSILON + indices.to(torch.float)) # unpack","specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) * mask_param min_value = torch.rand(1) * (specgram.size(axis)","min_log_mel = (min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0 log_t","\"compute_deltas\", \"detect_pitch_frequency\", \"DB_to_amplitude\", \"mu_law_encoding\", \"mu_law_decoding\", \"complex_norm\", \"angle\", \"magphase\", \"phase_vocoder\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \"spectral_centroid\",","window=window, length=length).float() # Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length,","both sides so that the :math:`t`-th frame is centered at time :math:`t \\times","at start). Only applicable if center == false, ignored if center==true (int, default","cmn_window window_end = t + 1 if window_start < 0: window_end -= window_start","expects an input with values between 0 and quantization_channels - 1 and returns","power) # randomly initialize the phase batch, freq, frames = specgram.size() if rand_init:","# Repack batch x_db = x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor, ref:","= \\frac{\\sum_{n=1}^{\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\sum_{n=1}^{\\text{N}} n^2} where :math:`d_t` is the deltas","Changes the encoding for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample","-> Tensor: r\"\"\"Given a STFT tensor, speed up in time without modifying pitch","= None, ) -> Tensor: r\"\"\" Apply codecs as a form of augmentation.","mask_end - mask_start < mask_param if axis == 1: specgram[:, mask_start:mask_end] = mask_value","f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \"At least one mel","0, frames_per_chunk: int = 0, simulate_first_pass_online: bool = False, recompute_frame: int = 500,","] def spectrogram( waveform: Tensor, pad: int, window: Tensor, n_fft: int, hop_length: int,","= complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value:","= 0 if last_window_start == -1: input_part = waveform[:, window_start: window_end - window_start,","between -1 and 1 and returns a signal encoded with values from 0","passed to padding (Default: ``\"replicate\"``) Returns: Tensor: Tensor of deltas of dimension (...,","compute DB to amplitude. Returns: Tensor: Output tensor in power/amplitude scale. \"\"\" return","raise ValueError('Only Frequency and Time masking are supported') device = specgrams.device dtype =","freq bins # Equivalent filterbank construction by Librosa all_freqs = torch.linspace(0, sample_rate //","frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p = lags +","nccf = torch.cat(output_lag, -1) return nccf def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor,","signal analysis in python.\" In Proceedings of the 14th python in science conference,","pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1) values, _ = torch.median(roll, -1) return","cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance = cur_sumsq","(int): Number of channels Returns: Tensor: Input after mu-law decoding \"\"\" mu =","phase_advance (Tensor): Expected phase advance in each bin. Dimension of (freq, 1) Returns:","not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) /","smoothing. Args: waveform (Tensor): Tensor of audio of dimension (..., freq, time) sample_rate","- waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag = []","a DCT transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized depending on norm. Args:","n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) * (n","If this is set to false, the incomplete frames near the ending edge","be either magnitude-only or complex. Args: waveform (Tensor): Tensor of audio of dimension","window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) # Update our phase estimates","Tensor, mel_scale: str = \"htk\") -> Tensor: \"\"\"Convert mel bin numbers to frequencies.","inputs should include a channel dimension and have the form `(batch, channel, freq,","fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \"At least one mel filterbank","power: float = 1.0 ) -> Tuple[Tensor, Tensor]: r\"\"\"Separate a complex-valued spectrogram with","equals the ``length`` parameter if given. \"\"\" assert momentum < 1, 'momentum={} >","win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft,","time) \"\"\" if axis != 2 and axis != 3: raise ValueError('Only Frequency","else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2,","padding of signal window (Tensor): Window tensor that is applied/multiplied to each frame/window","mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts =","2 -> time) Returns: Tensor: Masked spectrogram of dimensions (channel, freq, time) \"\"\"","can be detected (Hz) (Default: ``85``). freq_high (int, optional): Highest frequency that can","(Tensor): Audio data. Must be 2 dimensional. See also ```channels_first```. sample_rate (int): Sample","values from 0 to quantization_channels - 1. Args: x (Tensor): Input tensor quantization_channels","waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype device = waveform.device last_window_start","assign to the masked columns axis (int): Axis to apply masking on (2","\"please use `normalized=False`.\") # pack batch shape = specgram.size() specgram = specgram.reshape([-1] +","if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The number","hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return","specgrams: Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor: r\"\"\" Apply","exceed min-f0 (default: 10.0) penalty_factor (float, optional): Cost factor for FO change. (default:","optional): Maximum number of frames of latency that we allow pitch tracking to","0) e.g., 1 for energy, 2 for power, etc. If None, then the","f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) # create overlapping triangles zero","The momentum parameter for fast Griffin-Lim. Setting this to 0 recovers the original","freq, time), freq is ``n_fft // 2 + 1`` and ``n_fft`` is the","(Tensor): Tensor of audio of dimension (..., time) pad (int): Two sided padding","= torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch,","Librosa all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) # calculate mel freq bins","to apply masking on (2 -> frequency, 3 -> time) Returns: Tensor: Masked","there is a matrix A of size (..., ``n_freqs``), the applied result would","(Default: ``htk``) Returns: Tensor: Triangular filter banks (fb matrix) of size (``n_freqs``, ``n_mels``)","scaled to be approx constant energy per channel enorm = 2.0 / (f_pts[2:n_mels","the waveform, :math:`N` is the length of a frame, :math:`b_i` is the beginning","freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length) # Convert indices","(int, optional): Maximum number of frames of latency that we allow pitch tracking","of frequencies to highlight/apply f_min (float): Minimum frequency (Hz) f_max (float): Maximum frequency","_mel_to_hz(mels: Tensor, mel_scale: str = \"htk\") -> Tensor: \"\"\"Convert mel bin numbers to","= alphas * norm_1 + (1 - alphas) * norm_0 real_stretch = mag","mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram: Tensor, mask_param:",":math:`N` is the length of a frame, :math:`b_i` is the beginning of frame","+ ~mask * b[0] indices = mask * a[1] + ~mask * b[1]","\"\"\" # pack batch shape = list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf","'ortho' or None) Returns: Tensor: The transformation matrix, to be right-multiplied to row-wise","torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu + 1) /","formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it","cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype,","sample_rate (int): Sample rate of the audio waveform. format (str): File format. channels_first","x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier if top_db","Args: n_mfcc (int): Number of mfc coefficients to retain n_mels (int): Number of","results to avoid redundancy. Default: ``True`` Returns: Tensor: Dimension (..., freq, time), freq","*= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding(","_ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\"rate\", f\"{sample_rate}\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch(","if momentum: angles = angles - tprev.mul_(momentum / (1 + momentum)) angles =","// 2 # twice sum of integer squared denom = n * (n","energy :math:`\\sum_{n=j}^{j+N-1} w^2(n)`. \"\"\" EPSILON = 10 ** (-9) # Number of lags","power=1., normalized=False) freqs = torch.linspace(0, sample_rate // 2, steps=1 + n_fft // 2,","transformation. Implementation ported from `librosa`. * [1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>,","Args: waveform (Tensor): The input waveform of shape `(..., time)`. sample_rate (float): Sample","frames) where freq is ``n_fft // 2 + 1``. window (Tensor): Window tensor","Example >>> specgram = torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram) >>> delta2","frame :math:`i`, :math:`E(j)` is the energy :math:`\\sum_{n=j}^{j+N-1} w^2(n)`. \"\"\" EPSILON = 10 **","# freq bins # Equivalent filterbank construction by Librosa all_freqs = torch.linspace(0, sample_rate","denom # unpack batch output = output.reshape(shape) return output def _compute_nccf( waveform: Tensor,","average CMN computation (int, default = 600) min_cmn_window (int, optional): Minimum CMN window","center: window_start = t - cmn_window // 2 window_end = window_start + cmn_window","for the magnitude spectrogram, (must be > 0) e.g., 1 for energy, 2","else: variance = cur_sumsq variance = variance / window_frames variance -= ((cur_sum **","*= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform","= False, recompute_frame: int = 500, snip_edges: bool = True, ) -> torch.Tensor:","converted to power/amplitude scale. ref (float): Reference which the output will be scaled","``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The number of frames used for energy","1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu return","on method described in [1]. This function computes the equivalent of `compute-kaldi-pitch-feats` from","it waveform = torch.nn.functional.pad(waveform, (pad, pad), \"constant\") # pack batch shape = waveform.size()","waveform (Hz) frame_time (float, optional): Duration of a frame (Default: ``10 ** (-2)``).","optional): Cost factor for FO change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency","(Tensor): Mels converted in Hz \"\"\" if mel_scale not in ['slaney', 'htk']: raise","the latter is taken. \"\"\" lag_min = int(math.ceil(sample_rate / freq_high)) # Find near","to the decibel scale. The output of each tensor in a batch depends","shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 / power)","// 2``) win_length (int): Window size. (Default: ``n_fft``) power (float): Exponent for the","torch.no_grad():\" back when JIT supports it waveform = torch.nn.functional.pad(waveform, (pad, pad), \"constant\") #","win_length (int): Window size. (Default: ``n_fft``) power (float): Exponent for the magnitude spectrogram,","x: Tensor, ref: float, power: float ) -> Tensor: r\"\"\"Turn a tensor from","math.log(6.4) / 27.0 if freq >= min_log_hz: mels = min_log_mel + math.log(freq /","= torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for t in range(num_frames): window_start =","3400, ) -> Tensor: r\"\"\"Detect pitch frequency. It is implemented using normalized cross-correlation","torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has ``[channel, time]`` else ``[time, channel]``. \"\"\"","= torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch example masking specgrams = specgrams.transpose(axis,","dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1, :]) # Time","dimension (..., time) pad (int): Two sided padding of signal window (Tensor): Window","window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack batch spec_f = spec_f.reshape(shape[:-1]","change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency for LowPass filter (Hz) (default:","forward pointers, after revising our estimate of the signal energy. Relevant if ``frames_per_chunk","the time axis. The spectral centroid is defined as the weighted average of","= 10.0, min_f0: float = 50, max_f0: float = 400, soft_min_f0: float =","normalize by magnitude after stft. n_iter (int): Number of iteration for phase recovery","+ list(shape[-2:])) specgram = specgram.pow(1 / power) # randomly initialize the phase batch,","- f_pts[:-1] # (n_mels + 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs,","assign to the masked columns axis (int): Axis to apply masking on (1","format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float =","decibel scale. Input should take the form `(..., freq, time)`. Batched inputs should","soft way, must not exceed min-f0 (default: 10.0) penalty_factor (float, optional): Cost factor","<NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \"librosa: Audio and music signal analysis","lowpass filter, more gives sharper filter. (default: 1) upsample_filter_width (int, optional): Integer that","x_db.size() packed_channels = shape[-3] if x_db.dim() > 2 else 1 x_db = x_db.reshape(-1,",">>> x.shape # with 231 == ceil(300 / 1.3) torch.Size([2, 1025, 231, 2])","lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result = result.reshape(shape[:-1] + result.shape[-2:])","<NAME> and <NAME>, \"Signal estimation from modified short-time Fourier transform,\" IEEE Trans. ASSP,","sample_rate // 2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2","- top_db).view(-1, 1, 1, 1)) # Repack batch x_db = x_db.reshape(shape) return x_db","angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch waveform = waveform.reshape(shape[:-2] +","x (Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input after","for computing delta (Default: ``5``) mode (str, optional): Mode parameter passed to padding","form of augmentation. Args: waveform (Tensor): Audio data. Must be 2 dimensional. See","(int): Number of mel filterbanks sample_rate (int): Sample rate of the audio waveform","= torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0 =","The number of frames used for energy normalization. (default: 0) simulate_first_pass_online (bool, optional):","nccf def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float = 0.99","audio signal. The spectrogram can be either magnitude-only or complex. Args: waveform (Tensor):","specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 / power) # randomly initialize the phase","Optional[str] ) -> Tensor: r\"\"\"Create a DCT transformation matrix with shape (``n_mels``, ``n_mfcc``),","s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2)","[3] <NAME> and <NAME>, \"Signal estimation from modified short-time Fourier transform,\" IEEE Trans.","that is applied/multiplied to each frame/window n_fft (int): Size of FFT hop_length (int):","device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack",":math:`i`, :math:`E(j)` is the energy :math:`\\sum_{n=j}^{j+N-1} w^2(n)`. \"\"\" EPSILON = 10 ** (-9)","for energy, 2 for power, etc. normalized (bool): Whether to normalize by magnitude","n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim) /","`waveform`. frame_length (float, optional): Frame length in milliseconds. (default: 25.0) frame_shift (float, optional):","and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The number of frames used for","+ 1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[...,","(num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid(","augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float = 25.0, frame_shift:","optional): controls whether to return half of results to avoid redundancy. Default: ``True``","dct *= 2.0 else: assert norm == \"ortho\" dct[0] *= 1.0 / math.sqrt(2.0)","of a frame, :math:`b_i` is the beginning of frame :math:`i`, :math:`E(j)` is the","algorithm measures. (default: 0.005) nccf_ballast (float, optional): Increasing this factor reduces NCCF for","between -1 and 1. Args: x_mu (Tensor): Input tensor quantization_channels (int): Number of","from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. Args: specgrams (Tensor):","b[1] return values, indices def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int )","\"\"\" mu = quantization_channels - 1.0 if not x.is_floating_point(): x = x.to(torch.float) mu","If None, then the complex spectrum is returned instead. normalized (bool): Whether to","phase_advance: Tensor ) -> Tensor: r\"\"\"Given a STFT tensor, speed up in time","win_length: int = 30, freq_low: int = 85, freq_high: int = 3400, )","2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, 2014,","augmentation. Args: waveform (Tensor): Audio data. Must be 2 dimensional. See also ```channels_first```.","Returns: Tensor: Input after mu-law encoding \"\"\" mu = quantization_channels - 1.0 if","maximum value of that tensor, and so may return different values for an","complex=2)` Example >>> freq, hop_length = 1025, 512 >>> # (channel, freq, time,","= 10.0, penalty_factor: float = 0.1, lowpass_cutoff: float = 1000, resample_frequency: float =","torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) * (n + 0.5)","- 1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x","assert win_length >= 3 n = (win_length - 1) // 2 # twice","<https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has been scaled to between -1 and","retain n_mels (int): Number of mel filterbanks norm (str or None): Norm to","b: Tuple[Tensor, Tensor], thresh: float = 0.99 ) -> Tuple[Tensor, Tensor]: \"\"\" Take","thresh: float = 0.99 ) -> Tuple[Tensor, Tensor]: \"\"\" Take value from first","231 == ceil(300 / 1.3) torch.Size([2, 1025, 231, 2]) \"\"\" # pack batch","> num_frames: window_start -= (window_end - num_frames) window_end = num_frames if window_start <","The spectral centroid is defined as the weighted average of the frequency values,","in the log-scale part min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) /","add \"with torch.no_grad():\" back when JIT supports it waveform = torch.nn.functional.pad(waveform, (pad, pad),","in the linear scale f_min = 0.0 f_sp = 200.0 / 3 freqs","companding. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the","= True, compression: Optional[float] = None, encoding: Optional[str] = None, bits_per_sample: Optional[int] =","should take the form `(..., freq, time)`. Batched inputs should include a channel","max(t + 1, min_cmn_window) if window_end > num_frames: window_start -= (window_end - num_frames)","x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1,","be ``A * create_fb_matrix(A.size(-1), ...)``. \"\"\" if norm is not None and norm","computation (int, default = 600) min_cmn_window (int, optional): Minimum CMN window used at","if window_end > num_frames: window_start -= (window_end - num_frames) window_end = num_frames if","\\sum_{n=1}^{\\text{N}} n^2} where :math:`d_t` is the deltas at time :math:`t`, :math:`c_t` is the","indices def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int ) -> Tensor: r\"\"\"","``3400``). Returns: Tensor: Tensor of freq of dimension (..., frame) \"\"\" # pack",":] else: if window_start > last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum -=","specgram = specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) * mask_param min_value = torch.rand(1)","specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype)","<NAME>, and <NAME>. \"librosa: Audio and music signal analysis in python.\" In Proceedings","sample_rate, freq_high) indices = _median_smoothing(indices, win_length) # Convert indices to frequency EPSILON =","x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu +","determines filter width of lowpass filter, more gives sharper filter. (default: 1) upsample_filter_width","of the audio waveform. format (str): File format. channels_first (bool): When True, both","= torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) * (n + 0.5) * k)","and quantization_channels - 1 and returns a signal scaled between -1 and 1.","+= frame_to_add if norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames = window_end -","(float): Sample rate of `waveform`. frame_length (float, optional): Frame length in milliseconds. (default:","0) frames_per_chunk (int, optional): The number of frames used for energy normalization. (default:","normalization). (Default: ``None``) mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default:","cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int, pad: int, window: Tensor,","math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int ) ->","win_length: int, power: float, normalized: bool, n_iter: int, momentum: float, length: Optional[int], rand_init:","milliseconds. (default: 25.0) frame_shift (float, optional): Frame shift in milliseconds. (default: 10.0) min_f0","estimate of the phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window,","Tensor, sample_rate: int, frame_time: float, freq_low: int ) -> Tensor: r\"\"\" Compute Normalized","consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode,","when upsampling NCCF. (default: 5) max_frames_latency (int, optional): Maximum number of frames of","Used for formats other than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str,","STFT windows win_length (int): Window size power (float or None): Exponent for the","of audio of dimension (..., freq, time) win_length (int, optional): The window length","lag indices += lag_min # Add 1 empirical calibration offset indices += 1","complex_tensor: Tensor ) -> Tensor: r\"\"\"Compute the angle of complex tensor input. Args:","torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long())","energy per channel enorm = 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb","= torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return","- angle_0 - phase_advance phase = phase - 2 * math.pi * torch.round(phase","tensor. Shape of `(..., )` \"\"\" # Replace by torch.norm once issue is","Resulting Tensor. If ``channels_first=True``, it has ``[channel, time]`` else ``[time, channel]``. \"\"\" bytes","coefficients of a tensor, usually a spectrogram: .. math:: d_t = \\frac{\\sum_{n=1}^{\\text{N}} n","the triangular mel weights by the width of the mel band (area normalization).","ref (float): Reference which the output will be scaled by. power (float): If","the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The input waveform of","0: window_start = 0 if last_window_start == -1: input_part = waveform[:, window_start: window_end","= _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels +","spectrogram: .. math:: d_t = \\frac{\\sum_{n=1}^{\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\sum_{n=1}^{\\text{N}} n^2} where",") output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf def _combine_max( a: Tuple[Tensor, Tensor],","cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for t in range(num_frames): window_start",":] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance = cur_sumsq variance =","Apply codecs as a form of augmentation. Args: waveform (Tensor): Audio data. Must","window_start = 0 window_end = 0 if center: window_start = t - cmn_window","= n * (n + 1) * (2 * n + 1) /","float, amin: float, db_multiplier: float, top_db: Optional[float] = None ) -> Tensor: r\"\"\"Turn","Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor: r\"\"\" Apply a","axis (int): Axis to apply masking on (2 -> frequency, 3 -> time)","1.0 phase_0 = angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0,","(Tensor): Tensor of audio of dimension (..., freq, time) sample_rate (int): The sample","r\"\"\"Create a frequency bin conversion matrix. Args: n_freqs (int): Number of frequencies to","``5``) mode (str, optional): Mode parameter passed to padding (Default: ``\"replicate\"``) Returns: Tensor:","norm == \"ortho\" dct[0] *= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels))","time axis. The spectral centroid is defined as the weighted average of the","tensor, speed up in time without modifying pitch by a factor of ``rate``.","``axis``. Mask will be applied from indices ``[v_0, v_0 + v)``, where ``v``","* math.log10(1.0 + (freq / 700.0)) # Fill in the linear part f_min","last_window_start == -1: input_part = waveform[:, window_start: window_end - window_start, :] cur_sum +=","max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame,","magnitude. Args: waveform (Tensor): Tensor of audio of dimension (..., time) sample_rate (int):","frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) #","num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype =","math.pi * torch.rand(batch, freq, frames) else: angles = torch.zeros(batch, freq, frames) angles =","math.log10(1.0 + (freq / 700.0)) # Fill in the linear part f_min =","cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1, :] else: if window_start > last_window_start:","t, :] - cur_sum / window_frames if norm_vars: if window_frames == 1: cmn_waveform[:,","length of the expected output. rand_init (bool): Initializes phase randomly if True, to","pitch and NCCF. Reference: - A pitch extraction algorithm tuned for automatic speech","of lags, then the latter is taken. \"\"\" lag_min = int(math.ceil(sample_rate / freq_high))","power: float ) -> Tensor: r\"\"\"Turn a tensor from the decibel scale to","matrix with shape (``n_mels``, ``n_mfcc``), normalized depending on norm. Args: n_mfcc (int): Number","value for `n_mels` ({n_mels}) may be set too high. \" f\"Or, the value","a signal scaled between -1 and 1. Args: x_mu (Tensor): Input tensor quantization_channels","def amplitude_to_DB( x: Tensor, multiplier: float, amin: float, db_multiplier: float, top_db: Optional[float] =","for amplitude amin (float): Number to clamp ``x`` db_multiplier (float): Log10(max(reference value and","Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: mels (float): Frequency in","1.0) / mu return x def complex_norm( complex_tensor: Tensor, power: float = 1.0","of the norm. (Default: `1.0`) Returns: (Tensor, Tensor): The magnitude and phase of","-> Tensor: r\"\"\"Compute waveform from a linear scale magnitude spectrogram using the Griffin-Lim","angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1)","Frame shift in milliseconds. (default: 10.0) min_f0 (float, optional): Minimum F0 to search","unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if","not exceed min-f0 (default: 10.0) penalty_factor (float, optional): Cost factor for FO change.","7000) lowpass_filter_width (int, optional): Integer that determines filter width of lowpass filter, more","(int, optional): Minimum CMN window used at start of decoding (adds latency only","all the lags is very close to the first half of lags, then","the padding method used when :attr:`center` is ``True``. Default: ``\"reflect\"`` onesided (bool, optional):","= torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \"\"\"","= x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor, ref: float, power: float )","mode=mode) kernel = torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output","mask_param min_value = torch.rand(1) * (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end =",":math:`t \\times \\text{hop\\_length}`. Default: ``True`` pad_mode (string, optional): controls the padding method used","Tensor of freq of dimension (..., frame) \"\"\" input_shape = waveform.shape num_frames, num_feats","music signal analysis in python.\" In Proceedings of the 14th python in science","full clip. Args: x (Tensor): Input spectrogram(s) before being converted to decibel scale.","ceil(time/rate), complex=2)` Example >>> freq, hop_length = 1025, 512 >>> # (channel, freq,","- 1) // 2 # \"replicate\" padding in any dimension indices = torch.nn.functional.pad(","of dimension (..., freq, time) sample_rate (int): The sample rate of the waveform","specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) * mask_param min_value =","18-25. 2015. * [2] <NAME>., <NAME>., & <NAME>. \"A fast Griffin-Lim algorithm,\" IEEE","Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` Return: Tensor: Angle of a","cmn_waveform[:, t, :] = waveform[:, t, :] - cur_sum / window_frames if norm_vars:","# (channel, freq, time, complex=2) >>> complex_specgrams = torch.randn(2, freq, 300, 2) >>>","== 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int,","tracking to introduce into the feature processing (affects output only if ``frames_per_chunk >","momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates waveform = torch.istft(specgram","scale. ref (float): Reference which the output will be scaled by. power (float):","(n_mels + 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2)","for phase recovery process. momentum (float): The momentum parameter for fast Griffin-Lim. Setting","be detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor of freq of dimension (...,","- alphas) * norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch = mag *","to apply masking on (1 -> frequency, 2 -> time) Returns: Tensor: Masked","(min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert mask_end - mask_start < mask_param if","a full clip. Args: x (Tensor): Input spectrogram(s) before being converted to decibel","allow pitch tracking to introduce into the feature processing (affects output only if","``[time, channel]``. compression (float): Used for formats other than WAV. For mor details","The magnitude and phase of the complex tensor \"\"\" mag = complex_norm(complex_tensor, power)","n_iter: int, momentum: float, length: Optional[int], rand_init: bool ) -> Tensor: r\"\"\"Compute waveform","cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int, pad: int, window: Tensor, n_fft: int,","mels (Tensor): Mel frequencies mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``.","= 1.3 # Speed up by 30% >>> phase_advance = torch.linspace( >>> 0,","Tensor: Triangular filter banks (fb matrix) of size (``n_freqs``, ``n_mels``) meaning number of","1) / 3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n, n","compression: Optional[float] = None, encoding: Optional[str] = None, bits_per_sample: Optional[int] = None, )","sample_rate (int): Sample rate of the audio waveform norm (Optional[str]): If 'slaney', divide","torch.median(roll, -1) return values def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float =","to normalize by magnitude after stft. n_iter (int): Number of iteration for phase",">>> # (channel, freq, time, complex=2) >>> complex_specgrams = torch.randn(2, freq, 300, 2)","only at start). Only applicable if center == false, ignored if center==true (int,","left. (bool, default = false) norm_vars (bool, optional): If true, normalize variance to","File format. channels_first (bool): When True, both the input and output Tensor have","FFT hop_length (int): Length of hop between STFT windows win_length (int): Window size","see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding for the supported formats. For","not the final version of the features, which is the default. (default: False)","f_min = 0.0 f_sp = 200.0 / 3 mels = (freq - f_min)","time)`. sample_rate (float): Sample rate of `waveform`. frame_length (float, optional): Frame length in","torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1) values, _ =","2 half = torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best) indices = best[1]","at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio of","0.5) * k) # size (n_mfcc, n_mels) if norm is None: dct *=","x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor, ref: float, power: float ) ->","* (specgrams.size(axis) - value) # Create broadcastable mask mask_start = min_value[..., None, None]","Tensor: Tensor of freq of dimension (..., frame) \"\"\" input_shape = waveform.shape num_frames,","-> frequency, 2 -> time) Returns: Tensor: Masked spectrogram of dimensions (channel, freq,","= specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert win_length >= 3 n =","(int): Sample rate of the audio waveform norm (Optional[str]): If 'slaney', divide the","- 1) // 2 # twice sum of integer squared denom = n","= (min_value + value)[..., None, None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) #","tensor, usually a spectrogram: .. math:: d_t = \\frac{\\sum_{n=1}^{\\text{N}} n (c_{t+n} - c_{t-n})}{2","padding (Default: ``\"replicate\"``) Returns: Tensor: Tensor of deltas of dimension (..., freq, time)","\"and will be removed in v0.9.0 release. To suppress this warning, \" \"please","to be approx constant energy per channel enorm = 2.0 / (f_pts[2:n_mels +","the number of frames is the file size divided by the frame-shift. This",":] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames = ( (s1","(default: 1) upsample_filter_width (int, optional): Integer that determines filter width when upsampling NCCF.","on Applications of Signal Processing to Audio and Acoustics (pp. 1-4), Oct. 2013.","\"\"\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample )","(float, optional): Minimum f0, applied in soft way, must not exceed min-f0 (default:","pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \"\"\" shape = waveform.shape waveform = waveform.reshape(-1, shape[-1]) result","normalized is not used in Griffin-Lim, \" \"and will be removed in v0.9.0","-> Tensor: r\"\"\"Decode mu-law encoded signal. For more info see the `Wikipedia Entry","Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels converted","default = false) Returns: Tensor: Tensor of freq of dimension (..., frame) \"\"\"","masking on (2 -> frequency, 3 -> time) Returns: Tensor: Masked spectrograms of","sample_rate (float): Sample rate of `waveform`. frame_length (float, optional): Frame length in milliseconds.","= shape[-3] if x_db.dim() > 2 else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2],","Griffin-Lim method. Values near 1 can lead to faster convergence, but above 1","Tensor: r\"\"\" Compute the spectral centroid for each channel along the time axis.","with dimension of `(..., freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length = 1025,","Tensor: Dimension (..., time) \"\"\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length,","the applied result would be ``A * create_fb_matrix(A.size(-1), ...)``. \"\"\" if norm is","min_cmn_window (int, optional): Minimum CMN window used at start of decoding (adds latency","(Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum f0, applied in soft way, must","freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min,","(float or None, optional): Minimum negative cut-off in decibels. A reasonable number is","and phase of the complex tensor \"\"\" mag = complex_norm(complex_tensor, power) phase =","n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) # Update","a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float = 0.99 ) -> Tuple[Tensor,","Maximum number of frames of latency that we allow pitch tracking to introduce","int, mask_value: float, axis: int ) -> Tensor: r\"\"\" Apply a mask along","tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` Return: Tensor: Angle","masked columns axis (int): Axis to apply masking on (1 -> frequency, 2","(Tensor): The input waveform of shape `(..., time)`. sample_rate (float): Sample rate of","the phase batch, freq, frames = specgram.size() if rand_init: angles = 2 *","window_end = num_frames if window_start < 0: window_start = 0 if last_window_start ==","freqs def create_fb_matrix( n_freqs: int, f_min: float, f_max: float, n_mels: int, sample_rate: int,","see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit depth for the supported formats.","time), freq is ``n_fft // 2 + 1`` and ``n_fft`` is the number","hertz f_diff = f_pts[1:] - f_pts[:-1] # (n_mels + 1) slopes = f_pts.unsqueeze(0)","supports it waveform = torch.nn.functional.pad(waveform, (pad, pad), \"constant\") # pack batch shape =","pitch that our algorithm measures. (default: 0.005) nccf_ballast (float, optional): Increasing this factor","int = 0, frames_per_chunk: int = 0, simulate_first_pass_online: bool = False, recompute_frame: int","/ (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any():","/ torch.log1p(mu) x_mu = ((x_mu + 1) / 2 * mu + 0.5).to(torch.int64)","of frames. (default: True) Returns: Tensor: Pitch feature. Shape: ``(batch, frames 2)`` where","specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end), mask_value) specgrams = specgrams.transpose(axis,","Audio and music signal analysis in python.\" In Proceedings of the 14th python","/ 700.0)) # Fill in the linear part f_min = 0.0 f_sp =","e.g., 1 for energy, 2 for power, etc. If None, then the complex","min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value) # Create broadcastable mask","interval. Args: specgram (Tensor): Real spectrogram (channel, freq, time) mask_param (int): Number of","waveform: Tensor, cmn_window: int = 600, min_cmn_window: int = 100, center: bool =","The spectrogram can be either magnitude-only or complex. Args: waveform (Tensor): Tensor of","dim=-1) roll = indices.unfold(-1, win_length, 1) values, _ = torch.median(roll, -1) return values","minimal lag indices += lag_min # Add 1 empirical calibration offset indices +=","/ denom # unpack batch output = output.reshape(shape) return output def _compute_nccf( waveform:","to row-wise data of size (``n_mels``, ``n_mfcc``). \"\"\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels))","def _median_smoothing( indices: Tensor, win_length: int ) -> Tensor: r\"\"\" Apply median smoothing","(adds latency only at start). Only applicable if center == false, ignored if","``(batch, frames 2)`` where the last dimension corresponds to pitch and NCCF. Reference:","time) win_length (int, optional): The window length used for computing delta (Default: ``5``)","(n + 1) * (2 * n + 1) / 3 specgram =","+ 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1)","applied/multiplied to each frame/window n_fft (int): Size of FFT, creates ``n_fft // 2","3: raise ValueError('Only Frequency and Time masking are supported') device = specgrams.device dtype","= mask * a[1] + ~mask * b[1] return values, indices def _find_max_per_frame(","for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor.","-> Tensor: r\"\"\"Turn a tensor from the decibel scale to the power/amplitude scale.","freq, time) mask_param (int): Number of columns to be masked will be uniformly","filter width of lowpass filter, more gives sharper filter. (default: 1) upsample_filter_width (int,","suppress this warning, \" \"please use `normalized=False`.\") # pack batch shape = specgram.size()","denom = n * (n + 1) * (2 * n + 1)","Tensor, n_fft: int, hop_length: int, win_length: int, power: Optional[float], normalized: bool, center: bool","after stft. n_iter (int): Number of iteration for phase recovery process. momentum (float):","3 mels = (freq - f_min) / f_sp # Fill in the log-scale","= torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, )","values between 0 and quantization_channels - 1 and returns a signal scaled between","1) values, _ = torch.median(roll, -1) return values def detect_pitch_frequency( waveform: Tensor, sample_rate:","When True, both the input and output Tensor have dimension ``[channel, time]``. Otherwise,","< 0'.format(momentum) if normalized: warnings.warn( \"The argument normalized is not used in Griffin-Lim,","* math.pi)) # Compute Phase Accum phase = phase + phase_advance phase =","25.0) frame_shift (float, optional): Frame shift in milliseconds. (default: 10.0) min_f0 (float, optional):","(pp. 1-4), Oct. 2013. * [3] <NAME> and <NAME>, \"Signal estimation from modified","by magnitude after stft. n_iter (int): Number of iteration for phase recovery process.","This expects an input with values between 0 and quantization_channels - 1 and","sharper filter. (default: 1) upsample_filter_width (int, optional): Integer that determines filter width when","\"\"\" if pad > 0: # TODO add \"with torch.no_grad():\" back when JIT","Size of FFT hop_length (int): Length of hop between STFT windows win_length (int):","to check lags = int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length","float = 400, soft_min_f0: float = 10.0, penalty_factor: float = 0.1, lowpass_cutoff: float","* b[0]) values = mask * a[0] + ~mask * b[0] indices =","bool = True, ) -> torch.Tensor: \"\"\"Extract pitch based on method described in","result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency,","default values are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length,","mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor:","highlight/apply to x the number of filterbanks. Each column is a filterbank so","None] mask_end = (min_value + value)[..., None, None] mask = torch.arange(0, specgrams.size(axis), device=device,","For each frame, take the highest value of NCCF, apply centered median smoothing,","applied in soft way, must not exceed min-f0 (default: 10.0) penalty_factor (float, optional):","ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor): A magnitude-only STFT spectrogram","float = 1.0 ) -> Tensor: r\"\"\"Compute the norm of complex tensor input.","centroid is defined as the weighted average of the frequency values, weighted by","scale to the decibel scale. The output of each tensor in a batch","== \"htk\": return 700.0 * (10.0**(mels / 2595.0) - 1.0) # Fill in","take the form `(..., freq, time)`. Batched inputs should include a channel dimension","(n_freqs, n_mels + 2) # create overlapping triangles zero = torch.zeros(1) down_slopes =","window_end - window_start last_window_start = window_start last_window_end = window_end cmn_waveform[:, t, :] =","(default: 10.0) penalty_factor (float, optional): Cost factor for FO change. (default: 0.1) lowpass_cutoff","rate of the waveform (Hz) frame_time (float, optional): Duration of a frame (Default:","avoid redundancy. Default: ``True`` Returns: Tensor: Dimension (..., freq, time), freq is ``n_fft","hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) # Update our","twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest relative change in pitch that","or None): Norm to use (either 'ortho' or None) Returns: Tensor: The transformation","and Time masking are supported') device = specgrams.device dtype = specgrams.dtype value =","m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels + 2) f_pts =","x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu) *",">= min_log_hz: mels = min_log_mel + math.log(freq / min_log_hz) / logstep return mels","now the nonlinear scale min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) /","int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p =","back minimal lag indices += lag_min # Add 1 empirical calibration offset indices","delta2 = compute_deltas(delta) \"\"\" device = specgram.device dtype = specgram.dtype # pack batch","600, min_cmn_window: int = 100, center: bool = False, norm_vars: bool = False,","Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Encode signal based on mu-law companding. For","(window_frames ** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance cmn_waveform","1)) freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec(","estimates waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack","(10.0**(mels / 2595.0) - 1.0) # Fill in the linear scale f_min =","sample_rate (int): Sample rate of the audio waveform pad (int): Two sided padding","= specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 / power) #","to the power/amplitude scale. Args: x (Tensor): Input tensor before being converted to","400.0) soft_min_f0 (float, optional): Minimum f0, applied in soft way, must not exceed","30% >>> phase_advance = torch.linspace( >>> 0, math.pi * hop_length, freq)[..., None] >>>","axis == 1: specgram[:, mask_start:mask_end] = mask_value elif axis == 2: specgram[:, :,","+ 1) * (2 * n + 1) / 3 specgram = torch.nn.functional.pad(specgram,","optional): Changes the encoding for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`.","(int, default = 600) min_cmn_window (int, optional): Minimum CMN window used at start","-*- coding: utf-8 -*- import io import math import warnings from typing import","import torchaudio __all__ = [ \"spectrogram\", \"griffinlim\", \"amplitude_to_DB\", \"DB_to_amplitude\", \"compute_deltas\", \"compute_kaldi_pitch\", \"create_fb_matrix\", \"create_dct\",","dimension of `(..., freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length = 1025, 512","true, the function will output features that correspond to what an online decoder","* b[0] indices = mask * a[1] + ~mask * b[1] return values,","algorithm assumes the signal has been scaled to between -1 and 1 and","int ) -> Tensor: r\"\"\"Encode signal based on mu-law companding. For more info","# (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not None","signal based on mu-law companding. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_","phase_advance = torch.linspace( >>> 0, math.pi * hop_length, freq)[..., None] >>> x =","freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0","first pass of decoding -- not the final version of the features, which","+ complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float, axis:","to clamp ``x`` db_multiplier (float): Log10(max(reference value and amin)) top_db (float or None,","for LowPass filter (Hz) (default: 1000) resample_frequency (float, optional): Frequency that we down-sample","the waveform (Hz) frame_time (float, optional): Duration of a frame (Default: ``10 **","python in science conference, pp. 18-25. 2015. * [2] <NAME>., <NAME>., & <NAME>.","(int, default = 100) center (bool, optional): If true, use a window centered","# And now the nonlinear scale min_log_hz = 1000.0 min_log_mel = (min_log_hz -","of None or 'slaney'\") # freq bins # Equivalent filterbank construction by Librosa","device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate to 0 rebuilt","is ``True``. Default: ``\"reflect\"`` onesided (bool, optional): controls whether to return half of","(int or None): Array length of the expected output. rand_init (bool): Initializes phase","(min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0 if freq >=","r\"\"\"Create a DCT transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized depending on norm.","numbers to frequencies. Args: mels (Tensor): Mel frequencies mel_scale (str, optional): Scale to","> 0) e.g., 1 for energy, 2 for power, etc. normalized (bool): Whether","the normed input tensor. Shape of `(..., )` \"\"\" # Replace by torch.norm","applied/multiplied to each frame/window n_fft (int): Size of FFT hop_length (int): Length of","device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats,","time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0","(Tensor): Tensor of audio of dimension (..., time) sample_rate (int): Sample rate of","- window_start, :] cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part **","Speed up by 30% >>> phase_advance = torch.linspace( >>> 0, math.pi * hop_length,","recompute some of the forward pointers, after revising our estimate of the signal","length=length).float() # Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length,","more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has ``[channel,","Tensor: r\"\"\"Detect pitch frequency. It is implemented using normalized cross-correlation function and median","frames of latency that we allow pitch tracking to introduce into the feature","usually a spectrogram: .. math:: d_t = \\frac{\\sum_{n=1}^{\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\sum_{n=1}^{\\text{N}}","torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power: float = 1.0 )","Angle of a complex tensor. Shape of `(..., )` \"\"\" return torch.atan2(complex_tensor[..., 1],","phase. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float): Power of",")` \"\"\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power: float","(-1.0 * slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:, 2:]","\\frac{\\sum_{n=1}^{\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\sum_{n=1}^{\\text{N}} n^2} where :math:`d_t` is the deltas at","frame_to_remove = waveform[:, last_window_start, :] cur_sum -= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove","= specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value","1, 'momentum={} > 1 can be unstable'.format(momentum) assert momentum >= 0, 'momentum={} <","number of frequencies to highlight/apply to x the number of filterbanks. Each column","with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False,","(float, optional): Cutoff frequency for LowPass filter (Hz) (default: 1000) resample_frequency (float, optional):","not None: # Expand batch shape = x_db.size() packed_channels = shape[-3] if x_db.dim()","Tensor, multiplier: float, amin: float, db_multiplier: float, top_db: Optional[float] = None ) ->","time equals the ``length`` parameter if given. \"\"\" assert momentum < 1, 'momentum={}","complex_specgrams: Tensor, rate: float, phase_advance: Tensor ) -> Tensor: r\"\"\"Given a STFT tensor,","complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1,","*= math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int )","value for `n_freqs` ({n_freqs}) may be set too low.\" ) return fb def","time) sample_rate (int): Sample rate of the audio waveform pad (int): Two sided","the input and output Tensor have dimension ``[channel, time]``. Otherwise, they have dimension","angles = rebuilt if momentum: angles = angles - tprev.mul_(momentum / (1 +","to between -1 and 1 and returns a signal encoded with values from","is the energy :math:`\\sum_{n=j}^{j+N-1} w^2(n)`. \"\"\" EPSILON = 10 ** (-9) # Number","per utterance. Args: waveform (Tensor): Tensor of audio of dimension (..., freq, time)","0.005) nccf_ballast (float, optional): Increasing this factor reduces NCCF for quiet frames (default:","10 ** (-2), win_length: int = 30, freq_low: int = 85, freq_high: int","function computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The input","+ 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int ) -> Tensor:","snip_edges (bool, optional): If this is set to false, the incomplete frames near","used at start of decoding (adds latency only at start). Only applicable if","None, then the complex spectrum is returned instead. normalized (bool): Whether to normalize","science conference, pp. 18-25. 2015. * [2] <NAME>., <NAME>., & <NAME>. \"A fast","sample_rate: int, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, )","== ceil(300 / 1.3) torch.Size([2, 1025, 231, 2]) \"\"\" # pack batch shape","delta coefficients of a tensor, usually a spectrogram: .. math:: d_t = \\frac{\\sum_{n=1}^{\\text{N}}","Complex Specgrams Stretch with dimension of `(..., freq, ceil(time/rate), complex=2)` Example >>> freq,","given window. \"\"\" # Centered windowed pad_length = (win_length - 1) // 2","a tensor from the decibel scale to the power/amplitude scale. Args: x (Tensor):","of decoding -- not the final version of the features, which is the","for power, etc. If None, then the complex spectrum is returned instead. normalized","/ freq_high)) # Find near enough max that is smallest best = torch.max(nccf[...,","E(m+b_i)}}, where :math:`\\phi_i(m)` is the NCCF at frame :math:`i` with lag :math:`m`, :math:`w`","return half of results to avoid redundancy. Default: ``True`` Returns: Tensor: Dimension (...,","algorithm,\" IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (pp.","by magnitude after stft center (bool, optional): whether to pad :attr:`waveform` on both","Tensor, window: Tensor, n_fft: int, hop_length: int, win_length: int, power: float, normalized: bool,","# (n_freqs, n_mels + 2) # create overlapping triangles zero = torch.zeros(1) down_slopes","complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float):","power) def _hz_to_mel(freq: float, mel_scale: str = \"htk\") -> float: r\"\"\"Convert Hz to","None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch example masking specgrams","* mask_param min_value = torch.rand(1) * (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end","If true, use a window centered on the current frame (to the extent","into snippets vs. a full clip. Args: x (Tensor): Input spectrogram(s) before being","audio waveform. format (str): File format. channels_first (bool): When True, both the input","freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor, cmn_window: int = 600,","(float): Power of the norm. (Default: `1.0`) Returns: (Tensor, Tensor): The magnitude and","return indices def _median_smoothing( indices: Tensor, win_length: int ) -> Tensor: r\"\"\" Apply","Number of mel filterbanks sample_rate (int): Sample rate of the audio waveform norm","* create_fb_matrix(A.size(-1), ...)``. \"\"\" if norm is not None and norm != \"slaney\":","detected (Hz) (Default: ``85``). freq_high (int, optional): Highest frequency that can be detected","normalized: warnings.warn( \"The argument normalized is not used in Griffin-Lim, \" \"and will","elementwise. \"\"\" mask = (a[0] > thresh * b[0]) values = mask *","is a matrix A of size (..., ``n_freqs``), the applied result would be","Tensor: r\"\"\" Apply sliding-window cepstral mean (and optionally variance) normalization per utterance. Args:","(default: 25.0) frame_shift (float, optional): Frame shift in milliseconds. (default: 10.0) min_f0 (float,","Oct. 2013. * [3] <NAME> and <NAME>, \"Signal estimation from modified short-time Fourier","for quiet frames (default: 7000) lowpass_filter_width (int, optional): Integer that determines filter width","-1) specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end), mask_value) specgrams = specgrams.transpose(axis, -1)","= 600, min_cmn_window: int = 100, center: bool = False, norm_vars: bool =","(2 * math.pi)) # Compute Phase Accum phase = phase + phase_advance phase","cur_sum / window_frames if norm_vars: if window_frames == 1: cmn_waveform[:, t, :] =","won't be snipped, so that the number of frames is the file size","lowpass_filter_width (int, optional): Integer that determines filter width of lowpass filter, more gives","is the beginning of frame :math:`i`, :math:`E(j)` is the energy :math:`\\sum_{n=j}^{j+N-1} w^2(n)`. \"\"\"","into its magnitude and phase. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)`","Proceedings of the 14th python in science conference, pp. 18-25. 2015. * [2]","to each frame/window n_fft (int): Size of FFT, creates ``n_fft // 2 +","* (10.0**(mels / 2595.0) - 1.0) # Fill in the linear scale f_min","max_f0: float = 400, soft_min_f0: float = 10.0, penalty_factor: float = 0.1, lowpass_cutoff:","where the last dimension corresponds to pitch and NCCF. Reference: - A pitch","specgram.dtype # pack batch shape = specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert","ceil(300 / 1.3) torch.Size([2, 1025, 231, 2]) \"\"\" # pack batch shape =","create_fb_matrix(A.size(-1), ...)``. \"\"\" if norm is not None and norm != \"slaney\": raise","-1, :] else: if window_start > last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum","other than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the","math:: \\phi_i(m) = \\frac{\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\phi_i(m)` is the","`(..., complex=2)` power (float): Power of the norm. (Default: `1.0`). Returns: Tensor: Power","right-multiplied to row-wise data of size (``n_mels``, ``n_mfcc``). \"\"\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n =","bins # Equivalent filterbank construction by Librosa all_freqs = torch.linspace(0, sample_rate // 2,","`n_freqs` ({n_freqs}) may be set too low.\" ) return fb def create_dct( n_mfcc:","of dimension (..., freq, frames) where freq is ``n_fft // 2 + 1``.","Mel frequencies mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``)","used for computing delta (Default: ``5``) mode (str, optional): Mode parameter passed to","= waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default values are consistent with librosa.core.spectrum._spectrogram","sample_rate / (EPSILON + indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:]))","hop_length: int, win_length: int, ) -> Tensor: r\"\"\" Compute the spectral centroid for","of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` Return:","and <NAME>. \"librosa: Audio and music signal analysis in python.\" In Proceedings of","Output tensor in power/amplitude scale. \"\"\" return ref * torch.pow(torch.pow(10.0, 0.1 * x),","(int): Number of mfc coefficients to retain n_mels (int): Number of mel filterbanks","tensor over the given window. \"\"\" # Centered windowed pad_length = (win_length -","1000) >>> delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \"\"\" device = specgram.device","bin numbers to frequencies. Args: mels (Tensor): Mel frequencies mel_scale (str, optional): Scale","on (1 -> frequency, 2 -> time) Returns: Tensor: Masked spectrogram of dimensions","[0, 0, 0, 2]) # (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1","Number of mfc coefficients to retain n_mels (int): Number of mel filterbanks norm","lags + num_of_frames * frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) #","_combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float = 0.99 ) ->","and amin)) top_db (float or None, optional): Minimum negative cut-off in decibels. A","k) # size (n_mfcc, n_mels) if norm is None: dct *= 2.0 else:","window_end = 0 if center: window_start = t - cmn_window // 2 window_end","time :math:`t`, :math:`c_t` is the spectrogram coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``.","```channels_first```. sample_rate (int): Sample rate of the audio waveform. format (str): File format.","Args: x (Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input","else: window_start = t - cmn_window window_end = t + 1 if window_start","Optional[float] = None, encoding: Optional[str] = None, bits_per_sample: Optional[int] = None, ) ->","* k) # size (n_mfcc, n_mels) if norm is None: dct *= 2.0","``[v_0, v_0 + v)``, where ``v`` is sampled from ``uniform(0, mask_param)``, and ``v_0``","ValueError('mel_scale should be one of \"htk\" or \"slaney\".') if mel_scale == \"htk\": return","that assuming there is a matrix A of size (..., ``n_freqs``), the applied","``\"reflect\"`` onesided (bool, optional): controls whether to return half of results to avoid","(int, optional): Lowest frequency that can be detected (Hz) (Default: ``85``). freq_high (int,","Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \"\"\" shape = waveform.shape","\"amplitude_to_DB\", \"DB_to_amplitude\", \"compute_deltas\", \"compute_kaldi_pitch\", \"create_fb_matrix\", \"create_dct\", \"compute_deltas\", \"detect_pitch_frequency\", \"DB_to_amplitude\", \"mu_law_encoding\", \"mu_law_decoding\", \"complex_norm\", \"angle\",","pad), \"constant\") # pack batch shape = waveform.size() waveform = waveform.reshape(-1, shape[-1]) #","ignored if center==true (int, default = 100) center (bool, optional): If true, use","pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:])","* specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int, format: str,","/ 2 * mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels:","waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0,","of `waveform`. frame_length (float, optional): Frame length in milliseconds. (default: 25.0) frame_shift (float,","If power equals 1, will compute DB to power. If 0.5, will compute","the form `(..., freq, time)`. Batched inputs should include a channel dimension and","= torch.linspace(0, sample_rate // 2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim","[2] <NAME>., <NAME>., & <NAME>. \"A fast Griffin-Lim algorithm,\" IEEE Workshop on Applications","import warnings from typing import Optional, Tuple import torch from torch import Tensor","freq >= min_log_hz: mels = min_log_mel + math.log(freq / min_log_hz) / logstep return","near enough max that is smallest best = torch.max(nccf[..., lag_min:], -1) half_size =","return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float = 25.0,","so may return different values for an audio clip split into snippets vs.","n_fft: int, hop_length: int, win_length: int, power: float, normalized: bool, n_iter: int, momentum:","torch.tensor(0.) for _ in range(n_iter): # Store the previous iterate tprev = rebuilt","time, complex=2) >>> complex_specgrams = torch.randn(2, freq, 300, 2) >>> rate = 1.3","by Librosa all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) # calculate mel freq","(float): Exponent for the magnitude spectrogram, (must be > 0) e.g., 1 for","if mel_scale == \"htk\": return 2595.0 * math.log10(1.0 + (freq / 700.0)) #","implemented using normalized cross-correlation function and median smoothing. Args: waveform (Tensor): Tensor of","normalized=False, onesided=True, return_complex=True, ) ) # Update our phase estimates angles = rebuilt","(mask < mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram:","Tensor: r\"\"\"Compute the angle of complex tensor input. Args: complex_tensor (Tensor): Tensor shape","f\"The value for `n_mels` ({n_mels}) may be set too high. \" f\"Or, the","14th python in science conference, pp. 18-25. 2015. * [2] <NAME>., <NAME>., &","window_start = t - cmn_window window_end = t + 1 if window_start <","frequency for LowPass filter (Hz) (default: 1000) resample_frequency (float, optional): Frequency that we","(default: 0.005) nccf_ballast (float, optional): Increasing this factor reduces NCCF for quiet frames","a STFT tensor, speed up in time without modifying pitch by a factor","rate: float, phase_advance: Tensor ) -> Tensor: r\"\"\"Given a STFT tensor, speed up","angle of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)`","1) * (2 * n + 1) / 3 specgram = torch.nn.functional.pad(specgram, (n,","Sample rate of the audio waveform. format (str): File format. channels_first (bool): When","for compatibility with online pitch extraction. A non-critical parameter; the frame at which","optional): Smallest relative change in pitch that our algorithm measures. (default: 0.005) nccf_ballast","specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0,","norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1, :] else: if window_start >","frequencies to highlight/apply f_min (float): Minimum frequency (Hz) f_max (float): Maximum frequency (Hz)","for `n_mels` ({n_mels}) may be set too high. \" f\"Or, the value for","_mod_utils import torchaudio __all__ = [ \"spectrogram\", \"griffinlim\", \"amplitude_to_DB\", \"DB_to_amplitude\", \"compute_deltas\", \"compute_kaldi_pitch\", \"create_fb_matrix\",","-= window_start window_start = 0 if not center: if window_end > t: window_end","__all__ = [ \"spectrogram\", \"griffinlim\", \"amplitude_to_DB\", \"DB_to_amplitude\", \"compute_deltas\", \"compute_kaldi_pitch\", \"create_fb_matrix\", \"create_dct\", \"compute_deltas\", \"detect_pitch_frequency\",","min_log_hz) / logstep return mels def _mel_to_hz(mels: Tensor, mel_scale: str = \"htk\") ->","normalization. (default: 0) simulate_first_pass_online (bool, optional): If true, the function will output features","torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf =","waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames,","= waveform.reshape(-1, shape[-1]) # default values are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft(","from the power/amplitude scale to the decibel scale. The output of each tensor","db_multiplier (float): Log10(max(reference value and amin)) top_db (float or None, optional): Minimum negative","(mels >= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel)) return","waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file(","0, simulate_first_pass_online: bool = False, recompute_frame: int = 500, snip_edges: bool = True,",":] cur_sum -= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove ** 2) if window_end","signal. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input","of size (``n_freqs``, ``n_mels``) meaning number of frequencies to highlight/apply to x the","the masked columns axis (int): Axis to apply masking on (2 -> frequency,","the second, elementwise. \"\"\" mask = (a[0] > thresh * b[0]) values =","the decibel scale. The output of each tensor in a batch depends on","batch shape = list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate,","(int): Window size power (float or None): Exponent for the magnitude spectrogram, (must","if norm_vars: if window_frames == 1: cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats,","(float, optional): Maximum F0 to search for (Hz) (default: 400.0) soft_min_f0 (float, optional):","\"htk\") -> Tensor: \"\"\"Convert mel bin numbers to frequencies. Args: mels (Tensor): Mel","optional): Maximum F0 to search for (Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum","the log-scale part min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp","shape = waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default values are consistent with","by a factor of ``rate``. Args: complex_specgrams (Tensor): Dimension of `(..., freq, time,","sum of integer squared denom = n * (n + 1) * (2","1 for energy, 2 for power, etc. normalized (bool): Whether to normalize by","waveform: torch.Tensor, sample_rate: float, frame_length: float = 25.0, frame_shift: float = 10.0, min_f0:","or 'slaney'\") # freq bins # Equivalent filterbank construction by Librosa all_freqs =","torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) -","rate = 1.3 # Speed up by 30% >>> phase_advance = torch.linspace( >>>","of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The input waveform of shape `(...,","* torch.round(phase / (2 * math.pi)) # Compute Phase Accum phase = phase","+ 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) /","if True, to zero otherwise. Returns: torch.Tensor: waveform of (..., time), where time","= waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[...,","window centered on the current frame (to the extent possible, modulo end effects).","if ``frames_per_chunk > 0``. recompute_frame (int, optional): Only relevant for compatibility with online","= _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between each mel point and each",") -> Tensor: r\"\"\"Turn a tensor from the decibel scale to the power/amplitude","r\"\"\"Decode mu-law encoded signal. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This","int = 85, freq_high: int = 3400, ) -> Tensor: r\"\"\"Detect pitch frequency.","JIT supports it waveform = torch.nn.functional.pad(waveform, (pad, pad), \"constant\") # pack batch shape","io import math import warnings from typing import Optional, Tuple import torch from","and time is the number of window hops (n_frame). \"\"\" if pad >","mag = alphas * norm_1 + (1 - alphas) * norm_0 real_stretch =","mask_param] mask_value (float): Value to assign to the masked columns axis (int): Axis","are supported') # unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def","import module_utils as _mod_utils import torchaudio __all__ = [ \"spectrogram\", \"griffinlim\", \"amplitude_to_DB\", \"DB_to_amplitude\",","shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) * mask_param","= multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier if top_db is","= torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag = alphas *","issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor","Cross-Correlation Function (NCCF). .. math:: \\phi_i(m) = \\frac{\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\sqrt{E(b_i) E(m+b_i)}},","norm is None: dct *= 2.0 else: assert norm == \"ortho\" dct[0] *=","dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames,","4000) delta_pitch( float, optional): Smallest relative change in pitch that our algorithm measures.","part min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep =","what an online decoder would see in the first pass of decoding --","is 80. (Default: ``None``) Returns: Tensor: Output tensor in decibel scale \"\"\" x_db",":math:`t`-th frame is centered at time :math:`t \\times \\text{hop\\_length}`. Default: ``True`` pad_mode (string,","rand_init: angles = 2 * math.pi * torch.rand(batch, freq, frames) else: angles =","shape[-3] if x_db.dim() > 2 else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1])","(int): Window size. (Default: ``n_fft``) power (float): Exponent for the magnitude spectrogram, (must","and returns a signal encoded with values from 0 to quantization_channels - 1.","phase = angle_1 - angle_0 - phase_advance phase = phase - 2 *","the norm. (Default: `1.0`). Returns: Tensor: Power of the normed input tensor. Shape","waveform: Tensor, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, power:","and music signal analysis in python.\" In Proceedings of the 14th python in","spectrograms (batch, channel, freq, time) mask_param (int): Number of columns to be masked","factor for FO change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency for LowPass","lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result","center==true (int, default = 100) center (bool, optional): If true, use a window","number of filterbanks. Each column is a filterbank so that assuming there is","rebuilt # Invert with our current estimate of the phases inverse = torch.istft(specgram","multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier if top_db is not","the power/amplitude scale to the decibel scale. The output of each tensor in","to use (either 'ortho' or None) Returns: Tensor: The transformation matrix, to be","band (area normalization). (Default: ``None``) mel_scale (str, optional): Scale to use: ``htk`` or","cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0)","specgrams def mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float, axis: int ) ->","'slaney'\") # freq bins # Equivalent filterbank construction by Librosa all_freqs = torch.linspace(0,","(min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0 log_t = (mels","For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with","Hz \"\"\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be one","window_start last_window_end = window_end cmn_waveform[:, t, :] = waveform[:, t, :] - cur_sum","f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not","f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels)","``10 ** (-2)``). win_length (int, optional): The window length for median smoothing (in","pp.236–243, Apr. 1984. Args: specgram (Tensor): A magnitude-only STFT spectrogram of dimension (...,","Example >>> freq, hop_length = 1025, 512 >>> # (channel, freq, time, complex=2)","num_frames, num_feats, dtype=dtype, device=device) for t in range(num_frames): window_start = 0 window_end =","!= \"slaney\": raise ValueError(\"norm must be one of None or 'slaney'\") # freq","-1 and 1. Args: x_mu (Tensor): Input tensor quantization_channels (int): Number of channels","# pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram =","number of Fourier bins, and time is the number of window hops (n_frame).","supported') # unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas(","= torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch waveform","delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \"\"\" device = specgram.device dtype =","device = specgram.device dtype = specgram.dtype # pack batch shape = specgram.size() specgram","pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, ) -> Tensor:","freq_high: int = 3400, ) -> Tensor: r\"\"\"Detect pitch frequency. It is implemented","num_channels, num_feats, dtype=dtype, device=device) else: variance = cur_sumsq variance = variance / window_frames","return x def complex_norm( complex_tensor: Tensor, power: float = 1.0 ) -> Tensor:","an online decoder would see in the first pass of decoding -- not","2 + 1`` and ``n_fft`` is the number of Fourier bins, and time","window_end cmn_waveform[:, t, :] = waveform[:, t, :] - cur_sum / window_frames if","(str, optional): Mode parameter passed to padding (Default: ``\"replicate\"``) Returns: Tensor: Tensor of","frequency that can be detected (Hz) (Default: ``85``). freq_high (int, optional): Highest frequency","norm_1 + (1 - alphas) * norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch","that can be detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor of freq of","in Hz \"\"\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be","torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu + 1) / 2 * mu +","2 for power, etc. normalized (bool): Whether to normalize by magnitude after stft.","* math.pi * torch.round(phase / (2 * math.pi)) # Compute Phase Accum phase","using the Griffin-Lim transformation. Implementation ported from `librosa`. * [1] McFee, Brian, <NAME>,","angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram rebuilt = torch.view_as_real(","return waveform def amplitude_to_DB( x: Tensor, multiplier: float, amin: float, db_multiplier: float, top_db:","< 1, 'momentum={} > 1 can be unstable'.format(momentum) assert momentum >= 0, 'momentum={}","= min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs def create_fb_matrix( n_freqs:","num_of_frames = int(math.ceil(waveform_length / frame_size)) p = lags + num_of_frames * frame_size -","sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. Args: specgrams","(s1 * s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2,","2 - 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) /","/ (2 * math.pi)) # Compute Phase Accum phase = phase + phase_advance","+ shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high)","and Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \"\"\" shape =","2013. * [3] <NAME> and <NAME>, \"Signal estimation from modified short-time Fourier transform,\"","of frequencies to highlight/apply to x the number of filterbanks. Each column is","a[0] + ~mask * b[0] indices = mask * a[1] + ~mask *","stft. n_iter (int): Number of iteration for phase recovery process. momentum (float): The","Replace by torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power)","-> Tensor: r\"\"\" Compute Normalized Cross-Correlation Function (NCCF). .. math:: \\phi_i(m) = \\frac{\\sum_{n=b_i}^{b_i","-2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate:","dimension ``[time, channel]``. compression (float): Used for formats other than WAV. For mor","Processing to Audio and Acoustics (pp. 1-4), Oct. 2013. * [3] <NAME> and","cmn_window (int, optional): Window in frames for running average CMN computation (int, default","`(..., freq, time, complex=2)` rate (float): Speed-up factor phase_advance (Tensor): Expected phase advance","/ (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates","last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum -= frame_to_remove if norm_vars: cur_sumsq -=","is the number of Fourier bins, and time is the number of window","mel_scale == \"htk\": return 2595.0 * math.log10(1.0 + (freq / 700.0)) # Fill","dim=-1) \\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate","float, freq_low: int ) -> Tensor: r\"\"\" Compute Normalized Cross-Correlation Function (NCCF). ..","n_mels: int, sample_rate: int, norm: Optional[str] = None, mel_scale: str = \"htk\", )","specgram def compute_deltas( specgram: Tensor, win_length: int = 5, mode: str = \"replicate\"","_find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length) # Convert indices to frequency EPSILON","(int): Size of FFT, creates ``n_fft // 2 + 1`` bins hop_length (int):","# Update our phase estimates angles = rebuilt if momentum: angles = angles","in range(n_iter): # Store the previous iterate tprev = rebuilt # Invert with","Signal Processing to Audio and Acoustics (pp. 1-4), Oct. 2013. * [3] <NAME>","= 10 ** (-2), win_length: int = 30, freq_low: int = 85, freq_high:","2 * mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int","mag, phase def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor ) -> Tensor:","sample_rate: int, frame_time: float = 10 ** (-2), win_length: int = 30, freq_low:",") -> Tensor: r\"\"\"Create a DCT transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized","# Store the previous iterate tprev = rebuilt # Invert with our current","40, 1000) >>> delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \"\"\" device =","optional): Cutoff frequency for LowPass filter (Hz) (default: 1000) resample_frequency (float, optional): Frequency","True, both the input and output Tensor have dimension ``[channel, time]``. Otherwise, they","of the complex tensor \"\"\" mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor) return","a frame (Default: ``10 ** (-2)``). win_length (int, optional): The window length for","onesided: bool = True ) -> Tensor: r\"\"\"Create a spectrogram or a batch","tensor that is applied/multiplied to each frame/window n_fft (int): Size of FFT hop_length","window_frames variance -= ((cur_sum ** 2) / (window_frames ** 2)) variance = torch.pow(variance,","= waveform.shape[0] dtype = waveform.dtype device = waveform.device last_window_start = last_window_end = -1","2, 1)[:, -1, :] else: if window_start > last_window_start: frame_to_remove = waveform[:, last_window_start,","where freq is ``n_fft // 2 + 1``. window (Tensor): Window tensor that","frame at which we recompute some of the forward pointers, after revising our","split into snippets vs. a full clip. Args: x (Tensor): Input spectrogram(s) before","f_max (float): Maximum frequency (Hz) n_mels (int): Number of mel filterbanks sample_rate (int):","the frequency values, weighted by their magnitude. Args: waveform (Tensor): Tensor of audio","'sliding_window_cmn', \"spectral_centroid\", \"apply_codec\", ] def spectrogram( waveform: Tensor, pad: int, window: Tensor, n_fft:","output def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float, freq_low: int ) ->","3 n = (win_length - 1) // 2 # twice sum of integer","# \"replicate\" padding in any dimension indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\"constant\",","= \"replicate\" ) -> Tensor: r\"\"\"Compute delta coefficients of a tensor, usually a","current frame (to the extent possible, modulo end effects). If false, window is","(default: 7000) lowpass_filter_width (int, optional): Integer that determines filter width of lowpass filter,","channels_first: bool = True, compression: Optional[float] = None, encoding: Optional[str] = None, bits_per_sample:","quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law encoding \"\"\" mu","Time masking are supported') # unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return","* torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu + 1) / 2 * mu","the number of window hops (n_frame). \"\"\" if pad > 0: # TODO","the width of the mel band (area normalization). (Default: ``None``) mel_scale (str, optional):","= False, ) -> Tensor: r\"\"\" Apply sliding-window cepstral mean (and optionally variance)","to frequency EPSILON = 10 ** (-9) freq = sample_rate / (EPSILON +","x: Tensor, multiplier: float, amin: float, db_multiplier: float, top_db: Optional[float] = None )","int, f_min: float, f_max: float, n_mels: int, sample_rate: int, norm: Optional[str] = None,","Griffin-Lim algorithm,\" IEEE Workshop on Applications of Signal Processing to Audio and Acoustics","2 and axis != 3: raise ValueError('Only Frequency and Time masking are supported')","= slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes))","time) \"\"\" # pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:]))","be applied from indices ``[v_0, v_0 + v)``, where ``v`` is sampled from","> 0) e.g., 1 for energy, 2 for power, etc. If None, then","dimensional. See also ```channels_first```. sample_rate (int): Sample rate of the audio waveform. format","with shape `(..., 2)` into its magnitude and phase. Args: complex_tensor (Tensor): Tensor","of (freq, 1) Returns: Tensor: Complex Specgrams Stretch with dimension of `(..., freq,","that the number of frames is the file size divided by the frame-shift.","scale. Args: x (Tensor): Input tensor before being converted to power/amplitude scale. ref","cur_sumsq += (frame_to_add ** 2) window_frames = window_end - window_start last_window_start = window_start","vs. a full clip. Args: x (Tensor): Input spectrogram(s) before being converted to","torch.linspace( >>> 0, math.pi * hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate,","norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames = window_end - window_start last_window_start =","freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with 231","then the complex spectrum is returned instead. normalized (bool): Whether to normalize by","spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if power is not None: if power","freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles)","return fb def create_dct( n_mfcc: int, n_mels: int, norm: Optional[str] ) -> Tensor:","w^2(n)`. \"\"\" EPSILON = 10 ** (-9) # Number of lags to check","of the waveform (Hz) frame_time (float, optional): Duration of a frame (Default: ``10","clamp ``x`` db_multiplier (float): Log10(max(reference value and amin)) top_db (float or None, optional):",") -> Tensor: r\"\"\"Compute waveform from a linear scale magnitude spectrogram using the","min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep = math.log(6.4)","\"\"\" assert momentum < 1, 'momentum={} > 1 can be unstable'.format(momentum) assert momentum","the spectrogram coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor","freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor, cmn_window: int","back when JIT supports it waveform = torch.nn.functional.pad(waveform, (pad, pad), \"constant\") # pack","(freq - f_min) / f_sp # Fill in the log-scale part min_log_hz =","3 freqs = f_min + f_sp * mels # And now the nonlinear","= torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2,","controls the padding method used when :attr:`center` is ``True``. Default: ``\"reflect\"`` onesided (bool,","2494-2498, doi: 10.1109/ICASSP.2014.6854049. \"\"\" shape = waveform.shape waveform = waveform.reshape(-1, shape[-1]) result =","that is smallest best = torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] // 2","** 2) if window_end > last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum +=","down-sample the signal to. Must be more than twice lowpass-cutoff. (default: 4000) delta_pitch(","@_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int, format: str, channels_first: bool = True,","(string, optional): controls the padding method used when :attr:`center` is ``True``. Default: ``\"reflect\"``","bytes, effects=[[\"rate\", f\"{sample_rate}\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate:","(float or None): Exponent for the magnitude spectrogram, (must be > 0) e.g.,","warnings.warn( \"The argument normalized is not used in Griffin-Lim, \" \"and will be","of the norm. (Default: `1.0`). Returns: Tensor: Power of the normed input tensor.","/ window_frames variance -= ((cur_sum ** 2) / (window_frames ** 2)) variance =","Optional[float] = None ) -> Tensor: r\"\"\"Turn a spectrogram from the power/amplitude scale","(Tensor): Tensor of audio of dimension (..., freq, time) cmn_window (int, optional): Window","Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi:","power (float or None): Exponent for the magnitude spectrogram, (must be > 0)","A non-critical parameter; the frame at which we recompute some of the forward","= last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels,","the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect',","Mode parameter passed to padding (Default: ``\"replicate\"``) Returns: Tensor: Tensor of deltas of","# http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels)","= int(math.ceil(waveform_length / frame_size)) p = lags + num_of_frames * frame_size - waveform_length","Must be 2 dimensional. See also ```channels_first```. sample_rate (int): Sample rate of the","* s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2,","-= (frame_to_remove ** 2) if window_end > last_window_end: frame_to_add = waveform[:, last_window_end, :]","along ``axis``. Mask will be applied from indices ``[v_0, v_0 + v)``, where","(pad_length, 0), mode=\"constant\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1)","+ (num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def","audio clip split into snippets vs. a full clip. Args: x (Tensor): Input","( Default: ``win_length // 2``) win_length (int): Window size. (Default: ``n_fft``) power (float):","min_cmn_window: int = 100, center: bool = False, norm_vars: bool = False, )","more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has","mean (and optionally variance) normalization per utterance. Args: waveform (Tensor): Tensor of audio","= 2 * math.pi * torch.rand(batch, freq, frames) else: angles = torch.zeros(batch, freq,","``A * create_fb_matrix(A.size(-1), ...)``. \"\"\" if norm is not None and norm !=","float = 10.0, min_f0: float = 50, max_f0: float = 400, soft_min_f0: float","specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor, win_length: int = 5,","torch.rand(batch, freq, frames) else: angles = torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()],","a mask along ``axis``. Mask will be applied from indices ``[v_0, v_0 +","(int): Number of frequencies to highlight/apply f_min (float): Minimum frequency (Hz) f_max (float):","500, snip_edges: bool = True, ) -> torch.Tensor: \"\"\"Extract pitch based on method","optional): Increasing this factor reduces NCCF for quiet frames (default: 7000) lowpass_filter_width (int,","1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x =","= specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) * mask_param min_value = torch.rand(1) *","+= 1 return indices def _median_smoothing( indices: Tensor, win_length: int ) -> Tensor:","= waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p = lags + num_of_frames *","values = mask * a[0] + ~mask * b[0] indices = mask *","waveform (Tensor): Tensor of audio of dimension (..., freq, time) sample_rate (int): The","quantization_channels: int ) -> Tensor: r\"\"\"Encode signal based on mu-law companding. For more","Tensor from torchaudio._internal import module_utils as _mod_utils import torchaudio __all__ = [ \"spectrogram\",","Input tensor before being converted to power/amplitude scale. ref (float): Reference which the","into the feature processing (affects output only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``)","specgram.pow(1 / power) # randomly initialize the phase batch, freq, frames = specgram.size()","Number of columns to be masked will be uniformly sampled from [0, mask_param]","batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor, win_length:","lag_min # Add 1 empirical calibration offset indices += 1 return indices def","= waveform[:, window_start: window_end - window_start, :] cur_sum += torch.sum(input_part, 1) if norm_vars:","torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value) # Create broadcastable mask mask_start =","/ logstep return mels def _mel_to_hz(mels: Tensor, mel_scale: str = \"htk\") -> Tensor:","<NAME>., & <NAME>. \"A fast Griffin-Lim algorithm,\" IEEE Workshop on Applications of Signal","(int): Length of hop between STFT windows win_length (int): Window size Returns: Tensor:","complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0,","of augmentation. Args: waveform (Tensor): Audio data. Must be 2 dimensional. See also","The input waveform of shape `(..., time)`. sample_rate (float): Sample rate of `waveform`.","or \"slaney\".') if mel_scale == \"htk\": return 700.0 * (10.0**(mels / 2595.0) -","way, must not exceed min-f0 (default: 10.0) penalty_factor (float, optional): Cost factor for","of a complex tensor. Shape of `(..., )` \"\"\" return torch.atan2(complex_tensor[..., 1], complex_tensor[...,","supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit","per channel enorm = 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *=","`(..., freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length = 1025, 512 >>> #","In Proceedings of the 14th python in science conference, pp. 18-25. 2015. *","(Default: ``None``) Returns: Tensor: Output tensor in decibel scale \"\"\" x_db = multiplier","high. \" f\"Or, the value for `n_freqs` ({n_freqs}) may be set too low.\"","def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor ) -> Tensor: r\"\"\"Given a","with 231 == ceil(300 / 1.3) torch.Size([2, 1025, 231, 2]) \"\"\" # pack","2: specgram[:, :, mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency and Time masking","values are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window,","``htk``) Returns: freqs (Tensor): Mels converted in Hz \"\"\" if mel_scale not in","mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency and Time masking are supported') #","Window tensor that is applied/multiplied to each frame/window n_fft (int): Size of FFT","pack batch shape = waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default values are","or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels converted in Hz \"\"\" if","Mels converted in Hz \"\"\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale","+ waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor, multiplier: float, amin: float, db_multiplier:","== 0.).any(): warnings.warn( \"At least one mel filterbank has all zero values. \"","lags is very close to the first half of lags, then the latter","Fill in the log-scale part min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min)","matrix, to be right-multiplied to row-wise data of size (``n_mels``, ``n_mfcc``). \"\"\" #","channel, freq, time) mask_param (int): Number of columns to be masked will be","= torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis)","math.pi * hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape","``uniform(0, max_v - v)``. Args: specgrams (Tensor): Real spectrograms (batch, channel, freq, time)","win_length, 1) values, _ = torch.median(roll, -1) return values def detect_pitch_frequency( waveform: Tensor,","window_frames = window_end - window_start last_window_start = window_start last_window_end = window_end cmn_waveform[:, t,","def sliding_window_cmn( waveform: Tensor, cmn_window: int = 600, min_cmn_window: int = 100, center:","dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 - angle_0 - phase_advance","value) # Create broadcastable mask mask_start = min_value[..., None, None] mask_end = (min_value","t - cmn_window window_end = t + 1 if window_start < 0: window_end","our algorithm measures. (default: 0.005) nccf_ballast (float, optional): Increasing this factor reduces NCCF","nccf_ballast (float, optional): Increasing this factor reduces NCCF for quiet frames (default: 7000)","a signal encoded with values from 0 to quantization_channels - 1. Args: x","NCCF. Reference: - A pitch extraction algorithm tuned for automatic speech recognition <NAME>,","returned instead. normalized (bool): Whether to normalize by magnitude after stft center (bool,","2, n_freqs) # calculate mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max =","-> time) Returns: Tensor: Masked spectrogram of dimensions (channel, freq, time) \"\"\" #","number of frames of latency that we allow pitch tracking to introduce into","complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float, axis: int ) ->","constant energy per channel enorm = 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels])","latency only at start). Only applicable if center == false, ignored if center==true","of lowpass filter, more gives sharper filter. (default: 1) upsample_filter_width (int, optional): Integer","Tensor: Dimension (..., freq, time), freq is ``n_fft // 2 + 1`` and","specgram.reshape(1, -1, shape[-1]) assert win_length >= 3 n = (win_length - 1) //","= mask * a[0] + ~mask * b[0] indices = mask * a[1]","cur_sumsq variance = variance / window_frames variance -= ((cur_sum ** 2) / (window_frames","> last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum += frame_to_add if norm_vars: cur_sumsq","phase recovery process. momentum (float): The momentum parameter for fast Griffin-Lim. Setting this","\"compute_deltas\", \"compute_kaldi_pitch\", \"create_fb_matrix\", \"create_dct\", \"compute_deltas\", \"detect_pitch_frequency\", \"DB_to_amplitude\", \"mu_law_encoding\", \"mu_law_decoding\", \"complex_norm\", \"angle\", \"magphase\", \"phase_vocoder\",","include a channel dimension and have the form `(batch, channel, freq, time)`. multiplier","complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:])","output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf def _combine_max( a: Tuple[Tensor, Tensor], b:","frames. (default: True) Returns: Tensor: Pitch feature. Shape: ``(batch, frames 2)`` where the","utf-8 -*- import io import math import warnings from typing import Optional, Tuple","Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor): A magnitude-only STFT","e.g., 1 for energy, 2 for power, etc. normalized (bool): Whether to normalize","= 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values","pack batch shape = specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert win_length >=","Apply sliding-window cepstral mean (and optionally variance) normalization per utterance. Args: waveform (Tensor):","by the width of the mel band (area normalization). (Default: ``None``) mel_scale (str,","the :math:`t`-th frame is centered at time :math:`t \\times \\text{hop\\_length}`. Default: ``True`` pad_mode","false, window is to the left. (bool, default = false) norm_vars (bool, optional):","Hz to Mels. Args: freqs (float): Frequencies in Hz mel_scale (str, optional): Scale","= specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 / power) # randomly initialize the","encoding (str, optional): Changes the encoding for the supported formats. For more details","size divided by the frame-shift. This makes different types of features give the","slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:, 2:] / f_diff[1:]","that can be detected (Hz) (Default: ``85``). freq_high (int, optional): Highest frequency that","sliding_window_cmn( waveform: Tensor, cmn_window: int = 600, min_cmn_window: int = 100, center: bool","r\"\"\"Separate a complex-valued spectrogram with shape `(..., 2)` into its magnitude and phase.","n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1])","length in milliseconds. (default: 25.0) frame_shift (float, optional): Frame shift in milliseconds. (default:","- f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \"At least one","optional): Integer that determines filter width when upsampling NCCF. (default: 5) max_frames_latency (int,","complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power: float = 1.0 ) -> Tuple[Tensor,","optional): If true, the function will output features that correspond to what an","last_window_end, :] cur_sum += frame_to_add if norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames","bool, n_iter: int, momentum: float, length: Optional[int], rand_init: bool ) -> Tensor: r\"\"\"Compute","of FFT hop_length (int): Length of hop between STFT windows win_length (int): Window","if top_db is not None: # Expand batch shape = x_db.size() packed_channels =","Specgrams Stretch with dimension of `(..., freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length","sample_rate: int, frame_time: float, freq_low: int ) -> Tensor: r\"\"\" Compute Normalized Cross-Correlation","thresh * b[0]) values = mask * a[0] + ~mask * b[0] indices","# Add 1 empirical calibration offset indices += 1 return indices def _median_smoothing(","return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor, n_fft:","dimension (..., freq, time) cmn_window (int, optional): Window in frames for running average","frequency bin conversion matrix. Args: n_freqs (int): Number of frequencies to highlight/apply f_min","mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. All examples will have the","optional): Minimum F0 to search for (Hz) (default: 50.0) max_f0 (float, optional): Maximum","final version of the features, which is the default. (default: False) Relevant if","specgram = torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta)","def mu_law_decoding( x_mu: Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Decode mu-law encoded signal.","frame/window n_fft (int): Size of FFT, creates ``n_fft // 2 + 1`` bins","complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0","weighted average of the frequency values, weighted by their magnitude. Args: waveform (Tensor):","linear scale magnitude spectrogram using the Griffin-Lim transformation. Implementation ported from `librosa`. *","\"\"\" return ref * torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq: float, mel_scale:","with values between 0 and quantization_channels - 1 and returns a signal scaled","1.3) torch.Size([2, 1025, 231, 2]) \"\"\" # pack batch shape = complex_specgrams.size() complex_specgrams","n_fft (int): Size of FFT hop_length (int): Length of hop between STFT windows","in decibel scale \"\"\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier","EPSILON = 10 ** (-9) # Number of lags to check lags =","Args: waveform (Tensor): Tensor of audio of dimension (..., freq, time) cmn_window (int,","optional): Integer that determines filter width of lowpass filter, more gives sharper filter.","** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance cmn_waveform =","/ 3 freqs = f_min + f_sp * mels # And now the","return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor, n_fft: int, hop_length:","complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float): Power of the norm.","1. Args: x_mu (Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor:","return 700.0 * (10.0**(mels / 2595.0) - 1.0) # Fill in the linear","+ 1``. window (Tensor): Window tensor that is applied/multiplied to each frame/window n_fft","- window_start last_window_start = window_start last_window_end = window_end cmn_waveform[:, t, :] = waveform[:,","-1)) - top_db).view(-1, 1, 1, 1)) # Repack batch x_db = x_db.reshape(shape) return","frequency EPSILON = 10 ** (-9) freq = sample_rate / (EPSILON + indices.to(torch.float))","2]) \"\"\" # pack batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:]))","batch shape = waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default values are consistent","center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) # Update our phase estimates angles","power/amplitude scale to the decibel scale. The output of each tensor in a","STFT windows. ( Default: ``win_length // 2``) win_length (int): Window size. (Default: ``n_fft``)","``htk``) Returns: Tensor: Triangular filter banks (fb matrix) of size (``n_freqs``, ``n_mels``) meaning","phase advance in each bin. Dimension of (freq, 1) Returns: Tensor: Complex Specgrams","are supported') device = specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype)","in frames for running average CMN computation (int, default = 600) min_cmn_window (int,","of dimension (..., time) sample_rate (int): Sample rate of the audio waveform pad","formats other than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes","last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats,","the beginning of frame :math:`i`, :math:`E(j)` is the energy :math:`\\sum_{n=j}^{j+N-1} w^2(n)`. \"\"\" EPSILON","the original Griffin-Lim method. Values near 1 can lead to faster convergence, but","= torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram,","be detected (Hz) (Default: ``85``). freq_high (int, optional): Highest frequency that can be","Tensor of freq of dimension (..., frame) \"\"\" # pack batch shape =","Stretch with dimension of `(..., freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length =","size. (Default: ``n_fft``) power (float): Exponent for the magnitude spectrogram, (must be >","1 if window_start < 0: window_end -= window_start window_start = 0 if not","which we recompute some of the forward pointers, after revising our estimate of","(bool, optional): whether to pad :attr:`waveform` on both sides so that the :math:`t`-th","power (float): If power equals 1, will compute DB to power. If 0.5,","``\"replicate\"``) Returns: Tensor: Tensor of deltas of dimension (..., freq, time) Example >>>","r\"\"\" Compute Normalized Cross-Correlation Function (NCCF). .. math:: \\phi_i(m) = \\frac{\\sum_{n=b_i}^{b_i + N-1}","/ (window_frames ** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance","sample_rate: int, format: str, channels_first: bool = True, compression: Optional[float] = None, encoding:","the Griffin-Lim transformation. Implementation ported from `librosa`. * [1] McFee, Brian, <NAME>, <NAME>,",":] - cur_sum / window_frames if norm_vars: if window_frames == 1: cmn_waveform[:, t,","to highlight/apply to x the number of filterbanks. Each column is a filterbank","-> Tensor: r\"\"\"Create a DCT transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized depending","for automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE","formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit depth","converted to decibel scale. Input should take the form `(..., freq, time)`. Batched","(default: False) Relevant if ``frames_per_chunk > 0``. recompute_frame (int, optional): Only relevant for","fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor ) ->","2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values ==","by. power (float): If power equals 1, will compute DB to power. If","Tensor shape of `(..., complex=2)` power (float): Power of the norm. (Default: `1.0`)","``v_0`` from ``uniform(0, max_v - v)``. Args: specgrams (Tensor): Real spectrograms (batch, channel,","= torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels)","onesided=True, return_complex=True, ) ) # Update our phase estimates angles = rebuilt if","dct[0] *= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return dct.t() def","Mels \"\"\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be one","A reasonable number is 80. (Default: ``None``) Returns: Tensor: Output tensor in decibel","(EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf","difference between each mel point and each stft freq point in hertz f_diff","n_mfcc: int, n_mels: int, norm: Optional[str] ) -> Tensor: r\"\"\"Create a DCT transformation","Args: waveform (Tensor): Audio data. Must be 2 dimensional. See also ```channels_first```. sample_rate","Tensor: Tensor of deltas of dimension (..., freq, time) Example >>> specgram =","depending on norm. Args: n_mfcc (int): Number of mfc coefficients to retain n_mels","window_frames if norm_vars: if window_frames == 1: cmn_waveform[:, t, :] = torch.zeros( num_channels,","the incomplete frames near the ending edge won't be snipped, so that the","waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor,","# -*- coding: utf-8 -*- import io import math import warnings from typing","penalty_factor: float = 0.1, lowpass_cutoff: float = 1000, resample_frequency: float = 4000, delta_pitch:","\"\"\" mask = (a[0] > thresh * b[0]) values = mask * a[0]","= -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype,","pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate // 2,","sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length) #","is to the left. (bool, default = false) norm_vars (bool, optional): If true,","of dimension (..., freq, time) win_length (int, optional): The window length used for","padding in any dimension indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\"constant\", value=0. )","power is not None: if power == 1.0: return spec_f.abs() return spec_f.abs().pow(power) return","(-9) freq = sample_rate / (EPSILON + indices.to(torch.float)) # unpack batch freq =","divided by the frame-shift. This makes different types of features give the same","# Equivalent filterbank construction by Librosa all_freqs = torch.linspace(0, sample_rate // 2, n_freqs)","Sample rate of the audio waveform pad (int): Two sided padding of signal","(bool, optional): If true, the function will output features that correspond to what","= spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if power is not","the output will be scaled by. power (float): If power equals 1, will","Frequency and Time masking are supported') # unpack batch specgram = specgram.reshape(shape[:-2] +","// 2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return","specgram[:, mask_start:mask_end] = mask_value elif axis == 2: specgram[:, :, mask_start:mask_end] = mask_value","of the mel band (area normalization). (Default: ``None``) mel_scale (str, optional): Scale to","quantization_channels - 1. Args: x (Tensor): Input tensor quantization_channels (int): Number of channels","an input with values between 0 and quantization_channels - 1 and returns a","= True ) -> Tensor: r\"\"\"Create a spectrogram or a batch of spectrograms","half = torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best) indices = best[1] #","(Tensor): Dimension of `(..., freq, time, complex=2)` rate (float): Speed-up factor phase_advance (Tensor):","the signal energy. Relevant if ``frames_per_chunk > 0``. (default: 500) snip_edges (bool, optional):","= 30, freq_low: int = 85, freq_high: int = 3400, ) -> Tensor:","/ math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor,","def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float = 25.0, frame_shift: float =","n_freqs: int, f_min: float, f_max: float, n_mels: int, sample_rate: int, norm: Optional[str] =","encoding \"\"\" mu = quantization_channels - 1.0 if not x.is_floating_point(): x = x.to(torch.float)","Returns: Tensor: Tensor of freq of dimension (..., frame) \"\"\" input_shape = waveform.shape","frame (Default: ``10 ** (-2)``). win_length (int, optional): The window length for median","after mu-law encoding \"\"\" mu = quantization_channels - 1.0 if not x.is_floating_point(): x","check lags = int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length =","time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio of dimension","nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best) indices","``30``). freq_low (int, optional): Lowest frequency that can be detected (Hz) (Default: ``85``).","# (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps +","# pack batch shape = waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default values","Tensor. If ``channels_first=True``, it has ``[channel, time]`` else ``[time, channel]``. \"\"\" bytes =","1``. window (Tensor): Window tensor that is applied/multiplied to each frame/window n_fft (int):","int = 3400, ) -> Tensor: r\"\"\"Detect pitch frequency. It is implemented using","(float): Speed-up factor phase_advance (Tensor): Expected phase advance in each bin. Dimension of","between each mel point and each stft freq point in hertz f_diff =","Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins, freq, 2) complex_specgrams_0","/ frame_size)) p = lags + num_of_frames * frame_size - waveform_length waveform =","80. (Default: ``None``) Returns: Tensor: Output tensor in decibel scale \"\"\" x_db =","Tensor: Input after mu-law encoding \"\"\" mu = quantization_channels - 1.0 if not","compression (float): Used for formats other than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`.","(bool, optional): If true, use a window centered on the current frame (to","Dimension (..., time) \"\"\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1.,","= torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1) values, _","shift in milliseconds. (default: 10.0) min_f0 (float, optional): Minimum F0 to search for","\"replicate\" ) -> Tensor: r\"\"\"Compute delta coefficients of a tensor, usually a spectrogram:","fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not None and norm ==","Tensor: r\"\"\"Decode mu-law encoded signal. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_","\"The argument normalized is not used in Griffin-Lim, \" \"and will be removed","hop between STFT windows win_length (int): Window size Returns: Tensor: Dimension (..., time)","not converge. length (int or None): Array length of the expected output. rand_init","input tensor. Shape of `(..., )` \"\"\" # Replace by torch.norm once issue","10 ** (-9) freq = sample_rate / (EPSILON + indices.to(torch.float)) # unpack batch","-> Tensor: r\"\"\"Detect pitch frequency. It is implemented using normalized cross-correlation function and","1, upsample_filter_width: int = 5, max_frames_latency: int = 0, frames_per_chunk: int = 0,","feature. Shape: ``(batch, frames 2)`` where the last dimension corresponds to pitch and","return_complex=True, ) # unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f","if window_end > last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum += frame_to_add if","<https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values between 0 and quantization_channels - 1","= 25.0, frame_shift: float = 10.0, min_f0: float = 50, max_f0: float =","(2 -> frequency, 3 -> time) Returns: Tensor: Masked spectrograms of dimensions (batch,",">= 0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \"The argument normalized is not","db_multiplier if top_db is not None: # Expand batch shape = x_db.size() packed_channels","- v)``. Args: specgrams (Tensor): Real spectrograms (batch, channel, freq, time) mask_param (int):","!= 2 and axis != 3: raise ValueError('Only Frequency and Time masking are","hop_length (int): Length of hop between STFT windows win_length (int): Window size power","return specgrams def mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float, axis: int )","2 dimensional. See also ```channels_first```. sample_rate (int): Sample rate of the audio waveform.","Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values between 0 and quantization_channels -","normalized cross-correlation function and median smoothing. Args: waveform (Tensor): Tensor of audio of","(Default: ``3400``). Returns: Tensor: Tensor of freq of dimension (..., frame) \"\"\" #","(n_frame). \"\"\" if pad > 0: # TODO add \"with torch.no_grad():\" back when","Tensor], b: Tuple[Tensor, Tensor], thresh: float = 0.99 ) -> Tuple[Tensor, Tensor]: \"\"\"","cmn_window else: window_start = t - cmn_window window_end = t + 1 if","Maximum F0 to search for (Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum f0,","torch.stack([angles.cos(), angles.sin()], dim=-1) \\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the",":] cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:,","dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for t in","(float): Maximum frequency (Hz) n_mels (int): Number of mel filterbanks sample_rate (int): Sample","mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int ) ->","\"htk\", ) -> Tensor: r\"\"\"Create a frequency bin conversion matrix. Args: n_freqs (int):","be one of \"htk\" or \"slaney\".') if mel_scale == \"htk\": return 700.0 *","slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if","has been scaled to between -1 and 1 and returns a signal encoded","Values near 1 can lead to faster convergence, but above 1 may not","to be masked will be uniformly sampled from [0, mask_param] mask_value (float): Value","where :math:`\\phi_i(m)` is the NCCF at frame :math:`i` with lag :math:`m`, :math:`w` is","indices = best[1] # Add back minimal lag indices += lag_min # Add","_compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float, freq_low: int ) -> Tensor: r\"\"\"","shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices","bits_per_sample (int, optional): Changes the bit depth for the supported formats. For more","quantization_channels - 1.0 if not x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype)","1000) resample_frequency (float, optional): Frequency that we down-sample the signal to. Must be","t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) ==","cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform","/ f_sp logstep = math.log(6.4) / 27.0 log_t = (mels >= min_log_mel) freqs[log_t]","Implementation ported from `librosa`. * [1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>,","f_min (float): Minimum frequency (Hz) f_max (float): Maximum frequency (Hz) n_mels (int): Number","would be ``A * create_fb_matrix(A.size(-1), ...)``. \"\"\" if norm is not None and","-*- import io import math import warnings from typing import Optional, Tuple import","dtype=dtype, device=device) for t in range(num_frames): window_start = 0 window_end = 0 if","1: cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance =","optional): Mode parameter passed to padding (Default: ``\"replicate\"``) Returns: Tensor: Tensor of deltas","1.0 ) -> Tensor: r\"\"\"Compute the norm of complex tensor input. Args: complex_tensor","(n, n), mode=mode) kernel = torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1,","# Number of lags to check lags = int(math.ceil(sample_rate / freq_low)) frame_size =","masking are supported') # unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram","lag :math:`m`, :math:`w` is the waveform, :math:`N` is the length of a frame,","frame) \"\"\" # pack batch shape = list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:])","they have dimension ``[time, channel]``. compression (float): Used for formats other than WAV.","list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0","Number to clamp ``x`` db_multiplier (float): Log10(max(reference value and amin)) top_db (float or","in a batch depends on the maximum value of that tensor, and so","(..., time) sample_rate (int): Sample rate of the audio waveform pad (int): Two","file size divided by the frame-shift. This makes different types of features give","* db_multiplier if top_db is not None: # Expand batch shape = x_db.size()","enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \"At least one mel filterbank has all","spec_f /= window.pow(2.).sum().sqrt() if power is not None: if power == 1.0: return","mode: str = \"replicate\" ) -> Tensor: r\"\"\"Compute delta coefficients of a tensor,","- value) # Create broadcastable mask mask_start = min_value[..., None, None] mask_end =","centered at time :math:`t \\times \\text{hop\\_length}`. Default: ``True`` pad_mode (string, optional): controls the","the number of Fourier bins, and time is the number of window hops","r\"\"\" Apply median smoothing to the 1D tensor over the given window. \"\"\"","previous iterate tprev = rebuilt # Invert with our current estimate of the","freq, time) \"\"\" # pack batch shape = specgram.size() specgram = specgram.reshape([-1] +","Changes the bit depth for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`.","\"\"\" # pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value","the final version of the features, which is the default. (default: False) Relevant","\"\"\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs =","steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs *","x_mu (Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input after","\"reflect\", onesided: bool = True ) -> Tensor: r\"\"\"Create a spectrogram or a","and phase. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float): Power","to amplitude. Returns: Tensor: Output tensor in power/amplitude scale. \"\"\" return ref *","= complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams: Tensor,","scale magnitude spectrogram using the Griffin-Lim transformation. Implementation ported from `librosa`. * [1]","== 1: specgram[:, mask_start:mask_end] = mask_value elif axis == 2: specgram[:, :, mask_start:mask_end]","Tensor: r\"\"\"Compute the norm of complex tensor input. Args: complex_tensor (Tensor): Tensor shape","specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 / power) # randomly","Return: Tensor: Angle of a complex tensor. Shape of `(..., )` \"\"\" return","waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch","torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0 = angle(complex_specgrams[...,","d_t = \\frac{\\sum_{n=1}^{\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\sum_{n=1}^{\\text{N}} n^2} where :math:`d_t` is the","\"\"\" Take value from first if bigger than a multiplicative factor of the","window_start -= (window_end - num_frames) window_end = num_frames if window_start < 0: window_start","= angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates waveform = torch.istft(specgram * angles,","27.0 if freq >= min_log_hz: mels = min_log_mel + math.log(freq / min_log_hz) /","signal has been scaled to between -1 and 1 and returns a signal","one of \"htk\" or \"slaney\".') if mel_scale == \"htk\": return 2595.0 * math.log10(1.0","sampled from [0, mask_param] mask_value (float): Value to assign to the masked columns","waveform pad (int): Two sided padding of signal window (Tensor): Window tensor that","Shape of `(..., )` \"\"\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor:","center: bool = True, pad_mode: str = \"reflect\", onesided: bool = True )","spectrograms from a raw audio signal. The spectrogram can be either magnitude-only or",":math:`\\phi_i(m)` is the NCCF at frame :math:`i` with lag :math:`m`, :math:`w` is the","= 7000, lowpass_filter_width: int = 1, upsample_filter_width: int = 5, max_frames_latency: int =","default = 600) min_cmn_window (int, optional): Minimum CMN window used at start of","twice sum of integer squared denom = n * (n + 1) *","of audio of dimension (..., time) sample_rate (int): Sample rate of the audio","for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes","# Add back minimal lag indices += lag_min # Add 1 empirical calibration","waveform = waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices =","is implemented using normalized cross-correlation function and median smoothing. Args: waveform (Tensor): Tensor","`(..., 2)` into its magnitude and phase. Args: complex_tensor (Tensor): Tensor shape of","This function computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The","(Tensor): Tensor shape of `(..., complex=2)` Return: Tensor: Angle of a complex tensor.","variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] +","0: # TODO add \"with torch.no_grad():\" back when JIT supports it waveform =","Tensor: The transformation matrix, to be right-multiplied to row-wise data of size (``n_mels``,","/ (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return","or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter banks (fb matrix) of size","speed up in time without modifying pitch by a factor of ``rate``. Args:","# https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor ) -> Tensor:","median smoothing. Args: waveform (Tensor): Tensor of audio of dimension (..., freq, time)","waveform[:, t, :] - cur_sum / window_frames if norm_vars: if window_frames == 1:","(str, optional): Changes the encoding for the supported formats. For more details see","channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\"rate\",","masking are supported') device = specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device,","max that is smallest best = torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] //","angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor )","encoded signal. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an","from torchaudio._internal import module_utils as _mod_utils import torchaudio __all__ = [ \"spectrogram\", \"griffinlim\",","for energy normalization. (default: 0) simulate_first_pass_online (bool, optional): If true, the function will","by the frame-shift. This makes different types of features give the same number","\"spectrogram\", \"griffinlim\", \"amplitude_to_DB\", \"DB_to_amplitude\", \"compute_deltas\", \"compute_kaldi_pitch\", \"create_fb_matrix\", \"create_dct\", \"compute_deltas\", \"detect_pitch_frequency\", \"DB_to_amplitude\", \"mu_law_encoding\", \"mu_law_decoding\",","+ 1, min_cmn_window) if window_end > num_frames: window_start -= (window_end - num_frames) window_end","waveform (Tensor): Tensor of audio of dimension (..., time) sample_rate (int): Sample rate","windows win_length (int): Window size power (float or None): Exponent for the magnitude","# Per batch example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) &","_hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels + 2)","frame is centered at time :math:`t \\times \\text{hop\\_length}`. Default: ``True`` pad_mode (string, optional):","normed input tensor. Shape of `(..., )` \"\"\" # Replace by torch.norm once","// 2 window_end = window_start + cmn_window else: window_start = t - cmn_window","as a form of augmentation. Args: waveform (Tensor): Audio data. Must be 2","pad (int): Two sided padding of signal window (Tensor): Window tensor that is","(batch, channel, freq, time) \"\"\" if axis != 2 and axis != 3:","if pad > 0: # TODO add \"with torch.no_grad():\" back when JIT supports","of signal window (Tensor): Window tensor that is applied/multiplied to each frame/window n_fft","the weighted average of the frequency values, weighted by their magnitude. Args: waveform","compute_deltas( specgram: Tensor, win_length: int = 5, mode: str = \"replicate\" ) ->","the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the","complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0)","window_start window_start = 0 if not center: if window_end > t: window_end =","highlight/apply f_min (float): Minimum frequency (Hz) f_max (float): Maximum frequency (Hz) n_mels (int):","b[0]) values = mask * a[0] + ~mask * b[0] indices = mask","\"\"\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier if","of mel filterbanks norm (str or None): Norm to use (either 'ortho' or","Axis to apply masking on (2 -> frequency, 3 -> time) Returns: Tensor:","optional): Frame shift in milliseconds. (default: 10.0) min_f0 (float, optional): Minimum F0 to","cur_sumsq -= (frame_to_remove ** 2) if window_end > last_window_end: frame_to_add = waveform[:, last_window_end,","raw audio signal. The spectrogram can be either magnitude-only or complex. Args: waveform","angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase =","= indices.unfold(-1, win_length, 1) values, _ = torch.median(roll, -1) return values def detect_pitch_frequency(","10 ** (-9) # Number of lags to check lags = int(math.ceil(sample_rate /","Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float = 0.99 ) -> Tuple[Tensor, Tensor]:","= _combine_max(half, best) indices = best[1] # Add back minimal lag indices +=","0 window_end = 0 if center: window_start = t - cmn_window // 2","\"apply_codec\", ] def spectrogram( waveform: Tensor, pad: int, window: Tensor, n_fft: int, hop_length:","return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float, axis: int )","Compute Phase Accum phase = phase + phase_advance phase = torch.cat([phase_0, phase[..., :-1]],","int, momentum: float, length: Optional[int], rand_init: bool ) -> Tensor: r\"\"\"Compute waveform from","(default: 5) max_frames_latency (int, optional): Maximum number of frames of latency that we","median smoothing (in number of frames) (Default: ``30``). freq_low (int, optional): Lowest frequency","of audio of dimension (..., time) pad (int): Two sided padding of signal","+ 1 if window_start < 0: window_end -= window_start window_start = 0 if","\"\"\" # pack batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps","window_end > last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum += frame_to_add if norm_vars:","to the left. (bool, default = false) norm_vars (bool, optional): If true, normalize","(freq / 700.0)) # Fill in the linear part f_min = 0.0 f_sp","torch.nn.functional.pad(waveform, (pad, pad), \"constant\") # pack batch shape = waveform.size() waveform = waveform.reshape(-1,","optional): Window in frames for running average CMN computation (int, default = 600)","dimension (..., freq, time) sample_rate (int): The sample rate of the waveform (Hz)","in pitch that our algorithm measures. (default: 0.005) nccf_ballast (float, optional): Increasing this","\"angle\", \"magphase\", \"phase_vocoder\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \"spectral_centroid\", \"apply_codec\", ] def spectrogram( waveform: Tensor,","True ) -> Tensor: r\"\"\"Create a spectrogram or a batch of spectrograms from","normalized (bool): Whether to normalize by magnitude after stft. n_iter (int): Number of","Tensor: Power of the normed input tensor. Shape of `(..., )` \"\"\" #","freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length = 1025, 512 >>> # (channel,","0 if center: window_start = t - cmn_window // 2 window_end = window_start","(int): Size of FFT hop_length (int): Length of hop between STFT windows win_length","iterate to 0 rebuilt = torch.tensor(0.) for _ in range(n_iter): # Store the","if (fb.max(dim=0).values == 0.).any(): warnings.warn( \"At least one mel filterbank has all zero","with our current estimate of the phases inverse = torch.istft(specgram * angles, n_fft=n_fft,","= output.reshape(shape) return output def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float, freq_low:","the norm of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(...,","def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float, freq_low: int ) -> Tensor:","columns to be masked will be uniformly sampled from [0, mask_param] mask_value (float):","= 100) center (bool, optional): If true, use a window centered on the","cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform","factor of ``rate``. Args: complex_specgrams (Tensor): Dimension of `(..., freq, time, complex=2)` rate","num_feats, dtype=dtype, device=device) else: variance = cur_sumsq variance = variance / window_frames variance","\"\"\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be one of","Returns: Tensor: Dimension (..., time) \"\"\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length,","_ in range(n_iter): # Store the previous iterate tprev = rebuilt # Invert","Optional[int] = None, ) -> Tensor: r\"\"\" Apply codecs as a form of","angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2,","indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1)","hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate // 2, steps=1 + n_fft","Fill in the linear part f_min = 0.0 f_sp = 200.0 / 3","if bigger than a multiplicative factor of the second, elementwise. \"\"\" mask =","= rebuilt # Invert with our current estimate of the phases inverse =","mel bin numbers to frequencies. Args: mels (Tensor): Mel frequencies mel_scale (str, optional):","\"mu_law_decoding\", \"complex_norm\", \"angle\", \"magphase\", \"phase_vocoder\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \"spectral_centroid\", \"apply_codec\", ] def spectrogram(","is sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. All","= math.log(6.4) / 27.0 if freq >= min_log_hz: mels = min_log_mel + math.log(freq","value.long()).squeeze() assert mask_end - mask_start < mask_param if axis == 1: specgram[:, mask_start:mask_end]","the length of a frame, :math:`b_i` is the beginning of frame :math:`i`, :math:`E(j)`","window_start < 0: window_end -= window_start window_start = 0 if not center: if","r\"\"\"Detect pitch frequency. It is implemented using normalized cross-correlation function and median smoothing.","* torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu + 1) / 2","soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges,","creates ``n_fft // 2 + 1`` bins hop_length (int): Length of hop between",":math:`w` is the waveform, :math:`N` is the length of a frame, :math:`b_i` is","the 14th python in science conference, pp. 18-25. 2015. * [2] <NAME>., <NAME>.,","scale f_min = 0.0 f_sp = 200.0 / 3 freqs = f_min +","will have the same mask interval. Args: specgram (Tensor): Real spectrogram (channel, freq,","of `(..., complex=2)` Return: Tensor: Angle of a complex tensor. Shape of `(...,","* frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p = lags","float = 10.0, penalty_factor: float = 0.1, lowpass_cutoff: float = 1000, resample_frequency: float","indices += lag_min # Add 1 empirical calibration offset indices += 1 return","of a tensor, usually a spectrogram: .. math:: d_t = \\frac{\\sum_{n=1}^{\\text{N}} n (c_{t+n}","def DB_to_amplitude( x: Tensor, ref: float, power: float ) -> Tensor: r\"\"\"Turn a","frame) \"\"\" input_shape = waveform.shape num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames,","function will output features that correspond to what an online decoder would see","Args: x (Tensor): Input spectrogram(s) before being converted to decibel scale. Input should","== \"ortho\" dct[0] *= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return","float, normalized: bool, n_iter: int, momentum: float, length: Optional[int], rand_init: bool ) ->","** (-2), win_length: int = 30, freq_low: int = 85, freq_high: int =","= 85, freq_high: int = 3400, ) -> Tensor: r\"\"\"Detect pitch frequency. It","list(shape[-2:])) specgram = specgram.pow(1 / power) # randomly initialize the phase batch, freq,","frequencies. Args: mels (Tensor): Mel frequencies mel_scale (str, optional): Scale to use: ``htk``","norm != \"slaney\": raise ValueError(\"norm must be one of None or 'slaney'\") #","The window length used for computing delta (Default: ``5``) mode (str, optional): Mode","(float, optional): Frequency that we down-sample the signal to. Must be more than","The output of each tensor in a batch depends on the maximum value","online pitch extraction. A non-critical parameter; the frame at which we recompute some","-1) mag = alphas * norm_1 + (1 - alphas) * norm_0 real_stretch","used for energy normalization. (default: 0) simulate_first_pass_online (bool, optional): If true, the function","else: raise ValueError('Only Frequency and Time masking are supported') # unpack batch specgram","['slaney', 'htk']: raise ValueError('mel_scale should be one of \"htk\" or \"slaney\".') if mel_scale","\"spectral_centroid\", \"apply_codec\", ] def spectrogram( waveform: Tensor, pad: int, window: Tensor, n_fft: int,","spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if power is not None:","optional): Changes the bit depth for the supported formats. For more details see","Tensor: Complex Specgrams Stretch with dimension of `(..., freq, ceil(time/rate), complex=2)` Example >>>","angle_1 - angle_0 - phase_advance phase = phase - 2 * math.pi *","-> Tensor: r\"\"\" Compute the spectral centroid for each channel along the time","float, optional): Smallest relative change in pitch that our algorithm measures. (default: 0.005)","input_part = waveform[:, window_start: window_end - window_start, :] cur_sum += torch.sum(input_part, 1) if","Tensor: r\"\"\"Create a spectrogram or a batch of spectrograms from a raw audio",":attr:`center` is ``True``. Default: ``\"reflect\"`` onesided (bool, optional): controls whether to return half","Returns: Tensor: Triangular filter banks (fb matrix) of size (``n_freqs``, ``n_mels``) meaning number","at start of decoding (adds latency only at start). Only applicable if center","1D tensor over the given window. \"\"\" # Centered windowed pad_length = (win_length","cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1,","Tensor, rate: float, phase_advance: Tensor ) -> Tensor: r\"\"\"Given a STFT tensor, speed","STFT windows win_length (int): Window size Returns: Tensor: Dimension (..., time) \"\"\" specgram","``slaney``. (Default: ``htk``) Returns: mels (float): Frequency in Mels \"\"\" if mel_scale not","variance / window_frames variance -= ((cur_sum ** 2) / (window_frames ** 2)) variance","dtype=dtype) # Per batch example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start)","size power (float or None): Exponent for the magnitude spectrogram, (must be >","of dimensions (channel, freq, time) \"\"\" # pack batch shape = specgram.size() specgram","assumes the signal has been scaled to between -1 and 1 and returns","alphas = time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1, :]) # Time Padding","mode (str, optional): Mode parameter passed to padding (Default: ``\"replicate\"``) Returns: Tensor: Tensor","Acoustics (pp. 1-4), Oct. 2013. * [3] <NAME> and <NAME>, \"Signal estimation from","unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor,","spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor, n_fft: int, hop_length: int,","cmn_window: int = 600, min_cmn_window: int = 100, center: bool = False, norm_vars:","== \"slaney\": # Slaney-style mel is scaled to be approx constant energy per","device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for t in range(num_frames):",":attr:`waveform` on both sides so that the :math:`t`-th frame is centered at time","# Create broadcastable mask mask_start = min_value[..., None, None] mask_end = (min_value +","- mask_start < mask_param if axis == 1: specgram[:, mask_start:mask_end] = mask_value elif","pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, power: Optional[float], normalized:","0), mode=\"constant\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll","create_dct( n_mfcc: int, n_mels: int, norm: Optional[str] ) -> Tensor: r\"\"\"Create a DCT","the current frame (to the extent possible, modulo end effects). If false, window","= waveform.device last_window_start = last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device)","def complex_norm( complex_tensor: Tensor, power: float = 1.0 ) -> Tensor: r\"\"\"Compute the","if normalized: spec_f /= window.pow(2.).sum().sqrt() if power is not None: if power ==","specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end), mask_value) specgrams","(area normalization). (Default: ``None``) mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``.","+ 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \"At","Create broadcastable mask mask_start = min_value[..., None, None] mask_end = (min_value + value)[...,","is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor )","Args: n_freqs (int): Number of frequencies to highlight/apply f_min (float): Minimum frequency (Hz)","batch output = output.reshape(shape) return output def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time:","+ 1`` and ``n_fft`` is the number of Fourier bins, and time is","= ( (s1 * s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON","window_end = window_start + cmn_window else: window_start = t - cmn_window window_end =","milliseconds. (default: 10.0) min_f0 (float, optional): Minimum F0 to search for (Hz) (default:","Optional, Tuple import torch from torch import Tensor from torchaudio._internal import module_utils as","scale. \"\"\" return ref * torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq: float,","= quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu,","None: # Expand batch shape = x_db.size() packed_channels = shape[-3] if x_db.dim() >","Tuple import torch from torch import Tensor from torchaudio._internal import module_utils as _mod_utils","empirical calibration offset indices += 1 return indices def _median_smoothing( indices: Tensor, win_length:","variance = cur_sumsq variance = variance / window_frames variance -= ((cur_sum ** 2)","torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu) * 2 - 1.0 x =","power) phase = angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams: Tensor, rate: float,","+ indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def","shape[-1]) # default values are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft,","one of None or 'slaney'\") # freq bins # Equivalent filterbank construction by","Tuple[Tensor, Tensor]: \"\"\" Take value from first if bigger than a multiplicative factor","calibration offset indices += 1 return indices def _median_smoothing( indices: Tensor, win_length: int","``rate``. Args: complex_specgrams (Tensor): Dimension of `(..., freq, time, complex=2)` rate (float): Speed-up","= waveform.shape num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels =","may be set too high. \" f\"Or, the value for `n_freqs` ({n_freqs}) may","torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor, n_fft: int, hop_length: int, win_length: int,","amplitude amin (float): Number to clamp ``x`` db_multiplier (float): Log10(max(reference value and amin))","\"\"\" # Replace by torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5","dtype = specgram.dtype # pack batch shape = specgram.size() specgram = specgram.reshape(1, -1,","(``n_mels``, ``n_mfcc``), normalized depending on norm. Args: n_mfcc (int): Number of mfc coefficients","* [2] <NAME>., <NAME>., & <NAME>. \"A fast Griffin-Lim algorithm,\" IEEE Workshop on","<NAME> 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence,","data. Must be 2 dimensional. See also ```channels_first```. sample_rate (int): Sample rate of","be right-multiplied to row-wise data of size (``n_mels``, ``n_mfcc``). \"\"\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n","= [] for lag in range(1, lags + 1): s1 = waveform[..., :-lag].unfold(-1,","default. (default: False) Relevant if ``frames_per_chunk > 0``. recompute_frame (int, optional): Only relevant","f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between each mel point and","shape = x_db.size() packed_channels = shape[-3] if x_db.dim() > 2 else 1 x_db","= torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance = cur_sumsq variance = variance","Use 10. for power and 20. for amplitude amin (float): Number to clamp","phase of the complex tensor \"\"\" mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor)","phase - 2 * math.pi * torch.round(phase / (2 * math.pi)) # Compute","If true, normalize variance to one. (bool, default = false) Returns: Tensor: Tensor","optional): Only relevant for compatibility with online pitch extraction. A non-critical parameter; the","relevant for compatibility with online pitch extraction. A non-critical parameter; the frame at","/ 3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n, n +","squared denom = n * (n + 1) * (2 * n +","None): Exponent for the magnitude spectrogram, (must be > 0) e.g., 1 for","bool ) -> Tensor: r\"\"\"Compute waveform from a linear scale magnitude spectrogram using","win_length: int = 5, mode: str = \"replicate\" ) -> Tensor: r\"\"\"Compute delta","Tensor of audio of dimension (..., freq, time) cmn_window (int, optional): Window in","= torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\"rate\", f\"{sample_rate}\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform:","a complex-valued spectrogram with shape `(..., 2)` into its magnitude and phase. Args:","float, n_mels: int, sample_rate: int, norm: Optional[str] = None, mel_scale: str = \"htk\",","``v`` is sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``.","not None and norm == \"slaney\": # Slaney-style mel is scaled to be","0: window_end -= window_start window_start = 0 if not center: if window_end >","specgram = specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 / power) # randomly initialize","/ float(n_mels) * (n + 0.5) * k) # size (n_mfcc, n_mels) if","Shape of `(..., )` \"\"\" # Replace by torch.norm once issue is fixed","``n_freqs``), the applied result would be ``A * create_fb_matrix(A.size(-1), ...)``. \"\"\" if norm","return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor, n_fft: int, hop_length: int, win_length:","specgram: Tensor, win_length: int = 5, mode: str = \"replicate\" ) -> Tensor:","the first half of lags, then the latter is taken. \"\"\" lag_min =","and output Tensor have dimension ``[channel, time]``. Otherwise, they have dimension ``[time, channel]``.","Tensor have dimension ``[channel, time]``. Otherwise, they have dimension ``[time, channel]``. compression (float):","float = 0.005, nccf_ballast: float = 7000, lowpass_filter_width: int = 1, upsample_filter_width: int","``True`` Returns: Tensor: Dimension (..., freq, time), freq is ``n_fft // 2 +","1) Returns: Tensor: Complex Specgrams Stretch with dimension of `(..., freq, ceil(time/rate), complex=2)`","redundancy. Default: ``True`` Returns: Tensor: Dimension (..., freq, time), freq is ``n_fft //","(int): Length of hop between STFT windows win_length (int): Window size power (float","utterance. Args: waveform (Tensor): Tensor of audio of dimension (..., freq, time) cmn_window","power and 20. for amplitude amin (float): Number to clamp ``x`` db_multiplier (float):","freq, time, complex=2) >>> complex_specgrams = torch.randn(2, freq, 300, 2) >>> rate =","input_shape = waveform.shape num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels","in soft way, must not exceed min-f0 (default: 10.0) penalty_factor (float, optional): Cost","the spectral centroid for each channel along the time axis. The spectral centroid","max_v - v)``. All examples will have the same mask interval. Args: specgram","* [1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \"librosa: Audio","to the first half of lags, then the latter is taken. \"\"\" lag_min","Shape: ``(batch, frames 2)`` where the last dimension corresponds to pitch and NCCF.","details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding for the supported formats.","1)[:, -1, :] else: if window_start > last_window_start: frame_to_remove = waveform[:, last_window_start, :]","in any dimension indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\"constant\", value=0. ) indices[...,","create_fb_matrix( n_freqs: int, f_min: float, f_max: float, n_mels: int, sample_rate: int, norm: Optional[str]","measures. (default: 0.005) nccf_ballast (float, optional): Increasing this factor reduces NCCF for quiet","recovers the original Griffin-Lim method. Values near 1 can lead to faster convergence,","half of results to avoid redundancy. Default: ``True`` Returns: Tensor: Dimension (..., freq,","if window_frames == 1: cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device)","Tensor, sample_rate: int, freq_high: int ) -> Tensor: r\"\"\" For each frame, take","(specgrams.size(axis) - value) # Create broadcastable mask mask_start = min_value[..., None, None] mask_end","\"slaney\".') if mel_scale == \"htk\": return 2595.0 * math.log10(1.0 + (freq / 700.0))","each frame/window n_fft (int): Size of FFT, creates ``n_fft // 2 + 1``","power) def angle( complex_tensor: Tensor ) -> Tensor: r\"\"\"Compute the angle of complex","freqs (Tensor): Mels converted in Hz \"\"\" if mel_scale not in ['slaney', 'htk']:","momentum < 1, 'momentum={} > 1 can be unstable'.format(momentum) assert momentum >= 0,","(..., freq, time) sample_rate (int): The sample rate of the waveform (Hz) frame_time","-1) best = _combine_max(half, best) indices = best[1] # Add back minimal lag","Power of the norm. (Default: `1.0`). Returns: Tensor: Power of the normed input","is ``n_fft // 2 + 1`` and ``n_fft`` is the number of Fourier","/ specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int, format: str, channels_first: bool","frames (default: 7000) lowpass_filter_width (int, optional): Integer that determines filter width of lowpass","nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices =","complex=2) >>> complex_specgrams = torch.randn(2, freq, 300, 2) >>> rate = 1.3 #","= torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 -","waveform: Tensor, sample_rate: int, format: str, channels_first: bool = True, compression: Optional[float] =","norm is not None and norm == \"slaney\": # Slaney-style mel is scaled","(..., freq, time) win_length (int, optional): The window length used for computing delta","1 return indices def _median_smoothing( indices: Tensor, win_length: int ) -> Tensor: r\"\"\"","corresponds to pitch and NCCF. Reference: - A pitch extraction algorithm tuned for","f_min + f_sp * mels # And now the nonlinear scale min_log_hz =","= angles - tprev.mul_(momentum / (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return","= -2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor,","to be right-multiplied to row-wise data of size (``n_mels``, ``n_mfcc``). \"\"\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II","in range(num_frames): window_start = 0 window_end = 0 if center: window_start = t","int, frame_time: float, freq_low: int ) -> Tensor: r\"\"\" Compute Normalized Cross-Correlation Function","to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter banks (fb","- value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert mask_end -","input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack","`(..., time)`. sample_rate (float): Sample rate of `waveform`. frame_length (float, optional): Frame length","Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins, freq, 2)","Maximum frequency (Hz) n_mels (int): Number of mel filterbanks sample_rate (int): Sample rate","mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch example masking specgrams =","mu_law_decoding( x_mu: Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Decode mu-law encoded signal. For","(float, optional): Minimum F0 to search for (Hz) (default: 50.0) max_f0 (float, optional):","-= multiplier * db_multiplier if top_db is not None: # Expand batch shape","values, _ = torch.median(roll, -1) return values def detect_pitch_frequency( waveform: Tensor, sample_rate: int,","be masked will be uniformly sampled from [0, mask_param] mask_value (float): Value to","Integer that determines filter width when upsampling NCCF. (default: 5) max_frames_latency (int, optional):","optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: mels (float): Frequency","max among all the lags is very close to the first half of",") -> Tensor: r\"\"\" Apply codecs as a form of augmentation. Args: waveform","scaled between -1 and 1. Args: x_mu (Tensor): Input tensor quantization_channels (int): Number","(Tensor): A magnitude-only STFT spectrogram of dimension (..., freq, frames) where freq is","- f_min) / f_sp logstep = math.log(6.4) / 27.0 log_t = (mels >=","int, frame_time: float = 10 ** (-2), win_length: int = 30, freq_low: int","audio of dimension (..., time) sample_rate (int): Sample rate of the audio waveform","Default: ``\"reflect\"`` onesided (bool, optional): controls whether to return half of results to","frames for running average CMN computation (int, default = 600) min_cmn_window (int, optional):","some of the forward pointers, after revising our estimate of the signal energy.","1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack batch output","automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE International","[0, mask_param] mask_value (float): Value to assign to the masked columns axis (int):","coefficients to retain n_mels (int): Number of mel filterbanks norm (str or None):","min_value[..., None, None] mask_end = (min_value + value)[..., None, None] mask = torch.arange(0,","\"constant\") # pack batch shape = waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default","/ f_sp # Fill in the log-scale part min_log_hz = 1000.0 min_log_mel =","(-9) # Number of lags to check lags = int(math.ceil(sample_rate / freq_low)) frame_size","specgram.device dtype = specgram.dtype # pack batch shape = specgram.size() specgram = specgram.reshape(1,","None, optional): Minimum negative cut-off in decibels. A reasonable number is 80. (Default:","a factor of ``rate``. Args: complex_specgrams (Tensor): Dimension of `(..., freq, time, complex=2)`","of lags to check lags = int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate *","None: dct *= 2.0 else: assert norm == \"ortho\" dct[0] *= 1.0 /","** 2, 1)[:, -1, :] else: if window_start > last_window_start: frame_to_remove = waveform[:,","bool = False, recompute_frame: int = 500, snip_edges: bool = True, ) ->","that correspond to what an online decoder would see in the first pass","if norm is None: dct *= 2.0 else: assert norm == \"ortho\" dct[0]","mel weights by the width of the mel band (area normalization). (Default: ``None``)","torch.nn.functional.pad( indices, (pad_length, 0), mode=\"constant\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length * [indices[...,","near the ending edge won't be snipped, so that the number of frames","half_size = nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half,","output features that correspond to what an online decoder would see in the","time, complex=2)` rate (float): Speed-up factor phase_advance (Tensor): Expected phase advance in each",">>> complex_specgrams = torch.randn(2, freq, 300, 2) >>> rate = 1.3 # Speed","Phase Accum phase = phase + phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1)","mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value) # Create broadcastable","to search for (Hz) (default: 50.0) max_f0 (float, optional): Maximum F0 to search","time) Example >>> specgram = torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram) >>>","1 can be unstable'.format(momentum) assert momentum >= 0, 'momentum={} < 0'.format(momentum) if normalized:","all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) # create overlapping triangles zero = torch.zeros(1)","* [3] <NAME> and <NAME>, \"Signal estimation from modified short-time Fourier transform,\" IEEE","str, channels_first: bool = True, compression: Optional[float] = None, encoding: Optional[str] = None,","in science conference, pp. 18-25. 2015. * [2] <NAME>., <NAME>., & <NAME>. \"A","Equivalent filterbank construction by Librosa all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) #","output = output.reshape(shape) return output def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float,","slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) # create overlapping","soft_min_f0: float = 10.0, penalty_factor: float = 0.1, lowpass_cutoff: float = 1000, resample_frequency:","of Signal Processing to Audio and Acoustics (pp. 1-4), Oct. 2013. * [3]","= cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return","one. (bool, default = false) Returns: Tensor: Tensor of freq of dimension (...,","str = \"htk\") -> float: r\"\"\"Convert Hz to Mels. Args: freqs (float): Frequencies","rand_init (bool): Initializes phase randomly if True, to zero otherwise. Returns: torch.Tensor: waveform","to retain n_mels (int): Number of mel filterbanks norm (str or None): Norm","k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) * (n + 0.5) *","= torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu return x def","(Tensor): Tensor shape of `(..., complex=2)` power (float): Power of the norm. (Default:","axis (int): Axis to apply masking on (1 -> frequency, 2 -> time)","Tensor, n_fft: int, hop_length: int, win_length: int, ) -> Tensor: r\"\"\" Compute the","-1: input_part = waveform[:, window_start: window_end - window_start, :] cur_sum += torch.sum(input_part, 1)","center (bool, optional): If true, use a window centered on the current frame","of window hops (n_frame). \"\"\" if pad > 0: # TODO add \"with","more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values","v)``, where ``v`` is sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v","Args: waveform (Tensor): Tensor of audio of dimension (..., freq, time) sample_rate (int):","p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag,","(float, optional): Cost factor for FO change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff","+= torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1, :]","scale. The output of each tensor in a batch depends on the maximum","to what an online decoder would see in the first pass of decoding","Frame length in milliseconds. (default: 25.0) frame_shift (float, optional): Frame shift in milliseconds.","# pack batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps =","+ phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag","``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter banks (fb matrix) of","# Centered windowed pad_length = (win_length - 1) // 2 # \"replicate\" padding","== false, ignored if center==true (int, default = 100) center (bool, optional): If",">>> 0, math.pi * hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance)","dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2],","window_start, :] cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2,","waveform.device last_window_start = last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq","momentum parameter for fast Griffin-Lim. Setting this to 0 recovers the original Griffin-Lim","window_start last_window_start = window_start last_window_end = window_end cmn_waveform[:, t, :] = waveform[:, t,","``frames_per_chunk > 0``. recompute_frame (int, optional): Only relevant for compatibility with online pitch","compatibility with online pitch extraction. A non-critical parameter; the frame at which we","~mask * b[0] indices = mask * a[1] + ~mask * b[1] return","1.0 if not x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu =","a window centered on the current frame (to the extent possible, modulo end","len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate:","Centered windowed pad_length = (win_length - 1) // 2 # \"replicate\" padding in","= \"reflect\", onesided: bool = True ) -> Tensor: r\"\"\"Create a spectrogram or","= waveform[:, t, :] - cur_sum / window_frames if norm_vars: if window_frames ==","value from first if bigger than a multiplicative factor of the second, elementwise.","frames used for energy normalization. (default: 0) simulate_first_pass_online (bool, optional): If true, the","all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) # calculate mel freq bins m_min","torch.rand(1) * (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze()","( (s1 * s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON +","best[1] # Add back minimal lag indices += lag_min # Add 1 empirical","filterbank has all zero values. \" f\"The value for `n_mels` ({n_mels}) may be",") -> Tensor: r\"\"\" For each frame, take the highest value of NCCF,","``85``). freq_high (int, optional): Highest frequency that can be detected (Hz) (Default: ``3400``).","randomly if True, to zero otherwise. Returns: torch.Tensor: waveform of (..., time), where","hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with","return ref * torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq: float, mel_scale: str","- min_log_mel)) return freqs def create_fb_matrix( n_freqs: int, f_min: float, f_max: float, n_mels:","coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio","International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498,","of spectrograms from a raw audio signal. The spectrogram can be either magnitude-only","\"htk\": return 2595.0 * math.log10(1.0 + (freq / 700.0)) # Fill in the","def create_fb_matrix( n_freqs: int, f_min: float, f_max: float, n_mels: int, sample_rate: int, norm:","mu_law_encoding( x: Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Encode signal based on mu-law","Tensor, win_length: int = 5, mode: str = \"replicate\" ) -> Tensor: r\"\"\"Compute","and 1. Args: x_mu (Tensor): Input tensor quantization_channels (int): Number of channels Returns:","the linear part f_min = 0.0 f_sp = 200.0 / 3 mels =","form `(..., freq, time)`. Batched inputs should include a channel dimension and have","max_v - v)``. Args: specgrams (Tensor): Real spectrograms (batch, channel, freq, time) mask_param","Each column is a filterbank so that assuming there is a matrix A","clip. Args: x (Tensor): Input spectrogram(s) before being converted to decibel scale. Input","(float): Log10(max(reference value and amin)) top_db (float or None, optional): Minimum negative cut-off","-> frequency, 3 -> time) Returns: Tensor: Masked spectrograms of dimensions (batch, channel,","5, mode: str = \"replicate\" ) -> Tensor: r\"\"\"Compute delta coefficients of a","(Default: ``30``). freq_low (int, optional): Lowest frequency that can be detected (Hz) (Default:","with lag :math:`m`, :math:`w` is the waveform, :math:`N` is the length of a","ref * torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq: float, mel_scale: str =","filter. (default: 1) upsample_filter_width (int, optional): Integer that determines filter width when upsampling","-> Tensor: \"\"\"Convert mel bin numbers to frequencies. Args: mels (Tensor): Mel frequencies","best = torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] // 2 half = torch.max(nccf[...,","a channel dimension and have the form `(batch, channel, freq, time)`. multiplier (float):","= ((x_mu) / mu) * 2 - 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x)",">>> delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \"\"\" device = specgram.device dtype","shape = list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time,","> 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The number of frames","Griffin-Lim transformation. Implementation ported from `librosa`. * [1] McFee, Brian, <NAME>, <NAME>, <NAME>,","= time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams","<NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \"librosa: Audio and music signal analysis in","float = 4000, delta_pitch: float = 0.005, nccf_ballast: float = 7000, lowpass_filter_width: int","see in the first pass of decoding -- not the final version of","batch, freq, frames = specgram.size() if rand_init: angles = 2 * math.pi *","examples will have the same mask interval. Args: specgram (Tensor): Real spectrogram (channel,","specgram = specgram.pow(1 / power) # randomly initialize the phase batch, freq, frames","\"Signal estimation from modified short-time Fourier transform,\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243,","= torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform =","window_start = t - cmn_window // 2 window_end = window_start + cmn_window else:","for each channel along the time axis. The spectral centroid is defined as","2 * math.pi * torch.round(phase / (2 * math.pi)) # Compute Phase Accum","depends on the maximum value of that tensor, and so may return different","== 1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window:","mel_scale: str = \"htk\") -> Tensor: \"\"\"Convert mel bin numbers to frequencies. Args:","power, etc. normalized (bool): Whether to normalize by magnitude after stft. n_iter (int):","from a linear scale magnitude spectrogram using the Griffin-Lim transformation. Implementation ported from","mask_start < mask_param if axis == 1: specgram[:, mask_start:mask_end] = mask_value elif axis","Optional[float], normalized: bool, center: bool = True, pad_mode: str = \"reflect\", onesided: bool","0.1, lowpass_cutoff: float = 1000, resample_frequency: float = 4000, delta_pitch: float = 0.005,","Length of hop between STFT windows win_length (int): Window size power (float or","compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \"\"\" device = specgram.device dtype = specgram.dtype #","phase estimates angles = rebuilt if momentum: angles = angles - tprev.mul_(momentum /","Window size power (float or None): Exponent for the magnitude spectrogram, (must be","same number of frames. (default: True) Returns: Tensor: Pitch feature. Shape: ``(batch, frames","Setting this to 0 recovers the original Griffin-Lim method. Values near 1 can","elif axis == 2: specgram[:, :, mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency","transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized depending on norm. Args: n_mfcc (int):","2015. * [2] <NAME>., <NAME>., & <NAME>. \"A fast Griffin-Lim algorithm,\" IEEE Workshop","of channels Returns: Tensor: Input after mu-law encoding \"\"\" mu = quantization_channels -","be > 0) e.g., 1 for energy, 2 for power, etc. normalized (bool):","True, ) -> torch.Tensor: \"\"\"Extract pitch based on method described in [1]. This","== \"htk\": return 2595.0 * math.log10(1.0 + (freq / 700.0)) # Fill in","- 1.0) / mu return x def complex_norm( complex_tensor: Tensor, power: float =","(freq, 1) Returns: Tensor: Complex Specgrams Stretch with dimension of `(..., freq, ceil(time/rate),","Tensor, cmn_window: int = 600, min_cmn_window: int = 100, center: bool = False,","energy, 2 for power, etc. If None, then the complex spectrum is returned","* b[1] return values, indices def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int","phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag = alphas","time)`. multiplier (float): Use 10. for power and 20. for amplitude amin (float):","specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return","= window_start last_window_end = window_end cmn_waveform[:, t, :] = waveform[:, t, :] -","be 2 dimensional. See also ```channels_first```. sample_rate (int): Sample rate of the audio","The sample rate of the waveform (Hz) frame_time (float, optional): Duration of a","magnitude spectrogram, (must be > 0) e.g., 1 for energy, 2 for power,","/ mu return x def complex_norm( complex_tensor: Tensor, power: float = 1.0 )","masked columns axis (int): Axis to apply masking on (2 -> frequency, 3","dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf def _combine_max( a: Tuple[Tensor,","median smoothing, and convert to frequency. Note: If the max among all the","extent possible, modulo end effects). If false, window is to the left. (bool,","momentum >= 0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \"The argument normalized is","values. \" f\"The value for `n_mels` ({n_mels}) may be set too high. \"","Tensor: r\"\"\"Compute delta coefficients of a tensor, usually a spectrogram: .. math:: d_t",") -> Tensor: r\"\"\"Turn a spectrogram from the power/amplitude scale to the decibel","<NAME>, <NAME>, and <NAME>. \"librosa: Audio and music signal analysis in python.\" In","x (Tensor): Input spectrogram(s) before being converted to decibel scale. Input should take","rate, phase_advance) >>> x.shape # with 231 == ceil(300 / 1.3) torch.Size([2, 1025,","\"\"\" lag_min = int(math.ceil(sample_rate / freq_high)) # Find near enough max that is","we down-sample the signal to. Must be more than twice lowpass-cutoff. (default: 4000)","(..., freq, time), freq is ``n_fft // 2 + 1`` and ``n_fft`` is","num_frames: window_start -= (window_end - num_frames) window_end = num_frames if window_start < 0:","equals 1, will compute DB to power. If 0.5, will compute DB to","math.log(freq / min_log_hz) / logstep return mels def _mel_to_hz(mels: Tensor, mel_scale: str =","= torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames,","torch.randn(2, freq, 300, 2) >>> rate = 1.3 # Speed up by 30%","+ torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf def","= phase + phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase,","with values from 0 to quantization_channels - 1. Args: x (Tensor): Input tensor","sample_rate: int, norm: Optional[str] = None, mel_scale: str = \"htk\", ) -> Tensor:","center: bool = False, norm_vars: bool = False, ) -> Tensor: r\"\"\" Apply","Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True,","complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int,","window_start = 0 if not center: if window_end > t: window_end = max(t","top_db is not None: # Expand batch shape = x_db.size() packed_channels = shape[-3]","from 0 to quantization_channels - 1. Args: x (Tensor): Input tensor quantization_channels (int):","modulo end effects). If false, window is to the left. (bool, default =","r\"\"\"Turn a spectrogram from the power/amplitude scale to the decibel scale. The output","nonlinear scale min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep","resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result =","\\text{hop\\_length}`. Default: ``True`` pad_mode (string, optional): controls the padding method used when :attr:`center`","Tensor: Masked spectrogram of dimensions (channel, freq, time) \"\"\" # pack batch shape","optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels","mask_value (float): Value to assign to the masked columns axis (int): Axis to","batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor, multiplier:","Apr. 1984. Args: specgram (Tensor): A magnitude-only STFT spectrogram of dimension (..., freq,","A of size (..., ``n_freqs``), the applied result would be ``A * create_fb_matrix(A.size(-1),","freq def sliding_window_cmn( waveform: Tensor, cmn_window: int = 600, min_cmn_window: int = 100,","Increasing this factor reduces NCCF for quiet frames (default: 7000) lowpass_filter_width (int, optional):","(0, p)) # Compute lags output_lag = [] for lag in range(1, lags","be set too high. \" f\"Or, the value for `n_freqs` ({n_freqs}) may be","r\"\"\"Compute waveform from a linear scale magnitude spectrogram using the Griffin-Lim transformation. Implementation","1 and returns a signal scaled between -1 and 1. Args: x_mu (Tensor):","_hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale)","// 2, n_freqs) # calculate mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max","def mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor:","= (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert mask_end - mask_start < mask_param",":, mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency and Time masking are supported')","1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom","= 50, max_f0: float = 400, soft_min_f0: float = 10.0, penalty_factor: float =","resample_frequency: float = 4000, delta_pitch: float = 0.005, nccf_ballast: float = 7000, lowpass_filter_width:","Tensor, n_fft: int, hop_length: int, win_length: int, power: float, normalized: bool, n_iter: int,","int, hop_length: int, win_length: int, power: float, normalized: bool, n_iter: int, momentum: float,","width when upsampling NCCF. (default: 5) max_frames_latency (int, optional): Maximum number of frames","introduce into the feature processing (affects output only if ``frames_per_chunk > 0`` and","norm: Optional[str] ) -> Tensor: r\"\"\"Create a DCT transformation matrix with shape (``n_mels``,","(``n_freqs``, ``n_mels``) meaning number of frequencies to highlight/apply to x the number of","(Default: ``n_fft``) power (float): Exponent for the magnitude spectrogram, (must be > 0)","0``. recompute_frame (int, optional): Only relevant for compatibility with online pitch extraction. A","Number of mel filterbanks norm (str or None): Norm to use (either 'ortho'","(int, optional): The window length for median smoothing (in number of frames) (Default:","bool = False, norm_vars: bool = False, ) -> Tensor: r\"\"\" Apply sliding-window","= f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) # create overlapping triangles","Tensor: r\"\"\"Given a STFT tensor, speed up in time without modifying pitch by","conference, pp. 18-25. 2015. * [2] <NAME>., <NAME>., & <NAME>. \"A fast Griffin-Lim","torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch example masking specgrams = specgrams.transpose(axis, -1)","= torch.randn(2, freq, 300, 2) >>> rate = 1.3 # Speed up by","Tensor: Masked spectrograms of dimensions (batch, channel, freq, time) \"\"\" if axis !=","same mask interval. Args: specgram (Tensor): Real spectrogram (channel, freq, time) mask_param (int):","Default: ``win_length // 2``) win_length (int): Window size. (Default: ``n_fft``) power (float): Exponent","mask = (a[0] > thresh * b[0]) values = mask * a[0] +","angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And","This algorithm assumes the signal has been scaled to between -1 and 1","and convert to frequency. Note: If the max among all the lags is","(n_mfcc, n_mels) if norm is None: dct *= 2.0 else: assert norm ==","by their magnitude. Args: waveform (Tensor): Tensor of audio of dimension (..., time)","cross-correlation function and median smoothing. Args: waveform (Tensor): Tensor of audio of dimension","use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: mels (float): Frequency in Mels \"\"\"","width of the mel band (area normalization). (Default: ``None``) mel_scale (str, optional): Scale","last_window_start = window_start last_window_end = window_end cmn_waveform[:, t, :] = waveform[:, t, :]","point and each stft freq point in hertz f_diff = f_pts[1:] - f_pts[:-1]","speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE International Conference","power (float): Power of the norm. (Default: `1.0`) Returns: (Tensor, Tensor): The magnitude","- v)``. All examples will have the same mask interval. Args: specgram (Tensor):","max_f0 (float, optional): Maximum F0 to search for (Hz) (default: 400.0) soft_min_f0 (float,","# Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window,","hops (n_frame). \"\"\" if pad > 0: # TODO add \"with torch.no_grad():\" back",") -> Tensor: r\"\"\"Create a frequency bin conversion matrix. Args: n_freqs (int): Number","a linear scale magnitude spectrogram using the Griffin-Lim transformation. Implementation ported from `librosa`.","lead to faster convergence, but above 1 may not converge. length (int or","r\"\"\" For each frame, take the highest value of NCCF, apply centered median","lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest relative change in pitch that our","than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest relative change in pitch","if norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames = window_end - window_start last_window_start","phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag =","norm_vars: cur_sumsq -= (frame_to_remove ** 2) if window_end > last_window_end: frame_to_add = waveform[:,","= rebuilt if momentum: angles = angles - tprev.mul_(momentum / (1 + momentum))","(int): Two sided padding of signal window (Tensor): Window tensor that is applied/multiplied","complex tensor \"\"\" mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag, phase","Number of channels Returns: Tensor: Input after mu-law decoding \"\"\" mu = quantization_channels","complex_norm( complex_tensor: Tensor, power: float = 1.0 ) -> Tensor: r\"\"\"Compute the norm","along the time axis. The spectral centroid is defined as the weighted average","mu = quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu =","of `(..., complex=2)` power (float): Power of the norm. (Default: `1.0`). Returns: Tensor:","< 0: window_end -= window_start window_start = 0 if not center: if window_end","apply masking on (1 -> frequency, 2 -> time) Returns: Tensor: Masked spectrogram","time) \"\"\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs","spectrum is returned instead. normalized (bool): Whether to normalize by magnitude after stft","hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse,","return freq def sliding_window_cmn( waveform: Tensor, cmn_window: int = 600, min_cmn_window: int =","and each stft freq point in hertz f_diff = f_pts[1:] - f_pts[:-1] #","is not None: if power == 1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f)","or None, optional): Minimum negative cut-off in decibels. A reasonable number is 80.","0.0 f_sp = 200.0 / 3 freqs = f_min + f_sp * mels","frequency (Hz) f_max (float): Maximum frequency (Hz) n_mels (int): Number of mel filterbanks","shape of `(..., complex=2)` power (float): Power of the norm. (Default: `1.0`) Returns:","so that assuming there is a matrix A of size (..., ``n_freqs``), the","+ 2) # create overlapping triangles zero = torch.zeros(1) down_slopes = (-1.0 *","window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate // 2, steps=1","/ f_sp logstep = math.log(6.4) / 27.0 if freq >= min_log_hz: mels =","int, hop_length: int, win_length: int, ) -> Tensor: r\"\"\" Compute the spectral centroid","\"detect_pitch_frequency\", \"DB_to_amplitude\", \"mu_law_encoding\", \"mu_law_decoding\", \"complex_norm\", \"angle\", \"magphase\", \"phase_vocoder\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \"spectral_centroid\", \"apply_codec\",","window=window, length=length) # unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def","frequency values, weighted by their magnitude. Args: waveform (Tensor): Tensor of audio of","depth for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting","that we down-sample the signal to. Must be more than twice lowpass-cutoff. (default:","spectrogram, (must be > 0) e.g., 1 for energy, 2 for power, etc.","2 + 1`` bins hop_length (int): Length of hop between STFT windows. (","int ) -> Tensor: r\"\"\" For each frame, take the highest value of","(Hz) (Default: ``3400``). Returns: Tensor: Tensor of freq of dimension (..., frame) \"\"\"","\"\"\" mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag, phase def phase_vocoder(","``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. All examples will have","of ``rate``. Args: complex_specgrams (Tensor): Dimension of `(..., freq, time, complex=2)` rate (float):","Update our phase estimates angles = rebuilt if momentum: angles = angles -","- cmn_window // 2 window_end = window_start + cmn_window else: window_start = t","(float, optional): Frame length in milliseconds. (default: 25.0) frame_shift (float, optional): Frame shift","# Invert with our current estimate of the phases inverse = torch.istft(specgram *","Tuple[Tensor, Tensor]: r\"\"\"Separate a complex-valued spectrogram with shape `(..., 2)` into its magnitude","torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not None and norm == \"slaney\": #","Tuple[Tensor, Tensor], thresh: float = 0.99 ) -> Tuple[Tensor, Tensor]: \"\"\" Take value","power, etc. If None, then the complex spectrum is returned instead. normalized (bool):","return nccf def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float =","``None``) Returns: Tensor: Output tensor in decibel scale \"\"\" x_db = multiplier *","window_end > t: window_end = max(t + 1, min_cmn_window) if window_end > num_frames:","width of lowpass filter, more gives sharper filter. (default: 1) upsample_filter_width (int, optional):","if freq >= min_log_hz: mels = min_log_mel + math.log(freq / min_log_hz) / logstep","mu) * 2 - 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) -","= 0.99 ) -> Tuple[Tensor, Tensor]: \"\"\" Take value from first if bigger","win_length=win_length, window=window, length=length) # unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform","an audio clip split into snippets vs. a full clip. Args: x (Tensor):","frequency (Hz) n_mels (int): Number of mel filterbanks sample_rate (int): Sample rate of","Number of channels Returns: Tensor: Input after mu-law encoding \"\"\" mu = quantization_channels","# Expand batch shape = x_db.size() packed_channels = shape[-3] if x_db.dim() > 2","min=amin)) x_db -= multiplier * db_multiplier if top_db is not None: # Expand","computing delta (Default: ``5``) mode (str, optional): Mode parameter passed to padding (Default:","int, freq_high: int ) -> Tensor: r\"\"\" For each frame, take the highest","from the decibel scale to the power/amplitude scale. Args: x (Tensor): Input tensor","frame_length (float, optional): Frame length in milliseconds. (default: 25.0) frame_shift (float, optional): Frame","None ) -> Tensor: r\"\"\"Turn a spectrogram from the power/amplitude scale to the","short-time Fourier transform,\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram","(n_freqs, n_mels) up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) fb =","= torch.linspace( >>> 0, math.pi * hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams,","num_channels, num_frames, num_feats, dtype=dtype, device=device) for t in range(num_frames): window_start = 0 window_end","= (mels >= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel))","frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove ** 2) if window_end > last_window_end: frame_to_add","(..., freq, frames) where freq is ``n_fft // 2 + 1``. window (Tensor):","FFT, creates ``n_fft // 2 + 1`` bins hop_length (int): Length of hop","a matrix A of size (..., ``n_freqs``), the applied result would be ``A","import torch from torch import Tensor from torchaudio._internal import module_utils as _mod_utils import","is scaled to be approx constant energy per channel enorm = 2.0 /","If ``channels_first=True``, it has ``[channel, time]`` else ``[time, channel]``. \"\"\" bytes = io.BytesIO()","\"ortho\" dct[0] *= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return dct.t()","Returns: Tensor: Tensor of deltas of dimension (..., freq, time) Example >>> specgram","multiplicative factor of the second, elementwise. \"\"\" mask = (a[0] > thresh *","= window_end cmn_waveform[:, t, :] = waveform[:, t, :] - cur_sum / window_frames","= best[1] # Add back minimal lag indices += lag_min # Add 1","bits_per_sample: Optional[int] = None, ) -> Tensor: r\"\"\" Apply codecs as a form","+ list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps %","is smallest best = torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] // 2 half","tensor before being converted to power/amplitude scale. ref (float): Reference which the output","False) Relevant if ``frames_per_chunk > 0``. recompute_frame (int, optional): Only relevant for compatibility","pad > 0: # TODO add \"with torch.no_grad():\" back when JIT supports it","int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames =","between STFT windows. ( Default: ``win_length // 2``) win_length (int): Window size. (Default:","not None and norm != \"slaney\": raise ValueError(\"norm must be one of None","n_mels) if norm is None: dct *= 2.0 else: assert norm == \"ortho\"","optional): The window length for median smoothing (in number of frames) (Default: ``30``).",":py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has ``[channel, time]`` else ``[time,","Returns: torch.Tensor: waveform of (..., time), where time equals the ``length`` parameter if","min_log_mel + math.log(freq / min_log_hz) / logstep return mels def _mel_to_hz(mels: Tensor, mel_scale:","None: if power == 1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim(","else: angles = torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\ .to(dtype=specgram.dtype,","angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates waveform = torch.istft(specgram * angles, n_fft=n_fft,","the form `(batch, channel, freq, time)`. multiplier (float): Use 10. for power and","dtype=x_mu.dtype) x = ((x_mu) / mu) * 2 - 1.0 x = torch.sign(x)","If the max among all the lags is very close to the first",":math:`i` with lag :math:`m`, :math:`w` is the waveform, :math:`N` is the length of","pad :attr:`waveform` on both sides so that the :math:`t`-th frame is centered at","min_log_mel)) return freqs def create_fb_matrix( n_freqs: int, f_min: float, f_max: float, n_mels: int,","input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) #","bin. Dimension of (freq, 1) Returns: Tensor: Complex Specgrams Stretch with dimension of","frequency, 2 -> time) Returns: Tensor: Masked spectrogram of dimensions (channel, freq, time)","= \\frac{\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\phi_i(m)` is the NCCF at","window: Tensor, n_fft: int, hop_length: int, win_length: int, power: Optional[float], normalized: bool, center:","value)[..., None, None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch example","energy normalization. (default: 0) simulate_first_pass_online (bool, optional): If true, the function will output","win_length: int, power: Optional[float], normalized: bool, center: bool = True, pad_mode: str =","``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The number of","\"complex_norm\", \"angle\", \"magphase\", \"phase_vocoder\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \"spectral_centroid\", \"apply_codec\", ] def spectrogram( waveform:","is ``n_fft // 2 + 1``. window (Tensor): Window tensor that is applied/multiplied","have dimension ``[channel, time]``. Otherwise, they have dimension ``[time, channel]``. compression (float): Used","is a filterbank so that assuming there is a matrix A of size","Integer that determines filter width of lowpass filter, more gives sharper filter. (default:","mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams:","= specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device,","if center: window_start = t - cmn_window // 2 window_end = window_start +","and ``v_0`` from ``uniform(0, max_v - v)``. Args: specgrams (Tensor): Real spectrograms (batch,","`compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The input waveform of shape `(..., time)`.","<NAME> and <NAME> 2014 IEEE International Conference on Acoustics, Speech and Signal Processing","recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE International Conference on","in the linear part f_min = 0.0 f_sp = 200.0 / 3 mels","after mu-law decoding \"\"\" mu = quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu","(float): Value to assign to the masked columns axis (int): Axis to apply","applied from indices ``[v_0, v_0 + v)``, where ``v`` is sampled from ``uniform(0,","0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The number of frames used","time), where time equals the ``length`` parameter if given. \"\"\" assert momentum <",":] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) == 2:","iteration for phase recovery process. momentum (float): The momentum parameter for fast Griffin-Lim.","2 + 1``. window (Tensor): Window tensor that is applied/multiplied to each frame/window","= 200.0 / 3 freqs = f_min + f_sp * mels # And","latter is taken. \"\"\" lag_min = int(math.ceil(sample_rate / freq_high)) # Find near enough","freq, frames) else: angles = torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1)","will compute DB to power. If 0.5, will compute DB to amplitude. Returns:","is the waveform, :math:`N` is the length of a frame, :math:`b_i` is the","[] for lag in range(1, lags + 1): s1 = waveform[..., :-lag].unfold(-1, frame_size,","features give the same number of frames. (default: True) Returns: Tensor: Pitch feature.","t in range(num_frames): window_start = 0 window_end = 0 if center: window_start =","Workshop on Applications of Signal Processing to Audio and Acoustics (pp. 1-4), Oct.","int(math.ceil(sample_rate / freq_high)) # Find near enough max that is smallest best =","* norm_1 + (1 - alphas) * norm_0 real_stretch = mag * torch.cos(phase_acc)","(must be > 0) e.g., 1 for energy, 2 for power, etc. If","= angle_1 - angle_0 - phase_advance phase = phase - 2 * math.pi","doi: 10.1109/ICASSP.2014.6854049. \"\"\" shape = waveform.shape waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch(","tensor quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law encoding \"\"\"","``None``) mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns:","time) Returns: Tensor: Masked spectrograms of dimensions (batch, channel, freq, time) \"\"\" if","NCCF at frame :math:`i` with lag :math:`m`, :math:`w` is the waveform, :math:`N` is","math.pi * torch.round(phase / (2 * math.pi)) # Compute Phase Accum phase =","num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype","dimension ``[channel, time]``. Otherwise, they have dimension ``[time, channel]``. compression (float): Used for","Tensor: Angle of a complex tensor. Shape of `(..., )` \"\"\" return torch.atan2(complex_tensor[...,","weights by the width of the mel band (area normalization). (Default: ``None``) mel_scale","has all zero values. \" f\"The value for `n_mels` ({n_mels}) may be set",":-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :]","mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu) * 2 - 1.0","= (a[0] > thresh * b[0]) values = mask * a[0] + ~mask","# Convert indices to frequency EPSILON = 10 ** (-9) freq = sample_rate","x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu)","if window_end > t: window_end = max(t + 1, min_cmn_window) if window_end >","audio waveform norm (Optional[str]): If 'slaney', divide the triangular mel weights by the","windowed pad_length = (win_length - 1) // 2 # \"replicate\" padding in any",") -> Tensor: r\"\"\"Decode mu-law encoded signal. For more info see the `Wikipedia","-1 and 1 and returns a signal encoded with values from 0 to","window length for median smoothing (in number of frames) (Default: ``30``). freq_low (int,","r\"\"\"Compute delta coefficients of a tensor, usually a spectrogram: .. math:: d_t =","\"DB_to_amplitude\", \"mu_law_encoding\", \"mu_law_decoding\", \"complex_norm\", \"angle\", \"magphase\", \"phase_vocoder\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \"spectral_centroid\", \"apply_codec\", ]","\"\"\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi /","\"\"\" EPSILON = 10 ** (-9) # Number of lags to check lags","unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor,","shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff,","a complex tensor. Shape of `(..., )` \"\"\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0])","-> Tensor: r\"\"\"Create a frequency bin conversion matrix. Args: n_freqs (int): Number of","~mask * b[1] return values, indices def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high:","use `normalized=False`.\") # pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:]))","mu return x def complex_norm( complex_tensor: Tensor, power: float = 1.0 ) ->","of frame :math:`i`, :math:`E(j)` is the energy :math:`\\sum_{n=j}^{j+N-1} w^2(n)`. \"\"\" EPSILON = 10","`(..., complex=2)` Return: Tensor: Angle of a complex tensor. Shape of `(..., )`","hop_length (int): Length of hop between STFT windows. ( Default: ``win_length // 2``)","multiplier (float): Use 10. for power and 20. for amplitude amin (float): Number","the complex spectrum is returned instead. normalized (bool): Whether to normalize by magnitude","x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu *","channel enorm = 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0)",":]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins,",":] cur_sum += frame_to_add if norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames =","``length`` parameter if given. \"\"\" assert momentum < 1, 'momentum={} > 1 can","compute DB to power. If 0.5, will compute DB to amplitude. Returns: Tensor:","torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch waveform =","rate of the audio waveform pad (int): Two sided padding of signal window","= [ \"spectrogram\", \"griffinlim\", \"amplitude_to_DB\", \"DB_to_amplitude\", \"compute_deltas\", \"compute_kaldi_pitch\", \"create_fb_matrix\", \"create_dct\", \"compute_deltas\", \"detect_pitch_frequency\", \"DB_to_amplitude\",","Compute Normalized Cross-Correlation Function (NCCF). .. math:: \\phi_i(m) = \\frac{\\sum_{n=b_i}^{b_i + N-1} w(n)","Tensor: r\"\"\" Apply codecs as a form of augmentation. Args: waveform (Tensor): Audio","indices ``[v_0, v_0 + v)``, where ``v`` is sampled from ``uniform(0, mask_param)``, and","win_length (int, optional): The window length used for computing delta (Default: ``5``) mode","value and amin)) top_db (float or None, optional): Minimum negative cut-off in decibels.","that our algorithm measures. (default: 0.005) nccf_ballast (float, optional): Increasing this factor reduces","after stft center (bool, optional): whether to pad :attr:`waveform` on both sides so","power/amplitude scale. Args: x (Tensor): Input tensor before being converted to power/amplitude scale.","tuned for automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014","in time without modifying pitch by a factor of ``rate``. Args: complex_specgrams (Tensor):","time) pad (int): Two sided padding of signal window (Tensor): Window tensor that","phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild","axis == 2: specgram[:, :, mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency and","freq of dimension (..., frame) \"\"\" input_shape = waveform.shape num_frames, num_feats = input_shape[-2:]","mask_end = (min_value.long() + value.long()).squeeze() assert mask_end - mask_start < mask_param if axis","waveform: Tensor, sample_rate: int, frame_time: float, freq_low: int ) -> Tensor: r\"\"\" Compute","more than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest relative change in","= window_end - window_start last_window_start = window_start last_window_end = window_end cmn_waveform[:, t, :]","= _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices,","((cur_sum ** 2) / (window_frames ** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t,","waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor, multiplier: float, amin: float, db_multiplier: float,","(str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular","mel_scale: str = \"htk\", ) -> Tensor: r\"\"\"Create a frequency bin conversion matrix.",":1, :]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) #","Returns: Tensor: Input after mu-law decoding \"\"\" mu = quantization_channels - 1.0 if","Tensor of audio of dimension (..., freq, time) sample_rate (int): The sample rate","to 0 recovers the original Griffin-Lim method. Values near 1 can lead to","(either 'ortho' or None) Returns: Tensor: The transformation matrix, to be right-multiplied to","power. If 0.5, will compute DB to amplitude. Returns: Tensor: Output tensor in","dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int ) -> Tensor: r\"\"\"Encode signal based","mu-law companding. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes","pack batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0,","p=2, dim=-1) phase = angle_1 - angle_0 - phase_advance phase = phase -","angles = torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\ .to(dtype=specgram.dtype, device=specgram.device)","normalization per utterance. Args: waveform (Tensor): Tensor of audio of dimension (..., freq,","min_value = torch.rand(1) * (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long()","matrix) of size (``n_freqs``, ``n_mels``) meaning number of frequencies to highlight/apply to x","imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch","min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs def","magnitude after stft. n_iter (int): Number of iteration for phase recovery process. momentum","decoding \"\"\" mu = quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float)","* 2 - 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0)","(float): Power of the norm. (Default: `1.0`). Returns: Tensor: Power of the normed","of frames of latency that we allow pitch tracking to introduce into the","+ torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf","= specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate to 0 rebuilt = torch.tensor(0.)","or ``slaney``. (Default: ``htk``) Returns: mels (float): Frequency in Mels \"\"\" if mel_scale","# Slaney-style mel is scaled to be approx constant energy per channel enorm","spectrogram (channel, freq, time) mask_param (int): Number of columns to be masked will","filter width when upsampling NCCF. (default: 5) max_frames_latency (int, optional): Maximum number of","and so may return different values for an audio clip split into snippets","win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) # Update our phase","x_db = x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor, ref: float, power: float","mel_scale == \"htk\": return 700.0 * (10.0**(mels / 2595.0) - 1.0) # Fill","1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1","centered on the current frame (to the extent possible, modulo end effects). If","x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x)) /","decibel scale \"\"\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier *","1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding( x:","time without modifying pitch by a factor of ``rate``. Args: complex_specgrams (Tensor): Dimension","torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram rebuilt","torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \"\"\" device","# pack batch shape = list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf =","num_frames if window_start < 0: window_start = 0 if last_window_start == -1: input_part","Add 1 empirical calibration offset indices += 1 return indices def _median_smoothing( indices:","waveform. format (str): File format. channels_first (bool): When True, both the input and","false) norm_vars (bool, optional): If true, normalize variance to one. (bool, default =","2)` into its magnitude and phase. Args: complex_tensor (Tensor): Tensor shape of `(...,","output Tensor have dimension ``[channel, time]``. Otherwise, they have dimension ``[time, channel]``. compression","<NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE International Conference on Acoustics,","(default: 50.0) max_f0 (float, optional): Maximum F0 to search for (Hz) (default: 400.0)","deltas of dimension (..., freq, time) Example >>> specgram = torch.randn(1, 40, 1000)","* x), power) def _hz_to_mel(freq: float, mel_scale: str = \"htk\") -> float: r\"\"\"Convert","Tensor of audio of dimension (..., time) sample_rate (int): Sample rate of the","torch import Tensor from torchaudio._internal import module_utils as _mod_utils import torchaudio __all__ =","analysis in python.\" In Proceedings of the 14th python in science conference, pp.","Optional[str] = None, bits_per_sample: Optional[int] = None, ) -> Tensor: r\"\"\" Apply codecs","pitch by a factor of ``rate``. Args: complex_specgrams (Tensor): Dimension of `(..., freq,","= 200.0 / 3 mels = (freq - f_min) / f_sp # Fill","int(math.ceil(waveform_length / frame_size)) p = lags + num_of_frames * frame_size - waveform_length waveform","frame_time (float, optional): Duration of a frame (Default: ``10 ** (-2)``). win_length (int,","torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros(","Args: waveform (Tensor): Tensor of audio of dimension (..., time) sample_rate (int): Sample","to zero otherwise. Returns: torch.Tensor: waveform of (..., time), where time equals the","math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor, quantization_channels:","determines filter width when upsampling NCCF. (default: 5) max_frames_latency (int, optional): Maximum number","be removed in v0.9.0 release. To suppress this warning, \" \"please use `normalized=False`.\")","complex. Args: waveform (Tensor): Tensor of audio of dimension (..., time) pad (int):","ref: float, power: float ) -> Tensor: r\"\"\"Turn a tensor from the decibel",":math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio of dimension (...,","codecs as a form of augmentation. Args: waveform (Tensor): Audio data. Must be","Fourier bins, and time is the number of window hops (n_frame). \"\"\" if","c_{t-n})}{2 \\sum_{n=1}^{\\text{N}} n^2} where :math:`d_t` is the deltas at time :math:`t`, :math:`c_t` is","unstable'.format(momentum) assert momentum >= 0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \"The argument","warning, \" \"please use `normalized=False`.\") # pack batch shape = specgram.size() specgram =","min_cmn_window) if window_end > num_frames: window_start -= (window_end - num_frames) window_end = num_frames","mels (float): Frequency in Mels \"\"\" if mel_scale not in ['slaney', 'htk']: raise","center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack batch spec_f = spec_f.reshape(shape[:-1] +","-= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove ** 2) if window_end > last_window_end:","frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency,","** (-9) freq = sample_rate / (EPSILON + indices.to(torch.float)) # unpack batch freq","unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor,","from typing import Optional, Tuple import torch from torch import Tensor from torchaudio._internal","x_db -= multiplier * db_multiplier if top_db is not None: # Expand batch","the value for `n_freqs` ({n_freqs}) may be set too low.\" ) return fb","# calculate mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale)","(int): Sample rate of the audio waveform. format (str): File format. channels_first (bool):","(Default: ``85``). freq_high (int, optional): Highest frequency that can be detected (Hz) (Default:","* (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu return x def complex_norm( complex_tensor:","-> Tensor: r\"\"\" For each frame, take the highest value of NCCF, apply","have the same mask interval. Args: specgram (Tensor): Real spectrogram (channel, freq, time)","Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has ``[channel, time]`` else ``[time, channel]``.","gives sharper filter. (default: 1) upsample_filter_width (int, optional): Integer that determines filter width","85, freq_high: int = 3400, ) -> Tensor: r\"\"\"Detect pitch frequency. It is","of that tensor, and so may return different values for an audio clip","the difference between each mel point and each stft freq point in hertz","packed_channels = shape[-3] if x_db.dim() > 2 else 1 x_db = x_db.reshape(-1, packed_channels,","n * (n + 1) * (2 * n + 1) / 3","\"htk\") -> float: r\"\"\"Convert Hz to Mels. Args: freqs (float): Frequencies in Hz","matrix A of size (..., ``n_freqs``), the applied result would be ``A *","= angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1,","window.pow(2.).sum().sqrt() if power is not None: if power == 1.0: return spec_f.abs() return","freq, time)`. multiplier (float): Use 10. for power and 20. for amplitude amin","number of frames) (Default: ``30``). freq_low (int, optional): Lowest frequency that can be","frequency. Note: If the max among all the lags is very close to","log-scale part min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep","(..., time), where time equals the ``length`` parameter if given. \"\"\" assert momentum","up in time without modifying pitch by a factor of ``rate``. Args: complex_specgrams","complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype)","2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2]","-> Tensor: r\"\"\"Compute the norm of complex tensor input. Args: complex_tensor (Tensor): Tensor","its magnitude and phase. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power","(Default: ``htk``) Returns: freqs (Tensor): Mels converted in Hz \"\"\" if mel_scale not","return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int, pad: int, window: Tensor, n_fft:","frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size))","lag in range(1, lags + 1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames,","specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate to 0 rebuilt =","# Return the final phase estimates waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length,","time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams =","equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The input waveform of shape","bool, center: bool = True, pad_mode: str = \"reflect\", onesided: bool = True","a[1] + ~mask * b[1] return values, indices def _find_max_per_frame( nccf: Tensor, sample_rate:","400, soft_min_f0: float = 10.0, penalty_factor: float = 0.1, lowpass_cutoff: float = 1000,","Must be more than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest relative","by 30% >>> phase_advance = torch.linspace( >>> 0, math.pi * hop_length, freq)[..., None]","a tensor, usually a spectrogram: .. math:: d_t = \\frac{\\sum_{n=1}^{\\text{N}} n (c_{t+n} -","[1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \"librosa: Audio and","matrix. Args: n_freqs (int): Number of frequencies to highlight/apply f_min (float): Minimum frequency","default = false) norm_vars (bool, optional): If true, normalize variance to one. (bool,","shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1, 1))","win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate // 2, steps=1 + n_fft //","end effects). If false, window is to the left. (bool, default = false)","frames_per_chunk: int = 0, simulate_first_pass_online: bool = False, recompute_frame: int = 500, snip_edges:","= phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with 231 == ceil(300 / 1.3)","f_min) / f_sp # Fill in the log-scale part min_log_hz = 1000.0 min_log_mel","p = lags + num_of_frames * frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0,","<NAME>. \"A fast Griffin-Lim algorithm,\" IEEE Workshop on Applications of Signal Processing to","to search for (Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum f0, applied in","of NCCF, apply centered median smoothing, and convert to frequency. Note: If the","change in pitch that our algorithm measures. (default: 0.005) nccf_ballast (float, optional): Increasing","IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, 2014, pp.","((x_mu + 1) / 2 * mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding(","f_min: float, f_max: float, n_mels: int, sample_rate: int, norm: Optional[str] = None, mel_scale:","decoding (adds latency only at start). Only applicable if center == false, ignored","so that the :math:`t`-th frame is centered at time :math:`t \\times \\text{hop\\_length}`. Default:","dimension indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\"constant\", value=0. ) indices[..., :pad_length] =","100) center (bool, optional): If true, use a window centered on the current","center == false, ignored if center==true (int, default = 100) center (bool, optional):","+ 0.5) * k) # size (n_mfcc, n_mels) if norm is None: dct","rate of the audio waveform. format (str): File format. channels_first (bool): When True,","dimensions (batch, channel, freq, time) \"\"\" if axis != 2 and axis !=","\"slaney\": # Slaney-style mel is scaled to be approx constant energy per channel","(bool, optional): controls whether to return half of results to avoid redundancy. Default:","'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \"spectral_centroid\", \"apply_codec\", ] def spectrogram( waveform: Tensor, pad: int, window:","lags + 1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 =","modified short-time Fourier transform,\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args:","removed in v0.9.0 release. To suppress this warning, \" \"please use `normalized=False`.\") #","Minimum F0 to search for (Hz) (default: 50.0) max_f0 (float, optional): Maximum F0","scaled to between -1 and 1 and returns a signal encoded with values","v0.9.0 release. To suppress this warning, \" \"please use `normalized=False`.\") # pack batch","torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu return x def complex_norm(","the bit depth for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns:","Returns: Tensor: Masked spectrogram of dimensions (channel, freq, time) \"\"\" # pack batch","for power, etc. normalized (bool): Whether to normalize by magnitude after stft. n_iter","zero values. \" f\"The value for `n_mels` ({n_mels}) may be set too high.","on the current frame (to the extent possible, modulo end effects). If false,","encoding: Optional[str] = None, bits_per_sample: Optional[int] = None, ) -> Tensor: r\"\"\" Apply",":num_of_frames, :] output_frames = ( (s1 * s2).sum(-1) / (EPSILON + torch.norm(s1, p=2,","f\"{sample_rate}\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length:","Acoustics, Speech and Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \"\"\"","output only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional):","any dimension indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\"constant\", value=0. ) indices[..., :pad_length]","float: r\"\"\"Convert Hz to Mels. Args: freqs (float): Frequencies in Hz mel_scale (str,","mu-law encoded signal. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects","phase_advance) >>> x.shape # with 231 == ceil(300 / 1.3) torch.Size([2, 1025, 231,","possible, modulo end effects). If false, window is to the left. (bool, default","(float, optional): Increasing this factor reduces NCCF for quiet frames (default: 7000) lowpass_filter_width","str = \"htk\", ) -> Tensor: r\"\"\"Create a frequency bin conversion matrix. Args:","-> Tensor: r\"\"\"Compute the angle of complex tensor input. Args: complex_tensor (Tensor): Tensor","negative cut-off in decibels. A reasonable number is 80. (Default: ``None``) Returns: Tensor:","assert momentum >= 0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \"The argument normalized","batch shape = x_db.size() packed_channels = shape[-3] if x_db.dim() > 2 else 1","Tensor: \"\"\"Convert mel bin numbers to frequencies. Args: mels (Tensor): Mel frequencies mel_scale","for power and 20. for amplitude amin (float): Number to clamp ``x`` db_multiplier","highest value of NCCF, apply centered median smoothing, and convert to frequency. Note:",") bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\"rate\", f\"{sample_rate}\"]], channels_first=channels_first, format=format) return augmented","10. for power and 20. for amplitude amin (float): Number to clamp ``x``","(1 - alphas) * norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch = mag","module_utils as _mod_utils import torchaudio __all__ = [ \"spectrogram\", \"griffinlim\", \"amplitude_to_DB\", \"DB_to_amplitude\", \"compute_deltas\",","if center == false, ignored if center==true (int, default = 100) center (bool,","torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf def _combine_max(","Input after mu-law encoding \"\"\" mu = quantization_channels - 1.0 if not x.is_floating_point():","> 2 else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db,","(int, optional): The number of frames used for energy normalization. (default: 0) simulate_first_pass_online","to the masked columns axis (int): Axis to apply masking on (2 ->","({n_mels}) may be set too high. \" f\"Or, the value for `n_freqs` ({n_freqs})","(bool): Initializes phase randomly if True, to zero otherwise. Returns: torch.Tensor: waveform of","(Tensor): Expected phase advance in each bin. Dimension of (freq, 1) Returns: Tensor:","optional): controls the padding method used when :attr:`center` is ``True``. Default: ``\"reflect\"`` onesided","masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end), mask_value)","spectrogram can be either magnitude-only or complex. Args: waveform (Tensor): Tensor of audio","Duration of a frame (Default: ``10 ** (-2)``). win_length (int, optional): The window","`normalized=False`.\") # pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram","= torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) * (n +","``n_fft // 2 + 1`` bins hop_length (int): Length of hop between STFT","by torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def","(channel, freq, time) mask_param (int): Number of columns to be masked will be","(fb.max(dim=0).values == 0.).any(): warnings.warn( \"At least one mel filterbank has all zero values.","norm (Optional[str]): If 'slaney', divide the triangular mel weights by the width of","(channel, freq, time, complex=2) >>> complex_specgrams = torch.randn(2, freq, 300, 2) >>> rate","x), power) def _hz_to_mel(freq: float, mel_scale: str = \"htk\") -> float: r\"\"\"Convert Hz","# unpack batch output = output.reshape(shape) return output def _compute_nccf( waveform: Tensor, sample_rate:","create overlapping triangles zero = torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2]) /","the extent possible, modulo end effects). If false, window is to the left.","is very close to the first half of lags, then the latter is","batch x_db = x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor, ref: float, power:","(n + 0.5) * k) # size (n_mfcc, n_mels) if norm is None:","between STFT windows win_length (int): Window size power (float or None): Exponent for","n_freqs (int): Number of frequencies to highlight/apply f_min (float): Minimum frequency (Hz) f_max","return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int,","shape `(..., time)`. sample_rate (float): Sample rate of `waveform`. frame_length (float, optional): Frame","/ 27.0 log_t = (mels >= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep *","0.5, will compute DB to amplitude. Returns: Tensor: Output tensor in power/amplitude scale.","(ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \"\"\" shape = waveform.shape waveform =","+= (frame_to_add ** 2) window_frames = window_end - window_start last_window_start = window_start last_window_end","1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power: float = 1.0 ) ->","input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` Return: Tensor: Angle of","factor of the second, elementwise. \"\"\" mask = (a[0] > thresh * b[0])","-> Tensor: r\"\"\" Apply median smoothing to the 1D tensor over the given","* torch.rand(batch, freq, frames) else: angles = torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(),","lag_min = int(math.ceil(sample_rate / freq_high)) # Find near enough max that is smallest","of audio of dimension (..., freq, time) cmn_window (int, optional): Window in frames","(min_value.long() + value.long()).squeeze() assert mask_end - mask_start < mask_param if axis == 1:","For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit depth for","(freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int, format:","1 may not converge. length (int or None): Array length of the expected","the power/amplitude scale. Args: x (Tensor): Input tensor before being converted to power/amplitude","Batched inputs should include a channel dimension and have the form `(batch, channel,","return mels def _mel_to_hz(mels: Tensor, mel_scale: str = \"htk\") -> Tensor: \"\"\"Convert mel","at time :math:`t`, :math:`c_t` is the spectrogram coeffcients at time :math:`t`, :math:`N` is","indices: Tensor, win_length: int ) -> Tensor: r\"\"\" Apply median smoothing to the","of mfc coefficients to retain n_mels (int): Number of mel filterbanks norm (str","different types of features give the same number of frames. (default: True) Returns:","`1.0`). Returns: Tensor: Power of the normed input tensor. Shape of `(..., )`","normalize variance to one. (bool, default = false) Returns: Tensor: Tensor of freq","= waveform[:, last_window_start, :] cur_sum -= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove **","is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio of dimension (..., freq, time)","close to the first half of lags, then the latter is taken. \"\"\"","= torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu) * 2 - 1.0 x","1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1,","= compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \"\"\" device = specgram.device dtype = specgram.dtype","the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values between 0 and","to. Must be more than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest","# with 231 == ceil(300 / 1.3) torch.Size([2, 1025, 231, 2]) \"\"\" #","2 * math.pi * torch.rand(batch, freq, frames) else: angles = torch.zeros(batch, freq, frames)","dtype=dtype) * (specgrams.size(axis) - value) # Create broadcastable mask mask_start = min_value[..., None,","dimensions (channel, freq, time) \"\"\" # pack batch shape = specgram.size() specgram =","optional): Lowest frequency that can be detected (Hz) (Default: ``85``). freq_high (int, optional):","1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack batch output =","the magnitude spectrogram, (must be > 0) e.g., 1 for energy, 2 for","f_sp = 200.0 / 3 mels = (freq - f_min) / f_sp #","warnings from typing import Optional, Tuple import torch from torch import Tensor from",">>> rate = 1.3 # Speed up by 30% >>> phase_advance = torch.linspace(","mag * torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1)","center (bool, optional): whether to pad :attr:`waveform` on both sides so that the","freq, time) cmn_window (int, optional): Window in frames for running average CMN computation","float, length: Optional[int], rand_init: bool ) -> Tensor: r\"\"\"Compute waveform from a linear","to power. If 0.5, will compute DB to amplitude. Returns: Tensor: Output tensor","False, norm_vars: bool = False, ) -> Tensor: r\"\"\" Apply sliding-window cepstral mean","input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype device","magnitude-only STFT spectrogram of dimension (..., freq, frames) where freq is ``n_fft //","dtype=dtype, device=device) else: variance = cur_sumsq variance = variance / window_frames variance -=","n_mels (int): Number of mel filterbanks sample_rate (int): Sample rate of the audio","no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor): A magnitude-only STFT spectrogram of dimension","torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel,","delta_pitch( float, optional): Smallest relative change in pitch that our algorithm measures. (default:","given. \"\"\" assert momentum < 1, 'momentum={} > 1 can be unstable'.format(momentum) assert","...)``. \"\"\" if norm is not None and norm != \"slaney\": raise ValueError(\"norm","shape `(..., 2)` into its magnitude and phase. Args: complex_tensor (Tensor): Tensor shape","# unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams:","argument normalized is not used in Griffin-Lim, \" \"and will be removed in","x def complex_norm( complex_tensor: Tensor, power: float = 1.0 ) -> Tensor: r\"\"\"Compute","Tensor, power: float = 1.0 ) -> Tuple[Tensor, Tensor]: r\"\"\"Separate a complex-valued spectrogram","window length used for computing delta (Default: ``5``) mode (str, optional): Mode parameter","1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1))","# randomly initialize the phase batch, freq, frames = specgram.size() if rand_init: angles","(..., freq, time) Example >>> specgram = torch.randn(1, 40, 1000) >>> delta =","float, power: float ) -> Tensor: r\"\"\"Turn a tensor from the decibel scale","(EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1))","min_log_hz: mels = min_log_mel + math.log(freq / min_log_hz) / logstep return mels def","indices def _median_smoothing( indices: Tensor, win_length: int ) -> Tensor: r\"\"\" Apply median","not used in Griffin-Lim, \" \"and will be removed in v0.9.0 release. To","output_frames = ( (s1 * s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) /","specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value =","``htk`` or ``slaney``. (Default: ``htk``) Returns: mels (float): Frequency in Mels \"\"\" if",":-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:, 2:] / f_diff[1:] #","``n_mfcc``). \"\"\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi","parameter if given. \"\"\" assert momentum < 1, 'momentum={} > 1 can be","* angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram rebuilt =","freq_high) indices = _median_smoothing(indices, win_length) # Convert indices to frequency EPSILON = 10","of features give the same number of frames. (default: True) Returns: Tensor: Pitch","to pitch and NCCF. Reference: - A pitch extraction algorithm tuned for automatic","mask_start = min_value[..., None, None] mask_end = (min_value + value)[..., None, None] mask","upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result = result.reshape(shape[:-1] + result.shape[-2:]) return","the ``length`` parameter if given. \"\"\" assert momentum < 1, 'momentum={} > 1","Store the previous iterate tprev = rebuilt # Invert with our current estimate","(min_value + value)[..., None, None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per","of freq of dimension (..., frame) \"\"\" # pack batch shape = list(waveform.size())","we allow pitch tracking to introduce into the feature processing (affects output only","use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter banks (fb matrix)","** (-9) # Number of lags to check lags = int(math.ceil(sample_rate / freq_low))","2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between each mel point","+= lag_min # Add 1 empirical calibration offset indices += 1 return indices","# And initialize the previous iterate to 0 rebuilt = torch.tensor(0.) for _","waveform of shape `(..., time)`. sample_rate (float): Sample rate of `waveform`. frame_length (float,","the left. (bool, default = false) norm_vars (bool, optional): If true, normalize variance","(str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor):","otherwise. Returns: torch.Tensor: waveform of (..., time), where time equals the ``length`` parameter","of the second, elementwise. \"\"\" mask = (a[0] > thresh * b[0]) values","of size (``n_mels``, ``n_mfcc``). \"\"\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1)","relative change in pitch that our algorithm measures. (default: 0.005) nccf_ballast (float, optional):","if rand_init: angles = 2 * math.pi * torch.rand(batch, freq, frames) else: angles","tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float): Power","reduces NCCF for quiet frames (default: 7000) lowpass_filter_width (int, optional): Integer that determines","(time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2,","angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 =","dimension (..., freq, frames) where freq is ``n_fft // 2 + 1``. window","* torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier if top_db is not None:","sliding-window cepstral mean (and optionally variance) normalization per utterance. Args: waveform (Tensor): Tensor","tensor \"\"\" mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag, phase def","Cost factor for FO change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency for","``frames_per_chunk > 0``. (default: 500) snip_edges (bool, optional): If this is set to","estimates angles = rebuilt if momentum: angles = angles - tprev.mul_(momentum / (1","filterbank so that assuming there is a matrix A of size (..., ``n_freqs``),","int, sample_rate: int, norm: Optional[str] = None, mel_scale: str = \"htk\", ) ->","float = 50, max_f0: float = 400, soft_min_f0: float = 10.0, penalty_factor: float","only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The","of FFT, creates ``n_fft // 2 + 1`` bins hop_length (int): Length of","phase = phase - 2 * math.pi * torch.round(phase / (2 * math.pi))","win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack batch spec_f =","if mel_scale == \"htk\": return 700.0 * (10.0**(mels / 2595.0) - 1.0) #","groups=specgram.shape[1]) / denom # unpack batch output = output.reshape(shape) return output def _compute_nccf(","correspond to what an online decoder would see in the first pass of","variance) normalization per utterance. Args: waveform (Tensor): Tensor of audio of dimension (...,","= ((x_mu + 1) / 2 * mu + 0.5).to(torch.int64) return x_mu def"],"string":"[\n \"signal to. Must be more than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional):\",\n \"of the phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float()\",\n \"int = 100, center: bool = False, norm_vars: bool = False, ) ->\",\n \"amin)) top_db (float or None, optional): Minimum negative cut-off in decibels. A reasonable\",\n \"etc. If None, then the complex spectrum is returned instead. normalized (bool): Whether\",\n \"= quantization_channels - 1.0 if not x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu,\",\n \"the first pass of decoding -- not the final version of the features,\",\n \"torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs def create_fb_matrix( n_freqs: int, f_min: float,\",\n \"((x_mu) / mu) * 2 - 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) *\",\n \"Frequencies in Hz mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default:\",\n \"on Acoustics, Speech and Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049.\",\n \"specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n, n + 1, 1,\",\n \"waveform.shape[0] dtype = waveform.dtype device = waveform.device last_window_start = last_window_end = -1 cur_sum\",\n \"be uniformly sampled from [0, mask_param] mask_value (float): Value to assign to the\",\n \"(float): If power equals 1, will compute DB to power. If 0.5, will\",\n \"STFT spectrogram of dimension (..., freq, frames) where freq is ``n_fft // 2\",\n \"(fb matrix) of size (``n_freqs``, ``n_mels``) meaning number of frequencies to highlight/apply to\",\n \"(bool, default = false) norm_vars (bool, optional): If true, normalize variance to one.\",\n \"= torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device)\",\n \"the same number of frames. (default: True) Returns: Tensor: Pitch feature. Shape: ``(batch,\",\n \"# twice sum of integer squared denom = n * (n + 1)\",\n \"so that the number of frames is the file size divided by the\",\n \"pitch extraction. A non-critical parameter; the frame at which we recompute some of\",\n \"import Optional, Tuple import torch from torch import Tensor from torchaudio._internal import module_utils\",\n \"\\\"DB_to_amplitude\\\", \\\"compute_deltas\\\", \\\"compute_kaldi_pitch\\\", \\\"create_fb_matrix\\\", \\\"create_dct\\\", \\\"compute_deltas\\\", \\\"detect_pitch_frequency\\\", \\\"DB_to_amplitude\\\", \\\"mu_law_encoding\\\", \\\"mu_law_decoding\\\", \\\"complex_norm\\\", \\\"angle\\\", \\\"magphase\\\",\",\n \"either magnitude-only or complex. Args: waveform (Tensor): Tensor of audio of dimension (...,\",\n \") # Update our phase estimates angles = rebuilt if momentum: angles =\",\n \"= angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0,\",\n \"dimension (..., freq, time) Example >>> specgram = torch.randn(1, 40, 1000) >>> delta\",\n \"True, compression: Optional[float] = None, encoding: Optional[str] = None, bits_per_sample: Optional[int] = None,\",\n \"deltas at time :math:`t`, :math:`c_t` is the spectrogram coeffcients at time :math:`t`, :math:`N`\",\n \") return fb def create_dct( n_mfcc: int, n_mels: int, norm: Optional[str] ) ->\",\n \"``[channel, time]`` else ``[time, channel]``. \\\"\\\"\\\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first,\",\n \"= \\\"htk\\\", ) -> Tensor: r\\\"\\\"\\\"Create a frequency bin conversion matrix. Args: n_freqs\",\n \"def mu_law_encoding( x: Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Encode signal based on\",\n \"the angle of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(...,\",\n \"window_start + cmn_window else: window_start = t - cmn_window window_end = t +\",\n \"spectrogram from the power/amplitude scale to the decibel scale. The output of each\",\n \"shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate,\",\n \"freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs def create_fb_matrix(\",\n \") -> Tensor: r\\\"\\\"\\\" Apply a mask along ``axis``. Mask will be applied\",\n \"x_db def DB_to_amplitude( x: Tensor, ref: float, power: float ) -> Tensor: r\\\"\\\"\\\"Turn\",\n \"power (float): Power of the norm. (Default: `1.0`). Returns: Tensor: Power of the\",\n \"https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor ) -> Tensor: r\\\"\\\"\\\"Compute\",\n \"mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu)\",\n \"for lag in range(1, lags + 1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[...,\",\n \"1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) # create\",\n \"hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack batch spec_f\",\n \"mels = min_log_mel + math.log(freq / min_log_hz) / logstep return mels def _mel_to_hz(mels:\",\n \"of `(..., freq, time, complex=2)` rate (float): Speed-up factor phase_advance (Tensor): Expected phase\",\n \"is defined as the weighted average of the frequency values, weighted by their\",\n \"\\\"compute_kaldi_pitch\\\", \\\"create_fb_matrix\\\", \\\"create_dct\\\", \\\"compute_deltas\\\", \\\"detect_pitch_frequency\\\", \\\"DB_to_amplitude\\\", \\\"mu_law_encoding\\\", \\\"mu_law_decoding\\\", \\\"complex_norm\\\", \\\"angle\\\", \\\"magphase\\\", \\\"phase_vocoder\\\", 'mask_along_axis',\",\n \">>> specgram = torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram) >>> delta2 =\",\n \"``uniform(0, max_v - v)``. All examples will have the same mask interval. Args:\",\n \"int = 5, mode: str = \\\"replicate\\\" ) -> Tensor: r\\\"\\\"\\\"Compute delta coefficients\",\n \"0'.format(momentum) if normalized: warnings.warn( \\\"The argument normalized is not used in Griffin-Lim, \\\"\",\n \"= 0 if center: window_start = t - cmn_window // 2 window_end =\",\n \"window (Tensor): Window tensor that is applied/multiplied to each frame/window n_fft (int): Size\",\n \"result would be ``A * create_fb_matrix(A.size(-1), ...)``. \\\"\\\"\\\" if norm is not None\",\n \"1025, 512 >>> # (channel, freq, time, complex=2) >>> complex_specgrams = torch.randn(2, freq,\",\n \"freqs = f_min + f_sp * mels # And now the nonlinear scale\",\n \"false, the incomplete frames near the ending edge won't be snipped, so that\",\n \"-1) return values def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float = 10\",\n \"complex spectrum is returned instead. normalized (bool): Whether to normalize by magnitude after\",\n \"Only relevant for compatibility with online pitch extraction. A non-critical parameter; the frame\",\n \"is the file size divided by the frame-shift. This makes different types of\",\n \"decibel scale. The output of each tensor in a batch depends on the\",\n \"masked will be uniformly sampled from [0, mask_param] mask_value (float): Value to assign\",\n \"(mels[log_t] - min_log_mel)) return freqs def create_fb_matrix( n_freqs: int, f_min: float, f_max: float,\",\n \"Output tensor in decibel scale \\\"\\\"\\\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db\",\n \"> 0: # TODO add \\\"with torch.no_grad():\\\" back when JIT supports it waveform\",\n \"Reference which the output will be scaled by. power (float): If power equals\",\n \"freq, 300, 2) >>> rate = 1.3 # Speed up by 30% >>>\",\n \"EPSILON = 10 ** (-9) freq = sample_rate / (EPSILON + indices.to(torch.float)) #\",\n \"initialize the phase batch, freq, frames = specgram.size() if rand_init: angles = 2\",\n \"Tensor of audio of dimension (..., time) pad (int): Two sided padding of\",\n \"# Compute Phase Accum phase = phase + phase_advance phase = torch.cat([phase_0, phase[...,\",\n \"the number of filterbanks. Each column is a filterbank so that assuming there\",\n \"dct *= math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int\",\n \"hop between STFT windows win_length (int): Window size power (float or None): Exponent\",\n \"= (-1.0 * slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:,\",\n \"CMN computation (int, default = 600) min_cmn_window (int, optional): Minimum CMN window used\",\n \"above 1 may not converge. length (int or None): Array length of the\",\n \"Tensor: Input after mu-law decoding \\\"\\\"\\\" mu = quantization_channels - 1.0 if not\",\n \"optional): Highest frequency that can be detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor\",\n \"window hops (n_frame). \\\"\\\"\\\" if pad > 0: # TODO add \\\"with torch.no_grad():\\\"\",\n \"frame_to_add if norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames = window_end - window_start\",\n \"r\\\"\\\"\\\" Compute the spectral centroid for each channel along the time axis. The\",\n \"recompute_frame (int, optional): Only relevant for compatibility with online pitch extraction. A non-critical\",\n \"-2, -1)) - top_db).view(-1, 1, 1, 1)) # Repack batch x_db = x_db.reshape(shape)\",\n \"the last dimension corresponds to pitch and NCCF. Reference: - A pitch extraction\",\n \"Returns: freqs (Tensor): Mels converted in Hz \\\"\\\"\\\" if mel_scale not in ['slaney',\",\n \"(default: 1000) resample_frequency (float, optional): Frequency that we down-sample the signal to. Must\",\n \"Returns: Tensor: Output tensor in decibel scale \\\"\\\"\\\" x_db = multiplier * torch.log10(torch.clamp(x,\",\n \"in power/amplitude scale. \\\"\\\"\\\" return ref * torch.pow(torch.pow(10.0, 0.1 * x), power) def\",\n \"0 if last_window_start == -1: input_part = waveform[:, window_start: window_end - window_start, :]\",\n \"(frame_to_add ** 2) window_frames = window_end - window_start last_window_start = window_start last_window_end =\",\n \"the file size divided by the frame-shift. This makes different types of features\",\n \"of dimension (..., frame) \\\"\\\"\\\" input_shape = waveform.shape num_frames, num_feats = input_shape[-2:] waveform\",\n \"\\\\times \\\\text{hop\\\\_length}`. Default: ``True`` pad_mode (string, optional): controls the padding method used when\",\n \"frequency that can be detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor of freq\",\n \"or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 2595.0 * math.log10(1.0 + (freq /\",\n \"x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1, 1)) # Repack\",\n \"torch.cat(output_lag, -1) return nccf def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh:\",\n \"Invert with our current estimate of the phases inverse = torch.istft(specgram * angles,\",\n \"freq, time) sample_rate (int): The sample rate of the waveform (Hz) frame_time (float,\",\n \"librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided,\",\n \"= specgram.size() if rand_init: angles = 2 * math.pi * torch.rand(batch, freq, frames)\",\n \"norm_vars: if window_frames == 1: cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats, dtype=dtype,\",\n \"mask_start) & (mask < mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams def\",\n \"based on mu-law companding. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This\",\n \"\\\" \\\"please use `normalized=False`.\\\") # pack batch shape = specgram.size() specgram = specgram.reshape([-1]\",\n \"n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft(\",\n \"(pad, pad), \\\"constant\\\") # pack batch shape = waveform.size() waveform = waveform.reshape(-1, shape[-1])\",\n \"form `(batch, channel, freq, time)`. multiplier (float): Use 10. for power and 20.\",\n \"= f_pts[1:] - f_pts[:-1] # (n_mels + 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1)\",\n \"previous iterate to 0 rebuilt = torch.tensor(0.) for _ in range(n_iter): # Store\",\n \">= mask_start) & (mask < mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams\",\n \"freq_low: int ) -> Tensor: r\\\"\\\"\\\" Compute Normalized Cross-Correlation Function (NCCF). .. math::\",\n \"first half of lags, then the latter is taken. \\\"\\\"\\\" lag_min = int(math.ceil(sample_rate\",\n \"win_length (int, optional): The window length for median smoothing (in number of frames)\",\n \"number of window hops (n_frame). \\\"\\\"\\\" if pad > 0: # TODO add\",\n \"2) # create overlapping triangles zero = torch.zeros(1) down_slopes = (-1.0 * slopes[:,\",\n \"= (win_length - 1) // 2 # twice sum of integer squared denom\",\n \"r\\\"\\\"\\\"Create a spectrogram or a batch of spectrograms from a raw audio signal.\",\n \"sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width,\",\n \"extraction. A non-critical parameter; the frame at which we recompute some of the\",\n \"rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True,\",\n \"``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio of dimension (..., freq, time) win_length\",\n \"* torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) #\",\n \"last dimension corresponds to pitch and NCCF. Reference: - A pitch extraction algorithm\",\n \"over the given window. \\\"\\\"\\\" # Centered windowed pad_length = (win_length - 1)\",\n \"x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu return x\",\n \") -> Tensor: r\\\"\\\"\\\"Compute the norm of complex tensor input. Args: complex_tensor (Tensor):\",\n \"0) simulate_first_pass_online (bool, optional): If true, the function will output features that correspond\",\n \"int, n_mels: int, norm: Optional[str] ) -> Tensor: r\\\"\\\"\\\"Create a DCT transformation matrix\",\n \"0 recovers the original Griffin-Lim method. Values near 1 can lead to faster\",\n \"also ```channels_first```. sample_rate (int): Sample rate of the audio waveform. format (str): File\",\n \"indices = _median_smoothing(indices, win_length) # Convert indices to frequency EPSILON = 10 **\",\n \"pad_length = (win_length - 1) // 2 # \\\"replicate\\\" padding in any dimension\",\n \"median smoothing to the 1D tensor over the given window. \\\"\\\"\\\" # Centered\",\n \"0.1) lowpass_cutoff (float, optional): Cutoff frequency for LowPass filter (Hz) (default: 1000) resample_frequency\",\n \"- cmn_window window_end = t + 1 if window_start < 0: window_end -=\",\n \"sample_rate, channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes,\",\n \"waveform (Tensor): The input waveform of shape `(..., time)`. sample_rate (float): Sample rate\",\n \"/= window.pow(2.).sum().sqrt() if power is not None: if power == 1.0: return spec_f.abs()\",\n \"p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 - angle_0 -\",\n \"= specgram.dtype # pack batch shape = specgram.size() specgram = specgram.reshape(1, -1, shape[-1])\",\n \"is the default. (default: False) Relevant if ``frames_per_chunk > 0``. recompute_frame (int, optional):\",\n \"size (``n_freqs``, ``n_mels``) meaning number of frequencies to highlight/apply to x the number\",\n \"from [0, mask_param] mask_value (float): Value to assign to the masked columns axis\",\n \"The transformation matrix, to be right-multiplied to row-wise data of size (``n_mels``, ``n_mfcc``).\",\n \"which is the default. (default: False) Relevant if ``frames_per_chunk > 0``. recompute_frame (int,\",\n \"this warning, \\\" \\\"please use `normalized=False`.\\\") # pack batch shape = specgram.size() specgram\",\n \"torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1, :] else:\",\n \"p)) # Compute lags output_lag = [] for lag in range(1, lags +\",\n \"normalized depending on norm. Args: n_mfcc (int): Number of mfc coefficients to retain\",\n \"momentum: float, length: Optional[int], rand_init: bool ) -> Tensor: r\\\"\\\"\\\"Compute waveform from a\",\n \"int, format: str, channels_first: bool = True, compression: Optional[float] = None, encoding: Optional[str]\",\n \"of (..., time), where time equals the ``length`` parameter if given. \\\"\\\"\\\" assert\",\n \"freq of dimension (..., frame) \\\"\\\"\\\" # pack batch shape = list(waveform.size()) waveform\",\n \"of `(..., )` \\\"\\\"\\\" # Replace by torch.norm once issue is fixed #\",\n \"mel band (area normalization). (Default: ``None``) mel_scale (str, optional): Scale to use: ``htk``\",\n \"1. Args: x (Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor:\",\n \"recompute_frame: int = 500, snip_edges: bool = True, ) -> torch.Tensor: \\\"\\\"\\\"Extract pitch\",\n \"Exponent for the magnitude spectrogram, (must be > 0) e.g., 1 for energy,\",\n \"= specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) * mask_param min_value\",\n \"# TODO add \\\"with torch.no_grad():\\\" back when JIT supports it waveform = torch.nn.functional.pad(waveform,\",\n \"2.0 else: assert norm == \\\"ortho\\\" dct[0] *= 1.0 / math.sqrt(2.0) dct *=\",\n \"Per batch example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask\",\n \"padding method used when :attr:`center` is ``True``. Default: ``\\\"reflect\\\"`` onesided (bool, optional): controls\",\n \"recovery process. momentum (float): The momentum parameter for fast Griffin-Lim. Setting this to\",\n \"= waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor, multiplier: float, amin:\",\n \"bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max,\",\n \"& (mask < mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams def mask_along_axis(\",\n \"def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float = 0.99 )\",\n \"= 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep = math.log(6.4) /\",\n \"= 0, frames_per_chunk: int = 0, simulate_first_pass_online: bool = False, recompute_frame: int =\",\n \"complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams: Tensor, rate:\",\n \"a filterbank so that assuming there is a matrix A of size (...,\",\n \"n), mode=mode) kernel = torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1)\",\n \"(new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long())\",\n \"to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: mels (float): Frequency in Mels\",\n \"applied result would be ``A * create_fb_matrix(A.size(-1), ...)``. \\\"\\\"\\\" if norm is not\",\n \"``n_fft``) power (float): Exponent for the magnitude spectrogram, (must be > 0) e.g.,\",\n \"complex_tensor: Tensor, power: float = 1.0 ) -> Tensor: r\\\"\\\"\\\"Compute the norm of\",\n \"\\\"htk\\\" or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 700.0 * (10.0**(mels / 2595.0)\",\n \"mfc coefficients to retain n_mels (int): Number of mel filterbanks norm (str or\",\n \"mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. Args: specgrams (Tensor): Real spectrograms\",\n \"* (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert\",\n \"CMN window used at start of decoding (adds latency only at start). Only\",\n \"= input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype\",\n \"device = waveform.device last_window_start = last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype,\",\n \"or None) Returns: Tensor: The transformation matrix, to be right-multiplied to row-wise data\",\n \"assert norm == \\\"ortho\\\" dct[0] *= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 /\",\n \"\\\"replicate\\\" padding in any dimension indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\\\"constant\\\", value=0.\",\n \"freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length /\",\n \"size Returns: Tensor: Dimension (..., time) \\\"\\\"\\\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft,\",\n \"decibels. A reasonable number is 80. (Default: ``None``) Returns: Tensor: Output tensor in\",\n \"norm is not None and norm != \\\"slaney\\\": raise ValueError(\\\"norm must be one\",\n \"in hertz f_diff = f_pts[1:] - f_pts[:-1] # (n_mels + 1) slopes =\",\n \"\\\"\\\"\\\" if axis != 2 and axis != 3: raise ValueError('Only Frequency and\",\n \"detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor of freq of dimension (..., frame)\",\n \"+= torch.cumsum(input_part ** 2, 1)[:, -1, :] else: if window_start > last_window_start: frame_to_remove\",\n \"variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform =\",\n \"the decibel scale to the power/amplitude scale. Args: x (Tensor): Input tensor before\",\n \"phase_acc = torch.cumsum(phase, -1) mag = alphas * norm_1 + (1 - alphas)\",\n \"= mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch\",\n \"the frame at which we recompute some of the forward pointers, after revising\",\n \"torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented, _ =\",\n \"float = 0.99 ) -> Tuple[Tensor, Tensor]: \\\"\\\"\\\" Take value from first if\",\n \"phase def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor ) -> Tensor: r\\\"\\\"\\\"Given\",\n \"dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value) #\",\n \"n_fft: int, hop_length: int, win_length: int, power: Optional[float], normalized: bool, center: bool =\",\n \"Expand batch shape = x_db.size() packed_channels = shape[-3] if x_db.dim() > 2 else\",\n \"= torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True,\",\n \"_hz_to_mel(freq: float, mel_scale: str = \\\"htk\\\") -> float: r\\\"\\\"\\\"Convert Hz to Mels. Args:\",\n \"using normalized cross-correlation function and median smoothing. Args: waveform (Tensor): Tensor of audio\",\n \"if ``frames_per_chunk > 0``. (default: 500) snip_edges (bool, optional): If this is set\",\n \"f_diff = f_pts[1:] - f_pts[:-1] # (n_mels + 1) slopes = f_pts.unsqueeze(0) -\",\n \"Relevant if ``frames_per_chunk > 0``. recompute_frame (int, optional): Only relevant for compatibility with\",\n \"_median_smoothing(indices, win_length) # Convert indices to frequency EPSILON = 10 ** (-9) freq\",\n \"will be applied from indices ``[v_0, v_0 + v)``, where ``v`` is sampled\",\n \"Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \\\"\\\"\\\" shape = waveform.shape waveform\",\n \"the nonlinear scale min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp\",\n \"1`` bins hop_length (int): Length of hop between STFT windows. ( Default: ``win_length\",\n \"will compute DB to amplitude. Returns: Tensor: Output tensor in power/amplitude scale. \\\"\\\"\\\"\",\n \"1`` and ``n_fft`` is the number of Fourier bins, and time is the\",\n \"shape[-1]) assert win_length >= 3 n = (win_length - 1) // 2 #\",\n \"(Tensor): Mel frequencies mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default:\",\n \"n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack batch\",\n \"that we allow pitch tracking to introduce into the feature processing (affects output\",\n \"Args: specgram (Tensor): A magnitude-only STFT spectrogram of dimension (..., freq, frames) where\",\n \"<NAME>, <NAME> and <NAME> 2014 IEEE International Conference on Acoustics, Speech and Signal\",\n \"min_f0: float = 50, max_f0: float = 400, soft_min_f0: float = 10.0, penalty_factor:\",\n \"= waveform.dtype device = waveform.device last_window_start = last_window_end = -1 cur_sum = torch.zeros(num_channels,\",\n \"``n_fft`` is the number of Fourier bins, and time is the number of\",\n \"/ min_log_hz) / logstep return mels def _mel_to_hz(mels: Tensor, mel_scale: str = \\\"htk\\\")\",\n \"int, window: Tensor, n_fft: int, hop_length: int, win_length: int, power: Optional[float], normalized: bool,\",\n \"n_mels) up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero,\",\n \"is not None and norm == \\\"slaney\\\": # Slaney-style mel is scaled to\",\n \"n + 1) / 3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel =\",\n \"If false, window is to the left. (bool, default = false) norm_vars (bool,\",\n \"modifying pitch by a factor of ``rate``. Args: complex_specgrams (Tensor): Dimension of `(...,\",\n \"audio waveform pad (int): Two sided padding of signal window (Tensor): Window tensor\",\n \"torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu + 1) / 2 *\",\n \"transform,\\\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor): A\",\n \"unpack batch output = output.reshape(shape) return output def _compute_nccf( waveform: Tensor, sample_rate: int,\",\n \"Pitch feature. Shape: ``(batch, frames 2)`` where the last dimension corresponds to pitch\",\n \"(int): Window size Returns: Tensor: Dimension (..., time) \\\"\\\"\\\" specgram = spectrogram(waveform, pad=pad,\",\n \"int ) -> Tensor: r\\\"\\\"\\\" Apply median smoothing to the 1D tensor over\",\n \"(float): Frequency in Mels \\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale\",\n \"# Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins, freq,\",\n \"and norm != \\\"slaney\\\": raise ValueError(\\\"norm must be one of None or 'slaney'\\\")\",\n \"(2 * n + 1) / 3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode)\",\n \"soft_min_f0 (float, optional): Minimum f0, applied in soft way, must not exceed min-f0\",\n \"pack batch shape = list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform,\",\n \"batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor, cmn_window:\",\n \"None, bits_per_sample: Optional[int] = None, ) -> Tensor: r\\\"\\\"\\\" Apply codecs as a\",\n \"(Hz) n_mels (int): Number of mel filterbanks sample_rate (int): Sample rate of the\",\n \"between 0 and quantization_channels - 1 and returns a signal scaled between -1\",\n \"amplitude. Returns: Tensor: Output tensor in power/amplitude scale. \\\"\\\"\\\" return ref * torch.pow(torch.pow(10.0,\",\n \"at which we recompute some of the forward pointers, after revising our estimate\",\n \"== 1: cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance\",\n \"power/amplitude scale. \\\"\\\"\\\" return ref * torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq:\",\n \") -> Tensor: r\\\"\\\"\\\"Encode signal based on mu-law companding. For more info see\",\n \"Tensor: Tensor of freq of dimension (..., frame) \\\"\\\"\\\" # pack batch shape\",\n \"among all the lags is very close to the first half of lags,\",\n \"def _hz_to_mel(freq: float, mel_scale: str = \\\"htk\\\") -> float: r\\\"\\\"\\\"Convert Hz to Mels.\",\n \"Tensor): The magnitude and phase of the complex tensor \\\"\\\"\\\" mag = complex_norm(complex_tensor,\",\n \"fb def create_dct( n_mfcc: int, n_mels: int, norm: Optional[str] ) -> Tensor: r\\\"\\\"\\\"Create\",\n \"Returns: Tensor: Masked spectrograms of dimensions (batch, channel, freq, time) \\\"\\\"\\\" if axis\",\n \"list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor, cmn_window: int = 600, min_cmn_window: int\",\n \"with online pitch extraction. A non-critical parameter; the frame at which we recompute\",\n \"and returns a signal scaled between -1 and 1. Args: x_mu (Tensor): Input\",\n \"(Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law\",\n \"spectrogram coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of\",\n \"cmn_window // 2 window_end = window_start + cmn_window else: window_start = t -\",\n \"(affects output only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int,\",\n \"unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor,\",\n \"norm_vars: bool = False, ) -> Tensor: r\\\"\\\"\\\" Apply sliding-window cepstral mean (and\",\n \"Tensor, power: float = 1.0 ) -> Tensor: r\\\"\\\"\\\"Compute the norm of complex\",\n \"freq, time) win_length (int, optional): The window length used for computing delta (Default:\",\n \"quiet frames (default: 7000) lowpass_filter_width (int, optional): Integer that determines filter width of\",\n \"waveform (Tensor): Tensor of audio of dimension (..., freq, time) cmn_window (int, optional):\",\n \"float = 25.0, frame_shift: float = 10.0, min_f0: float = 50, max_f0: float\",\n \"filter (Hz) (default: 1000) resample_frequency (float, optional): Frequency that we down-sample the signal\",\n \"= \\\"htk\\\") -> float: r\\\"\\\"\\\"Convert Hz to Mels. Args: freqs (float): Frequencies in\",\n \"-> Tensor: r\\\"\\\"\\\"Create a spectrogram or a batch of spectrograms from a raw\",\n \"# (n_mels + 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels +\",\n \"true, normalize variance to one. (bool, default = false) Returns: Tensor: Tensor of\",\n \":math:`b_i` is the beginning of frame :math:`i`, :math:`E(j)` is the energy :math:`\\\\sum_{n=j}^{j+N-1} w^2(n)`.\",\n \"when :attr:`center` is ``True``. Default: ``\\\"reflect\\\"`` onesided (bool, optional): controls whether to return\",\n \"on norm. Args: n_mfcc (int): Number of mfc coefficients to retain n_mels (int):\",\n \"= torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu\",\n \"Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law decoding\",\n \"+ N-1} w(n) w(m+n)}{\\\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\\\phi_i(m)` is the NCCF at frame :math:`i`\",\n \"Take value from first if bigger than a multiplicative factor of the second,\",\n \"min-f0 (default: 10.0) penalty_factor (float, optional): Cost factor for FO change. (default: 0.1)\",\n \"norm. Args: n_mfcc (int): Number of mfc coefficients to retain n_mels (int): Number\",\n \"assert mask_end - mask_start < mask_param if axis == 1: specgram[:, mask_start:mask_end] =\",\n \"512 >>> # (channel, freq, time, complex=2) >>> complex_specgrams = torch.randn(2, freq, 300,\",\n \"b[0] indices = mask * a[1] + ~mask * b[1] return values, indices\",\n \"not None: if power == 1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def\",\n \"def griffinlim( specgram: Tensor, window: Tensor, n_fft: int, hop_length: int, win_length: int, power:\",\n \"number is 80. (Default: ``None``) Returns: Tensor: Output tensor in decibel scale \\\"\\\"\\\"\",\n \"the given window. \\\"\\\"\\\" # Centered windowed pad_length = (win_length - 1) //\",\n \"expected output. rand_init (bool): Initializes phase randomly if True, to zero otherwise. Returns:\",\n \"time) sample_rate (int): The sample rate of the waveform (Hz) frame_time (float, optional):\",\n \"channel]``. compression (float): Used for formats other than WAV. For mor details see\",\n \"row-wise data of size (``n_mels``, ``n_mfcc``). \\\"\\\"\\\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k\",\n \"filter banks (fb matrix) of size (``n_freqs``, ``n_mels``) meaning number of frequencies to\",\n \"optional): whether to pad :attr:`waveform` on both sides so that the :math:`t`-th frame\",\n \"specgram.size() if rand_init: angles = 2 * math.pi * torch.rand(batch, freq, frames) else:\",\n \"2595.0) - 1.0) # Fill in the linear scale f_min = 0.0 f_sp\",\n \"(``n_mels``, ``n_mfcc``). \\\"\\\"\\\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct =\",\n \"multiplier: float, amin: float, db_multiplier: float, top_db: Optional[float] = None ) -> Tensor:\",\n \"magnitude and phase of the complex tensor \\\"\\\"\\\" mag = complex_norm(complex_tensor, power) phase\",\n \"math.pi)) # Compute Phase Accum phase = phase + phase_advance phase = torch.cat([phase_0,\",\n \"mask_param (int): Number of columns to be masked will be uniformly sampled from\",\n \"\\\"\\\"\\\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power: float =\",\n \"\\\"mu_law_encoding\\\", \\\"mu_law_decoding\\\", \\\"complex_norm\\\", \\\"angle\\\", \\\"magphase\\\", \\\"phase_vocoder\\\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \\\"spectral_centroid\\\", \\\"apply_codec\\\", ] def\",\n \"2 # twice sum of integer squared denom = n * (n +\",\n \"for running average CMN computation (int, default = 600) min_cmn_window (int, optional): Minimum\",\n \"torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats))\",\n \"will output features that correspond to what an online decoder would see in\",\n \"* mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value) # Create\",\n \"= false) norm_vars (bool, optional): If true, normalize variance to one. (bool, default\",\n \"power: float, normalized: bool, n_iter: int, momentum: float, length: Optional[int], rand_init: bool )\",\n \"int ) -> Tensor: r\\\"\\\"\\\" Compute Normalized Cross-Correlation Function (NCCF). .. math:: \\\\phi_i(m)\",\n \">>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with 231 == ceil(300\",\n \"num_channels = waveform.shape[0] dtype = waveform.dtype device = waveform.device last_window_start = last_window_end =\",\n \"(win_length - 1) // 2 # twice sum of integer squared denom =\",\n \"Otherwise, they have dimension ``[time, channel]``. compression (float): Used for formats other than\",\n \"waveform norm (Optional[str]): If 'slaney', divide the triangular mel weights by the width\",\n \"= None ) -> Tensor: r\\\"\\\"\\\"Turn a spectrogram from the power/amplitude scale to\",\n \") -> Tensor: r\\\"\\\"\\\"Create a spectrogram or a batch of spectrograms from a\",\n \"/ float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int ) -> Tensor:\",\n \"num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels,\",\n \"= 0 window_end = 0 if center: window_start = t - cmn_window //\",\n \"= compute_deltas(delta) \\\"\\\"\\\" device = specgram.device dtype = specgram.dtype # pack batch shape\",\n \"be one of \\\"htk\\\" or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 2595.0 *\",\n \"hop_length (int): Length of hop between STFT windows win_length (int): Window size Returns:\",\n \"frames 2)`` where the last dimension corresponds to pitch and NCCF. Reference: -\",\n \"(float): Minimum frequency (Hz) f_max (float): Maximum frequency (Hz) n_mels (int): Number of\",\n \"Tensor, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, power: Optional[float],\",\n \"frames = specgram.size() if rand_init: angles = 2 * math.pi * torch.rand(batch, freq,\",\n \"in the first pass of decoding -- not the final version of the\",\n \"start of decoding (adds latency only at start). Only applicable if center ==\",\n \"phase = phase + phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc =\",\n \"_ = torch.median(roll, -1) return values def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time:\",\n \"resample_frequency (float, optional): Frequency that we down-sample the signal to. Must be more\",\n \"(bool): Whether to normalize by magnitude after stft center (bool, optional): whether to\",\n \":math:`c_t` is the spectrogram coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram\",\n \"signal encoded with values from 0 to quantization_channels - 1. Args: x (Tensor):\",\n \"200.0 / 3 freqs = f_min + f_sp * mels # And now\",\n \"Tensor: r\\\"\\\"\\\" Apply a mask along ``axis``. Mask will be applied from indices\",\n \"= torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag = [] for lag in\",\n \":py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding for the supported formats. For more\",\n \"complex_tensor (Tensor): Tensor shape of `(..., complex=2)` Return: Tensor: Angle of a complex\",\n \"last_window_end = window_end cmn_waveform[:, t, :] = waveform[:, t, :] - cur_sum /\",\n \"Tensor, sample_rate: int, format: str, channels_first: bool = True, compression: Optional[float] = None,\",\n \"signal energy. Relevant if ``frames_per_chunk > 0``. (default: 500) snip_edges (bool, optional): If\",\n \"float ) -> Tensor: r\\\"\\\"\\\"Turn a tensor from the decibel scale to the\",\n \"v_0 + v)``, where ``v`` is sampled from ``uniform(0, mask_param)``, and ``v_0`` from\",\n \"the lags is very close to the first half of lags, then the\",\n \"one mel filterbank has all zero values. \\\" f\\\"The value for `n_mels` ({n_mels})\",\n \"is the NCCF at frame :math:`i` with lag :math:`m`, :math:`w` is the waveform,\",\n \"effects=[[\\\"rate\\\", f\\\"{sample_rate}\\\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float,\",\n \"of dimension (..., freq, time) cmn_window (int, optional): Window in frames for running\",\n \"(Default: ``5``) mode (str, optional): Mode parameter passed to padding (Default: ``\\\"replicate\\\"``) Returns:\",\n \"onesided (bool, optional): controls whether to return half of results to avoid redundancy.\",\n \"def spectral_centroid( waveform: Tensor, sample_rate: int, pad: int, window: Tensor, n_fft: int, hop_length:\",\n \"1) upsample_filter_width (int, optional): Integer that determines filter width when upsampling NCCF. (default:\",\n \"= int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames\",\n \"hop_length = 1025, 512 >>> # (channel, freq, time, complex=2) >>> complex_specgrams =\",\n \"range(1, lags + 1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2\",\n \"from modified short-time Fourier transform,\\\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984.\",\n \"Dimension of `(..., freq, time, complex=2)` rate (float): Speed-up factor phase_advance (Tensor): Expected\",\n \"(default: 0) frames_per_chunk (int, optional): The number of frames used for energy normalization.\",\n \"least one mel filterbank has all zero values. \\\" f\\\"The value for `n_mels`\",\n \"phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag = alphas * norm_1 +\",\n \"our estimate of the signal energy. Relevant if ``frames_per_chunk > 0``. (default: 500)\",\n \"[1]. This function computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor):\",\n \">>> phase_advance = torch.linspace( >>> 0, math.pi * hop_length, freq)[..., None] >>> x\",\n \"int, power: float, normalized: bool, n_iter: int, momentum: float, length: Optional[int], rand_init: bool\",\n \"= waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames = ( (s1 * s2).sum(-1)\",\n \"angles - tprev.mul_(momentum / (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the\",\n \"pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1)\",\n \"our current estimate of the phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length,\",\n \"complex tensor. Shape of `(..., )` \\\"\\\"\\\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def\",\n \"5, max_frames_latency: int = 0, frames_per_chunk: int = 0, simulate_first_pass_online: bool = False,\",\n \"> t: window_end = max(t + 1, min_cmn_window) if window_end > num_frames: window_start\",\n \"NCCF. (default: 5) max_frames_latency (int, optional): Maximum number of frames of latency that\",\n \"A magnitude-only STFT spectrogram of dimension (..., freq, frames) where freq is ``n_fft\",\n \"centered median smoothing, and convert to frequency. Note: If the max among all\",\n \"Length of hop between STFT windows win_length (int): Window size Returns: Tensor: Dimension\",\n \"-> Tensor: r\\\"\\\"\\\" Apply codecs as a form of augmentation. Args: waveform (Tensor):\",\n \"Kaldi. Args: waveform (Tensor): The input waveform of shape `(..., time)`. sample_rate (float):\",\n \"optional): Minimum negative cut-off in decibels. A reasonable number is 80. (Default: ``None``)\",\n \"Tensor of audio of dimension (..., freq, time) win_length (int, optional): The window\",\n \"second, elementwise. \\\"\\\"\\\" mask = (a[0] > thresh * b[0]) values = mask\",\n \"batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if power\",\n \"(a[0] > thresh * b[0]) values = mask * a[0] + ~mask *\",\n \"waveform = torch.nn.functional.pad(waveform, (pad, pad), \\\"constant\\\") # pack batch shape = waveform.size() waveform\",\n \"t, :] = waveform[:, t, :] - cur_sum / window_frames if norm_vars: if\",\n \"(Tensor): Input tensor before being converted to power/amplitude scale. ref (float): Reference which\",\n \"a frequency bin conversion matrix. Args: n_freqs (int): Number of frequencies to highlight/apply\",\n \"waveform from a linear scale magnitude spectrogram using the Griffin-Lim transformation. Implementation ported\",\n \":math:`d_t` is the deltas at time :math:`t`, :math:`c_t` is the spectrogram coeffcients at\",\n \"return output def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float, freq_low: int )\",\n \"/ window_frames if norm_vars: if window_frames == 1: cmn_waveform[:, t, :] = torch.zeros(\",\n \"> 1 can be unstable'.format(momentum) assert momentum >= 0, 'momentum={} < 0'.format(momentum) if\",\n \"Speed-up factor phase_advance (Tensor): Expected phase advance in each bin. Dimension of (freq,\",\n \"of audio of dimension (..., freq, time) sample_rate (int): The sample rate of\",\n \"output of each tensor in a batch depends on the maximum value of\",\n \"sample_rate: float, frame_length: float = 25.0, frame_shift: float = 10.0, min_f0: float =\",\n \"in python.\\\" In Proceedings of the 14th python in science conference, pp. 18-25.\",\n \"1) // 2 # \\\"replicate\\\" padding in any dimension indices = torch.nn.functional.pad( indices,\",\n \"Log10(max(reference value and amin)) top_db (float or None, optional): Minimum negative cut-off in\",\n \"= mask_value else: raise ValueError('Only Frequency and Time masking are supported') # unpack\",\n \"encoding, bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\\\"rate\\\", f\\\"{sample_rate}\\\"]], channels_first=channels_first, format=format)\",\n \"windows win_length (int): Window size Returns: Tensor: Dimension (..., time) \\\"\\\"\\\" specgram =\",\n \"4000, delta_pitch: float = 0.005, nccf_ballast: float = 7000, lowpass_filter_width: int = 1,\",\n \"for `n_freqs` ({n_freqs}) may be set too low.\\\" ) return fb def create_dct(\",\n \"= None, mel_scale: str = \\\"htk\\\", ) -> Tensor: r\\\"\\\"\\\"Create a frequency bin\",\n \"at frame :math:`i` with lag :math:`m`, :math:`w` is the waveform, :math:`N` is the\",\n \"all zero values. \\\" f\\\"The value for `n_mels` ({n_mels}) may be set too\",\n \"1 for energy, 2 for power, etc. If None, then the complex spectrum\",\n \"in ['slaney', 'htk']: raise ValueError('mel_scale should be one of \\\"htk\\\" or \\\"slaney\\\".') if\",\n \"freq, time) Example >>> specgram = torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram)\",\n \"time) cmn_window (int, optional): Window in frames for running average CMN computation (int,\",\n \"specgram: Tensor, window: Tensor, n_fft: int, hop_length: int, win_length: int, power: float, normalized:\",\n \"int, win_length: int, power: float, normalized: bool, n_iter: int, momentum: float, length: Optional[int],\",\n \"str = \\\"htk\\\") -> Tensor: \\\"\\\"\\\"Convert mel bin numbers to frequencies. Args: mels\",\n \"= True, ) -> torch.Tensor: \\\"\\\"\\\"Extract pitch based on method described in [1].\",\n \"this to 0 recovers the original Griffin-Lim method. Values near 1 can lead\",\n \"scale \\\"\\\"\\\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier\",\n \"float = 10 ** (-2), win_length: int = 30, freq_low: int = 85,\",\n \"x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with 231 == ceil(300 /\",\n \"(-2), win_length: int = 30, freq_low: int = 85, freq_high: int = 3400,\",\n \"1, 1)) # Repack batch x_db = x_db.reshape(shape) return x_db def DB_to_amplitude( x:\",\n \"if power == 1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram:\",\n \"torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu =\",\n \"faster convergence, but above 1 may not converge. length (int or None): Array\",\n \"version of the features, which is the default. (default: False) Relevant if ``frames_per_chunk\",\n \"-- not the final version of the features, which is the default. (default:\",\n \"torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack batch output = output.reshape(shape) return output\",\n \"running average CMN computation (int, default = 600) min_cmn_window (int, optional): Minimum CMN\",\n \"complex=2)` power (float): Power of the norm. (Default: `1.0`) Returns: (Tensor, Tensor): The\",\n \"Reference: - A pitch extraction algorithm tuned for automatic speech recognition <NAME>, <NAME>,\",\n \"# pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value =\",\n \"dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack batch\",\n \"= false) Returns: Tensor: Tensor of freq of dimension (..., frame) \\\"\\\"\\\" input_shape\",\n \"input and output Tensor have dimension ``[channel, time]``. Otherwise, they have dimension ``[time,\",\n \"s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size,\",\n \"is returned instead. normalized (bool): Whether to normalize by magnitude after stft center\",\n \"see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values between 0\",\n \"returns a signal scaled between -1 and 1. Args: x_mu (Tensor): Input tensor\",\n \"value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert mask_end - mask_start\",\n \"None) Returns: Tensor: The transformation matrix, to be right-multiplied to row-wise data of\",\n \"torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 - angle_0 - phase_advance phase = phase\",\n \"FO change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency for LowPass filter (Hz)\",\n \"integer squared denom = n * (n + 1) * (2 * n\",\n \"format (str): File format. channels_first (bool): When True, both the input and output\",\n \"input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float): Power of\",\n \"(batch, channel, freq, time) mask_param (int): Number of columns to be masked will\",\n \"-> Tensor: r\\\"\\\"\\\" Apply sliding-window cepstral mean (and optionally variance) normalization per utterance.\",\n \"described in [1]. This function computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args:\",\n \"Frequency that we down-sample the signal to. Must be more than twice lowpass-cutoff.\",\n \">>> delta2 = compute_deltas(delta) \\\"\\\"\\\" device = specgram.device dtype = specgram.dtype # pack\",\n \"- tprev.mul_(momentum / (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final\",\n \"(int, optional): Integer that determines filter width of lowpass filter, more gives sharper\",\n \"lags output_lag = [] for lag in range(1, lags + 1): s1 =\",\n \"pad_mode (string, optional): controls the padding method used when :attr:`center` is ``True``. Default:\",\n \"waveform.shape waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0,\",\n \"Normalized Cross-Correlation Function (NCCF). .. math:: \\\\phi_i(m) = \\\\frac{\\\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\\\sqrt{E(b_i)\",\n \"Fill in the linear scale f_min = 0.0 f_sp = 200.0 / 3\",\n \"assuming there is a matrix A of size (..., ``n_freqs``), the applied result\",\n \"= 0.1, lowpass_cutoff: float = 1000, resample_frequency: float = 4000, delta_pitch: float =\",\n \"scale. Input should take the form `(..., freq, time)`. Batched inputs should include\",\n \"be set too low.\\\" ) return fb def create_dct( n_mfcc: int, n_mels: int,\",\n \"converted in Hz \\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should\",\n \"Returns: (Tensor, Tensor): The magnitude and phase of the complex tensor \\\"\\\"\\\" mag\",\n \"`librosa`. * [1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \\\"librosa:\",\n \"audio of dimension (..., freq, time) sample_rate (int): The sample rate of the\",\n \"specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float, axis:\",\n \"math import warnings from typing import Optional, Tuple import torch from torch import\",\n \"f_sp logstep = math.log(6.4) / 27.0 log_t = (mels >= min_log_mel) freqs[log_t] =\",\n \"frame :math:`i` with lag :math:`m`, :math:`w` is the waveform, :math:`N` is the length\",\n \"upsample_filter_width (int, optional): Integer that determines filter width when upsampling NCCF. (default: 5)\",\n \"linear part f_min = 0.0 f_sp = 200.0 / 3 mels = (freq\",\n \":] output_frames = ( (s1 * s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2)\",\n \"is not None: # Expand batch shape = x_db.size() packed_channels = shape[-3] if\",\n \"IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (pp. 1-4),\",\n \"part f_min = 0.0 f_sp = 200.0 / 3 mels = (freq -\",\n \".. math:: \\\\phi_i(m) = \\\\frac{\\\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\\\phi_i(m)` is\",\n \"the energy :math:`\\\\sum_{n=j}^{j+N-1} w^2(n)`. \\\"\\\"\\\" EPSILON = 10 ** (-9) # Number of\",\n \"``[time, channel]``. \\\"\\\"\\\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding,\",\n \"after revising our estimate of the signal energy. Relevant if ``frames_per_chunk > 0``.\",\n \"list(shape[-2:])) value = torch.rand(1) * mask_param min_value = torch.rand(1) * (specgram.size(axis) - value)\",\n \"NCCF, apply centered median smoothing, and convert to frequency. Note: If the max\",\n \"= torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not None and norm == \\\"slaney\\\":\",\n \"spectral centroid is defined as the weighted average of the frequency values, weighted\",\n \"input with values between 0 and quantization_channels - 1 and returns a signal\",\n \"phase_0 = angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0,\",\n \"window: Tensor, n_fft: int, hop_length: int, win_length: int, power: float, normalized: bool, n_iter:\",\n \"values, indices def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int ) -> Tensor:\",\n \"device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def\",\n \"of iteration for phase recovery process. momentum (float): The momentum parameter for fast\",\n \"* hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape #\",\n \"complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas\",\n \"(Tensor): Tensor of audio of dimension (..., freq, time) win_length (int, optional): The\",\n \"= min_value[..., None, None] mask_end = (min_value + value)[..., None, None] mask =\",\n \"dct = torch.cos(math.pi / float(n_mels) * (n + 0.5) * k) # size\",\n \"** 2) / (window_frames ** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :]\",\n \":] = waveform[:, t, :] - cur_sum / window_frames if norm_vars: if window_frames\",\n \"Mels. Args: freqs (float): Frequencies in Hz mel_scale (str, optional): Scale to use:\",\n \"each frame/window n_fft (int): Size of FFT hop_length (int): Length of hop between\",\n \"axis: int ) -> Tensor: r\\\"\\\"\\\" Apply a mask along ``axis``. Mask will\",\n \"mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: mels\",\n \"specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor, win_length: int\",\n \"n_iter (int): Number of iteration for phase recovery process. momentum (float): The momentum\",\n \"= 5, mode: str = \\\"replicate\\\" ) -> Tensor: r\\\"\\\"\\\"Compute delta coefficients of\",\n \"convert to frequency. Note: If the max among all the lags is very\",\n \"values def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float = 10 ** (-2),\",\n \"smoothing (in number of frames) (Default: ``30``). freq_low (int, optional): Lowest frequency that\",\n \"normalized: bool, center: bool = True, pad_mode: str = \\\"reflect\\\", onesided: bool =\",\n \"* a[1] + ~mask * b[1] return values, indices def _find_max_per_frame( nccf: Tensor,\",\n \"* power) def angle( complex_tensor: Tensor ) -> Tensor: r\\\"\\\"\\\"Compute the angle of\",\n \"is set to false, the incomplete frames near the ending edge won't be\",\n \"Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \\\"\\\"\\\" shape = waveform.shape waveform = waveform.reshape(-1,\",\n \"compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float = 25.0, frame_shift: float = 10.0,\",\n \"frames_per_chunk (int, optional): The number of frames used for energy normalization. (default: 0)\",\n \"time]``. Otherwise, they have dimension ``[time, channel]``. compression (float): Used for formats other\",\n \"complex=2)` power (float): Power of the norm. (Default: `1.0`). Returns: Tensor: Power of\",\n \"mask_param if axis == 1: specgram[:, mask_start:mask_end] = mask_value elif axis == 2:\",\n \"if normalized: warnings.warn( \\\"The argument normalized is not used in Griffin-Lim, \\\" \\\"and\",\n \"= torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\\\ .to(dtype=specgram.dtype, device=specgram.device) specgram\",\n \"freqs (float): Frequencies in Hz mel_scale (str, optional): Scale to use: ``htk`` or\",\n \"For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has\",\n \"to assign to the masked columns axis (int): Axis to apply masking on\",\n \"frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames\",\n \"if norm_vars: cur_sumsq -= (frame_to_remove ** 2) if window_end > last_window_end: frame_to_add =\",\n \"= 1, upsample_filter_width: int = 5, max_frames_latency: int = 0, frames_per_chunk: int =\",\n \"point in hertz f_diff = f_pts[1:] - f_pts[:-1] # (n_mels + 1) slopes\",\n \"Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float): Power of the\",\n \"phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with 231 == ceil(300 / 1.3) torch.Size([2,\",\n \"phase batch, freq, frames = specgram.size() if rand_init: angles = 2 * math.pi\",\n \"t: window_end = max(t + 1, min_cmn_window) if window_end > num_frames: window_start -=\",\n \"angles = angles - tprev.mul_(momentum / (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) #\",\n \"Minimum negative cut-off in decibels. A reasonable number is 80. (Default: ``None``) Returns:\",\n \"complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float, axis: int\",\n \"the mel band (area normalization). (Default: ``None``) mel_scale (str, optional): Scale to use:\",\n \"rate of `waveform`. frame_length (float, optional): Frame length in milliseconds. (default: 25.0) frame_shift\",\n \"mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert mask_end - mask_start <\",\n \"complex_specgrams (Tensor): Dimension of `(..., freq, time, complex=2)` rate (float): Speed-up factor phase_advance\",\n \"# Replace by torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 *\",\n \"Initializes phase randomly if True, to zero otherwise. Returns: torch.Tensor: waveform of (...,\",\n \"# Fill in the log-scale part min_log_hz = 1000.0 min_log_mel = (min_log_hz -\",\n \"spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if power is\",\n \"2``) win_length (int): Window size. (Default: ``n_fft``) power (float): Exponent for the magnitude\",\n \"math:: d_t = \\\\frac{\\\\sum_{n=1}^{\\\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\\\sum_{n=1}^{\\\\text{N}} n^2} where :math:`d_t` is\",\n \"compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\\\"rate\\\", f\\\"{sample_rate}\\\"]],\",\n \"f_min) / f_sp logstep = math.log(6.4) / 27.0 log_t = (mels >= min_log_mel)\",\n \"+ math.log(freq / min_log_hz) / logstep return mels def _mel_to_hz(mels: Tensor, mel_scale: str\",\n \"online decoder would see in the first pass of decoding -- not the\",\n \"the phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() #\",\n \"imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def\",\n \"Tensor: r\\\"\\\"\\\"Compute waveform from a linear scale magnitude spectrogram using the Griffin-Lim transformation.\",\n \"x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu) * 2 -\",\n \"2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 =\",\n \"number of frames is the file size divided by the frame-shift. This makes\",\n \"\\\"\\\"\\\" if norm is not None and norm != \\\"slaney\\\": raise ValueError(\\\"norm must\",\n \"(str or None): Norm to use (either 'ortho' or None) Returns: Tensor: The\",\n \"has ``[channel, time]`` else ``[time, channel]``. \\\"\\\"\\\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate,\",\n \"torch from torch import Tensor from torchaudio._internal import module_utils as _mod_utils import torchaudio\",\n \"of decoding (adds latency only at start). Only applicable if center == false,\",\n \"= num_frames if window_start < 0: window_start = 0 if last_window_start == -1:\",\n \"have dimension ``[time, channel]``. compression (float): Used for formats other than WAV. For\",\n \"real_stretch = mag * torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch,\",\n \"of channels Returns: Tensor: Input after mu-law decoding \\\"\\\"\\\" mu = quantization_channels -\",\n \".to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate to 0\",\n \"= window_start + cmn_window else: window_start = t - cmn_window window_end = t\",\n \"algorithm tuned for automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME>\",\n \"1, min_cmn_window) if window_end > num_frames: window_start -= (window_end - num_frames) window_end =\",\n \"= torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size],\",\n \"optional): Minimum CMN window used at start of decoding (adds latency only at\",\n \"win_length: int, ) -> Tensor: r\\\"\\\"\\\" Compute the spectral centroid for each channel\",\n \"True, to zero otherwise. Returns: torch.Tensor: waveform of (..., time), where time equals\",\n \":num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames = (\",\n \"Note: If the max among all the lags is very close to the\",\n \"int = 0, simulate_first_pass_online: bool = False, recompute_frame: int = 500, snip_edges: bool\",\n \"// 2 # \\\"replicate\\\" padding in any dimension indices = torch.nn.functional.pad( indices, (pad_length,\",\n \"(default: 400.0) soft_min_f0 (float, optional): Minimum f0, applied in soft way, must not\",\n \"the forward pointers, after revising our estimate of the signal energy. Relevant if\",\n \"features, which is the default. (default: False) Relevant if ``frames_per_chunk > 0``. recompute_frame\",\n \"used in Griffin-Lim, \\\" \\\"and will be removed in v0.9.0 release. To suppress\",\n \"If 'slaney', divide the triangular mel weights by the width of the mel\",\n \"def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float = 10 ** (-2), win_length:\",\n \"optional): Duration of a frame (Default: ``10 ** (-2)``). win_length (int, optional): The\",\n \"this is set to false, the incomplete frames near the ending edge won't\",\n \"int, win_length: int, ) -> Tensor: r\\\"\\\"\\\" Compute the spectral centroid for each\",\n \"freq, frames) where freq is ``n_fft // 2 + 1``. window (Tensor): Window\",\n \">>> freq, hop_length = 1025, 512 >>> # (channel, freq, time, complex=2) >>>\",\n \"else ``[time, channel]``. \\\"\\\"\\\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format,\",\n \"<NAME>, \\\"Signal estimation from modified short-time Fourier transform,\\\" IEEE Trans. ASSP, vol.32, no.2,\",\n \"length=length) # unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB(\",\n \"None and norm == \\\"slaney\\\": # Slaney-style mel is scaled to be approx\",\n \"0 to quantization_channels - 1. Args: x (Tensor): Input tensor quantization_channels (int): Number\",\n \"device=device, dtype=dtype) # Per batch example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >=\",\n \"power (float): Exponent for the magnitude spectrogram, (must be > 0) e.g., 1\",\n \"torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for\",\n \"window_end = max(t + 1, min_cmn_window) if window_end > num_frames: window_start -= (window_end\",\n \"= max(t + 1, min_cmn_window) if window_end > num_frames: window_start -= (window_end -\",\n \"f0, applied in soft way, must not exceed min-f0 (default: 10.0) penalty_factor (float,\",\n \"= lags + num_of_frames * frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0, p))\",\n \"spectrogram or a batch of spectrograms from a raw audio signal. The spectrogram\",\n \"torch.linspace(0, sample_rate // 2, n_freqs) # calculate mel freq bins m_min = _hz_to_mel(f_min,\",\n \"Real spectrograms (batch, channel, freq, time) mask_param (int): Number of columns to be\",\n \"(float): Frequencies in Hz mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``.\",\n \"win_length: int ) -> Tensor: r\\\"\\\"\\\" Apply median smoothing to the 1D tensor\",\n \"(default: 4000) delta_pitch( float, optional): Smallest relative change in pitch that our algorithm\",\n \"spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor, n_fft: int,\",\n \"mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor: r\\\"\\\"\\\"\",\n \") # unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /=\",\n \"(bool): Whether to normalize by magnitude after stft. n_iter (int): Number of iteration\",\n \"griffinlim( specgram: Tensor, window: Tensor, n_fft: int, hop_length: int, win_length: int, power: float,\",\n \"and 1 and returns a signal encoded with values from 0 to quantization_channels\",\n \"1.3 # Speed up by 30% >>> phase_advance = torch.linspace( >>> 0, math.pi\",\n \"where time equals the ``length`` parameter if given. \\\"\\\"\\\" assert momentum < 1,\",\n \"Default: ``True`` Returns: Tensor: Dimension (..., freq, time), freq is ``n_fft // 2\",\n \"3 -> time) Returns: Tensor: Masked spectrograms of dimensions (batch, channel, freq, time)\",\n \"For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal\",\n \"+ ~mask * b[1] return values, indices def _find_max_per_frame( nccf: Tensor, sample_rate: int,\",\n \"is not None and norm != \\\"slaney\\\": raise ValueError(\\\"norm must be one of\",\n \"to Mels. Args: freqs (float): Frequencies in Hz mel_scale (str, optional): Scale to\",\n \"num_frames, num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype device = waveform.device last_window_start =\",\n \"the function will output features that correspond to what an online decoder would\",\n \"return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power: float = 1.0\",\n \"channels Returns: Tensor: Input after mu-law decoding \\\"\\\"\\\" mu = quantization_channels - 1.0\",\n \"= torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value) # Create broadcastable mask mask_start\",\n \"# size (n_mfcc, n_mels) if norm is None: dct *= 2.0 else: assert\",\n \"channel dimension and have the form `(batch, channel, freq, time)`. multiplier (float): Use\",\n \"apply masking on (2 -> frequency, 3 -> time) Returns: Tensor: Masked spectrograms\",\n \") -> Tensor: r\\\"\\\"\\\"Compute the angle of complex tensor input. Args: complex_tensor (Tensor):\",\n \"n_freqs) # calculate mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max,\",\n \"Tensor]: r\\\"\\\"\\\"Separate a complex-valued spectrogram with shape `(..., 2)` into its magnitude and\",\n \"specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor, win_length: int = 5, mode: str\",\n \"/ mu) * 2 - 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu))\",\n \"power/amplitude scale. ref (float): Reference which the output will be scaled by. power\",\n \"the features, which is the default. (default: False) Relevant if ``frames_per_chunk > 0``.\",\n \"time is the number of window hops (n_frame). \\\"\\\"\\\" if pad > 0:\",\n \"(-2)``). win_length (int, optional): The window length for median smoothing (in number of\",\n \"of frames) (Default: ``30``). freq_low (int, optional): Lowest frequency that can be detected\",\n \"list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices\",\n \"def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor:\",\n \"if given. \\\"\\\"\\\" assert momentum < 1, 'momentum={} > 1 can be unstable'.format(momentum)\",\n \"/ power) # randomly initialize the phase batch, freq, frames = specgram.size() if\",\n \"2 else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3,\",\n \"device=device) for t in range(num_frames): window_start = 0 window_end = 0 if center:\",\n \"A pitch extraction algorithm tuned for automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>,\",\n \"= math.log(6.4) / 27.0 log_t = (mels >= min_log_mel) freqs[log_t] = min_log_hz *\",\n \"torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) )\",\n \"0.99 ) -> Tuple[Tensor, Tensor]: \\\"\\\"\\\" Take value from first if bigger than\",\n \"\\\"phase_vocoder\\\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \\\"spectral_centroid\\\", \\\"apply_codec\\\", ] def spectrogram( waveform: Tensor, pad: int,\",\n \"(default: 10.0) min_f0 (float, optional): Minimum F0 to search for (Hz) (default: 50.0)\",\n \"= None, encoding: Optional[str] = None, bits_per_sample: Optional[int] = None, ) -> Tensor:\",\n \"variance -= ((cur_sum ** 2) / (window_frames ** 2)) variance = torch.pow(variance, -0.5)\",\n \"TODO add \\\"with torch.no_grad():\\\" back when JIT supports it waveform = torch.nn.functional.pad(waveform, (pad,\",\n \"must be one of None or 'slaney'\\\") # freq bins # Equivalent filterbank\",\n \"in milliseconds. (default: 10.0) min_f0 (float, optional): Minimum F0 to search for (Hz)\",\n \"``[channel, time]``. Otherwise, they have dimension ``[time, channel]``. compression (float): Used for formats\",\n \"(Default: `1.0`). Returns: Tensor: Power of the normed input tensor. Shape of `(...,\",\n \"= specgram.pow(1 / power) # randomly initialize the phase batch, freq, frames =\",\n \"latency that we allow pitch tracking to introduce into the feature processing (affects\",\n \"= cur_sumsq variance = variance / window_frames variance -= ((cur_sum ** 2) /\",\n \"mels def _mel_to_hz(mels: Tensor, mel_scale: str = \\\"htk\\\") -> Tensor: \\\"\\\"\\\"Convert mel bin\",\n \"norm: Optional[str] = None, mel_scale: str = \\\"htk\\\", ) -> Tensor: r\\\"\\\"\\\"Create a\",\n \"None or 'slaney'\\\") # freq bins # Equivalent filterbank construction by Librosa all_freqs\",\n \"(Default: `1.0`) Returns: (Tensor, Tensor): The magnitude and phase of the complex tensor\",\n \"device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1, :]) #\",\n \"`(..., complex=2)` power (float): Power of the norm. (Default: `1.0`) Returns: (Tensor, Tensor):\",\n \"from ``uniform(0, max_v - v)``. Args: specgrams (Tensor): Real spectrograms (batch, channel, freq,\",\n \") -> torch.Tensor: \\\"\\\"\\\"Extract pitch based on method described in [1]. This function\",\n \"if power is not None: if power == 1.0: return spec_f.abs() return spec_f.abs().pow(power)\",\n \"optional): The number of frames used for energy normalization. (default: 0) simulate_first_pass_online (bool,\",\n \"Input should take the form `(..., freq, time)`. Batched inputs should include a\",\n \"weighted by their magnitude. Args: waveform (Tensor): Tensor of audio of dimension (...,\",\n \"torchaudio._internal import module_utils as _mod_utils import torchaudio __all__ = [ \\\"spectrogram\\\", \\\"griffinlim\\\", \\\"amplitude_to_DB\\\",\",\n \"x_mu: Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Decode mu-law encoded signal. For more\",\n \"specgram: Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor: r\\\"\\\"\\\" Apply\",\n \"transformation matrix, to be right-multiplied to row-wise data of size (``n_mels``, ``n_mfcc``). \\\"\\\"\\\"\",\n \"the deltas at time :math:`t`, :math:`c_t` is the spectrogram coeffcients at time :math:`t`,\",\n \"shape = specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert win_length >= 3 n\",\n \"= torch.nn.functional.pad( indices, (pad_length, 0), mode=\\\"constant\\\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length *\",\n \"upsampling NCCF. (default: 5) max_frames_latency (int, optional): Maximum number of frames of latency\",\n \"win_length >= 3 n = (win_length - 1) // 2 # twice sum\",\n \"torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) * (n + 0.5) * k) #\",\n \"= waveform[:, last_window_end, :] cur_sum += frame_to_add if norm_vars: cur_sumsq += (frame_to_add **\",\n \"else: assert norm == \\\"ortho\\\" dct[0] *= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0\",\n \"tensor, and so may return different values for an audio clip split into\",\n \"frame/window n_fft (int): Size of FFT hop_length (int): Length of hop between STFT\",\n \"# unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt()\",\n \"Returns: Tensor: Power of the normed input tensor. Shape of `(..., )` \\\"\\\"\\\"\",\n \"dimension (..., freq, time) win_length (int, optional): The window length used for computing\",\n \"= False, norm_vars: bool = False, ) -> Tensor: r\\\"\\\"\\\" Apply sliding-window cepstral\",\n \"if not center: if window_end > t: window_end = max(t + 1, min_cmn_window)\",\n \"smoothing to the 1D tensor over the given window. \\\"\\\"\\\" # Centered windowed\",\n \"\\\" \\\"and will be removed in v0.9.0 release. To suppress this warning, \\\"\",\n \"DB_to_amplitude( x: Tensor, ref: float, power: float ) -> Tensor: r\\\"\\\"\\\"Turn a tensor\",\n \"will be removed in v0.9.0 release. To suppress this warning, \\\" \\\"please use\",\n \"num_feats)) if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform:\",\n \"10.0, penalty_factor: float = 0.1, lowpass_cutoff: float = 1000, resample_frequency: float = 4000,\",\n \"average of the frequency values, weighted by their magnitude. Args: waveform (Tensor): Tensor\",\n \"\\\\frac{\\\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\\\phi_i(m)` is the NCCF at frame\",\n \"feature processing (affects output only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0)\",\n \"F0 to search for (Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum f0, applied\",\n \"controls whether to return half of results to avoid redundancy. Default: ``True`` Returns:\",\n \"(c_{t+n} - c_{t-n})}{2 \\\\sum_{n=1}^{\\\\text{N}} n^2} where :math:`d_t` is the deltas at time :math:`t`,\",\n \"-1) return nccf def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float\",\n \"= specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float,\",\n \"Tensor: r\\\"\\\"\\\"Turn a tensor from the decibel scale to the power/amplitude scale. Args:\",\n \"(..., time) \\\"\\\"\\\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False)\",\n \"spectral centroid for each channel along the time axis. The spectral centroid is\",\n \"Highest frequency that can be detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor of\",\n \"complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins, freq, 2) complex_specgrams_0 =\",\n \"30, freq_low: int = 85, freq_high: int = 3400, ) -> Tensor: r\\\"\\\"\\\"Detect\",\n \"frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk,\",\n \"converge. length (int or None): Array length of the expected output. rand_init (bool):\",\n \"= torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 - angle_0 - phase_advance phase =\",\n \"0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Decode\",\n \"value of that tensor, and so may return different values for an audio\",\n \"mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) #\",\n \"waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p = lags + num_of_frames * frame_size\",\n \"length used for computing delta (Default: ``5``) mode (str, optional): Mode parameter passed\",\n \"shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1, 1)) #\",\n \"/ 1.3) torch.Size([2, 1025, 231, 2]) \\\"\\\"\\\" # pack batch shape = complex_specgrams.size()\",\n \"def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int ) -> Tensor: r\\\"\\\"\\\" For\",\n \"Dimension of (freq, 1) Returns: Tensor: Complex Specgrams Stretch with dimension of `(...,\",\n \"of deltas of dimension (..., freq, time) Example >>> specgram = torch.randn(1, 40,\",\n \"True, pad_mode: str = \\\"reflect\\\", onesided: bool = True ) -> Tensor: r\\\"\\\"\\\"Create\",\n \"= x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x))\",\n \"\\\"At least one mel filterbank has all zero values. \\\" f\\\"The value for\",\n \"length: Optional[int], rand_init: bool ) -> Tensor: r\\\"\\\"\\\"Compute waveform from a linear scale\",\n \"- all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) # create overlapping triangles zero =\",\n \"Returns: Tensor: Tensor of freq of dimension (..., frame) \\\"\\\"\\\" # pack batch\",\n \"else: if window_start > last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum -= frame_to_remove\",\n \"If 0.5, will compute DB to amplitude. Returns: Tensor: Output tensor in power/amplitude\",\n \"as the weighted average of the frequency values, weighted by their magnitude. Args:\",\n \"indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length) # Convert indices to\",\n \"channels_first (bool): When True, both the input and output Tensor have dimension ``[channel,\",\n \"* (mels[log_t] - min_log_mel)) return freqs def create_fb_matrix( n_freqs: int, f_min: float, f_max:\",\n \"lowpass_filter_width: int = 1, upsample_filter_width: int = 5, max_frames_latency: int = 0, frames_per_chunk:\",\n \"warnings.warn( \\\"At least one mel filterbank has all zero values. \\\" f\\\"The value\",\n \":math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio of dimension (..., freq,\",\n \"use (either 'ortho' or None) Returns: Tensor: The transformation matrix, to be right-multiplied\",\n \"of \\\"htk\\\" or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 700.0 * (10.0**(mels /\",\n \"audio of dimension (..., freq, time) win_length (int, optional): The window length used\",\n \"kernel = torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output =\",\n \"- 1 and returns a signal scaled between -1 and 1. Args: x_mu\",\n \"waveform, :math:`N` is the length of a frame, :math:`b_i` is the beginning of\",\n \"Smallest relative change in pitch that our algorithm measures. (default: 0.005) nccf_ballast (float,\",\n \"complex_specgrams = torch.randn(2, freq, 300, 2) >>> rate = 1.3 # Speed up\",\n \"bool = False, ) -> Tensor: r\\\"\\\"\\\" Apply sliding-window cepstral mean (and optionally\",\n \"each stft freq point in hertz f_diff = f_pts[1:] - f_pts[:-1] # (n_mels\",\n \"(..., frame) \\\"\\\"\\\" input_shape = waveform.shape num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1,\",\n \"tensor in decibel scale \\\"\\\"\\\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -=\",\n \"x (Tensor): Input tensor before being converted to power/amplitude scale. ref (float): Reference\",\n \"to avoid redundancy. Default: ``True`` Returns: Tensor: Dimension (..., freq, time), freq is\",\n \"*= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \\\"At least one mel filterbank has\",\n \"frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag =\",\n \"a batch of spectrograms from a raw audio signal. The spectrogram can be\",\n \"torch.cos(math.pi / float(n_mels) * (n + 0.5) * k) # size (n_mfcc, n_mels)\",\n \"logstep = math.log(6.4) / 27.0 log_t = (mels >= min_log_mel) freqs[log_t] = min_log_hz\",\n \"indices += 1 return indices def _median_smoothing( indices: Tensor, win_length: int ) ->\",\n \"method described in [1]. This function computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi.\",\n \"x the number of filterbanks. Each column is a filterbank so that assuming\",\n \"augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\\\"rate\\\", f\\\"{sample_rate}\\\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def\",\n \"Window tensor that is applied/multiplied to each frame/window n_fft (int): Size of FFT,\",\n \"None, ) -> Tensor: r\\\"\\\"\\\" Apply codecs as a form of augmentation. Args:\",\n \"mask * a[1] + ~mask * b[1] return values, indices def _find_max_per_frame( nccf:\",\n \"str = \\\"reflect\\\", onesided: bool = True ) -> Tensor: r\\\"\\\"\\\"Create a spectrogram\",\n \"of Fourier bins, and time is the number of window hops (n_frame). \\\"\\\"\\\"\",\n \"when JIT supports it waveform = torch.nn.functional.pad(waveform, (pad, pad), \\\"constant\\\") # pack batch\",\n \"1 can lead to faster convergence, but above 1 may not converge. length\",\n \"filterbanks sample_rate (int): Sample rate of the audio waveform norm (Optional[str]): If 'slaney',\",\n \"lowpass_cutoff: float = 1000, resample_frequency: float = 4000, delta_pitch: float = 0.005, nccf_ballast:\",\n \"float, db_multiplier: float, top_db: Optional[float] = None ) -> Tensor: r\\\"\\\"\\\"Turn a spectrogram\",\n \"and norm == \\\"slaney\\\": # Slaney-style mel is scaled to be approx constant\",\n \"* mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int )\",\n \"indices to frequency EPSILON = 10 ** (-9) freq = sample_rate / (EPSILON\",\n \"with shape (``n_mels``, ``n_mfcc``), normalized depending on norm. Args: n_mfcc (int): Number of\",\n \"or None): Array length of the expected output. rand_init (bool): Initializes phase randomly\",\n \"Mask will be applied from indices ``[v_0, v_0 + v)``, where ``v`` is\",\n \"2 window_end = window_start + cmn_window else: window_start = t - cmn_window window_end\",\n \"waveform[:, last_window_start, :] cur_sum -= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove ** 2)\",\n \"not center: if window_end > t: window_end = max(t + 1, min_cmn_window) if\",\n \"window is to the left. (bool, default = false) norm_vars (bool, optional): If\",\n \"// 2 + 1``. window (Tensor): Window tensor that is applied/multiplied to each\",\n \"penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, )\",\n \"'mask_along_axis_iid', 'sliding_window_cmn', \\\"spectral_centroid\\\", \\\"apply_codec\\\", ] def spectrogram( waveform: Tensor, pad: int, window: Tensor,\",\n \"to normalize by magnitude after stft center (bool, optional): whether to pad :attr:`waveform`\",\n \"2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox()\",\n \"min_log_mel = (min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0 if\",\n \"of filterbanks. Each column is a filterbank so that assuming there is a\",\n \"each tensor in a batch depends on the maximum value of that tensor,\",\n \"x = ((x_mu) / mu) * 2 - 1.0 x = torch.sign(x) *\",\n \"`(..., )` \\\"\\\"\\\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power:\",\n \"zero otherwise. Returns: torch.Tensor: waveform of (..., time), where time equals the ``length``\",\n \"(Default: ``None``) mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``)\",\n \"(must be > 0) e.g., 1 for energy, 2 for power, etc. normalized\",\n \"mel filterbanks norm (str or None): Norm to use (either 'ortho' or None)\",\n \"stft center (bool, optional): whether to pad :attr:`waveform` on both sides so that\",\n \"pitch tracking to introduce into the feature processing (affects output only if ``frames_per_chunk\",\n \"pp. 18-25. 2015. * [2] <NAME>., <NAME>., & <NAME>. \\\"A fast Griffin-Lim algorithm,\\\"\",\n \"tensor from the decibel scale to the power/amplitude scale. Args: x (Tensor): Input\",\n \"Hz mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns:\",\n \":-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag = alphas * norm_1 + (1\",\n \"if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1, :] else: if window_start\",\n \"win_length (int): Window size Returns: Tensor: Dimension (..., time) \\\"\\\"\\\" specgram = spectrogram(waveform,\",\n \"decoding -- not the final version of the features, which is the default.\",\n \"frames) (Default: ``30``). freq_low (int, optional): Lowest frequency that can be detected (Hz)\",\n \"\\\\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate to\",\n \"is taken. \\\"\\\"\\\" lag_min = int(math.ceil(sample_rate / freq_high)) # Find near enough max\",\n \"num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype device = waveform.device last_window_start = last_window_end\",\n \"in decibels. A reasonable number is 80. (Default: ``None``) Returns: Tensor: Output tensor\",\n \"(int, optional): Changes the bit depth for the supported formats. For more details\",\n \"float = 1000, resample_frequency: float = 4000, delta_pitch: float = 0.005, nccf_ballast: float\",\n \"float(n_mels) * (n + 0.5) * k) # size (n_mfcc, n_mels) if norm\",\n \"triangular mel weights by the width of the mel band (area normalization). (Default:\",\n \"alphas * norm_1 + (1 - alphas) * norm_0 real_stretch = mag *\",\n \"for (Hz) (default: 50.0) max_f0 (float, optional): Maximum F0 to search for (Hz)\",\n \"returns a signal encoded with values from 0 to quantization_channels - 1. Args:\",\n \"Args: specgram (Tensor): Tensor of audio of dimension (..., freq, time) win_length (int,\",\n \"2]) # (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps\",\n \"ValueError(\\\"norm must be one of None or 'slaney'\\\") # freq bins # Equivalent\",\n \"torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast,\",\n \"sample_rate: int, freq_high: int ) -> Tensor: r\\\"\\\"\\\" For each frame, take the\",\n \"(1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates waveform\",\n \"min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs def create_fb_matrix( n_freqs: int,\",\n \"return specgram def compute_deltas( specgram: Tensor, win_length: int = 5, mode: str =\",\n \"Whether to normalize by magnitude after stft. n_iter (int): Number of iteration for\",\n \"to faster convergence, but above 1 may not converge. length (int or None):\",\n \"of the expected output. rand_init (bool): Initializes phase randomly if True, to zero\",\n \"types of features give the same number of frames. (default: True) Returns: Tensor:\",\n \"Axis to apply masking on (1 -> frequency, 2 -> time) Returns: Tensor:\",\n \"r\\\"\\\"\\\"Given a STFT tensor, speed up in time without modifying pitch by a\",\n \"Tensor, ref: float, power: float ) -> Tensor: r\\\"\\\"\\\"Turn a tensor from the\",\n \"zero = torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2]) / f_diff[:-1] # (n_freqs,\",\n \"Args: mels (Tensor): Mel frequencies mel_scale (str, optional): Scale to use: ``htk`` or\",\n \"return values, indices def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int ) ->\",\n \"of frames used for energy normalization. (default: 0) simulate_first_pass_online (bool, optional): If true,\",\n \"of the forward pointers, after revising our estimate of the signal energy. Relevant\",\n \"before being converted to decibel scale. Input should take the form `(..., freq,\",\n \"the feature processing (affects output only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default:\",\n \"`n_mels` ({n_mels}) may be set too high. \\\" f\\\"Or, the value for `n_freqs`\",\n \"``n_fft // 2 + 1`` and ``n_fft`` is the number of Fourier bins,\",\n \"the linear scale f_min = 0.0 f_sp = 200.0 / 3 freqs =\",\n \"specgrams.size(axis), device=device, dtype=dtype) # Per batch example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask\",\n \"variance = variance / window_frames variance -= ((cur_sum ** 2) / (window_frames **\",\n \"from Kaldi. Args: waveform (Tensor): The input waveform of shape `(..., time)`. sample_rate\",\n \"= torch.tensor(0.) for _ in range(n_iter): # Store the previous iterate tprev =\",\n \"\\\"\\\"\\\" # Centered windowed pad_length = (win_length - 1) // 2 # \\\"replicate\\\"\",\n \"and <NAME> 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),\",\n \"spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True,\",\n \"be scaled by. power (float): If power equals 1, will compute DB to\",\n \"best = _combine_max(half, best) indices = best[1] # Add back minimal lag indices\",\n \"frequency, 3 -> time) Returns: Tensor: Masked spectrograms of dimensions (batch, channel, freq,\",\n \"Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Decode mu-law encoded signal. For more info\",\n \"1)) # Repack batch x_db = x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor,\",\n \"w(m+n)}{\\\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\\\phi_i(m)` is the NCCF at frame :math:`i` with lag :math:`m`,\",\n \"frame, :math:`b_i` is the beginning of frame :math:`i`, :math:`E(j)` is the energy :math:`\\\\sum_{n=j}^{j+N-1}\",\n \"= waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype device = waveform.device\",\n \"of hop between STFT windows. ( Default: ``win_length // 2``) win_length (int): Window\",\n \"optional): If true, normalize variance to one. (bool, default = false) Returns: Tensor:\",\n \"complex=2)` rate (float): Speed-up factor phase_advance (Tensor): Expected phase advance in each bin.\",\n \"< mask_param if axis == 1: specgram[:, mask_start:mask_end] = mask_value elif axis ==\",\n \"complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 =\",\n \":math:`\\\\sum_{n=j}^{j+N-1} w^2(n)`. \\\"\\\"\\\" EPSILON = 10 ** (-9) # Number of lags to\",\n \"10.0) min_f0 (float, optional): Minimum F0 to search for (Hz) (default: 50.0) max_f0\",\n \"// 2 + 1`` bins hop_length (int): Length of hop between STFT windows.\",\n \"and ``n_fft`` is the number of Fourier bins, and time is the number\",\n \"to Audio and Acoustics (pp. 1-4), Oct. 2013. * [3] <NAME> and <NAME>,\",\n \"(..., freq, time) cmn_window (int, optional): Window in frames for running average CMN\",\n \"Tensor: Output tensor in power/amplitude scale. \\\"\\\"\\\" return ref * torch.pow(torch.pow(10.0, 0.1 *\",\n \"= 3400, ) -> Tensor: r\\\"\\\"\\\"Detect pitch frequency. It is implemented using normalized\",\n \"(int): Axis to apply masking on (1 -> frequency, 2 -> time) Returns:\",\n \"// 2 half = torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best) indices =\",\n \"(bool): When True, both the input and output Tensor have dimension ``[channel, time]``.\",\n \"+ value)[..., None, None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch\",\n \"\\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 700.0 * (10.0**(mels / 2595.0) - 1.0)\",\n \"axis != 3: raise ValueError('Only Frequency and Time masking are supported') device =\",\n \"power == 1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor,\",\n \"to x the number of filterbanks. Each column is a filterbank so that\",\n \"smoothing, and convert to frequency. Note: If the max among all the lags\",\n \"will be uniformly sampled from [0, mask_param] mask_value (float): Value to assign to\",\n \"waveform[:, last_window_end, :] cur_sum += frame_to_add if norm_vars: cur_sumsq += (frame_to_add ** 2)\",\n \"return_complex=True, ) ) # Update our phase estimates angles = rebuilt if momentum:\",\n \"frame_time: float, freq_low: int ) -> Tensor: r\\\"\\\"\\\" Compute Normalized Cross-Correlation Function (NCCF).\",\n \"# default values are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length,\",\n \"optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter\",\n \"a form of augmentation. Args: waveform (Tensor): Audio data. Must be 2 dimensional.\",\n \"randomly initialize the phase batch, freq, frames = specgram.size() if rand_init: angles =\",\n \"Two sided padding of signal window (Tensor): Window tensor that is applied/multiplied to\",\n \"\\\" f\\\"Or, the value for `n_freqs` ({n_freqs}) may be set too low.\\\" )\",\n \"scaled by. power (float): If power equals 1, will compute DB to power.\",\n \"complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float,\",\n \"Length of hop between STFT windows. ( Default: ``win_length // 2``) win_length (int):\",\n \"multiplier * db_multiplier if top_db is not None: # Expand batch shape =\",\n \"float = 1.0 ) -> Tuple[Tensor, Tensor]: r\\\"\\\"\\\"Separate a complex-valued spectrogram with shape\",\n \"last_window_start, :] cur_sum -= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove ** 2) if\",\n \"frame_shift (float, optional): Frame shift in milliseconds. (default: 10.0) min_f0 (float, optional): Minimum\",\n \"`Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values between 0 and quantization_channels\",\n \"Expected phase advance in each bin. Dimension of (freq, 1) Returns: Tensor: Complex\",\n \"Repack batch x_db = x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor, ref: float,\",\n \"amin (float): Number to clamp ``x`` db_multiplier (float): Log10(max(reference value and amin)) top_db\",\n \"* (n + 1) * (2 * n + 1) / 3 specgram\",\n \"``True`` pad_mode (string, optional): controls the padding method used when :attr:`center` is ``True``.\",\n \"t, :] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance = cur_sumsq variance\",\n \"the highest value of NCCF, apply centered median smoothing, and convert to frequency.\",\n \"= specgram.reshape(1, -1, shape[-1]) assert win_length >= 3 n = (win_length - 1)\",\n \"Find near enough max that is smallest best = torch.max(nccf[..., lag_min:], -1) half_size\",\n \"optional): The window length used for computing delta (Default: ``5``) mode (str, optional):\",\n \"window_end = t + 1 if window_start < 0: window_end -= window_start window_start\",\n \"magnitude and phase. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float):\",\n \"= int(math.ceil(sample_rate / freq_high)) # Find near enough max that is smallest best\",\n \"bins, and time is the number of window hops (n_frame). \\\"\\\"\\\" if pad\",\n \"be > 0) e.g., 1 for energy, 2 for power, etc. If None,\",\n \"specgram = specgram.reshape(1, -1, shape[-1]) assert win_length >= 3 n = (win_length -\",\n \"angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates waveform = torch.istft(specgram *\",\n \"f_sp logstep = math.log(6.4) / 27.0 if freq >= min_log_hz: mels = min_log_mel\",\n \"r\\\"\\\"\\\" Apply a mask along ``axis``. Mask will be applied from indices ``[v_0,\",\n \"applicable if center == false, ignored if center==true (int, default = 100) center\",\n \"\\\"\\\"\\\"Extract pitch based on method described in [1]. This function computes the equivalent\",\n \"torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] +\",\n \"1 empirical calibration offset indices += 1 return indices def _median_smoothing( indices: Tensor,\",\n \"dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1)\",\n \"1 and returns a signal encoded with values from 0 to quantization_channels -\",\n \"(int, optional): The window length used for computing delta (Default: ``5``) mode (str,\",\n \"bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\\\"rate\\\", f\\\"{sample_rate}\\\"]], channels_first=channels_first, format=format) return\",\n \"Number of iteration for phase recovery process. momentum (float): The momentum parameter for\",\n \"release. To suppress this warning, \\\" \\\"please use `normalized=False`.\\\") # pack batch shape\",\n \"will be scaled by. power (float): If power equals 1, will compute DB\",\n \"\\\\phi_i(m) = \\\\frac{\\\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\\\phi_i(m)` is the NCCF\",\n \"= torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack batch output = output.reshape(shape) return\",\n \"(Hz) (Default: ``85``). freq_high (int, optional): Highest frequency that can be detected (Hz)\",\n \"float, top_db: Optional[float] = None ) -> Tensor: r\\\"\\\"\\\"Turn a spectrogram from the\",\n \"int, norm: Optional[str] ) -> Tensor: r\\\"\\\"\\\"Create a DCT transformation matrix with shape\",\n \"to introduce into the feature processing (affects output only if ``frames_per_chunk > 0``\",\n \"is None: dct *= 2.0 else: assert norm == \\\"ortho\\\" dct[0] *= 1.0\",\n \"defined as the weighted average of the frequency values, weighted by their magnitude.\",\n \"delta (Default: ``5``) mode (str, optional): Mode parameter passed to padding (Default: ``\\\"replicate\\\"``)\",\n \"be approx constant energy per channel enorm = 2.0 / (f_pts[2:n_mels + 2]\",\n \"upsample_filter_width: int = 5, max_frames_latency: int = 0, frames_per_chunk: int = 0, simulate_first_pass_online:\",\n \"_mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between each mel point and each stft\",\n \"= complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1\",\n \"(Default: ``10 ** (-2)``). win_length (int, optional): The window length for median smoothing\",\n \"low.\\\" ) return fb def create_dct( n_mfcc: int, n_mels: int, norm: Optional[str] )\",\n \"be snipped, so that the number of frames is the file size divided\",\n \"torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes\",\n \"spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False,\",\n \"* torch.log1p(mu)) - 1.0) / mu return x def complex_norm( complex_tensor: Tensor, power:\",\n \":math:`E(j)` is the energy :math:`\\\\sum_{n=j}^{j+N-1} w^2(n)`. \\\"\\\"\\\" EPSILON = 10 ** (-9) #\",\n \"<NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE International Conference on Acoustics, Speech\",\n \"specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate to 0 rebuilt = torch.tensor(0.) for\",\n \"# calculate the difference between each mel point and each stft freq point\",\n \") -> Tensor: r\\\"\\\"\\\"Given a STFT tensor, speed up in time without modifying\",\n \"of dimensions (batch, channel, freq, time) \\\"\\\"\\\" if axis != 2 and axis\",\n \"rand_init: bool ) -> Tensor: r\\\"\\\"\\\"Compute waveform from a linear scale magnitude spectrogram\",\n \"that tensor, and so may return different values for an audio clip split\",\n \"f_pts[:-1] # (n_mels + 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels\",\n \"should be one of \\\"htk\\\" or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 2595.0\",\n \"\\\"with torch.no_grad():\\\" back when JIT supports it waveform = torch.nn.functional.pad(waveform, (pad, pad), \\\"constant\\\")\",\n \"return values def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float = 10 **\",\n \"Optional[int], rand_init: bool ) -> Tensor: r\\\"\\\"\\\"Compute waveform from a linear scale magnitude\",\n \"waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor, multiplier: float, amin: float,\",\n \"= torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best) indices = best[1] # Add\",\n \"For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding for the\",\n \"if axis != 2 and axis != 3: raise ValueError('Only Frequency and Time\",\n \"frame_size, frame_size)[..., :num_of_frames, :] output_frames = ( (s1 * s2).sum(-1) / (EPSILON +\",\n \"angles = 2 * math.pi * torch.rand(batch, freq, frames) else: angles = torch.zeros(batch,\",\n \"None): Array length of the expected output. rand_init (bool): Initializes phase randomly if\",\n \"int, norm: Optional[str] = None, mel_scale: str = \\\"htk\\\", ) -> Tensor: r\\\"\\\"\\\"Create\",\n \"``n_mels``) meaning number of frequencies to highlight/apply to x the number of filterbanks.\",\n \"the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has been scaled to\",\n \"in milliseconds. (default: 25.0) frame_shift (float, optional): Frame shift in milliseconds. (default: 10.0)\",\n \"value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) *\",\n \"mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding for the supported\",\n \"``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels converted in Hz \\\"\\\"\\\" if mel_scale\",\n \"method used when :attr:`center` is ``True``. Default: ``\\\"reflect\\\"`` onesided (bool, optional): controls whether\",\n \"cmn_waveform[:, t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape)\",\n \"n^2} where :math:`d_t` is the deltas at time :math:`t`, :math:`c_t` is the spectrogram\",\n \"-> Tensor: r\\\"\\\"\\\"Turn a spectrogram from the power/amplitude scale to the decibel scale.\",\n \"\\\"htk\\\" or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 2595.0 * math.log10(1.0 + (freq\",\n \"\\\"\\\"\\\"Convert mel bin numbers to frequencies. Args: mels (Tensor): Mel frequencies mel_scale (str,\",\n \"phase + phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1)\",\n \"to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels converted in\",\n \"of mel filterbanks sample_rate (int): Sample rate of the audio waveform norm (Optional[str]):\",\n \"device=device, dtype=dtype) * (specgrams.size(axis) - value) # Create broadcastable mask mask_start = min_value[...,\",\n \"(in number of frames) (Default: ``30``). freq_low (int, optional): Lowest frequency that can\",\n \"of freq of dimension (..., frame) \\\"\\\"\\\" input_shape = waveform.shape num_frames, num_feats =\",\n \"int = 5, max_frames_latency: int = 0, frames_per_chunk: int = 0, simulate_first_pass_online: bool\",\n \"dtype = waveform.dtype device = waveform.device last_window_start = last_window_end = -1 cur_sum =\",\n \"torch.linspace(m_min, m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference\",\n \"divide the triangular mel weights by the width of the mel band (area\",\n \"``v_0`` from ``uniform(0, max_v - v)``. All examples will have the same mask\",\n \"Sample rate of `waveform`. frame_length (float, optional): Frame length in milliseconds. (default: 25.0)\",\n \"waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate,\",\n \"-= (window_end - num_frames) window_end = num_frames if window_start < 0: window_start =\",\n \"frame_to_add = waveform[:, last_window_end, :] cur_sum += frame_to_add if norm_vars: cur_sumsq += (frame_to_add\",\n \"int = 500, snip_edges: bool = True, ) -> torch.Tensor: \\\"\\\"\\\"Extract pitch based\",\n \"if window_start > last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum -= frame_to_remove if\",\n \"power equals 1, will compute DB to power. If 0.5, will compute DB\",\n \"# unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB( x:\",\n \"batch shape = specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert win_length >= 3\",\n \"meaning number of frequencies to highlight/apply to x the number of filterbanks. Each\",\n \"from first if bigger than a multiplicative factor of the second, elementwise. \\\"\\\"\\\"\",\n \"than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding\",\n \"is applied/multiplied to each frame/window n_fft (int): Size of FFT hop_length (int): Length\",\n \"that is applied/multiplied to each frame/window n_fft (int): Size of FFT, creates ``n_fft\",\n \"channels Returns: Tensor: Input after mu-law encoding \\\"\\\"\\\" mu = quantization_channels - 1.0\",\n \") -> Tuple[Tensor, Tensor]: r\\\"\\\"\\\"Separate a complex-valued spectrogram with shape `(..., 2)` into\",\n \"# Speed up by 30% >>> phase_advance = torch.linspace( >>> 0, math.pi *\",\n \"Audio data. Must be 2 dimensional. See also ```channels_first```. sample_rate (int): Sample rate\",\n \"to quantization_channels - 1. Args: x (Tensor): Input tensor quantization_channels (int): Number of\",\n \"& <NAME>. \\\"A fast Griffin-Lim algorithm,\\\" IEEE Workshop on Applications of Signal Processing\",\n \"= 400, soft_min_f0: float = 10.0, penalty_factor: float = 0.1, lowpass_cutoff: float =\",\n \"computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The input waveform\",\n \"where ``v`` is sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v -\",\n \"= torch.nn.functional.pad(waveform, (pad, pad), \\\"constant\\\") # pack batch shape = waveform.size() waveform =\",\n \"700.0)) # Fill in the linear part f_min = 0.0 f_sp = 200.0\",\n \"None and norm != \\\"slaney\\\": raise ValueError(\\\"norm must be one of None or\",\n \"norm. (Default: `1.0`). Returns: Tensor: Power of the normed input tensor. Shape of\",\n \"(float): Number to clamp ``x`` db_multiplier (float): Log10(max(reference value and amin)) top_db (float\",\n \"masking on (1 -> frequency, 2 -> time) Returns: Tensor: Masked spectrogram of\",\n \"Add back minimal lag indices += lag_min # Add 1 empirical calibration offset\",\n \"Convert indices to frequency EPSILON = 10 ** (-9) freq = sample_rate /\",\n \"normalized (bool): Whether to normalize by magnitude after stft center (bool, optional): whether\",\n \"last_window_start = last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq =\",\n \"sample rate of the waveform (Hz) frame_time (float, optional): Duration of a frame\",\n \"method. Values near 1 can lead to faster convergence, but above 1 may\",\n \"waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p = lags + num_of_frames\",\n \"\\\"\\\"\\\" input_shape = waveform.shape num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats)\",\n \"``channels_first=True``, it has ``[channel, time]`` else ``[time, channel]``. \\\"\\\"\\\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes,\",\n \"norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch =\",\n \"the ending edge won't be snipped, so that the number of frames is\",\n \"(int): Number of columns to be masked will be uniformly sampled from [0,\",\n \"= 1025, 512 >>> # (channel, freq, time, complex=2) >>> complex_specgrams = torch.randn(2,\",\n \"return dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Encode signal\",\n \"start). Only applicable if center == false, ignored if center==true (int, default =\",\n \"Tensor shape of `(..., complex=2)` Return: Tensor: Angle of a complex tensor. Shape\",\n \"Griffin-Lim. Setting this to 0 recovers the original Griffin-Lim method. Values near 1\",\n \"and 20. for amplitude amin (float): Number to clamp ``x`` db_multiplier (float): Log10(max(reference\",\n \"> last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum -= frame_to_remove if norm_vars: cur_sumsq\",\n \"freq is ``n_fft // 2 + 1`` and ``n_fft`` is the number of\",\n \"x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) -\",\n \"math.log(6.4) / 27.0 log_t = (mels >= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep\",\n \"0]) def magphase( complex_tensor: Tensor, power: float = 1.0 ) -> Tuple[Tensor, Tensor]:\",\n \"ValueError('Only Frequency and Time masking are supported') device = specgrams.device dtype = specgrams.dtype\",\n \"To suppress this warning, \\\" \\\"please use `normalized=False`.\\\") # pack batch shape =\",\n \"window_end > num_frames: window_start -= (window_end - num_frames) window_end = num_frames if window_start\",\n \"- c_{t-n})}{2 \\\\sum_{n=1}^{\\\\text{N}} n^2} where :math:`d_t` is the deltas at time :math:`t`, :math:`c_t`\",\n \"0.).any(): warnings.warn( \\\"At least one mel filterbank has all zero values. \\\" f\\\"The\",\n \"of dimension (..., frame) \\\"\\\"\\\" # pack batch shape = list(waveform.size()) waveform =\",\n \"mask * a[0] + ~mask * b[0] indices = mask * a[1] +\",\n \"(int, optional): Integer that determines filter width when upsampling NCCF. (default: 5) max_frames_latency\",\n \"= 0.0 f_sp = 200.0 / 3 mels = (freq - f_min) /\",\n \"in each bin. Dimension of (freq, 1) Returns: Tensor: Complex Specgrams Stretch with\",\n \"0.0 f_sp = 200.0 / 3 mels = (freq - f_min) / f_sp\",\n \"Slaney-style mel is scaled to be approx constant energy per channel enorm =\",\n \"1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor,\",\n \"s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames = ( (s1 *\",\n \"format. channels_first (bool): When True, both the input and output Tensor have dimension\",\n \"+ value.long()).squeeze() assert mask_end - mask_start < mask_param if axis == 1: specgram[:,\",\n \"Tensor: r\\\"\\\"\\\" For each frame, take the highest value of NCCF, apply centered\",\n \"pointers, after revising our estimate of the signal energy. Relevant if ``frames_per_chunk >\",\n \"coding: utf-8 -*- import io import math import warnings from typing import Optional,\",\n \"# Fill in the linear scale f_min = 0.0 f_sp = 200.0 /\",\n \"near 1 can lead to faster convergence, but above 1 may not converge.\",\n \"amin: float, db_multiplier: float, top_db: Optional[float] = None ) -> Tensor: r\\\"\\\"\\\"Turn a\",\n \"m_pts = torch.linspace(m_min, m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate\",\n \"cur_sum += frame_to_add if norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames = window_end\",\n \"Frequency and Time masking are supported') device = specgrams.device dtype = specgrams.dtype value\",\n \"< mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram: Tensor,\",\n \"rate (float): Speed-up factor phase_advance (Tensor): Expected phase advance in each bin. Dimension\",\n \"= 10 ** (-9) # Number of lags to check lags = int(math.ceil(sample_rate\",\n \"logstep = math.log(6.4) / 27.0 if freq >= min_log_hz: mels = min_log_mel +\",\n \"Audio and Acoustics (pp. 1-4), Oct. 2013. * [3] <NAME> and <NAME>, \\\"Signal\",\n \"= 0, simulate_first_pass_online: bool = False, recompute_frame: int = 500, snip_edges: bool =\",\n \"waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag = [] for\",\n \"of each tensor in a batch depends on the maximum value of that\",\n \"600) min_cmn_window (int, optional): Minimum CMN window used at start of decoding (adds\",\n \"complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor ) -> Tensor: r\\\"\\\"\\\"Compute the angle\",\n \"window used at start of decoding (adds latency only at start). Only applicable\",\n \"convergence, but above 1 may not converge. length (int or None): Array length\",\n \"rebuilt = torch.tensor(0.) for _ in range(n_iter): # Store the previous iterate tprev\",\n \"0) e.g., 1 for energy, 2 for power, etc. normalized (bool): Whether to\",\n \"Return the final phase estimates waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length,\",\n \"return different values for an audio clip split into snippets vs. a full\",\n \"lowpass_cutoff (float, optional): Cutoff frequency for LowPass filter (Hz) (default: 1000) resample_frequency (float,\",\n \"filter, more gives sharper filter. (default: 1) upsample_filter_width (int, optional): Integer that determines\",\n \"= specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor, win_length: int =\",\n \"1.0 ) -> Tuple[Tensor, Tensor]: r\\\"\\\"\\\"Separate a complex-valued spectrogram with shape `(..., 2)`\",\n \"Sample rate of the audio waveform norm (Optional[str]): If 'slaney', divide the triangular\",\n \"on the maximum value of that tensor, and so may return different values\",\n \"function and median smoothing. Args: waveform (Tensor): Tensor of audio of dimension (...,\",\n \"to frequency. Note: If the max among all the lags is very close\",\n \"mask_value elif axis == 2: specgram[:, :, mask_start:mask_end] = mask_value else: raise ValueError('Only\",\n \"spectral_centroid( waveform: Tensor, sample_rate: int, pad: int, window: Tensor, n_fft: int, hop_length: int,\",\n \"our phase estimates angles = rebuilt if momentum: angles = angles - tprev.mul_(momentum\",\n \"http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) *\",\n \"to 0 rebuilt = torch.tensor(0.) for _ in range(n_iter): # Store the previous\",\n \"def spectrogram( waveform: Tensor, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length:\",\n \"(Tensor): Window tensor that is applied/multiplied to each frame/window n_fft (int): Size of\",\n \"in [1]. This function computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform\",\n \"= (win_length - 1) // 2 # \\\"replicate\\\" padding in any dimension indices\",\n \"frame_length: float = 25.0, frame_shift: float = 10.0, min_f0: float = 50, max_f0:\",\n \"freq_high (int, optional): Highest frequency that can be detected (Hz) (Default: ``3400``). Returns:\",\n \"= 1000, resample_frequency: float = 4000, delta_pitch: float = 0.005, nccf_ballast: float =\",\n \"freq_high)) # Find near enough max that is smallest best = torch.max(nccf[..., lag_min:],\",\n \"value = torch.rand(1) * mask_param min_value = torch.rand(1) * (specgram.size(axis) - value) mask_start\",\n \"= torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu + 1)\",\n \"mel is scaled to be approx constant energy per channel enorm = 2.0\",\n \"def _mel_to_hz(mels: Tensor, mel_scale: str = \\\"htk\\\") -> Tensor: \\\"\\\"\\\"Convert mel bin numbers\",\n \"# Compute lags output_lag = [] for lag in range(1, lags + 1):\",\n \"calculate mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts\",\n \"-> torch.Tensor: \\\"\\\"\\\"Extract pitch based on method described in [1]. This function computes\",\n \"(bool, optional): If true, normalize variance to one. (bool, default = false) Returns:\",\n \"frames near the ending edge won't be snipped, so that the number of\",\n \"have the form `(batch, channel, freq, time)`. multiplier (float): Use 10. for power\",\n \"dim=-1) phase_acc = torch.cumsum(phase, -1) mag = alphas * norm_1 + (1 -\",\n \"+ n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim)\",\n \"shape of `(..., complex=2)` Return: Tensor: Angle of a complex tensor. Shape of\",\n \"range(n_iter): # Store the previous iterate tprev = rebuilt # Invert with our\",\n \"Value to assign to the masked columns axis (int): Axis to apply masking\",\n \"t - cmn_window // 2 window_end = window_start + cmn_window else: window_start =\",\n \"10.0, min_f0: float = 50, max_f0: float = 400, soft_min_f0: float = 10.0,\",\n \") -> Tensor: r\\\"\\\"\\\" Compute the spectral centroid for each channel along the\",\n \"should be one of \\\"htk\\\" or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 700.0\",\n \"(Tensor): Real spectrograms (batch, channel, freq, time) mask_param (int): Number of columns to\",\n \"(Hz) frame_time (float, optional): Duration of a frame (Default: ``10 ** (-2)``). win_length\",\n \"1-4), Oct. 2013. * [3] <NAME> and <NAME>, \\\"Signal estimation from modified short-time\",\n \"= x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1,\",\n \"values, weighted by their magnitude. Args: waveform (Tensor): Tensor of audio of dimension\",\n \"1) / 2 * mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor,\",\n \"of latency that we allow pitch tracking to introduce into the feature processing\",\n \"* mels # And now the nonlinear scale min_log_hz = 1000.0 min_log_mel =\",\n \"* torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs def create_fb_matrix( n_freqs: int, f_min:\",\n \"(and optionally variance) normalization per utterance. Args: waveform (Tensor): Tensor of audio of\",\n \"= torch.rand(1) * (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() +\",\n \"torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for t in range(num_frames): window_start = 0\",\n \"= waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0,\",\n \"({n_freqs}) may be set too low.\\\" ) return fb def create_dct( n_mfcc: int,\",\n \"0, 2]) # (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2,\",\n \"mask_value: float, axis: int ) -> Tensor: r\\\"\\\"\\\" Apply a mask along ``axis``.\",\n \"float, axis: int ) -> Tensor: r\\\"\\\"\\\" Apply a mask along ``axis``. Mask\",\n \"edge won't be snipped, so that the number of frames is the file\",\n \"last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum += frame_to_add if norm_vars: cur_sumsq +=\",\n \"spectrogram of dimension (..., freq, frames) where freq is ``n_fft // 2 +\",\n \"(window_end - num_frames) window_end = num_frames if window_start < 0: window_start = 0\",\n \"+ spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if power is not None: if\",\n \"may be set too low.\\\" ) return fb def create_dct( n_mfcc: int, n_mels:\",\n \"import math import warnings from typing import Optional, Tuple import torch from torch\",\n \"NCCF for quiet frames (default: 7000) lowpass_filter_width (int, optional): Integer that determines filter\",\n \"to decibel scale. Input should take the form `(..., freq, time)`. Batched inputs\",\n \"batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2),\",\n \"= 0 if not center: if window_end > t: window_end = max(t +\",\n \"waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width,\",\n \"signal scaled between -1 and 1. Args: x_mu (Tensor): Input tensor quantization_channels (int):\",\n \")` \\\"\\\"\\\" # Replace by torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return\",\n \"freq, frames = specgram.size() if rand_init: angles = 2 * math.pi * torch.rand(batch,\",\n \"spectrogram of dimensions (channel, freq, time) \\\"\\\"\\\" # pack batch shape = specgram.size()\",\n \"the encoding for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int,\",\n \"time) Returns: Tensor: Masked spectrogram of dimensions (channel, freq, time) \\\"\\\"\\\" # pack\",\n \"(bool, default = false) Returns: Tensor: Tensor of freq of dimension (..., frame)\",\n \"is the spectrogram coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor):\",\n \"And initialize the previous iterate to 0 rebuilt = torch.tensor(0.) for _ in\",\n \"time)`. Batched inputs should include a channel dimension and have the form `(batch,\",\n \"Tensor: Output tensor in decibel scale \\\"\\\"\\\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin))\",\n \"tensor. Shape of `(..., )` \\\"\\\"\\\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase(\",\n \"x_db.dim() > 2 else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db =\",\n \"'slaney', divide the triangular mel weights by the width of the mel band\",\n \"freq, hop_length = 1025, 512 >>> # (channel, freq, time, complex=2) >>> complex_specgrams\",\n \"waveform.reshape(-1, shape[-1]) # default values are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform,\",\n \"freq point in hertz f_diff = f_pts[1:] - f_pts[:-1] # (n_mels + 1)\",\n \"= torch.median(roll, -1) return values def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float\",\n \"return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor ) -> Tensor: r\\\"\\\"\\\"Compute the\",\n \"spectrogram( waveform: Tensor, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int,\",\n \"waveform = waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype device =\",\n \"channel, freq, time)`. multiplier (float): Use 10. for power and 20. for amplitude\",\n \"spectrogram with shape `(..., 2)` into its magnitude and phase. Args: complex_tensor (Tensor):\",\n \"time) mask_param (int): Number of columns to be masked will be uniformly sampled\",\n \"Compute the spectral centroid for each channel along the time axis. The spectral\",\n \"supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``,\",\n \"specgram (Tensor): Tensor of audio of dimension (..., freq, time) win_length (int, optional):\",\n \"n = (win_length - 1) // 2 # twice sum of integer squared\",\n \"iterate tprev = rebuilt # Invert with our current estimate of the phases\",\n \"phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor ) -> Tensor: r\\\"\\\"\\\"Given a STFT\",\n \"of dimension (..., freq, time) Example >>> specgram = torch.randn(1, 40, 1000) >>>\",\n \"very close to the first half of lags, then the latter is taken.\",\n \"# Find near enough max that is smallest best = torch.max(nccf[..., lag_min:], -1)\",\n \"best) indices = best[1] # Add back minimal lag indices += lag_min #\",\n \"num_frames) window_end = num_frames if window_start < 0: window_start = 0 if last_window_start\",\n \"torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size], -1)\",\n \"int ) -> Tensor: r\\\"\\\"\\\" Apply a mask along ``axis``. Mask will be\",\n \"(..., ``n_freqs``), the applied result would be ``A * create_fb_matrix(A.size(-1), ...)``. \\\"\\\"\\\" if\",\n \"= specgram.device dtype = specgram.dtype # pack batch shape = specgram.size() specgram =\",\n \"Args: x (Tensor): Input tensor before being converted to power/amplitude scale. ref (float):\",\n \"Cutoff frequency for LowPass filter (Hz) (default: 1000) resample_frequency (float, optional): Frequency that\",\n \"torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq: float, mel_scale: str = \\\"htk\\\") ->\",\n \"\\\"griffinlim\\\", \\\"amplitude_to_DB\\\", \\\"DB_to_amplitude\\\", \\\"compute_deltas\\\", \\\"compute_kaldi_pitch\\\", \\\"create_fb_matrix\\\", \\\"create_dct\\\", \\\"compute_deltas\\\", \\\"detect_pitch_frequency\\\", \\\"DB_to_amplitude\\\", \\\"mu_law_encoding\\\", \\\"mu_law_decoding\\\", \\\"complex_norm\\\",\",\n \"hop between STFT windows. ( Default: ``win_length // 2``) win_length (int): Window size.\",\n \"smallest best = torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] // 2 half =\",\n \"Frequency in Mels \\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should\",\n \"Whether to normalize by magnitude after stft center (bool, optional): whether to pad\",\n \"_find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int ) -> Tensor: r\\\"\\\"\\\" For each\",\n \"optional): Minimum f0, applied in soft way, must not exceed min-f0 (default: 10.0)\",\n \"snipped, so that the number of frames is the file size divided by\",\n \"batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 /\",\n \"of shape `(..., time)`. sample_rate (float): Sample rate of `waveform`. frame_length (float, optional):\",\n \"phase = angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance:\",\n \"frame_shift: float = 10.0, min_f0: float = 50, max_f0: float = 400, soft_min_f0:\",\n \"= (min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0 if freq\",\n \"a spectrogram: .. math:: d_t = \\\\frac{\\\\sum_{n=1}^{\\\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\\\sum_{n=1}^{\\\\text{N}} n^2}\",\n \"audio of dimension (..., freq, time) cmn_window (int, optional): Window in frames for\",\n \"the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If\",\n \"mu-law decoding \\\"\\\"\\\" mu = quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu =\",\n \"onesided=onesided, return_complex=True, ) # unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized:\",\n \"before being converted to power/amplitude scale. ref (float): Reference which the output will\",\n \"-> Tensor: r\\\"\\\"\\\"Compute delta coefficients of a tensor, usually a spectrogram: .. math::\",\n \"Triangular filter banks (fb matrix) of size (``n_freqs``, ``n_mels``) meaning number of frequencies\",\n \"= _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts,\",\n \"waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag = [] for lag\",\n \"1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom #\",\n \"signal. The spectrogram can be either magnitude-only or complex. Args: waveform (Tensor): Tensor\",\n \"frame-shift. This makes different types of features give the same number of frames.\",\n \"spectrograms of dimensions (batch, channel, freq, time) \\\"\\\"\\\" if axis != 2 and\",\n \"* frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag\",\n \"then the latter is taken. \\\"\\\"\\\" lag_min = int(math.ceil(sample_rate / freq_high)) # Find\",\n \"import Tensor from torchaudio._internal import module_utils as _mod_utils import torchaudio __all__ = [\",\n \"= 100, center: bool = False, norm_vars: bool = False, ) -> Tensor:\",\n \"None, encoding: Optional[str] = None, bits_per_sample: Optional[int] = None, ) -> Tensor: r\\\"\\\"\\\"\",\n \"``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter banks (fb matrix) of size (``n_freqs``,\",\n \"(..., time) pad (int): Two sided padding of signal window (Tensor): Window tensor\",\n \"Returns: Tensor: Complex Specgrams Stretch with dimension of `(..., freq, ceil(time/rate), complex=2)` Example\",\n \"extraction algorithm tuned for automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and\",\n \"float = 7000, lowpass_filter_width: int = 1, upsample_filter_width: int = 5, max_frames_latency: int\",\n \"hop_length: int, win_length: int, power: Optional[float], normalized: bool, center: bool = True, pad_mode:\",\n \"power: float = 1.0 ) -> Tensor: r\\\"\\\"\\\"Compute the norm of complex tensor\",\n \"(1 -> frequency, 2 -> time) Returns: Tensor: Masked spectrogram of dimensions (channel,\",\n \"-> Tensor: r\\\"\\\"\\\"Encode signal based on mu-law companding. For more info see the\",\n \"(win_length - 1) // 2 # \\\"replicate\\\" padding in any dimension indices =\",\n \"'htk']: raise ValueError('mel_scale should be one of \\\"htk\\\" or \\\"slaney\\\".') if mel_scale ==\",\n \"x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu\",\n \"0 rebuilt = torch.tensor(0.) for _ in range(n_iter): # Store the previous iterate\",\n \"input waveform of shape `(..., time)`. sample_rate (float): Sample rate of `waveform`. frame_length\",\n \"(float, optional): Frame shift in milliseconds. (default: 10.0) min_f0 (float, optional): Minimum F0\",\n \"norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 - angle_0 - phase_advance phase\",\n \"calculate the difference between each mel point and each stft freq point in\",\n \"100, center: bool = False, norm_vars: bool = False, ) -> Tensor: r\\\"\\\"\\\"\",\n \"beginning of frame :math:`i`, :math:`E(j)` is the energy :math:`\\\\sum_{n=j}^{j+N-1} w^2(n)`. \\\"\\\"\\\" EPSILON =\",\n \"snip_edges: bool = True, ) -> torch.Tensor: \\\"\\\"\\\"Extract pitch based on method described\",\n \"of dimension (..., time) pad (int): Two sided padding of signal window (Tensor):\",\n \"= (freq - f_min) / f_sp # Fill in the log-scale part min_log_hz\",\n \"to frequencies. Args: mels (Tensor): Mel frequencies mel_scale (str, optional): Scale to use:\",\n \"be unstable'.format(momentum) assert momentum >= 0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \\\"The\",\n \"= torch.cat(output_lag, -1) return nccf def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor],\",\n \"-0.5) cmn_waveform[:, t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if\",\n \"= x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu) * 2\",\n \"dimension and have the form `(batch, channel, freq, time)`. multiplier (float): Use 10.\",\n \"= 500, snip_edges: bool = True, ) -> torch.Tensor: \\\"\\\"\\\"Extract pitch based on\",\n \"cur_sum -= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove ** 2) if window_end >\",\n \"momentum: angles = angles - tprev.mul_(momentum / (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles))\",\n \"waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor, multiplier: float,\",\n \"300, 2) >>> rate = 1.3 # Speed up by 30% >>> phase_advance\",\n \"of `(..., freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length = 1025, 512 >>>\",\n \"\\\"A fast Griffin-Lim algorithm,\\\" IEEE Workshop on Applications of Signal Processing to Audio\",\n \"% 1.0 phase_0 = angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams,\",\n \"* (n + 0.5) * k) # size (n_mfcc, n_mels) if norm is\",\n \"cepstral mean (and optionally variance) normalization per utterance. Args: waveform (Tensor): Tensor of\",\n \"n_mels (int): Number of mel filterbanks norm (str or None): Norm to use\",\n \"window_start < 0: window_start = 0 if last_window_start == -1: input_part = waveform[:,\",\n \"and axis != 3: raise ValueError('Only Frequency and Time masking are supported') device\",\n \"spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate //\",\n \"that determines filter width when upsampling NCCF. (default: 5) max_frames_latency (int, optional): Maximum\",\n \"def magphase( complex_tensor: Tensor, power: float = 1.0 ) -> Tuple[Tensor, Tensor]: r\\\"\\\"\\\"Separate\",\n \"the complex tensor \\\"\\\"\\\" mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag,\",\n \"= 1.0 ) -> Tuple[Tensor, Tensor]: r\\\"\\\"\\\"Separate a complex-valued spectrogram with shape `(...,\",\n \"top_db: Optional[float] = None ) -> Tensor: r\\\"\\\"\\\"Turn a spectrogram from the power/amplitude\",\n \"bins hop_length (int): Length of hop between STFT windows. ( Default: ``win_length //\",\n \"-> Tuple[Tensor, Tensor]: r\\\"\\\"\\\"Separate a complex-valued spectrogram with shape `(..., 2)` into its\",\n \"batch example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask <\",\n \"waveform = waveform.reshape(-1, shape[-1]) # default values are consistent with librosa.core.spectrum._spectrogram spec_f =\",\n \"channel along the time axis. The spectral centroid is defined as the weighted\",\n \"frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length) # Convert\",\n \"1000, resample_frequency: float = 4000, delta_pitch: float = 0.005, nccf_ballast: float = 7000,\",\n \"\\\"htk\\\": return 700.0 * (10.0**(mels / 2595.0) - 1.0) # Fill in the\",\n \"sample_rate // 2, n_freqs) # calculate mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale)\",\n \"Time masking are supported') device = specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2],\",\n \"torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1],\",\n \"once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor:\",\n \"Returns: Tensor: Dimension (..., freq, time), freq is ``n_fft // 2 + 1``\",\n \"tensor quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law decoding \\\"\\\"\\\"\",\n \"= nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best)\",\n \"norm_vars (bool, optional): If true, normalize variance to one. (bool, default = false)\",\n \"= cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int, pad: int, window:\",\n \"(Tensor): Input spectrogram(s) before being converted to decibel scale. Input should take the\",\n \"@_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float = 25.0, frame_shift: float\",\n \"(bool, optional): If this is set to false, the incomplete frames near the\",\n \"delta_pitch: float = 0.005, nccf_ballast: float = 7000, lowpass_filter_width: int = 1, upsample_filter_width:\",\n \"a frame, :math:`b_i` is the beginning of frame :math:`i`, :math:`E(j)` is the energy\",\n \"the default. (default: False) Relevant if ``frames_per_chunk > 0``. recompute_frame (int, optional): Only\",\n \"Window size. (Default: ``n_fft``) power (float): Exponent for the magnitude spectrogram, (must be\",\n \"0 and quantization_channels - 1 and returns a signal scaled between -1 and\",\n \"False, recompute_frame: int = 500, snip_edges: bool = True, ) -> torch.Tensor: \\\"\\\"\\\"Extract\",\n \"Fourier transform,\\\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor):\",\n \"Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \\\"librosa: Audio and music signal\",\n \"x_mu = ((x_mu + 1) / 2 * mu + 0.5).to(torch.int64) return x_mu\",\n \"first if bigger than a multiplicative factor of the second, elementwise. \\\"\\\"\\\" mask\",\n \"of \\\"htk\\\" or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 2595.0 * math.log10(1.0 +\",\n \"Tensor: r\\\"\\\"\\\"Create a frequency bin conversion matrix. Args: n_freqs (int): Number of frequencies\",\n \"specgram (Tensor): Real spectrogram (channel, freq, time) mask_param (int): Number of columns to\",\n \"_combine_max(half, best) indices = best[1] # Add back minimal lag indices += lag_min\",\n \"info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has been\",\n \"batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) *\",\n \"dim=-1) phase = angle_1 - angle_0 - phase_advance phase = phase - 2\",\n \"- A pitch extraction algorithm tuned for automatic speech recognition <NAME>, <NAME>, <NAME>,\",\n \"which the output will be scaled by. power (float): If power equals 1,\",\n \"(str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: mels (float):\",\n \"(f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn(\",\n \"(int): Axis to apply masking on (2 -> frequency, 3 -> time) Returns:\",\n \"return freqs def create_fb_matrix( n_freqs: int, f_min: float, f_max: float, n_mels: int, sample_rate:\",\n \"int, win_length: int, power: Optional[float], normalized: bool, center: bool = True, pad_mode: str\",\n \"but above 1 may not converge. length (int or None): Array length of\",\n \"frame_size)[..., :num_of_frames, :] output_frames = ( (s1 * s2).sum(-1) / (EPSILON + torch.norm(s1,\",\n \"size (``n_mels``, ``n_mfcc``). \\\"\\\"\\\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct\",\n \") -> Tensor: r\\\"\\\"\\\"Detect pitch frequency. It is implemented using normalized cross-correlation function\",\n \"filterbank construction by Librosa all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) # calculate\",\n \"= complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device,\",\n \"DCT transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized depending on norm. Args: n_mfcc\",\n \"(float): Used for formats other than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding\",\n \"// 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim)\",\n \"be one of None or 'slaney'\\\") # freq bins # Equivalent filterbank construction\",\n \"num_of_frames * frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute lags\",\n \"taken. \\\"\\\"\\\" lag_min = int(math.ceil(sample_rate / freq_high)) # Find near enough max that\",\n \"details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has ``[channel, time]``\",\n \"int, hop_length: int, win_length: int, power: Optional[float], normalized: bool, center: bool = True,\",\n \"== 2: specgram[:, :, mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency and Time\",\n \":pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1) values,\",\n \"mel_scale=mel_scale) # calculate the difference between each mel point and each stft freq\",\n \"dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid(\",\n \"Args: specgrams (Tensor): Real spectrograms (batch, channel, freq, time) mask_param (int): Number of\",\n \"from `librosa`. * [1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>.\",\n \"- f_min) / f_sp logstep = math.log(6.4) / 27.0 if freq >= min_log_hz:\",\n \"norm of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)`\",\n \"to power/amplitude scale. ref (float): Reference which the output will be scaled by.\",\n \"Compute lags output_lag = [] for lag in range(1, lags + 1): s1\",\n \"Array length of the expected output. rand_init (bool): Initializes phase randomly if True,\",\n \"= min_log_mel + math.log(freq / min_log_hz) / logstep return mels def _mel_to_hz(mels: Tensor,\",\n \"and ``v_0`` from ``uniform(0, max_v - v)``. All examples will have the same\",\n \"set to false, the incomplete frames near the ending edge won't be snipped,\",\n \"WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding for\",\n \"= torch.linspace(m_min, m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the\",\n \"use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels converted in Hz\",\n \"signal window (Tensor): Window tensor that is applied/multiplied to each frame/window n_fft (int):\",\n \"shape of `(..., complex=2)` power (float): Power of the norm. (Default: `1.0`). Returns:\",\n \"torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle(\",\n \"window_end - window_start, :] cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part\",\n \"DB to power. If 0.5, will compute DB to amplitude. Returns: Tensor: Output\",\n \"supported') device = specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) *\",\n \"2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \\\"\\\"\\\" shape = waveform.shape waveform = waveform.reshape(-1, shape[-1])\",\n \"the final phase estimates waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window,\",\n \"= spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate\",\n \"mel_scale: str = \\\"htk\\\") -> float: r\\\"\\\"\\\"Convert Hz to Mels. Args: freqs (float):\",\n \"27.0 log_t = (mels >= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t]\",\n \"more gives sharper filter. (default: 1) upsample_filter_width (int, optional): Integer that determines filter\",\n \"alphas) * norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc)\",\n \"size (..., ``n_freqs``), the applied result would be ``A * create_fb_matrix(A.size(-1), ...)``. \\\"\\\"\\\"\",\n \"_compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length)\",\n \"torch.rand(1) * mask_param min_value = torch.rand(1) * (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze()\",\n \") -> Tensor: r\\\"\\\"\\\" Apply median smoothing to the 1D tensor over the\",\n \"encoding for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional):\",\n \"value=0. ) indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1,\",\n \"magnitude-only or complex. Args: waveform (Tensor): Tensor of audio of dimension (..., time)\",\n \"as _mod_utils import torchaudio __all__ = [ \\\"spectrogram\\\", \\\"griffinlim\\\", \\\"amplitude_to_DB\\\", \\\"DB_to_amplitude\\\", \\\"compute_deltas\\\", \\\"compute_kaldi_pitch\\\",\",\n \"And now the nonlinear scale min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min)\",\n \"of size (..., ``n_freqs``), the applied result would be ``A * create_fb_matrix(A.size(-1), ...)``.\",\n \"n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not None and norm\",\n \"magnitude after stft center (bool, optional): whether to pad :attr:`waveform` on both sides\",\n \"up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes,\",\n \"- phase_advance phase = phase - 2 * math.pi * torch.round(phase / (2\",\n \"2:] / f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm\",\n \"def compute_deltas( specgram: Tensor, win_length: int = 5, mode: str = \\\"replicate\\\" )\",\n \"if center==true (int, default = 100) center (bool, optional): If true, use a\",\n \"dimension (..., frame) \\\"\\\"\\\" input_shape = waveform.shape num_frames, num_feats = input_shape[-2:] waveform =\",\n \"// 2 + 1`` and ``n_fft`` is the number of Fourier bins, and\",\n \"a multiplicative factor of the second, elementwise. \\\"\\\"\\\" mask = (a[0] > thresh\",\n \"batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param:\",\n \"+ list(shape[-2:])) value = torch.rand(1) * mask_param min_value = torch.rand(1) * (specgram.size(axis) -\",\n \"<NAME>, <NAME>, <NAME>, and <NAME>. \\\"librosa: Audio and music signal analysis in python.\\\"\",\n \"'momentum={} > 1 can be unstable'.format(momentum) assert momentum >= 0, 'momentum={} < 0'.format(momentum)\",\n \"(Hz) f_max (float): Maximum frequency (Hz) n_mels (int): Number of mel filterbanks sample_rate\",\n \"Tensor ) -> Tensor: r\\\"\\\"\\\"Given a STFT tensor, speed up in time without\",\n \"we recompute some of the forward pointers, after revising our estimate of the\",\n \"time]`` else ``[time, channel]``. \\\"\\\"\\\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression,\",\n \"2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int, pad:\",\n \"Real spectrogram (channel, freq, time) mask_param (int): Number of columns to be masked\",\n \"complex-valued spectrogram with shape `(..., 2)` into its magnitude and phase. Args: complex_tensor\",\n \"optional): If true, use a window centered on the current frame (to the\",\n \"- cur_sum / window_frames if norm_vars: if window_frames == 1: cmn_waveform[:, t, :]\",\n \"construction by Librosa all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) # calculate mel\",\n \"(n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not None and\",\n \"Args: x_mu (Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input\",\n \"n (c_{t+n} - c_{t-n})}{2 \\\\sum_{n=1}^{\\\\text{N}} n^2} where :math:`d_t` is the deltas at time\",\n \"-1) half_size = nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size], -1) best =\",\n \"torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) #\",\n \"- f_min) / f_sp # Fill in the log-scale part min_log_hz = 1000.0\",\n \"frames is the file size divided by the frame-shift. This makes different types\",\n \"process. momentum (float): The momentum parameter for fast Griffin-Lim. Setting this to 0\",\n \"0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \\\"The argument normalized is not used\",\n \"of integer squared denom = n * (n + 1) * (2 *\",\n \"'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \\\"The argument normalized is not used in\",\n \"window: Tensor, n_fft: int, hop_length: int, win_length: int, ) -> Tensor: r\\\"\\\"\\\" Compute\",\n \"1984. Args: specgram (Tensor): A magnitude-only STFT spectrogram of dimension (..., freq, frames)\",\n \"(Optional[str]): If 'slaney', divide the triangular mel weights by the width of the\",\n \"n_fft: int, hop_length: int, win_length: int, ) -> Tensor: r\\\"\\\"\\\" Compute the spectral\",\n \"mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels + 2) f_pts\",\n \"search for (Hz) (default: 50.0) max_f0 (float, optional): Maximum F0 to search for\",\n \"is centered at time :math:`t \\\\times \\\\text{hop\\\\_length}`. Default: ``True`` pad_mode (string, optional): controls\",\n \"of hop between STFT windows win_length (int): Window size power (float or None):\",\n \"different values for an audio clip split into snippets vs. a full clip.\",\n \"scale min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep =\",\n \"angle( complex_tensor: Tensor ) -> Tensor: r\\\"\\\"\\\"Compute the angle of complex tensor input.\",\n \"It is implemented using normalized cross-correlation function and median smoothing. Args: waveform (Tensor):\",\n \"if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor,\",\n \"min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online,\",\n \"1: specgram[:, mask_start:mask_end] = mask_value elif axis == 2: specgram[:, :, mask_start:mask_end] =\",\n \"bool = True, compression: Optional[float] = None, encoding: Optional[str] = None, bits_per_sample: Optional[int]\",\n \"conversion matrix. Args: n_freqs (int): Number of frequencies to highlight/apply f_min (float): Minimum\",\n \"5) max_frames_latency (int, optional): Maximum number of frames of latency that we allow\",\n \"and NCCF. Reference: - A pitch extraction algorithm tuned for automatic speech recognition\",\n \"freq, time) \\\"\\\"\\\" if axis != 2 and axis != 3: raise ValueError('Only\",\n \"linear scale f_min = 0.0 f_sp = 200.0 / 3 freqs = f_min\",\n \"filterbanks norm (str or None): Norm to use (either 'ortho' or None) Returns:\",\n \"(to the extent possible, modulo end effects). If false, window is to the\",\n \"from a raw audio signal. The spectrogram can be either magnitude-only or complex.\",\n \"``x`` db_multiplier (float): Log10(max(reference value and amin)) top_db (float or None, optional): Minimum\",\n \"/ 3 mels = (freq - f_min) / f_sp # Fill in the\",\n \"STFT tensor, speed up in time without modifying pitch by a factor of\",\n \"Applications of Signal Processing to Audio and Acoustics (pp. 1-4), Oct. 2013. *\",\n \"(Tensor, Tensor): The magnitude and phase of the complex tensor \\\"\\\"\\\" mag =\",\n \"def angle( complex_tensor: Tensor ) -> Tensor: r\\\"\\\"\\\"Compute the angle of complex tensor\",\n \"2) if window_end > last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum += frame_to_add\",\n \"n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:])\",\n \"top_db).view(-1, 1, 1, 1)) # Repack batch x_db = x_db.reshape(shape) return x_db def\",\n \"db_multiplier: float, top_db: Optional[float] = None ) -> Tensor: r\\\"\\\"\\\"Turn a spectrogram from\",\n \"num_feats, dtype=dtype, device=device) for t in range(num_frames): window_start = 0 window_end = 0\",\n \"= t - cmn_window // 2 window_end = window_start + cmn_window else: window_start\",\n \"info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values between\",\n \"their magnitude. Args: waveform (Tensor): Tensor of audio of dimension (..., time) sample_rate\",\n \"`(..., )` \\\"\\\"\\\" # Replace by torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279\",\n \"* a[0] + ~mask * b[0] indices = mask * a[1] + ~mask\",\n \"= int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p\",\n \"indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\\\"constant\\\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length\",\n \"torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\\\"rate\\\", f\\\"{sample_rate}\\\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor,\",\n \"freqs = torch.linspace(0, sample_rate // 2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1))\",\n \"if norm is not None and norm != \\\"slaney\\\": raise ValueError(\\\"norm must be\",\n \"take the highest value of NCCF, apply centered median smoothing, and convert to\",\n \"(specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert mask_end\",\n \"dimension (..., frame) \\\"\\\"\\\" # pack batch shape = list(waveform.size()) waveform = waveform.reshape([-1]\",\n \"- 1.0) # Fill in the linear scale f_min = 0.0 f_sp =\",\n \"+ (1 - alphas) * norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch =\",\n \"If true, the function will output features that correspond to what an online\",\n \"of the features, which is the default. (default: False) Relevant if ``frames_per_chunk >\",\n \"reasonable number is 80. (Default: ``None``) Returns: Tensor: Output tensor in decibel scale\",\n \"mu-law encoding \\\"\\\"\\\" mu = quantization_channels - 1.0 if not x.is_floating_point(): x =\",\n \"sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. All examples\",\n \"in Hz mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``)\",\n \"advance in each bin. Dimension of (freq, 1) Returns: Tensor: Complex Specgrams Stretch\",\n \") -> Tensor: r\\\"\\\"\\\" Compute Normalized Cross-Correlation Function (NCCF). .. math:: \\\\phi_i(m) =\",\n \"= f_min + f_sp * mels # And now the nonlinear scale min_log_hz\",\n \"Speech and Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \\\"\\\"\\\" shape\",\n \"used when :attr:`center` is ``True``. Default: ``\\\"reflect\\\"`` onesided (bool, optional): controls whether to\",\n \"instead. normalized (bool): Whether to normalize by magnitude after stft center (bool, optional):\",\n \"1, 1, 1)) # Repack batch x_db = x_db.reshape(shape) return x_db def DB_to_amplitude(\",\n \"Input after mu-law decoding \\\"\\\"\\\" mu = quantization_channels - 1.0 if not x_mu.is_floating_point():\",\n \"-> time) Returns: Tensor: Masked spectrograms of dimensions (batch, channel, freq, time) \\\"\\\"\\\"\",\n \"Tensor shape of `(..., complex=2)` power (float): Power of the norm. (Default: `1.0`).\",\n \"= \\\"htk\\\") -> Tensor: \\\"\\\"\\\"Convert mel bin numbers to frequencies. Args: mels (Tensor):\",\n \"on mu-law companding. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm\",\n \"None, None] mask_end = (min_value + value)[..., None, None] mask = torch.arange(0, specgrams.size(axis),\",\n \"apply centered median smoothing, and convert to frequency. Note: If the max among\",\n \"estimate of the signal energy. Relevant if ``frames_per_chunk > 0``. (default: 500) snip_edges\",\n \"IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor): A magnitude-only\",\n \"= 4000, delta_pitch: float = 0.005, nccf_ballast: float = 7000, lowpass_filter_width: int =\",\n \"for _ in range(n_iter): # Store the previous iterate tprev = rebuilt #\",\n \"Args: specgram (Tensor): Real spectrogram (channel, freq, time) mask_param (int): Number of columns\",\n \"of the frequency values, weighted by their magnitude. Args: waveform (Tensor): Tensor of\",\n \"= None, bits_per_sample: Optional[int] = None, ) -> Tensor: r\\\"\\\"\\\" Apply codecs as\",\n \"f_pts[1:] - f_pts[:-1] # (n_mels + 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) #\",\n \"> 0``. (default: 500) snip_edges (bool, optional): If this is set to false,\",\n \"/ f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is\",\n \"None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with 231 ==\",\n \"= mask_value elif axis == 2: specgram[:, :, mask_start:mask_end] = mask_value else: raise\",\n \"sided padding of signal window (Tensor): Window tensor that is applied/multiplied to each\",\n \"== -1: input_part = waveform[:, window_start: window_end - window_start, :] cur_sum += torch.sum(input_part,\",\n \"spectrogram using the Griffin-Lim transformation. Implementation ported from `librosa`. * [1] McFee, Brian,\",\n \"length (int or None): Array length of the expected output. rand_init (bool): Initializes\",\n \"current estimate of the phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length,\",\n \"(EPSILON + indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq\",\n \"<NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE International Conference on Acoustics, Speech and\",\n \"(..., frame) \\\"\\\"\\\" # pack batch shape = list(waveform.size()) waveform = waveform.reshape([-1] +\",\n \"(Hz) (default: 50.0) max_f0 (float, optional): Maximum F0 to search for (Hz) (default:\",\n \"* slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:, 2:] /\",\n \"= angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor\",\n \"on both sides so that the :math:`t`-th frame is centered at time :math:`t\",\n \"Tensor of deltas of dimension (..., freq, time) Example >>> specgram = torch.randn(1,\",\n \"being converted to power/amplitude scale. ref (float): Reference which the output will be\",\n \"nccf: Tensor, sample_rate: int, freq_high: int ) -> Tensor: r\\\"\\\"\\\" For each frame,\",\n \"frequencies mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns:\",\n \"= _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length) # Convert indices to frequency\",\n \"raise ValueError(\\\"norm must be one of None or 'slaney'\\\") # freq bins #\",\n \"set too high. \\\" f\\\"Or, the value for `n_freqs` ({n_freqs}) may be set\",\n \"one of \\\"htk\\\" or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 700.0 * (10.0**(mels\",\n \"+ num_of_frames * frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute\",\n \"false) Returns: Tensor: Tensor of freq of dimension (..., frame) \\\"\\\"\\\" input_shape =\",\n \"specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int, format: str, channels_first: bool =\",\n \"torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack\",\n \"(int, optional): Only relevant for compatibility with online pitch extraction. A non-critical parameter;\",\n \"for (Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum f0, applied in soft way,\",\n \"= mag * torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch],\",\n \"for fast Griffin-Lim. Setting this to 0 recovers the original Griffin-Lim method. Values\",\n \"nccf_ballast: float = 7000, lowpass_filter_width: int = 1, upsample_filter_width: int = 5, max_frames_latency:\",\n \"if last_window_start == -1: input_part = waveform[:, window_start: window_end - window_start, :] cur_sum\",\n \"sides so that the :math:`t`-th frame is centered at time :math:`t \\\\times \\\\text{hop\\\\_length}`.\",\n \"approx constant energy per channel enorm = 2.0 / (f_pts[2:n_mels + 2] -\",\n \"- 1.0 if not x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu\",\n \"norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1\",\n \"mode=\\\"constant\\\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll =\",\n \"waveform.dtype device = waveform.device last_window_start = last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats,\",\n \"the audio waveform pad (int): Two sided padding of signal window (Tensor): Window\",\n \"should include a channel dimension and have the form `(batch, channel, freq, time)`.\",\n \"decoder would see in the first pass of decoding -- not the final\",\n \"bool = True, pad_mode: str = \\\"reflect\\\", onesided: bool = True ) ->\",\n \"Number of lags to check lags = int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate\",\n \"= 1.0 ) -> Tensor: r\\\"\\\"\\\"Compute the norm of complex tensor input. Args:\",\n \"-> float: r\\\"\\\"\\\"Convert Hz to Mels. Args: freqs (float): Frequencies in Hz mel_scale\",\n \"details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit depth for the supported\",\n \"window_frames == 1: cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else:\",\n \"int, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, ) ->\",\n \"each frame, take the highest value of NCCF, apply centered median smoothing, and\",\n \"+ 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) #\",\n \"on (2 -> frequency, 3 -> time) Returns: Tensor: Masked spectrograms of dimensions\",\n \"float, phase_advance: Tensor ) -> Tensor: r\\\"\\\"\\\"Given a STFT tensor, speed up in\",\n \"torch.round(phase / (2 * math.pi)) # Compute Phase Accum phase = phase +\",\n \"output_lag = [] for lag in range(1, lags + 1): s1 = waveform[...,\",\n \"1) if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1, :] else: if\",\n \"give the same number of frames. (default: True) Returns: Tensor: Pitch feature. Shape:\",\n \"< 0: window_start = 0 if last_window_start == -1: input_part = waveform[:, window_start:\",\n \"etc. normalized (bool): Whether to normalize by magnitude after stft. n_iter (int): Number\",\n \"= phase - 2 * math.pi * torch.round(phase / (2 * math.pi)) #\",\n \"231, 2]) \\\"\\\"\\\" # pack batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] +\",\n \"factor reduces NCCF for quiet frames (default: 7000) lowpass_filter_width (int, optional): Integer that\",\n \"ending edge won't be snipped, so that the number of frames is the\",\n \"Apply median smoothing to the 1D tensor over the given window. \\\"\\\"\\\" #\",\n \"Masked spectrograms of dimensions (batch, channel, freq, time) \\\"\\\"\\\" if axis != 2\",\n \"frame, take the highest value of NCCF, apply centered median smoothing, and convert\",\n \"up by 30% >>> phase_advance = torch.linspace( >>> 0, math.pi * hop_length, freq)[...,\",\n \"python.\\\" In Proceedings of the 14th python in science conference, pp. 18-25. 2015.\",\n \"scale to the power/amplitude scale. Args: x (Tensor): Input tensor before being converted\",\n \"false, ignored if center==true (int, default = 100) center (bool, optional): If true,\",\n \"waveform (Tensor): Audio data. Must be 2 dimensional. See also ```channels_first```. sample_rate (int):\",\n \"``n_fft // 2 + 1``. window (Tensor): Window tensor that is applied/multiplied to\",\n \"columns axis (int): Axis to apply masking on (2 -> frequency, 3 ->\",\n \"default = 100) center (bool, optional): If true, use a window centered on\",\n \"bigger than a multiplicative factor of the second, elementwise. \\\"\\\"\\\" mask = (a[0]\",\n \"frame_time: float = 10 ** (-2), win_length: int = 30, freq_low: int =\",\n \"f_max: float, n_mels: int, sample_rate: int, norm: Optional[str] = None, mel_scale: str =\",\n \"(default: 500) snip_edges (bool, optional): If this is set to false, the incomplete\",\n \"- 2 * math.pi * torch.round(phase / (2 * math.pi)) # Compute Phase\",\n \"frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames =\",\n \"that the :math:`t`-th frame is centered at time :math:`t \\\\times \\\\text{hop\\\\_length}`. Default: ``True``\",\n \"+ list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor, cmn_window: int = 600, min_cmn_window:\",\n \"waveform def amplitude_to_DB( x: Tensor, multiplier: float, amin: float, db_multiplier: float, top_db: Optional[float]\",\n \"normalized=False, onesided=onesided, return_complex=True, ) # unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if\",\n \"Minimum frequency (Hz) f_max (float): Maximum frequency (Hz) n_mels (int): Number of mel\",\n \"size (n_mfcc, n_mels) if norm is None: dct *= 2.0 else: assert norm\",\n \"\\\"\\\"\\\" mu = quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu\",\n \"``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. Args: specgrams (Tensor): Real\",\n \"a batch depends on the maximum value of that tensor, and so may\",\n \"(int, optional): Highest frequency that can be detected (Hz) (Default: ``3400``). Returns: Tensor:\",\n \"for t in range(num_frames): window_start = 0 window_end = 0 if center: window_start\",\n \"if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu)\",\n \"it has ``[channel, time]`` else ``[time, channel]``. \\\"\\\"\\\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform,\",\n \"This makes different types of features give the same number of frames. (default:\",\n \"final phase estimates waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length)\",\n \"return 2595.0 * math.log10(1.0 + (freq / 700.0)) # Fill in the linear\",\n \"energy, 2 for power, etc. normalized (bool): Whether to normalize by magnitude after\",\n \"Tensor: r\\\"\\\"\\\"Encode signal based on mu-law companding. For more info see the `Wikipedia\",\n \"norm. (Default: `1.0`) Returns: (Tensor, Tensor): The magnitude and phase of the complex\",\n \"= sample_rate / (EPSILON + indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1] +\",\n \"uniformly sampled from [0, mask_param] mask_value (float): Value to assign to the masked\",\n \"too high. \\\" f\\\"Or, the value for `n_freqs` ({n_freqs}) may be set too\",\n \"- 1. Args: x (Tensor): Input tensor quantization_channels (int): Number of channels Returns:\",\n \"in range(1, lags + 1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :]\",\n \"Accum phase = phase + phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc\",\n \"to each frame/window n_fft (int): Size of FFT hop_length (int): Length of hop\",\n \"x.shape # with 231 == ceil(300 / 1.3) torch.Size([2, 1025, 231, 2]) \\\"\\\"\\\"\",\n \"columns axis (int): Axis to apply masking on (1 -> frequency, 2 ->\",\n \"axis != 2 and axis != 3: raise ValueError('Only Frequency and Time masking\",\n \"half of lags, then the latter is taken. \\\"\\\"\\\" lag_min = int(math.ceil(sample_rate /\",\n \"** (-2)``). win_length (int, optional): The window length for median smoothing (in number\",\n \"torch.cumsum(input_part ** 2, 1)[:, -1, :] else: if window_start > last_window_start: frame_to_remove =\",\n \"n_mels + 2) # create overlapping triangles zero = torch.zeros(1) down_slopes = (-1.0\",\n \"the audio waveform norm (Optional[str]): If 'slaney', divide the triangular mel weights by\",\n \"= complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 =\",\n \"or a batch of spectrograms from a raw audio signal. The spectrogram can\",\n \"None, None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch example masking\",\n \"torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance = cur_sumsq variance = variance /\",\n \"= variance / window_frames variance -= ((cur_sum ** 2) / (window_frames ** 2))\",\n \"format: str, channels_first: bool = True, compression: Optional[float] = None, encoding: Optional[str] =\",\n \"kernel, groups=specgram.shape[1]) / denom # unpack batch output = output.reshape(shape) return output def\",\n \"0.005, nccf_ballast: float = 7000, lowpass_filter_width: int = 1, upsample_filter_width: int = 5,\",\n \"F0 to search for (Hz) (default: 50.0) max_f0 (float, optional): Maximum F0 to\",\n \"frequency. It is implemented using normalized cross-correlation function and median smoothing. Args: waveform\",\n \"(float): The momentum parameter for fast Griffin-Lim. Setting this to 0 recovers the\",\n \"n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate // 2, steps=1 +\",\n \"of the 14th python in science conference, pp. 18-25. 2015. * [2] <NAME>.,\",\n \"may return different values for an audio clip split into snippets vs. a\",\n \"time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1)\",\n \"# pack batch shape = specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert win_length\",\n \"x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Decode mu-law encoded\",\n \"simulate_first_pass_online (bool, optional): If true, the function will output features that correspond to\",\n \"specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int, format: str, channels_first:\",\n \"def create_dct( n_mfcc: int, n_mels: int, norm: Optional[str] ) -> Tensor: r\\\"\\\"\\\"Create a\",\n \"waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames = ( (s1 * s2).sum(-1) /\",\n \"2) >>> rate = 1.3 # Speed up by 30% >>> phase_advance =\",\n \"(float): Reference which the output will be scaled by. power (float): If power\",\n \"simulate_first_pass_online: bool = False, recompute_frame: int = 500, snip_edges: bool = True, )\",\n \"for energy, 2 for power, etc. If None, then the complex spectrum is\",\n \"Optional[str] = None, mel_scale: str = \\\"htk\\\", ) -> Tensor: r\\\"\\\"\\\"Create a frequency\",\n \"m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels\",\n \"* norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch\",\n \"indices.unfold(-1, win_length, 1) values, _ = torch.median(roll, -1) return values def detect_pitch_frequency( waveform:\",\n \"waveform: Tensor, sample_rate: int, frame_time: float = 10 ** (-2), win_length: int =\",\n \"the maximum value of that tensor, and so may return different values for\",\n \"DB to amplitude. Returns: Tensor: Output tensor in power/amplitude scale. \\\"\\\"\\\" return ref\",\n \"for an audio clip split into snippets vs. a full clip. Args: x\",\n \"fast Griffin-Lim algorithm,\\\" IEEE Workshop on Applications of Signal Processing to Audio and\",\n \"of the audio waveform pad (int): Two sided padding of signal window (Tensor):\",\n \"float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Encode\",\n \"<NAME>. \\\"librosa: Audio and music signal analysis in python.\\\" In Proceedings of the\",\n \"/ (EPSILON + indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return\",\n \"def apply_codec( waveform: Tensor, sample_rate: int, format: str, channels_first: bool = True, compression:\",\n \"Returns: Tensor: Pitch feature. Shape: ``(batch, frames 2)`` where the last dimension corresponds\",\n \"v)``. All examples will have the same mask interval. Args: specgram (Tensor): Real\",\n \"indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn(\",\n \"from torch import Tensor from torchaudio._internal import module_utils as _mod_utils import torchaudio __all__\",\n \"angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2])\",\n \"(int): Sample rate of the audio waveform pad (int): Two sided padding of\",\n \"`(..., freq, time)`. Batched inputs should include a channel dimension and have the\",\n \"20. for amplitude amin (float): Number to clamp ``x`` db_multiplier (float): Log10(max(reference value\",\n \"be more than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest relative change\",\n \"mels # And now the nonlinear scale min_log_hz = 1000.0 min_log_mel = (min_log_hz\",\n \"* torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq: float, mel_scale: str = \\\"htk\\\")\",\n \"norm (str or None): Norm to use (either 'ortho' or None) Returns: Tensor:\",\n \"data of size (``n_mels``, ``n_mfcc``). \\\"\\\"\\\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k =\",\n \"of hop between STFT windows win_length (int): Window size Returns: Tensor: Dimension (...,\",\n \"may not converge. length (int or None): Array length of the expected output.\",\n \"tprev = rebuilt # Invert with our current estimate of the phases inverse\",\n \"parameter for fast Griffin-Lim. Setting this to 0 recovers the original Griffin-Lim method.\",\n \"* n + 1) / 3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel\",\n \"can lead to faster convergence, but above 1 may not converge. length (int\",\n \"variance to one. (bool, default = false) Returns: Tensor: Tensor of freq of\",\n \"mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram: Tensor, mask_param: int,\",\n \"angle_0 - phase_advance phase = phase - 2 * math.pi * torch.round(phase /\",\n \"the signal to. Must be more than twice lowpass-cutoff. (default: 4000) delta_pitch( float,\",\n \"torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier if top_db is not None: #\",\n \"= torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram\",\n \"pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) # Update our phase estimates angles =\",\n \"if axis == 1: specgram[:, mask_start:mask_end] = mask_value elif axis == 2: specgram[:,\",\n \"are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center,\",\n \"\\\"magphase\\\", \\\"phase_vocoder\\\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \\\"spectral_centroid\\\", \\\"apply_codec\\\", ] def spectrogram( waveform: Tensor, pad:\",\n \"* angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch waveform = waveform.reshape(shape[:-2]\",\n \"whether to return half of results to avoid redundancy. Default: ``True`` Returns: Tensor:\",\n \"channel, freq, time) \\\"\\\"\\\" if axis != 2 and axis != 3: raise\",\n \"indices, (pad_length, 0), mode=\\\"constant\\\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)],\",\n \"than a multiplicative factor of the second, elementwise. \\\"\\\"\\\" mask = (a[0] >\",\n \"the signal has been scaled to between -1 and 1 and returns a\",\n \"is not used in Griffin-Lim, \\\" \\\"and will be removed in v0.9.0 release.\",\n \"(int): Number of channels Returns: Tensor: Input after mu-law encoding \\\"\\\"\\\" mu =\",\n \"a spectrogram from the power/amplitude scale to the decibel scale. The output of\",\n \"normalize by magnitude after stft center (bool, optional): whether to pad :attr:`waveform` on\",\n \"mels = (freq - f_min) / f_sp # Fill in the log-scale part\",\n \"down_slopes = (-1.0 * slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes =\",\n \"ValueError('Only Frequency and Time masking are supported') # unpack batch specgram = specgram.reshape(shape[:-2]\",\n \".. math:: d_t = \\\\frac{\\\\sum_{n=1}^{\\\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\\\sum_{n=1}^{\\\\text{N}} n^2} where :math:`d_t`\",\n \"Tensor: r\\\"\\\"\\\"Turn a spectrogram from the power/amplitude scale to the decibel scale. The\",\n \"``True``. Default: ``\\\"reflect\\\"`` onesided (bool, optional): controls whether to return half of results\",\n \"decibel scale to the power/amplitude scale. Args: x (Tensor): Input tensor before being\",\n \"torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch\",\n \"if x_db.dim() > 2 else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db\",\n \"range(num_frames): window_start = 0 window_end = 0 if center: window_start = t -\",\n \"+ cmn_window else: window_start = t - cmn_window window_end = t + 1\",\n \"torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best) indices = best[1] # Add back\",\n \"mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be one of \\\"htk\\\" or\",\n \"+ 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between each mel\",\n \"and <NAME>, \\\"Signal estimation from modified short-time Fourier transform,\\\" IEEE Trans. ASSP, vol.32,\",\n \"and Time masking are supported') # unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:])\",\n \"parameter passed to padding (Default: ``\\\"replicate\\\"``) Returns: Tensor: Tensor of deltas of dimension\",\n \"set too low.\\\" ) return fb def create_dct( n_mfcc: int, n_mels: int, norm:\",\n \"lag_min:], -1) half_size = nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size], -1) best\",\n \"frequencies to highlight/apply to x the number of filterbanks. Each column is a\",\n \"optionally variance) normalization per utterance. Args: waveform (Tensor): Tensor of audio of dimension\",\n \"(float, optional): Duration of a frame (Default: ``10 ** (-2)``). win_length (int, optional):\",\n \"float, mel_scale: str = \\\"htk\\\") -> float: r\\\"\\\"\\\"Convert Hz to Mels. Args: freqs\",\n \"+ 1`` bins hop_length (int): Length of hop between STFT windows. ( Default:\",\n \"filterbanks. Each column is a filterbank so that assuming there is a matrix\",\n \"0, math.pi * hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>>\",\n \"frame_size)) p = lags + num_of_frames * frame_size - waveform_length waveform = torch.nn.functional.pad(waveform,\",\n \"centroid for each channel along the time axis. The spectral centroid is defined\",\n \"if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be one of \\\"htk\\\"\",\n \"in Griffin-Lim, \\\" \\\"and will be removed in v0.9.0 release. To suppress this\",\n \"length of a frame, :math:`b_i` is the beginning of frame :math:`i`, :math:`E(j)` is\",\n \"Norm to use (either 'ortho' or None) Returns: Tensor: The transformation matrix, to\",\n \":math:`m`, :math:`w` is the waveform, :math:`N` is the length of a frame, :math:`b_i`\",\n \"t + 1 if window_start < 0: window_end -= window_start window_start = 0\",\n \"rebuilt if momentum: angles = angles - tprev.mul_(momentum / (1 + momentum)) angles\",\n \"= complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas =\",\n \"device = specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param\",\n \"the max among all the lags is very close to the first half\",\n \"indices = mask * a[1] + ~mask * b[1] return values, indices def\",\n \"torch.Size([2, 1025, 231, 2]) \\\"\\\"\\\" # pack batch shape = complex_specgrams.size() complex_specgrams =\",\n \"tprev.mul_(momentum / (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase\",\n \"# unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas( specgram:\",\n \"Only applicable if center == false, ignored if center==true (int, default = 100)\",\n \"parameter; the frame at which we recompute some of the forward pointers, after\",\n \"Minimum CMN window used at start of decoding (adds latency only at start).\",\n \"\\\"librosa: Audio and music signal analysis in python.\\\" In Proceedings of the 14th\",\n \"r\\\"\\\"\\\"Compute the angle of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of\",\n \"f_sp * mels # And now the nonlinear scale min_log_hz = 1000.0 min_log_mel\",\n \"number of frames used for energy normalization. (default: 0) simulate_first_pass_online (bool, optional): If\",\n \"int, power: Optional[float], normalized: bool, center: bool = True, pad_mode: str = \\\"reflect\\\",\",\n \"Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has been scaled to between -1\",\n \"normalized: spec_f /= window.pow(2.).sum().sqrt() if power is not None: if power == 1.0:\",\n \"2 for power, etc. If None, then the complex spectrum is returned instead.\",\n \"None, mel_scale: str = \\\"htk\\\", ) -> Tensor: r\\\"\\\"\\\"Create a frequency bin conversion\",\n \"too low.\\\" ) return fb def create_dct( n_mfcc: int, n_mels: int, norm: Optional[str]\",\n \"= waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf,\",\n \"= 0.005, nccf_ballast: float = 7000, lowpass_filter_width: int = 1, upsample_filter_width: int =\",\n \"1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0\",\n \"the NCCF at frame :math:`i` with lag :math:`m`, :math:`w` is the waveform, :math:`N`\",\n \"this factor reduces NCCF for quiet frames (default: 7000) lowpass_filter_width (int, optional): Integer\",\n \"sample_rate (int): The sample rate of the waveform (Hz) frame_time (float, optional): Duration\",\n \"= (min_value.long() + value.long()).squeeze() assert mask_end - mask_start < mask_param if axis ==\",\n \"<NAME>., <NAME>., & <NAME>. \\\"A fast Griffin-Lim algorithm,\\\" IEEE Workshop on Applications of\",\n \"channel]``. \\\"\\\"\\\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample\",\n \"`(batch, channel, freq, time)`. multiplier (float): Use 10. for power and 20. for\",\n \"of a frame (Default: ``10 ** (-2)``). win_length (int, optional): The window length\",\n \"based on method described in [1]. This function computes the equivalent of `compute-kaldi-pitch-feats`\",\n \"see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has ``[channel, time]`` else\",\n \"if not x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x)\",\n \"the audio waveform. format (str): File format. channels_first (bool): When True, both the\",\n \"revising our estimate of the signal energy. Relevant if ``frames_per_chunk > 0``. (default:\",\n \"50, max_f0: float = 400, soft_min_f0: float = 10.0, penalty_factor: float = 0.1,\",\n \"+ specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor, win_length: int = 5, mode:\",\n \"10.1109/ICASSP.2014.6854049. \\\"\\\"\\\" shape = waveform.shape waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform,\",\n \"encoded with values from 0 to quantization_channels - 1. Args: x (Tensor): Input\",\n \"device=device) else: variance = cur_sumsq variance = variance / window_frames variance -= ((cur_sum\",\n \"penalty_factor (float, optional): Cost factor for FO change. (default: 0.1) lowpass_cutoff (float, optional):\",\n \"(default: 0) simulate_first_pass_online (bool, optional): If true, the function will output features that\",\n \"lags, then the latter is taken. \\\"\\\"\\\" lag_min = int(math.ceil(sample_rate / freq_high)) #\",\n \"to false, the incomplete frames near the ending edge won't be snipped, so\",\n \"of the signal energy. Relevant if ``frames_per_chunk > 0``. (default: 500) snip_edges (bool,\",\n \"frames) else: angles = torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\\\\",\n \"mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor: r\\\"\\\"\\\"\",\n \"> 0``. recompute_frame (int, optional): Only relevant for compatibility with online pitch extraction.\",\n \"norm == \\\"slaney\\\": # Slaney-style mel is scaled to be approx constant energy\",\n \"(frame_to_remove ** 2) if window_end > last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum\",\n \"packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1,\",\n \"Apply a mask along ``axis``. Mask will be applied from indices ``[v_0, v_0\",\n \"0.1 * x), power) def _hz_to_mel(freq: float, mel_scale: str = \\\"htk\\\") -> float:\",\n \"momentum (float): The momentum parameter for fast Griffin-Lim. Setting this to 0 recovers\",\n \"up_slopes)) if norm is not None and norm == \\\"slaney\\\": # Slaney-style mel\",\n \"freq, time)`. Batched inputs should include a channel dimension and have the form\",\n \"torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag = [] for lag in range(1,\",\n \"LowPass filter (Hz) (default: 1000) resample_frequency (float, optional): Frequency that we down-sample the\",\n \"features that correspond to what an online decoder would see in the first\",\n \"max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result = result.reshape(shape[:-1] + result.shape[-2:]) return result\",\n \"bool = True ) -> Tensor: r\\\"\\\"\\\"Create a spectrogram or a batch of\",\n \"0, 0, 2]) # (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 =\",\n \"r\\\"\\\"\\\"Convert Hz to Mels. Args: freqs (float): Frequencies in Hz mel_scale (str, optional):\",\n \"and median smoothing. Args: waveform (Tensor): Tensor of audio of dimension (..., freq,\",\n \"without modifying pitch by a factor of ``rate``. Args: complex_specgrams (Tensor): Dimension of\",\n \"Dimension (..., freq, time), freq is ``n_fft // 2 + 1`` and ``n_fft``\",\n \"Default: ``True`` pad_mode (string, optional): controls the padding method used when :attr:`center` is\",\n \"output will be scaled by. power (float): If power equals 1, will compute\",\n \"at time :math:`t \\\\times \\\\text{hop\\\\_length}`. Default: ``True`` pad_mode (string, optional): controls the padding\",\n \"The window length for median smoothing (in number of frames) (Default: ``30``). freq_low\",\n \"(int): Number of iteration for phase recovery process. momentum (float): The momentum parameter\",\n \"`1.0`) Returns: (Tensor, Tensor): The magnitude and phase of the complex tensor \\\"\\\"\\\"\",\n \"Lowest frequency that can be detected (Hz) (Default: ``85``). freq_high (int, optional): Highest\",\n \"bit depth for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor:\",\n \"estimation from modified short-time Fourier transform,\\\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr.\",\n \"torch.log1p(mu)) - 1.0) / mu return x def complex_norm( complex_tensor: Tensor, power: float\",\n \"= freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor, cmn_window: int =\",\n \"both the input and output Tensor have dimension ``[channel, time]``. Otherwise, they have\",\n \"ported from `librosa`. * [1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and\",\n \"mu = quantization_channels - 1.0 if not x.is_floating_point(): x = x.to(torch.float) mu =\",\n \"quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Decode mu-law encoded signal. For more info see\",\n \"from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. All examples will\",\n \"freq, time, complex=2)` rate (float): Speed-up factor phase_advance (Tensor): Expected phase advance in\",\n \"being converted to decibel scale. Input should take the form `(..., freq, time)`.\",\n \"n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between each\",\n \"= angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase\",\n \"mel point and each stft freq point in hertz f_diff = f_pts[1:] -\",\n \"apply_codec( waveform: Tensor, sample_rate: int, format: str, channels_first: bool = True, compression: Optional[float]\",\n \"\\\" f\\\"The value for `n_mels` ({n_mels}) may be set too high. \\\" f\\\"Or,\",\n \"been scaled to between -1 and 1 and returns a signal encoded with\",\n \"power: Optional[float], normalized: bool, center: bool = True, pad_mode: str = \\\"reflect\\\", onesided:\",\n \"= specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end), mask_value) specgrams =\",\n \"window. \\\"\\\"\\\" # Centered windowed pad_length = (win_length - 1) // 2 #\",\n \"+ 1) / 3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n,\",\n \"freq_low (int, optional): Lowest frequency that can be detected (Hz) (Default: ``85``). freq_high\",\n \"m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between\",\n \"for formats other than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional):\",\n \"max_frames_latency (int, optional): Maximum number of frames of latency that we allow pitch\",\n \"whether to pad :attr:`waveform` on both sides so that the :math:`t`-th frame is\",\n \"mask along ``axis``. Mask will be applied from indices ``[v_0, v_0 + v)``,\",\n \"batch depends on the maximum value of that tensor, and so may return\",\n \"[indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1) values, _ = torch.median(roll, -1)\",\n \"batch of spectrograms from a raw audio signal. The spectrogram can be either\",\n \"None): Norm to use (either 'ortho' or None) Returns: Tensor: The transformation matrix,\",\n \"torch.Tensor: waveform of (..., time), where time equals the ``length`` parameter if given.\",\n \"dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu\",\n \"length for median smoothing (in number of frames) (Default: ``30``). freq_low (int, optional):\",\n \"See also ```channels_first```. sample_rate (int): Sample rate of the audio waveform. format (str):\",\n \"Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law encoding\",\n \"waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default values are consistent with librosa.core.spectrum._spectrogram spec_f\",\n \"Args: complex_specgrams (Tensor): Dimension of `(..., freq, time, complex=2)` rate (float): Speed-up factor\",\n \"50.0) max_f0 (float, optional): Maximum F0 to search for (Hz) (default: 400.0) soft_min_f0\",\n \"Tensor, sample_rate: int, frame_time: float = 10 ** (-2), win_length: int = 30,\",\n \"-= ((cur_sum ** 2) / (window_frames ** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:,\",\n \"the same mask interval. Args: specgram (Tensor): Real spectrogram (channel, freq, time) mask_param\",\n \"freq_low: int = 85, freq_high: int = 3400, ) -> Tensor: r\\\"\\\"\\\"Detect pitch\",\n \"r\\\"\\\"\\\"Compute the norm of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of\",\n \"search for (Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum f0, applied in soft\",\n \"float, f_max: float, n_mels: int, sample_rate: int, norm: Optional[str] = None, mel_scale: str\",\n \"f\\\"Or, the value for `n_freqs` ({n_freqs}) may be set too low.\\\" ) return\",\n \"(x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1, 1)) # Repack batch x_db =\",\n \"optional): If this is set to false, the incomplete frames near the ending\",\n \"is the number of window hops (n_frame). \\\"\\\"\\\" if pad > 0: #\",\n \"+ v)``, where ``v`` is sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0,\",\n \"bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0)\",\n \"float, frame_length: float = 25.0, frame_shift: float = 10.0, min_f0: float = 50,\",\n \"+ f_sp * mels # And now the nonlinear scale min_log_hz = 1000.0\",\n \"mask interval. Args: specgram (Tensor): Real spectrogram (channel, freq, time) mask_param (int): Number\",\n \"7000, lowpass_filter_width: int = 1, upsample_filter_width: int = 5, max_frames_latency: int = 0,\",\n \"(channel, freq, time) \\\"\\\"\\\" # pack batch shape = specgram.size() specgram = specgram.reshape([-1]\",\n \"-1) return specgrams def mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float, axis: int\",\n \"shape = waveform.shape waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length,\",\n \"log_t = (mels >= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] -\",\n \"`Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has been scaled to between\",\n \"delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result = result.reshape(shape[:-1]\",\n \"window_end -= window_start window_start = 0 if not center: if window_end > t:\",\n \") ) # Update our phase estimates angles = rebuilt if momentum: angles\",\n \"# (n_freqs, n_mels) up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) fb\",\n \"torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag = alphas * norm_1\",\n \"for median smoothing (in number of frames) (Default: ``30``). freq_low (int, optional): Lowest\",\n \"incomplete frames near the ending edge won't be snipped, so that the number\",\n \"/ 27.0 if freq >= min_log_hz: mels = min_log_mel + math.log(freq / min_log_hz)\",\n \"max_frames_latency: int = 0, frames_per_chunk: int = 0, simulate_first_pass_online: bool = False, recompute_frame:\",\n \"int, window: Tensor, n_fft: int, hop_length: int, win_length: int, ) -> Tensor: r\\\"\\\"\\\"\",\n \"2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \\\"At least\",\n \"= t - cmn_window window_end = t + 1 if window_start < 0:\",\n \"of `(..., complex=2)` power (float): Power of the norm. (Default: `1.0`) Returns: (Tensor,\",\n \"mask_param: int, mask_value: float, axis: int ) -> Tensor: r\\\"\\\"\\\" Apply a mask\",\n \"* torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3]\",\n \"where :math:`d_t` is the deltas at time :math:`t`, :math:`c_t` is the spectrogram coeffcients\",\n \"quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law decoding \\\"\\\"\\\" mu\",\n \"of the audio waveform norm (Optional[str]): If 'slaney', divide the triangular mel weights\",\n \"to the masked columns axis (int): Axis to apply masking on (1 ->\",\n \"Args: freqs (float): Frequencies in Hz mel_scale (str, optional): Scale to use: ``htk``\",\n \"dimension (..., time) sample_rate (int): Sample rate of the audio waveform pad (int):\",\n \"(default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency for LowPass filter (Hz) (default: 1000)\",\n \"*= 2.0 else: assert norm == \\\"ortho\\\" dct[0] *= 1.0 / math.sqrt(2.0) dct\",\n \"str = \\\"replicate\\\" ) -> Tensor: r\\\"\\\"\\\"Compute delta coefficients of a tensor, usually\",\n \"to highlight/apply f_min (float): Minimum frequency (Hz) f_max (float): Maximum frequency (Hz) n_mels\",\n \"3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n, n + 1,\",\n \"hop_length: int, win_length: int, power: float, normalized: bool, n_iter: int, momentum: float, length:\",\n \"= torch.rand(1) * mask_param min_value = torch.rand(1) * (specgram.size(axis) - value) mask_start =\",\n \"enough max that is smallest best = torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1]\",\n \"number of frames. (default: True) Returns: Tensor: Pitch feature. Shape: ``(batch, frames 2)``\",\n \"f_sp # Fill in the log-scale part min_log_hz = 1000.0 min_log_mel = (min_log_hz\",\n \"effects). If false, window is to the left. (bool, default = false) norm_vars\",\n \"nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result = result.reshape(shape[:-1] +\",\n \"n_fft (int): Size of FFT, creates ``n_fft // 2 + 1`` bins hop_length\",\n \"cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int, pad: int,\",\n \"can be either magnitude-only or complex. Args: waveform (Tensor): Tensor of audio of\",\n \"to pad :attr:`waveform` on both sides so that the :math:`t`-th frame is centered\",\n \"values for an audio clip split into snippets vs. a full clip. Args:\",\n \"of results to avoid redundancy. Default: ``True`` Returns: Tensor: Dimension (..., freq, time),\",\n \"window_start: window_end - window_start, :] cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq +=\",\n \"= torch.linspace(0, sample_rate // 2, n_freqs) # calculate mel freq bins m_min =\",\n \"normalized: bool, n_iter: int, momentum: float, length: Optional[int], rand_init: bool ) -> Tensor:\",\n \"phase randomly if True, to zero otherwise. Returns: torch.Tensor: waveform of (..., time),\",\n \"import io import math import warnings from typing import Optional, Tuple import torch\",\n \"- 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu\",\n \"complex=2)` Return: Tensor: Angle of a complex tensor. Shape of `(..., )` \\\"\\\"\\\"\",\n \"10.0) penalty_factor (float, optional): Cost factor for FO change. (default: 0.1) lowpass_cutoff (float,\",\n \"\\\"create_fb_matrix\\\", \\\"create_dct\\\", \\\"compute_deltas\\\", \\\"detect_pitch_frequency\\\", \\\"DB_to_amplitude\\\", \\\"mu_law_encoding\\\", \\\"mu_law_decoding\\\", \\\"complex_norm\\\", \\\"angle\\\", \\\"magphase\\\", \\\"phase_vocoder\\\", 'mask_along_axis', 'mask_along_axis_iid',\",\n \"angles.sin()], dim=-1) \\\\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous\",\n \"(Tensor): Real spectrogram (channel, freq, time) mask_param (int): Number of columns to be\",\n \"(Default: ``\\\"replicate\\\"``) Returns: Tensor: Tensor of deltas of dimension (..., freq, time) Example\",\n \"a spectrogram or a batch of spectrograms from a raw audio signal. The\",\n \"to return half of results to avoid redundancy. Default: ``True`` Returns: Tensor: Dimension\",\n \"Returns: Tensor: The transformation matrix, to be right-multiplied to row-wise data of size\",\n \"bin conversion matrix. Args: n_freqs (int): Number of frequencies to highlight/apply f_min (float):\",\n \"makes different types of features give the same number of frames. (default: True)\",\n \">= 3 n = (win_length - 1) // 2 # twice sum of\",\n \"torch.min(down_slopes, up_slopes)) if norm is not None and norm == \\\"slaney\\\": # Slaney-style\",\n \"enorm = 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if\",\n \"v)``. Args: specgrams (Tensor): Real spectrograms (batch, channel, freq, time) mask_param (int): Number\",\n \"torchaudio __all__ = [ \\\"spectrogram\\\", \\\"griffinlim\\\", \\\"amplitude_to_DB\\\", \\\"DB_to_amplitude\\\", \\\"compute_deltas\\\", \\\"compute_kaldi_pitch\\\", \\\"create_fb_matrix\\\", \\\"create_dct\\\", \\\"compute_deltas\\\",\",\n \"quantization_channels - 1 and returns a signal scaled between -1 and 1. Args:\",\n \"can be detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor of freq of dimension\",\n \"for FO change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency for LowPass filter\",\n \"mel filterbank has all zero values. \\\" f\\\"The value for `n_mels` ({n_mels}) may\",\n \"rate of the audio waveform norm (Optional[str]): If 'slaney', divide the triangular mel\",\n \"logstep return mels def _mel_to_hz(mels: Tensor, mel_scale: str = \\\"htk\\\") -> Tensor: \\\"\\\"\\\"Convert\",\n \"n_mfcc (int): Number of mfc coefficients to retain n_mels (int): Number of mel\",\n \"* math.pi * torch.rand(batch, freq, frames) else: angles = torch.zeros(batch, freq, frames) angles\",\n \"Tensor: r\\\"\\\"\\\"Create a DCT transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized depending on\",\n \"phase_advance phase = phase - 2 * math.pi * torch.round(phase / (2 *\",\n \"typing import Optional, Tuple import torch from torch import Tensor from torchaudio._internal import\",\n \"audio of dimension (..., time) pad (int): Two sided padding of signal window\",\n \"1) // 2 # twice sum of integer squared denom = n *\",\n \"0``. (default: 500) snip_edges (bool, optional): If this is set to false, the\",\n \"= 600) min_cmn_window (int, optional): Minimum CMN window used at start of decoding\",\n \"/ freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length\",\n \"waveform: Tensor, sample_rate: int, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length:\",\n \"spectrogram(s) before being converted to decibel scale. Input should take the form `(...,\",\n \"= True, pad_mode: str = \\\"reflect\\\", onesided: bool = True ) -> Tensor:\",\n \"not x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) *\",\n \"* [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1) values, _ = torch.median(roll,\",\n \"can be unstable'.format(momentum) assert momentum >= 0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn(\",\n \"(float): Use 10. for power and 20. for amplitude amin (float): Number to\",\n \"torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1, 1)) # Repack batch x_db\",\n \"from indices ``[v_0, v_0 + v)``, where ``v`` is sampled from ``uniform(0, mask_param)``,\",\n \"# unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform:\",\n \"tensor in power/amplitude scale. \\\"\\\"\\\" return ref * torch.pow(torch.pow(10.0, 0.1 * x), power)\",\n \"\\\"create_dct\\\", \\\"compute_deltas\\\", \\\"detect_pitch_frequency\\\", \\\"DB_to_amplitude\\\", \\\"mu_law_encoding\\\", \\\"mu_law_decoding\\\", \\\"complex_norm\\\", \\\"angle\\\", \\\"magphase\\\", \\\"phase_vocoder\\\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn',\",\n \":py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit depth for the supported formats. For\",\n \"magnitude spectrogram using the Griffin-Lim transformation. Implementation ported from `librosa`. * [1] McFee,\",\n \"torch.Tensor, sample_rate: float, frame_length: float = 25.0, frame_shift: float = 10.0, min_f0: float\",\n \"= torch.cos(math.pi / float(n_mels) * (n + 0.5) * k) # size (n_mfcc,\",\n \"True) Returns: Tensor: Pitch feature. Shape: ``(batch, frames 2)`` where the last dimension\",\n \"2595.0 * math.log10(1.0 + (freq / 700.0)) # Fill in the linear part\",\n \"window_start = 0 if last_window_start == -1: input_part = waveform[:, window_start: window_end -\",\n \"``win_length // 2``) win_length (int): Window size. (Default: ``n_fft``) power (float): Exponent for\",\n \"f_sp = 200.0 / 3 freqs = f_min + f_sp * mels #\",\n \"compute_deltas(delta) \\\"\\\"\\\" device = specgram.device dtype = specgram.dtype # pack batch shape =\",\n \"> thresh * b[0]) values = mask * a[0] + ~mask * b[0]\",\n \"= list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low)\",\n \"mask mask_start = min_value[..., None, None] mask_end = (min_value + value)[..., None, None]\",\n \"= t + 1 if window_start < 0: window_end -= window_start window_start =\",\n \"(NCCF). .. math:: \\\\phi_i(m) = \\\\frac{\\\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\\\phi_i(m)`\",\n \"= x_db.size() packed_channels = shape[-3] if x_db.dim() > 2 else 1 x_db =\",\n \"if window_start < 0: window_end -= window_start window_start = 0 if not center:\",\n \"center: if window_end > t: window_end = max(t + 1, min_cmn_window) if window_end\",\n \"2) window_frames = window_end - window_start last_window_start = window_start last_window_end = window_end cmn_waveform[:,\",\n \"inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the\",\n \"is the deltas at time :math:`t`, :math:`c_t` is the spectrogram coeffcients at time\",\n \"bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\\\"rate\\\", f\\\"{sample_rate}\\\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi()\",\n \"r\\\"\\\"\\\"Turn a tensor from the decibel scale to the power/amplitude scale. Args: x\",\n \"2) / (window_frames ** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :] *=\",\n \"more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit depth for the\",\n \"= 5, max_frames_latency: int = 0, frames_per_chunk: int = 0, simulate_first_pass_online: bool =\",\n \"torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\\\ .to(dtype=specgram.dtype, device=specgram.device) specgram =\",\n \"complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps\",\n \"int ) -> Tensor: r\\\"\\\"\\\"Decode mu-law encoded signal. For more info see the\",\n \"initialize the previous iterate to 0 rebuilt = torch.tensor(0.) for _ in range(n_iter):\",\n \"amplitude_to_DB( x: Tensor, multiplier: float, amin: float, db_multiplier: float, top_db: Optional[float] = None\",\n \"a raw audio signal. The spectrogram can be either magnitude-only or complex. Args:\",\n \"return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Decode mu-law\",\n \"torch.cumsum(phase, -1) mag = alphas * norm_1 + (1 - alphas) * norm_0\",\n \"-1, shape[-1]) assert win_length >= 3 n = (win_length - 1) // 2\",\n \"processing (affects output only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk\",\n \"if norm is not None and norm == \\\"slaney\\\": # Slaney-style mel is\",\n \"or None): Exponent for the magnitude spectrogram, (must be > 0) e.g., 1\",\n \"see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has been scaled\",\n \"[ \\\"spectrogram\\\", \\\"griffinlim\\\", \\\"amplitude_to_DB\\\", \\\"DB_to_amplitude\\\", \\\"compute_deltas\\\", \\\"compute_kaldi_pitch\\\", \\\"create_fb_matrix\\\", \\\"create_dct\\\", \\\"compute_deltas\\\", \\\"detect_pitch_frequency\\\", \\\"DB_to_amplitude\\\", \\\"mu_law_encoding\\\",\",\n \"Args: waveform (Tensor): Tensor of audio of dimension (..., time) pad (int): Two\",\n \"Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter banks\",\n \"mask_value else: raise ValueError('Only Frequency and Time masking are supported') # unpack batch\",\n \"specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert win_length >= 3 n = (win_length\",\n \"Function (NCCF). .. math:: \\\\phi_i(m) = \\\\frac{\\\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\\\sqrt{E(b_i) E(m+b_i)}}, where\",\n \"/ (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) )\",\n \"is applied/multiplied to each frame/window n_fft (int): Size of FFT, creates ``n_fft //\",\n \"offset indices += 1 return indices def _median_smoothing( indices: Tensor, win_length: int )\",\n \"dimension corresponds to pitch and NCCF. Reference: - A pitch extraction algorithm tuned\",\n \"if window_start < 0: window_start = 0 if last_window_start == -1: input_part =\",\n \"vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor): A magnitude-only STFT spectrogram of\",\n \"between STFT windows win_length (int): Window size Returns: Tensor: Dimension (..., time) \\\"\\\"\\\"\",\n \"mel filterbanks sample_rate (int): Sample rate of the audio waveform norm (Optional[str]): If\",\n \"Tensor]: \\\"\\\"\\\" Take value from first if bigger than a multiplicative factor of\",\n \"pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1\",\n \"roll = indices.unfold(-1, win_length, 1) values, _ = torch.median(roll, -1) return values def\",\n \"of `(..., )` \\\"\\\"\\\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor,\",\n \"Input spectrogram(s) before being converted to decibel scale. Input should take the form\",\n \"pitch based on method described in [1]. This function computes the equivalent of\",\n \"``n_mfcc``), normalized depending on norm. Args: n_mfcc (int): Number of mfc coefficients to\",\n \"fast Griffin-Lim. Setting this to 0 recovers the original Griffin-Lim method. Values near\",\n \"clip split into snippets vs. a full clip. Args: x (Tensor): Input spectrogram(s)\",\n \"(int): Number of mel filterbanks norm (str or None): Norm to use (either\",\n \"torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, )\",\n \"Masked spectrogram of dimensions (channel, freq, time) \\\"\\\"\\\" # pack batch shape =\",\n \"Tensor: r\\\"\\\"\\\" Compute Normalized Cross-Correlation Function (NCCF). .. math:: \\\\phi_i(m) = \\\\frac{\\\\sum_{n=b_i}^{b_i +\",\n \"Tensor, win_length: int ) -> Tensor: r\\\"\\\"\\\" Apply median smoothing to the 1D\",\n \") -> Tensor: r\\\"\\\"\\\" Apply sliding-window cepstral mean (and optionally variance) normalization per\",\n \"- num_frames) window_end = num_frames if window_start < 0: window_start = 0 if\",\n \"of frames is the file size divided by the frame-shift. This makes different\",\n \"each channel along the time axis. The spectral centroid is defined as the\",\n \":math:`t`, :math:`c_t` is the spectrogram coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args:\",\n \"r\\\"\\\"\\\" Apply codecs as a form of augmentation. Args: waveform (Tensor): Audio data.\",\n \"torch.Tensor: \\\"\\\"\\\"Extract pitch based on method described in [1]. This function computes the\",\n \"example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end),\",\n \"lags to check lags = int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate * frame_time))\",\n \"waveform.shape num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0]\",\n \"freq is ``n_fft // 2 + 1``. window (Tensor): Window tensor that is\",\n \"energy. Relevant if ``frames_per_chunk > 0``. (default: 500) snip_edges (bool, optional): If this\",\n \"Returns: mels (float): Frequency in Mels \\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']:\",\n \"= waveform.shape waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift,\",\n \"pass of decoding -- not the final version of the features, which is\",\n \"time :math:`t \\\\times \\\\text{hop\\\\_length}`. Default: ``True`` pad_mode (string, optional): controls the padding method\",\n \"/ 2595.0) - 1.0) # Fill in the linear scale f_min = 0.0\",\n \"in v0.9.0 release. To suppress this warning, \\\" \\\"please use `normalized=False`.\\\") # pack\",\n \"not in ['slaney', 'htk']: raise ValueError('mel_scale should be one of \\\"htk\\\" or \\\"slaney\\\".')\",\n \"False, ) -> Tensor: r\\\"\\\"\\\" Apply sliding-window cepstral mean (and optionally variance) normalization\",\n \"Tensor: r\\\"\\\"\\\" Apply median smoothing to the 1D tensor over the given window.\",\n \"win_length) # Convert indices to frequency EPSILON = 10 ** (-9) freq =\",\n \"= torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1, 1)) # Repack batch\",\n \"is the length of a frame, :math:`b_i` is the beginning of frame :math:`i`,\",\n \"p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf def _combine_max( a:\",\n \"freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform:\",\n \") -> Tensor: r\\\"\\\"\\\"Compute delta coefficients of a tensor, usually a spectrogram: ..\",\n \"of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power\",\n \"-> Tensor: r\\\"\\\"\\\" Apply a mask along ``axis``. Mask will be applied from\",\n \") -> Tuple[Tensor, Tensor]: \\\"\\\"\\\" Take value from first if bigger than a\",\n \"# Fill in the linear part f_min = 0.0 f_sp = 200.0 /\",\n \"channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float\",\n \"of the normed input tensor. Shape of `(..., )` \\\"\\\"\\\" # Replace by\",\n \"-> Tuple[Tensor, Tensor]: \\\"\\\"\\\" Take value from first if bigger than a multiplicative\",\n \"r\\\"\\\"\\\"Encode signal based on mu-law companding. For more info see the `Wikipedia Entry\",\n \"(default: True) Returns: Tensor: Pitch feature. Shape: ``(batch, frames 2)`` where the last\",\n \"+ 1) / 2 * mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu:\",\n \"Power of the normed input tensor. Shape of `(..., )` \\\"\\\"\\\" # Replace\",\n \"All examples will have the same mask interval. Args: specgram (Tensor): Real spectrogram\",\n \"x: Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Encode signal based on mu-law companding.\",\n \"mask_start:mask_end] = mask_value elif axis == 2: specgram[:, :, mask_start:mask_end] = mask_value else:\",\n \"output.reshape(shape) return output def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float, freq_low: int\",\n \"each bin. Dimension of (freq, 1) Returns: Tensor: Complex Specgrams Stretch with dimension\",\n \"torch.log1p(mu) x_mu = ((x_mu + 1) / 2 * mu + 0.5).to(torch.int64) return\",\n \"= _median_smoothing(indices, win_length) # Convert indices to frequency EPSILON = 10 ** (-9)\",\n \"1, will compute DB to power. If 0.5, will compute DB to amplitude.\",\n \"Window size Returns: Tensor: Dimension (..., time) \\\"\\\"\\\" specgram = spectrogram(waveform, pad=pad, window=window,\",\n \"specgrams = specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram: Tensor, mask_param: int, mask_value:\",\n \"specgrams (Tensor): Real spectrograms (batch, channel, freq, time) mask_param (int): Number of columns\",\n \"normalized=False) freqs = torch.linspace(0, sample_rate // 2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1,\",\n \"assert momentum < 1, 'momentum={} > 1 can be unstable'.format(momentum) assert momentum >=\",\n \"(Hz) (default: 1000) resample_frequency (float, optional): Frequency that we down-sample the signal to.\",\n \"complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` Return: Tensor:\",\n \"int, ) -> Tensor: r\\\"\\\"\\\" Compute the spectral centroid for each channel along\",\n \"optional): Frame length in milliseconds. (default: 25.0) frame_shift (float, optional): Frame shift in\",\n \"0 if not center: if window_end > t: window_end = max(t + 1,\",\n \"the 1D tensor over the given window. \\\"\\\"\\\" # Centered windowed pad_length =\",\n \"column is a filterbank so that assuming there is a matrix A of\",\n \"the expected output. rand_init (bool): Initializes phase randomly if True, to zero otherwise.\",\n \"int = 600, min_cmn_window: int = 100, center: bool = False, norm_vars: bool\",\n \"mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs\",\n \"_median_smoothing( indices: Tensor, win_length: int ) -> Tensor: r\\\"\\\"\\\" Apply median smoothing to\",\n \"n_mels: int, norm: Optional[str] ) -> Tensor: r\\\"\\\"\\\"Create a DCT transformation matrix with\",\n \"is sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. Args:\",\n \"top_db (float or None, optional): Minimum negative cut-off in decibels. A reasonable number\",\n \"= (min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0 log_t =\",\n \"return x_db def DB_to_amplitude( x: Tensor, ref: float, power: float ) -> Tensor:\",\n \"Relevant if ``frames_per_chunk > 0``. (default: 500) snip_edges (bool, optional): If this is\",\n \"must not exceed min-f0 (default: 10.0) penalty_factor (float, optional): Cost factor for FO\",\n \"(int): Length of hop between STFT windows. ( Default: ``win_length // 2``) win_length\",\n \"f_min) / f_sp logstep = math.log(6.4) / 27.0 if freq >= min_log_hz: mels\",\n \"500) snip_edges (bool, optional): If this is set to false, the incomplete frames\",\n \"-1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device)\",\n \"raise ValueError('mel_scale should be one of \\\"htk\\\" or \\\"slaney\\\".') if mel_scale == \\\"htk\\\":\",\n \"factor phase_advance (Tensor): Expected phase advance in each bin. Dimension of (freq, 1)\",\n \"= 0.0 f_sp = 200.0 / 3 freqs = f_min + f_sp *\",\n \"freq_high: int ) -> Tensor: r\\\"\\\"\\\" For each frame, take the highest value\",\n \"value of NCCF, apply centered median smoothing, and convert to frequency. Note: If\",\n \"the norm. (Default: `1.0`) Returns: (Tensor, Tensor): The magnitude and phase of the\",\n \"frame (to the extent possible, modulo end effects). If false, window is to\",\n \"banks (fb matrix) of size (``n_freqs``, ``n_mels``) meaning number of frequencies to highlight/apply\",\n \"waveform (Tensor): Tensor of audio of dimension (..., time) pad (int): Two sided\",\n \"axis. The spectral centroid is defined as the weighted average of the frequency\",\n \"in Mels \\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be\",\n \"Returns: Tensor: Output tensor in power/amplitude scale. \\\"\\\"\\\" return ref * torch.pow(torch.pow(10.0, 0.1\",\n \"2 # \\\"replicate\\\" padding in any dimension indices = torch.nn.functional.pad( indices, (pad_length, 0),\",\n \"\\\"slaney\\\": raise ValueError(\\\"norm must be one of None or 'slaney'\\\") # freq bins\",\n \"detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float = 10 ** (-2), win_length: int\",\n \"to padding (Default: ``\\\"replicate\\\"``) Returns: Tensor: Tensor of deltas of dimension (..., freq,\",\n \"stft freq point in hertz f_diff = f_pts[1:] - f_pts[:-1] # (n_mels +\",\n \"complex_tensor: Tensor, power: float = 1.0 ) -> Tuple[Tensor, Tensor]: r\\\"\\\"\\\"Separate a complex-valued\",\n \"specgram (Tensor): A magnitude-only STFT spectrogram of dimension (..., freq, frames) where freq\",\n \"2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs\",\n \"(str): File format. channels_first (bool): When True, both the input and output Tensor\",\n \"broadcastable mask mask_start = min_value[..., None, None] mask_end = (min_value + value)[..., None,\",\n \"lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames = ( (s1 * s2).sum(-1) / (EPSILON\",\n \"each mel point and each stft freq point in hertz f_diff = f_pts[1:]\",\n \"from ``uniform(0, max_v - v)``. All examples will have the same mask interval.\",\n \"the previous iterate tprev = rebuilt # Invert with our current estimate of\",\n \"output. rand_init (bool): Initializes phase randomly if True, to zero otherwise. Returns: torch.Tensor:\",\n \"# create overlapping triangles zero = torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2])\",\n \"use a window centered on the current frame (to the extent possible, modulo\",\n \"200.0 / 3 mels = (freq - f_min) / f_sp # Fill in\",\n \"700.0 * (10.0**(mels / 2595.0) - 1.0) # Fill in the linear scale\",\n \"format, encoding, bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\\\"rate\\\", f\\\"{sample_rate}\\\"]], channels_first=channels_first,\",\n \"tensor that is applied/multiplied to each frame/window n_fft (int): Size of FFT, creates\",\n \"int = 30, freq_low: int = 85, freq_high: int = 3400, ) ->\",\n \"Number of frequencies to highlight/apply f_min (float): Minimum frequency (Hz) f_max (float): Maximum\",\n \"snippets vs. a full clip. Args: x (Tensor): Input spectrogram(s) before being converted\",\n \"+ (freq / 700.0)) # Fill in the linear part f_min = 0.0\",\n \"shape (``n_mels``, ``n_mfcc``), normalized depending on norm. Args: n_mfcc (int): Number of mfc\",\n \"torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 - angle_0\",\n \"window_start > last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum -= frame_to_remove if norm_vars:\",\n \"tensor in a batch depends on the maximum value of that tensor, and\",\n \"Power of the norm. (Default: `1.0`) Returns: (Tensor, Tensor): The magnitude and phase\",\n \"int = 1, upsample_filter_width: int = 5, max_frames_latency: int = 0, frames_per_chunk: int\",\n \"lag_min:half_size], -1) best = _combine_max(half, best) indices = best[1] # Add back minimal\",\n \"``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels converted in Hz \\\"\\\"\\\"\",\n \"Tensor: Pitch feature. Shape: ``(batch, frames 2)`` where the last dimension corresponds to\",\n \"2)`` where the last dimension corresponds to pitch and NCCF. Reference: - A\",\n \">= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs\",\n \"that determines filter width of lowpass filter, more gives sharper filter. (default: 1)\",\n \"= torch.stack([angles.cos(), angles.sin()], dim=-1) \\\\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize\",\n \"\\\"\\\"\\\" device = specgram.device dtype = specgram.dtype # pack batch shape = specgram.size()\",\n \"would see in the first pass of decoding -- not the final version\",\n \"optional): Frequency that we down-sample the signal to. Must be more than twice\",\n \"pitch frequency. It is implemented using normalized cross-correlation function and median smoothing. Args:\",\n \"of columns to be masked will be uniformly sampled from [0, mask_param] mask_value\",\n \"original Griffin-Lim method. Values near 1 can lead to faster convergence, but above\",\n \"return mag, phase def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor ) ->\",\n \"w(n) w(m+n)}{\\\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\\\phi_i(m)` is the NCCF at frame :math:`i` with lag\",\n \") indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length,\",\n \"McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \\\"librosa: Audio and music\",\n \"waveform[:, window_start: window_end - window_start, :] cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq\",\n \"phase estimates waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) #\",\n \"f_min = 0.0 f_sp = 200.0 / 3 freqs = f_min + f_sp\",\n \"Tensor ) -> Tensor: r\\\"\\\"\\\"Compute the angle of complex tensor input. Args: complex_tensor\",\n \"+ momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates waveform =\",\n \"triangles zero = torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2]) / f_diff[:-1] #\",\n \"``htk``) Returns: mels (float): Frequency in Mels \\\"\\\"\\\" if mel_scale not in ['slaney',\",\n \"magphase( complex_tensor: Tensor, power: float = 1.0 ) -> Tuple[Tensor, Tensor]: r\\\"\\\"\\\"Separate a\",\n \"1025, 231, 2]) \\\"\\\"\\\" # pack batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1]\",\n \"mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch =\",\n \"pad_mode: str = \\\"reflect\\\", onesided: bool = True ) -> Tensor: r\\\"\\\"\\\"Create a\",\n \"mask_end = (min_value + value)[..., None, None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype)\",\n \"raise ValueError('Only Frequency and Time masking are supported') # unpack batch specgram =\",\n \"num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for t\",\n \"waveform of (..., time), where time equals the ``length`` parameter if given. \\\"\\\"\\\"\",\n \"(Default: ``htk``) Returns: mels (float): Frequency in Mels \\\"\\\"\\\" if mel_scale not in\",\n \"Size of FFT, creates ``n_fft // 2 + 1`` bins hop_length (int): Length\",\n \"pitch extraction algorithm tuned for automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME>\",\n \"** 2) window_frames = window_end - window_start last_window_start = window_start last_window_end = window_end\",\n \"rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1, :])\",\n \"to one. (bool, default = false) Returns: Tensor: Tensor of freq of dimension\",\n \"= torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n, n + 1, 1, device=device,\",\n \"the previous iterate to 0 rebuilt = torch.tensor(0.) for _ in range(n_iter): #\",\n \"Griffin-Lim, \\\" \\\"and will be removed in v0.9.0 release. To suppress this warning,\",\n \"windows. ( Default: ``win_length // 2``) win_length (int): Window size. (Default: ``n_fft``) power\",\n \"specgram[:, :, mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency and Time masking are\",\n \"1.0) # Fill in the linear scale f_min = 0.0 f_sp = 200.0\",\n \"device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value)\",\n \"/ f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs,\",\n \"N-1} w(n) w(m+n)}{\\\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\\\phi_i(m)` is the NCCF at frame :math:`i` with\",\n \"(int): The sample rate of the waveform (Hz) frame_time (float, optional): Duration of\",\n \"overlapping triangles zero = torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2]) / f_diff[:-1]\",\n \"and Acoustics (pp. 1-4), Oct. 2013. * [3] <NAME> and <NAME>, \\\"Signal estimation\",\n \"torch.linspace(0, sample_rate // 2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim =\",\n \"Minimum f0, applied in soft way, must not exceed min-f0 (default: 10.0) penalty_factor\",\n \"or complex. Args: waveform (Tensor): Tensor of audio of dimension (..., time) pad\",\n \"\\\"\\\"\\\" shape = waveform.shape waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate,\",\n \"output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack batch output = output.reshape(shape)\",\n \"the frame-shift. This makes different types of features give the same number of\",\n \"25.0, frame_shift: float = 10.0, min_f0: float = 50, max_f0: float = 400,\",\n \"Tensor, sample_rate: int, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int,\",\n \"win_length (int): Window size power (float or None): Exponent for the magnitude spectrogram,\",\n \"and have the form `(batch, channel, freq, time)`. multiplier (float): Use 10. for\",\n \"cut-off in decibels. A reasonable number is 80. (Default: ``None``) Returns: Tensor: Output\",\n \"quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype)\",\n \"io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented, _\",\n \"the masked columns axis (int): Axis to apply masking on (1 -> frequency,\",\n \"lags = int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1]\",\n \"Tensor], thresh: float = 0.99 ) -> Tuple[Tensor, Tensor]: \\\"\\\"\\\" Take value from\",\n \"Window in frames for running average CMN computation (int, default = 600) min_cmn_window\",\n \"to the 1D tensor over the given window. \\\"\\\"\\\" # Centered windowed pad_length\",\n \"= torch.cumsum(phase, -1) mag = alphas * norm_1 + (1 - alphas) *\",\n \"r\\\"\\\"\\\" Apply sliding-window cepstral mean (and optionally variance) normalization per utterance. Args: waveform\",\n \"(int, optional): Window in frames for running average CMN computation (int, default =\",\n \"min_f0 (float, optional): Minimum F0 to search for (Hz) (default: 50.0) max_f0 (float,\",\n \"true, use a window centered on the current frame (to the extent possible,\",\n \"* (2 * n + 1) / 3 specgram = torch.nn.functional.pad(specgram, (n, n),\",\n \"(torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu return x def complex_norm( complex_tensor: Tensor,\",\n \"freq = sample_rate / (EPSILON + indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1]\",\n \"= io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented,\",\n \"non-critical parameter; the frame at which we recompute some of the forward pointers,\",\n \"!= 3: raise ValueError('Only Frequency and Time masking are supported') device = specgrams.device\",\n \"float = 0.1, lowpass_cutoff: float = 1000, resample_frequency: float = 4000, delta_pitch: float\",\n \"= 10 ** (-9) freq = sample_rate / (EPSILON + indices.to(torch.float)) # unpack\",\n \"specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) * mask_param min_value = torch.rand(1) * (specgram.size(axis)\",\n \"min_log_mel = (min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0 log_t\",\n \"\\\"compute_deltas\\\", \\\"detect_pitch_frequency\\\", \\\"DB_to_amplitude\\\", \\\"mu_law_encoding\\\", \\\"mu_law_decoding\\\", \\\"complex_norm\\\", \\\"angle\\\", \\\"magphase\\\", \\\"phase_vocoder\\\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \\\"spectral_centroid\\\",\",\n \"window=window, length=length).float() # Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length,\",\n \"both sides so that the :math:`t`-th frame is centered at time :math:`t \\\\times\",\n \"at start). Only applicable if center == false, ignored if center==true (int, default\",\n \"cmn_window window_end = t + 1 if window_start < 0: window_end -= window_start\",\n \"expects an input with values between 0 and quantization_channels - 1 and returns\",\n \"power) # randomly initialize the phase batch, freq, frames = specgram.size() if rand_init:\",\n \"# Repack batch x_db = x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor, ref:\",\n \"= \\\\frac{\\\\sum_{n=1}^{\\\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\\\sum_{n=1}^{\\\\text{N}} n^2} where :math:`d_t` is the deltas\",\n \"Changes the encoding for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample\",\n \"-> Tensor: r\\\"\\\"\\\"Given a STFT tensor, speed up in time without modifying pitch\",\n \"= None, ) -> Tensor: r\\\"\\\"\\\" Apply codecs as a form of augmentation.\",\n \"mask_end - mask_start < mask_param if axis == 1: specgram[:, mask_start:mask_end] = mask_value\",\n \"f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \\\"At least one mel\",\n \"0, frames_per_chunk: int = 0, simulate_first_pass_online: bool = False, recompute_frame: int = 500,\",\n \"] def spectrogram( waveform: Tensor, pad: int, window: Tensor, n_fft: int, hop_length: int,\",\n \"= complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value:\",\n \"= 0 if last_window_start == -1: input_part = waveform[:, window_start: window_end - window_start,\",\n \"between -1 and 1 and returns a signal encoded with values from 0\",\n \"passed to padding (Default: ``\\\"replicate\\\"``) Returns: Tensor: Tensor of deltas of dimension (...,\",\n \"compute DB to amplitude. Returns: Tensor: Output tensor in power/amplitude scale. \\\"\\\"\\\" return\",\n \"raise ValueError('Only Frequency and Time masking are supported') device = specgrams.device dtype =\",\n \"freq bins # Equivalent filterbank construction by Librosa all_freqs = torch.linspace(0, sample_rate //\",\n \"frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p = lags +\",\n \"nccf = torch.cat(output_lag, -1) return nccf def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor,\",\n \"signal analysis in python.\\\" In Proceedings of the 14th python in science conference,\",\n \"pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1) values, _ = torch.median(roll, -1) return\",\n \"cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance = cur_sumsq\",\n \"(int): Number of channels Returns: Tensor: Input after mu-law decoding \\\"\\\"\\\" mu =\",\n \"phase_advance (Tensor): Expected phase advance in each bin. Dimension of (freq, 1) Returns:\",\n \"not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) /\",\n \"smoothing. Args: waveform (Tensor): Tensor of audio of dimension (..., freq, time) sample_rate\",\n \"- waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) # Compute lags output_lag = []\",\n \"a DCT transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized depending on norm. Args:\",\n \"n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) * (n\",\n \"If this is set to false, the incomplete frames near the ending edge\",\n \"be either magnitude-only or complex. Args: waveform (Tensor): Tensor of audio of dimension\",\n \"window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) # Update our phase estimates\",\n \"Tensor, mel_scale: str = \\\"htk\\\") -> Tensor: \\\"\\\"\\\"Convert mel bin numbers to frequencies.\",\n \"inputs should include a channel dimension and have the form `(batch, channel, freq,\",\n \"fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \\\"At least one mel filterbank\",\n \"power: float = 1.0 ) -> Tuple[Tensor, Tensor]: r\\\"\\\"\\\"Separate a complex-valued spectrogram with\",\n \"equals the ``length`` parameter if given. \\\"\\\"\\\" assert momentum < 1, 'momentum={} >\",\n \"win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft,\",\n \"time) \\\"\\\"\\\" if axis != 2 and axis != 3: raise ValueError('Only Frequency\",\n \"else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2,\",\n \"padding of signal window (Tensor): Window tensor that is applied/multiplied to each frame/window\",\n \"mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts =\",\n \"2 -> time) Returns: Tensor: Masked spectrogram of dimensions (channel, freq, time) \\\"\\\"\\\"\",\n \"can be detected (Hz) (Default: ``85``). freq_high (int, optional): Highest frequency that can\",\n \"(Tensor): Audio data. Must be 2 dimensional. See also ```channels_first```. sample_rate (int): Sample\",\n \"values from 0 to quantization_channels - 1. Args: x (Tensor): Input tensor quantization_channels\",\n \"waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype device = waveform.device last_window_start\",\n \"assign to the masked columns axis (int): Axis to apply masking on (2\",\n \"\\\"please use `normalized=False`.\\\") # pack batch shape = specgram.size() specgram = specgram.reshape([-1] +\",\n \"if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The number\",\n \"hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return\",\n \"specgrams: Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor: r\\\"\\\"\\\" Apply\",\n \"exceed min-f0 (default: 10.0) penalty_factor (float, optional): Cost factor for FO change. (default:\",\n \"optional): Maximum number of frames of latency that we allow pitch tracking to\",\n \"0) e.g., 1 for energy, 2 for power, etc. If None, then the\",\n \"f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) # create overlapping triangles zero\",\n \"The momentum parameter for fast Griffin-Lim. Setting this to 0 recovers the original\",\n \"freq, time), freq is ``n_fft // 2 + 1`` and ``n_fft`` is the\",\n \"(Tensor): Tensor of audio of dimension (..., time) pad (int): Two sided padding\",\n \"= torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch,\",\n \"Librosa all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) # calculate mel freq bins\",\n \"to apply masking on (2 -> frequency, 3 -> time) Returns: Tensor: Masked\",\n \"there is a matrix A of size (..., ``n_freqs``), the applied result would\",\n \"(Default: ``htk``) Returns: Tensor: Triangular filter banks (fb matrix) of size (``n_freqs``, ``n_mels``)\",\n \"scaled to be approx constant energy per channel enorm = 2.0 / (f_pts[2:n_mels\",\n \"the waveform, :math:`N` is the length of a frame, :math:`b_i` is the beginning\",\n \"freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length) # Convert indices\",\n \"(int, optional): Maximum number of frames of latency that we allow pitch tracking\",\n \"of frequencies to highlight/apply f_min (float): Minimum frequency (Hz) f_max (float): Maximum frequency\",\n \"_mel_to_hz(mels: Tensor, mel_scale: str = \\\"htk\\\") -> Tensor: \\\"\\\"\\\"Convert mel bin numbers to\",\n \"= alphas * norm_1 + (1 - alphas) * norm_0 real_stretch = mag\",\n \"mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram: Tensor, mask_param:\",\n \":math:`N` is the length of a frame, :math:`b_i` is the beginning of frame\",\n \"+ ~mask * b[0] indices = mask * a[1] + ~mask * b[1]\",\n \"\\\"\\\"\\\" # pack batch shape = list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf\",\n \"'ortho' or None) Returns: Tensor: The transformation matrix, to be right-multiplied to row-wise\",\n \"torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu + 1) /\",\n \"formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it\",\n \"cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype,\",\n \"sample_rate (int): Sample rate of the audio waveform. format (str): File format. channels_first\",\n \"x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier if top_db\",\n \"Args: n_mfcc (int): Number of mfc coefficients to retain n_mels (int): Number of\",\n \"results to avoid redundancy. Default: ``True`` Returns: Tensor: Dimension (..., freq, time), freq\",\n \"*= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding(\",\n \"_ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\\\"rate\\\", f\\\"{sample_rate}\\\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch(\",\n \"if momentum: angles = angles - tprev.mul_(momentum / (1 + momentum)) angles =\",\n \"// 2 # twice sum of integer squared denom = n * (n\",\n \"energy :math:`\\\\sum_{n=j}^{j+N-1} w^2(n)`. \\\"\\\"\\\" EPSILON = 10 ** (-9) # Number of lags\",\n \"power=1., normalized=False) freqs = torch.linspace(0, sample_rate // 2, steps=1 + n_fft // 2,\",\n \"transformation. Implementation ported from `librosa`. * [1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>,\",\n \"Args: waveform (Tensor): The input waveform of shape `(..., time)`. sample_rate (float): Sample\",\n \"frames) where freq is ``n_fft // 2 + 1``. window (Tensor): Window tensor\",\n \"Example >>> specgram = torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram) >>> delta2\",\n \"frame :math:`i`, :math:`E(j)` is the energy :math:`\\\\sum_{n=j}^{j+N-1} w^2(n)`. \\\"\\\"\\\" EPSILON = 10 **\",\n \"# freq bins # Equivalent filterbank construction by Librosa all_freqs = torch.linspace(0, sample_rate\",\n \"denom # unpack batch output = output.reshape(shape) return output def _compute_nccf( waveform: Tensor,\",\n \"average CMN computation (int, default = 600) min_cmn_window (int, optional): Minimum CMN window\",\n \"center: window_start = t - cmn_window // 2 window_end = window_start + cmn_window\",\n \"for the magnitude spectrogram, (must be > 0) e.g., 1 for energy, 2\",\n \"else: variance = cur_sumsq variance = variance / window_frames variance -= ((cur_sum **\",\n \"*= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform\",\n \"= False, recompute_frame: int = 500, snip_edges: bool = True, ) -> torch.Tensor:\",\n \"converted to power/amplitude scale. ref (float): Reference which the output will be scaled\",\n \"``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The number of frames used for energy\",\n \"1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu return\",\n \"on method described in [1]. This function computes the equivalent of `compute-kaldi-pitch-feats` from\",\n \"it waveform = torch.nn.functional.pad(waveform, (pad, pad), \\\"constant\\\") # pack batch shape = waveform.size()\",\n \"waveform (Hz) frame_time (float, optional): Duration of a frame (Default: ``10 ** (-2)``).\",\n \"optional): Cost factor for FO change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency\",\n \"(Tensor): Mels converted in Hz \\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']: raise\",\n \"the latter is taken. \\\"\\\"\\\" lag_min = int(math.ceil(sample_rate / freq_high)) # Find near\",\n \"to the decibel scale. The output of each tensor in a batch depends\",\n \"shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 / power)\",\n \"// 2``) win_length (int): Window size. (Default: ``n_fft``) power (float): Exponent for the\",\n \"torch.no_grad():\\\" back when JIT supports it waveform = torch.nn.functional.pad(waveform, (pad, pad), \\\"constant\\\") #\",\n \"win_length (int): Window size. (Default: ``n_fft``) power (float): Exponent for the magnitude spectrogram,\",\n \"x: Tensor, ref: float, power: float ) -> Tensor: r\\\"\\\"\\\"Turn a tensor from\",\n \"math.log(6.4) / 27.0 if freq >= min_log_hz: mels = min_log_mel + math.log(freq /\",\n \"= torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for t in range(num_frames): window_start =\",\n \"3400, ) -> Tensor: r\\\"\\\"\\\"Detect pitch frequency. It is implemented using normalized cross-correlation\",\n \"torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has ``[channel, time]`` else ``[time, channel]``. \\\"\\\"\\\"\",\n \"= torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch example masking specgrams = specgrams.transpose(axis,\",\n \"dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1, :]) # Time\",\n \"dimension (..., time) pad (int): Two sided padding of signal window (Tensor): Window\",\n \"window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack batch spec_f = spec_f.reshape(shape[:-1]\",\n \"change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency for LowPass filter (Hz) (default:\",\n \"forward pointers, after revising our estimate of the signal energy. Relevant if ``frames_per_chunk\",\n \"the time axis. The spectral centroid is defined as the weighted average of\",\n \"= 10.0, min_f0: float = 50, max_f0: float = 400, soft_min_f0: float =\",\n \"normalize by magnitude after stft. n_iter (int): Number of iteration for phase recovery\",\n \"+ list(shape[-2:])) specgram = specgram.pow(1 / power) # randomly initialize the phase batch,\",\n \"- f_pts[:-1] # (n_mels + 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs,\",\n \"assign to the masked columns axis (int): Axis to apply masking on (1\",\n \"format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float =\",\n \"decibel scale. Input should take the form `(..., freq, time)`. Batched inputs should\",\n \"soft way, must not exceed min-f0 (default: 10.0) penalty_factor (float, optional): Cost factor\",\n \"<NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \\\"librosa: Audio and music signal analysis\",\n \"lowpass filter, more gives sharper filter. (default: 1) upsample_filter_width (int, optional): Integer that\",\n \"x_db.size() packed_channels = shape[-3] if x_db.dim() > 2 else 1 x_db = x_db.reshape(-1,\",\n \">>> x.shape # with 231 == ceil(300 / 1.3) torch.Size([2, 1025, 231, 2])\",\n \"lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result = result.reshape(shape[:-1] + result.shape[-2:])\",\n \"<NAME> and <NAME>, \\\"Signal estimation from modified short-time Fourier transform,\\\" IEEE Trans. ASSP,\",\n \"sample_rate // 2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2\",\n \"- top_db).view(-1, 1, 1, 1)) # Repack batch x_db = x_db.reshape(shape) return x_db\",\n \"angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch waveform = waveform.reshape(shape[:-2] +\",\n \"x (Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input after\",\n \"for computing delta (Default: ``5``) mode (str, optional): Mode parameter passed to padding\",\n \"form of augmentation. Args: waveform (Tensor): Audio data. Must be 2 dimensional. See\",\n \"(int): Number of mel filterbanks sample_rate (int): Sample rate of the audio waveform\",\n \"= torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0 =\",\n \"The number of frames used for energy normalization. (default: 0) simulate_first_pass_online (bool, optional):\",\n \"nccf def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float = 0.99\",\n \"audio signal. The spectrogram can be either magnitude-only or complex. Args: waveform (Tensor):\",\n \"specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 / power) # randomly initialize the phase\",\n \"Optional[str] ) -> Tensor: r\\\"\\\"\\\"Create a DCT transformation matrix with shape (``n_mels``, ``n_mfcc``),\",\n \"s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2)\",\n \"[3] <NAME> and <NAME>, \\\"Signal estimation from modified short-time Fourier transform,\\\" IEEE Trans.\",\n \"that is applied/multiplied to each frame/window n_fft (int): Size of FFT hop_length (int):\",\n \"device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack\",\n \":math:`i`, :math:`E(j)` is the energy :math:`\\\\sum_{n=j}^{j+N-1} w^2(n)`. \\\"\\\"\\\" EPSILON = 10 ** (-9)\",\n \"for energy, 2 for power, etc. normalized (bool): Whether to normalize by magnitude\",\n \"n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim) /\",\n \"`waveform`. frame_length (float, optional): Frame length in milliseconds. (default: 25.0) frame_shift (float, optional):\",\n \"and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The number of frames used for\",\n \"+ 1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[...,\",\n \"(num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid(\",\n \"augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float = 25.0, frame_shift:\",\n \"optional): controls whether to return half of results to avoid redundancy. Default: ``True``\",\n \"dct *= 2.0 else: assert norm == \\\"ortho\\\" dct[0] *= 1.0 / math.sqrt(2.0)\",\n \"of a frame, :math:`b_i` is the beginning of frame :math:`i`, :math:`E(j)` is the\",\n \"algorithm measures. (default: 0.005) nccf_ballast (float, optional): Increasing this factor reduces NCCF for\",\n \"between -1 and 1. Args: x_mu (Tensor): Input tensor quantization_channels (int): Number of\",\n \"from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. Args: specgrams (Tensor):\",\n \"b[1] return values, indices def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int )\",\n \"\\\"\\\"\\\" mu = quantization_channels - 1.0 if not x.is_floating_point(): x = x.to(torch.float) mu\",\n \"If None, then the complex spectrum is returned instead. normalized (bool): Whether to\",\n \"phase_advance: Tensor ) -> Tensor: r\\\"\\\"\\\"Given a STFT tensor, speed up in time\",\n \"win_length: int = 30, freq_low: int = 85, freq_high: int = 3400, )\",\n \"2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, 2014,\",\n \"augmentation. Args: waveform (Tensor): Audio data. Must be 2 dimensional. See also ```channels_first```.\",\n \"Returns: Tensor: Input after mu-law encoding \\\"\\\"\\\" mu = quantization_channels - 1.0 if\",\n \"maximum value of that tensor, and so may return different values for an\",\n \"complex=2)` Example >>> freq, hop_length = 1025, 512 >>> # (channel, freq, time,\",\n \"= 10.0, penalty_factor: float = 0.1, lowpass_cutoff: float = 1000, resample_frequency: float =\",\n \"torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) * (n + 0.5)\",\n \"- 1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x\",\n \"assert win_length >= 3 n = (win_length - 1) // 2 # twice\",\n \"<https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has been scaled to between -1 and\",\n \"retain n_mels (int): Number of mel filterbanks norm (str or None): Norm to\",\n \"b: Tuple[Tensor, Tensor], thresh: float = 0.99 ) -> Tuple[Tensor, Tensor]: \\\"\\\"\\\" Take\",\n \"thresh: float = 0.99 ) -> Tuple[Tensor, Tensor]: \\\"\\\"\\\" Take value from first\",\n \"231 == ceil(300 / 1.3) torch.Size([2, 1025, 231, 2]) \\\"\\\"\\\" # pack batch\",\n \"> num_frames: window_start -= (window_end - num_frames) window_end = num_frames if window_start <\",\n \"The spectral centroid is defined as the weighted average of the frequency values,\",\n \"in the log-scale part min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) /\",\n \"add \\\"with torch.no_grad():\\\" back when JIT supports it waveform = torch.nn.functional.pad(waveform, (pad, pad),\",\n \"in the linear scale f_min = 0.0 f_sp = 200.0 / 3 freqs\",\n \"companding. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the\",\n \"= True, compression: Optional[float] = None, encoding: Optional[str] = None, bits_per_sample: Optional[int] =\",\n \"should take the form `(..., freq, time)`. Batched inputs should include a channel\",\n \"max(t + 1, min_cmn_window) if window_end > num_frames: window_start -= (window_end - num_frames)\",\n \"x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1,\",\n \"be ``A * create_fb_matrix(A.size(-1), ...)``. \\\"\\\"\\\" if norm is not None and norm\",\n \"computation (int, default = 600) min_cmn_window (int, optional): Minimum CMN window used at\",\n \"if window_end > num_frames: window_start -= (window_end - num_frames) window_end = num_frames if\",\n \"\\\\sum_{n=1}^{\\\\text{N}} n^2} where :math:`d_t` is the deltas at time :math:`t`, :math:`c_t` is the\",\n \"indices def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int ) -> Tensor: r\\\"\\\"\\\"\",\n \"``3400``). Returns: Tensor: Tensor of freq of dimension (..., frame) \\\"\\\"\\\" # pack\",\n \":] else: if window_start > last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum -=\",\n \"specgram = specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) * mask_param min_value = torch.rand(1)\",\n \"specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype)\",\n \"<NAME>, and <NAME>. \\\"librosa: Audio and music signal analysis in python.\\\" In Proceedings\",\n \"sample_rate, freq_high) indices = _median_smoothing(indices, win_length) # Convert indices to frequency EPSILON =\",\n \"x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu +\",\n \"determines filter width of lowpass filter, more gives sharper filter. (default: 1) upsample_filter_width\",\n \"of the audio waveform. format (str): File format. channels_first (bool): When True, both\",\n \"= torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) * (n + 0.5) * k)\",\n \"and quantization_channels - 1 and returns a signal scaled between -1 and 1.\",\n \"+= frame_to_add if norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames = window_end -\",\n \"(float): Sample rate of `waveform`. frame_length (float, optional): Frame length in milliseconds. (default:\",\n \"0) frames_per_chunk (int, optional): The number of frames used for energy normalization. (default:\",\n \"normalization). (Default: ``None``) mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default:\",\n \"cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int, pad: int, window: Tensor,\",\n \"math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int ) ->\",\n \"win_length: int, power: float, normalized: bool, n_iter: int, momentum: float, length: Optional[int], rand_init:\",\n \"milliseconds. (default: 25.0) frame_shift (float, optional): Frame shift in milliseconds. (default: 10.0) min_f0\",\n \"estimate of the phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window,\",\n \"Tensor, sample_rate: int, frame_time: float, freq_low: int ) -> Tensor: r\\\"\\\"\\\" Compute Normalized\",\n \"consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode,\",\n \"when upsampling NCCF. (default: 5) max_frames_latency (int, optional): Maximum number of frames of\",\n \"Used for formats other than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str,\",\n \"STFT windows win_length (int): Window size power (float or None): Exponent for the\",\n \"of audio of dimension (..., freq, time) win_length (int, optional): The window length\",\n \"lag indices += lag_min # Add 1 empirical calibration offset indices += 1\",\n \"complex_tensor: Tensor ) -> Tensor: r\\\"\\\"\\\"Compute the angle of complex tensor input. Args:\",\n \"torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long())\",\n \"energy per channel enorm = 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb\",\n \"= torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return\",\n \"- angle_0 - phase_advance phase = phase - 2 * math.pi * torch.round(phase\",\n \"tensor. Shape of `(..., )` \\\"\\\"\\\" # Replace by torch.norm once issue is\",\n \"Resulting Tensor. If ``channels_first=True``, it has ``[channel, time]`` else ``[time, channel]``. \\\"\\\"\\\" bytes\",\n \"coefficients of a tensor, usually a spectrogram: .. math:: d_t = \\\\frac{\\\\sum_{n=1}^{\\\\text{N}} n\",\n \"the triangular mel weights by the width of the mel band (area normalization).\",\n \"ref (float): Reference which the output will be scaled by. power (float): If\",\n \"the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The input waveform of\",\n \"0: window_start = 0 if last_window_start == -1: input_part = waveform[:, window_start: window_end\",\n \"= _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels +\",\n \"spectrogram: .. math:: d_t = \\\\frac{\\\\sum_{n=1}^{\\\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\\\sum_{n=1}^{\\\\text{N}} n^2} where\",\n \") output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf def _combine_max( a: Tuple[Tensor, Tensor],\",\n \"cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for t in range(num_frames): window_start\",\n \":] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance = cur_sumsq variance =\",\n \"Apply codecs as a form of augmentation. Args: waveform (Tensor): Audio data. Must\",\n \"window_start = 0 window_end = 0 if center: window_start = t - cmn_window\",\n \"= n * (n + 1) * (2 * n + 1) /\",\n \"float, amin: float, db_multiplier: float, top_db: Optional[float] = None ) -> Tensor: r\\\"\\\"\\\"Turn\",\n \"Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor: r\\\"\\\"\\\" Apply a\",\n \"axis (int): Axis to apply masking on (2 -> frequency, 3 -> time)\",\n \"1.0 phase_0 = angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0,\",\n \"(Tensor): Tensor of audio of dimension (..., freq, time) sample_rate (int): The sample\",\n \"r\\\"\\\"\\\"Create a frequency bin conversion matrix. Args: n_freqs (int): Number of frequencies to\",\n \"``5``) mode (str, optional): Mode parameter passed to padding (Default: ``\\\"replicate\\\"``) Returns: Tensor:\",\n \"norm == \\\"ortho\\\" dct[0] *= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels))\",\n \"time axis. The spectral centroid is defined as the weighted average of the\",\n \"tensor, speed up in time without modifying pitch by a factor of ``rate``.\",\n \"``axis``. Mask will be applied from indices ``[v_0, v_0 + v)``, where ``v``\",\n \"* math.log10(1.0 + (freq / 700.0)) # Fill in the linear part f_min\",\n \"last_window_start == -1: input_part = waveform[:, window_start: window_end - window_start, :] cur_sum +=\",\n \"max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame,\",\n \"magnitude. Args: waveform (Tensor): Tensor of audio of dimension (..., time) sample_rate (int):\",\n \"frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\\\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) #\",\n \"num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype =\",\n \"math.pi * torch.rand(batch, freq, frames) else: angles = torch.zeros(batch, freq, frames) angles =\",\n \"math.log10(1.0 + (freq / 700.0)) # Fill in the linear part f_min =\",\n \"cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1, :] else: if window_start > last_window_start:\",\n \"t, :] - cur_sum / window_frames if norm_vars: if window_frames == 1: cmn_waveform[:,\",\n \"length of the expected output. rand_init (bool): Initializes phase randomly if True, to\",\n \"pitch and NCCF. Reference: - A pitch extraction algorithm tuned for automatic speech\",\n \"of lags, then the latter is taken. \\\"\\\"\\\" lag_min = int(math.ceil(sample_rate / freq_high))\",\n \"power: float ) -> Tensor: r\\\"\\\"\\\"Turn a tensor from the decibel scale to\",\n \"matrix with shape (``n_mels``, ``n_mfcc``), normalized depending on norm. Args: n_mfcc (int): Number\",\n \"value for `n_mels` ({n_mels}) may be set too high. \\\" f\\\"Or, the value\",\n \"a signal scaled between -1 and 1. Args: x_mu (Tensor): Input tensor quantization_channels\",\n \"def amplitude_to_DB( x: Tensor, multiplier: float, amin: float, db_multiplier: float, top_db: Optional[float] =\",\n \"for amplitude amin (float): Number to clamp ``x`` db_multiplier (float): Log10(max(reference value and\",\n \"Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: mels (float): Frequency in\",\n \"1.0) / mu return x def complex_norm( complex_tensor: Tensor, power: float = 1.0\",\n \"of the norm. (Default: `1.0`) Returns: (Tensor, Tensor): The magnitude and phase of\",\n \"-> Tensor: r\\\"\\\"\\\"Compute waveform from a linear scale magnitude spectrogram using the Griffin-Lim\",\n \"angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1)\",\n \"Frame shift in milliseconds. (default: 10.0) min_f0 (float, optional): Minimum F0 to search\",\n \"unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if\",\n \"not exceed min-f0 (default: 10.0) penalty_factor (float, optional): Cost factor for FO change.\",\n \"7000) lowpass_filter_width (int, optional): Integer that determines filter width of lowpass filter, more\",\n \"(int, optional): Minimum CMN window used at start of decoding (adds latency only\",\n \"all the lags is very close to the first half of lags, then\",\n \"the padding method used when :attr:`center` is ``True``. Default: ``\\\"reflect\\\"`` onesided (bool, optional):\",\n \"= torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \\\"\\\"\\\"\",\n \"= x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor, ref: float, power: float )\",\n \"mode=mode) kernel = torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output\",\n \"mask_param min_value = torch.rand(1) * (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end =\",\n \":math:`t \\\\times \\\\text{hop\\\\_length}`. Default: ``True`` pad_mode (string, optional): controls the padding method used\",\n \"Tensor of freq of dimension (..., frame) \\\"\\\"\\\" input_shape = waveform.shape num_frames, num_feats\",\n \"music signal analysis in python.\\\" In Proceedings of the 14th python in science\",\n \"full clip. Args: x (Tensor): Input spectrogram(s) before being converted to decibel scale.\",\n \"ceil(time/rate), complex=2)` Example >>> freq, hop_length = 1025, 512 >>> # (channel, freq,\",\n \"- 1) // 2 # \\\"replicate\\\" padding in any dimension indices = torch.nn.functional.pad(\",\n \"of dimension (..., freq, time) sample_rate (int): The sample rate of the waveform\",\n \"specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) * mask_param min_value =\",\n \"18-25. 2015. * [2] <NAME>., <NAME>., & <NAME>. \\\"A fast Griffin-Lim algorithm,\\\" IEEE\",\n \"Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` Return: Tensor: Angle of a\",\n \"cmn_waveform[:, t, :] = waveform[:, t, :] - cur_sum / window_frames if norm_vars:\",\n \"# (channel, freq, time, complex=2) >>> complex_specgrams = torch.randn(2, freq, 300, 2) >>>\",\n \"== 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int,\",\n \"tracking to introduce into the feature processing (affects output only if ``frames_per_chunk >\",\n \"momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates waveform = torch.istft(specgram\",\n \"scale. ref (float): Reference which the output will be scaled by. power (float):\",\n \"(n_mels + 1) slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2)\",\n \"for phase recovery process. momentum (float): The momentum parameter for fast Griffin-Lim. Setting\",\n \"be detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor of freq of dimension (...,\",\n \"- alphas) * norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch = mag *\",\n \"to apply masking on (1 -> frequency, 2 -> time) Returns: Tensor: Masked\",\n \"(min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert mask_end - mask_start < mask_param if\",\n \"a full clip. Args: x (Tensor): Input spectrogram(s) before being converted to decibel\",\n \"allow pitch tracking to introduce into the feature processing (affects output only if\",\n \"``[time, channel]``. compression (float): Used for formats other than WAV. For mor details\",\n \"The magnitude and phase of the complex tensor \\\"\\\"\\\" mag = complex_norm(complex_tensor, power)\",\n \"n_iter: int, momentum: float, length: Optional[int], rand_init: bool ) -> Tensor: r\\\"\\\"\\\"Compute waveform\",\n \"cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int, pad: int, window: Tensor, n_fft: int,\",\n \"mels (Tensor): Mel frequencies mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``.\",\n \"= 1.3 # Speed up by 30% >>> phase_advance = torch.linspace( >>> 0,\",\n \"Tensor: Triangular filter banks (fb matrix) of size (``n_freqs``, ``n_mels``) meaning number of\",\n \"1) / 3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n, n\",\n \"compression: Optional[float] = None, encoding: Optional[str] = None, bits_per_sample: Optional[int] = None, )\",\n \"sample_rate (int): Sample rate of the audio waveform norm (Optional[str]): If 'slaney', divide\",\n \"torch.median(roll, -1) return values def detect_pitch_frequency( waveform: Tensor, sample_rate: int, frame_time: float =\",\n \"to normalize by magnitude after stft. n_iter (int): Number of iteration for phase\",\n \">>> # (channel, freq, time, complex=2) >>> complex_specgrams = torch.randn(2, freq, 300, 2)\",\n \"only at start). Only applicable if center == false, ignored if center==true (int,\",\n \"left. (bool, default = false) norm_vars (bool, optional): If true, normalize variance to\",\n \"File format. channels_first (bool): When True, both the input and output Tensor have\",\n \"FFT hop_length (int): Length of hop between STFT windows win_length (int): Window size\",\n \"see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding for the supported formats. For\",\n \"not the final version of the features, which is the default. (default: False)\",\n \"f_min = 0.0 f_sp = 200.0 / 3 mels = (freq - f_min)\",\n \"time)`. sample_rate (float): Sample rate of `waveform`. frame_length (float, optional): Frame length in\",\n \"torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1) values, _ =\",\n \"2 half = torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best) indices = best[1]\",\n \"at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio of\",\n \"0.5) * k) # size (n_mfcc, n_mels) if norm is None: dct *=\",\n \"x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor, ref: float, power: float ) ->\",\n \"* (specgrams.size(axis) - value) # Create broadcastable mask mask_start = min_value[..., None, None]\",\n \"Tensor: Tensor of freq of dimension (..., frame) \\\"\\\"\\\" input_shape = waveform.shape num_frames,\",\n \"-> frequency, 2 -> time) Returns: Tensor: Masked spectrogram of dimensions (channel, freq,\",\n \"= specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert win_length >= 3 n =\",\n \"(int): Sample rate of the audio waveform norm (Optional[str]): If 'slaney', divide the\",\n \"- 1) // 2 # twice sum of integer squared denom = n\",\n \"= (min_value + value)[..., None, None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) #\",\n \"tensor, usually a spectrogram: .. math:: d_t = \\\\frac{\\\\sum_{n=1}^{\\\\text{N}} n (c_{t+n} - c_{t-n})}{2\",\n \"padding (Default: ``\\\"replicate\\\"``) Returns: Tensor: Tensor of deltas of dimension (..., freq, time)\",\n \"\\\"and will be removed in v0.9.0 release. To suppress this warning, \\\" \\\"please\",\n \"to be approx constant energy per channel enorm = 2.0 / (f_pts[2:n_mels +\",\n \"the number of frames is the file size divided by the frame-shift. This\",\n \":] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] output_frames = ( (s1\",\n \"(default: 1) upsample_filter_width (int, optional): Integer that determines filter width when upsampling NCCF.\",\n \"on Applications of Signal Processing to Audio and Acoustics (pp. 1-4), Oct. 2013.\",\n \"\\\"\\\"\\\" bytes = io.BytesIO() torchaudio.backend.sox_io_backend.save(bytes, waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample )\",\n \"(float, optional): Minimum f0, applied in soft way, must not exceed min-f0 (default:\",\n \"pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \\\"\\\"\\\" shape = waveform.shape waveform = waveform.reshape(-1, shape[-1]) result\",\n \"normalized is not used in Griffin-Lim, \\\" \\\"and will be removed in v0.9.0\",\n \"-> Tensor: r\\\"\\\"\\\"Decode mu-law encoded signal. For more info see the `Wikipedia Entry\",\n \"Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels converted\",\n \"default = false) Returns: Tensor: Tensor of freq of dimension (..., frame) \\\"\\\"\\\"\",\n \"masking on (2 -> frequency, 3 -> time) Returns: Tensor: Masked spectrograms of\",\n \"sample_rate (float): Sample rate of `waveform`. frame_length (float, optional): Frame length in milliseconds.\",\n \"= shape[-3] if x_db.dim() > 2 else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2],\",\n \"Griffin-Lim method. Values near 1 can lead to faster convergence, but above 1\",\n \"Tensor: r\\\"\\\"\\\" Compute the spectral centroid for each channel along the time axis.\",\n \"with dimension of `(..., freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length = 1025,\",\n \"Tensor: Dimension (..., time) \\\"\\\"\\\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length,\",\n \"the applied result would be ``A * create_fb_matrix(A.size(-1), ...)``. \\\"\\\"\\\" if norm is\",\n \"min_cmn_window (int, optional): Minimum CMN window used at start of decoding (adds latency\",\n \"(Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum f0, applied in soft way, must\",\n \"freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min,\",\n \"(float or None, optional): Minimum negative cut-off in decibels. A reasonable number is\",\n \"and phase of the complex tensor \\\"\\\"\\\" mag = complex_norm(complex_tensor, power) phase =\",\n \"n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) # Update\",\n \"a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float = 0.99 ) -> Tuple[Tensor,\",\n \"Maximum number of frames of latency that we allow pitch tracking to introduce\",\n \"int, mask_value: float, axis: int ) -> Tensor: r\\\"\\\"\\\" Apply a mask along\",\n \"tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` Return: Tensor: Angle\",\n \"masked columns axis (int): Axis to apply masking on (1 -> frequency, 2\",\n \"(Tensor): The input waveform of shape `(..., time)`. sample_rate (float): Sample rate of\",\n \"the phase batch, freq, frames = specgram.size() if rand_init: angles = 2 *\",\n \"window_end = num_frames if window_start < 0: window_start = 0 if last_window_start ==\",\n \"freqs def create_fb_matrix( n_freqs: int, f_min: float, f_max: float, n_mels: int, sample_rate: int,\",\n \"see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit depth for the supported formats.\",\n \"time), freq is ``n_fft // 2 + 1`` and ``n_fft`` is the number\",\n \"hertz f_diff = f_pts[1:] - f_pts[:-1] # (n_mels + 1) slopes = f_pts.unsqueeze(0)\",\n \"supports it waveform = torch.nn.functional.pad(waveform, (pad, pad), \\\"constant\\\") # pack batch shape =\",\n \"pitch that our algorithm measures. (default: 0.005) nccf_ballast (float, optional): Increasing this factor\",\n \"int = 0, frames_per_chunk: int = 0, simulate_first_pass_online: bool = False, recompute_frame: int\",\n \"/ (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any():\",\n \"/ torch.log1p(mu) x_mu = ((x_mu + 1) / 2 * mu + 0.5).to(torch.int64)\",\n \"of frames. (default: True) Returns: Tensor: Pitch feature. Shape: ``(batch, frames 2)`` where\",\n \"specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end), mask_value) specgrams = specgrams.transpose(axis,\",\n \"Audio and music signal analysis in python.\\\" In Proceedings of the 14th python\",\n \"/ 700.0)) # Fill in the linear part f_min = 0.0 f_sp =\",\n \"e.g., 1 for energy, 2 for power, etc. If None, then the complex\",\n \"min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value) # Create broadcastable mask\",\n \"interval. Args: specgram (Tensor): Real spectrogram (channel, freq, time) mask_param (int): Number of\",\n \"waveform: Tensor, cmn_window: int = 600, min_cmn_window: int = 100, center: bool =\",\n \"The spectrogram can be either magnitude-only or complex. Args: waveform (Tensor): Tensor of\",\n \"dim=-1) roll = indices.unfold(-1, win_length, 1) values, _ = torch.median(roll, -1) return values\",\n \"minimal lag indices += lag_min # Add 1 empirical calibration offset indices +=\",\n \"/ denom # unpack batch output = output.reshape(shape) return output def _compute_nccf( waveform:\",\n \"to row-wise data of size (``n_mels``, ``n_mfcc``). \\\"\\\"\\\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels))\",\n \"def _median_smoothing( indices: Tensor, win_length: int ) -> Tensor: r\\\"\\\"\\\" Apply median smoothing\",\n \"(adds latency only at start). Only applicable if center == false, ignored if\",\n \"``(batch, frames 2)`` where the last dimension corresponds to pitch and NCCF. Reference:\",\n \"time) win_length (int, optional): The window length used for computing delta (Default: ``5``)\",\n \"(n + 1) * (2 * n + 1) / 3 specgram =\",\n \"+ 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1)\",\n \"applied/multiplied to each frame/window n_fft (int): Size of FFT, creates ``n_fft // 2\",\n \"3: raise ValueError('Only Frequency and Time masking are supported') device = specgrams.device dtype\",\n \"= mask * a[1] + ~mask * b[1] return values, indices def _find_max_per_frame(\",\n \"for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor.\",\n \"-> Tensor: r\\\"\\\"\\\"Turn a tensor from the decibel scale to the power/amplitude scale.\",\n \"freq, time) mask_param (int): Number of columns to be masked will be uniformly\",\n \"filter width of lowpass filter, more gives sharper filter. (default: 1) upsample_filter_width (int,\",\n \"suppress this warning, \\\" \\\"please use `normalized=False`.\\\") # pack batch shape = specgram.size()\",\n \"denom = n * (n + 1) * (2 * n + 1)\",\n \"Tensor, n_fft: int, hop_length: int, win_length: int, power: Optional[float], normalized: bool, center: bool\",\n \"after stft. n_iter (int): Number of iteration for phase recovery process. momentum (float):\",\n \"3 mels = (freq - f_min) / f_sp # Fill in the log-scale\",\n \"= torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, )\",\n \"values between 0 and quantization_channels - 1 and returns a signal scaled between\",\n \"1) values, _ = torch.median(roll, -1) return values def detect_pitch_frequency( waveform: Tensor, sample_rate:\",\n \"When True, both the input and output Tensor have dimension ``[channel, time]``. Otherwise,\",\n \"< 0'.format(momentum) if normalized: warnings.warn( \\\"The argument normalized is not used in Griffin-Lim,\",\n \"* math.pi)) # Compute Phase Accum phase = phase + phase_advance phase =\",\n \"25.0) frame_shift (float, optional): Frame shift in milliseconds. (default: 10.0) min_f0 (float, optional):\",\n \"(pp. 1-4), Oct. 2013. * [3] <NAME> and <NAME>, \\\"Signal estimation from modified\",\n \"by magnitude after stft. n_iter (int): Number of iteration for phase recovery process.\",\n \"This expects an input with values between 0 and quantization_channels - 1 and\",\n \"sharper filter. (default: 1) upsample_filter_width (int, optional): Integer that determines filter width when\",\n \"\\\"\\\"\\\" if pad > 0: # TODO add \\\"with torch.no_grad():\\\" back when JIT\",\n \"Size of FFT hop_length (int): Length of hop between STFT windows win_length (int):\",\n \"to check lags = int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length\",\n \"float = 400, soft_min_f0: float = 10.0, penalty_factor: float = 0.1, lowpass_cutoff: float\",\n \"* b[0]) values = mask * a[0] + ~mask * b[0] indices =\",\n \"bool = True, ) -> torch.Tensor: \\\"\\\"\\\"Extract pitch based on method described in\",\n \"result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency,\",\n \"default values are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length,\",\n \"mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor:\",\n \"highlight/apply to x the number of filterbanks. Each column is a filterbank so\",\n \"None] mask_end = (min_value + value)[..., None, None] mask = torch.arange(0, specgrams.size(axis), device=device,\",\n \"For each frame, take the highest value of NCCF, apply centered median smoothing,\",\n \"applied in soft way, must not exceed min-f0 (default: 10.0) penalty_factor (float, optional):\",\n \"ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor): A magnitude-only STFT spectrogram\",\n \"float = 1.0 ) -> Tensor: r\\\"\\\"\\\"Compute the norm of complex tensor input.\",\n \"centroid is defined as the weighted average of the frequency values, weighted by\",\n \"scale to the decibel scale. The output of each tensor in a batch\",\n \"== \\\"htk\\\": return 700.0 * (10.0**(mels / 2595.0) - 1.0) # Fill in\",\n \"take the form `(..., freq, time)`. Batched inputs should include a channel dimension\",\n \"(n_freqs, n_mels + 2) # create overlapping triangles zero = torch.zeros(1) down_slopes =\",\n \"window_end - window_start last_window_start = window_start last_window_end = window_end cmn_waveform[:, t, :] =\",\n \"(default: 10.0) penalty_factor (float, optional): Cost factor for FO change. (default: 0.1) lowpass_cutoff\",\n \"rate of the waveform (Hz) frame_time (float, optional): Duration of a frame (Default:\",\n \"avoid redundancy. Default: ``True`` Returns: Tensor: Dimension (..., freq, time), freq is ``n_fft\",\n \"hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) # Update our\",\n \"twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest relative change in pitch that\",\n \"or None): Norm to use (either 'ortho' or None) Returns: Tensor: The transformation\",\n \"and Time masking are supported') device = specgrams.device dtype = specgrams.dtype value =\",\n \"m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels + 2) f_pts =\",\n \"x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu) *\",\n \">= min_log_hz: mels = min_log_mel + math.log(freq / min_log_hz) / logstep return mels\",\n \"now the nonlinear scale min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) /\",\n \"int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p =\",\n \"back minimal lag indices += lag_min # Add 1 empirical calibration offset indices\",\n \"delta2 = compute_deltas(delta) \\\"\\\"\\\" device = specgram.device dtype = specgram.dtype # pack batch\",\n \"600, min_cmn_window: int = 100, center: bool = False, norm_vars: bool = False,\",\n \"Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Encode signal based on mu-law companding. For\",\n \"(window_frames ** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance cmn_waveform\",\n \"1)) freq_dim = -2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec(\",\n \"estimates waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack\",\n \"(10.0**(mels / 2595.0) - 1.0) # Fill in the linear scale f_min =\",\n \"sample_rate (int): Sample rate of the audio waveform pad (int): Two sided padding\",\n \"= specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 / power) #\",\n \"to the power/amplitude scale. Args: x (Tensor): Input tensor before being converted to\",\n \"400.0) soft_min_f0 (float, optional): Minimum f0, applied in soft way, must not exceed\",\n \"30% >>> phase_advance = torch.linspace( >>> 0, math.pi * hop_length, freq)[..., None] >>>\",\n \"axis == 1: specgram[:, mask_start:mask_end] = mask_value elif axis == 2: specgram[:, :,\",\n \"+ 1) * (2 * n + 1) / 3 specgram = torch.nn.functional.pad(specgram,\",\n \"optional): Changes the encoding for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`.\",\n \"(int, default = 600) min_cmn_window (int, optional): Minimum CMN window used at start\",\n \"-*- coding: utf-8 -*- import io import math import warnings from typing import\",\n \"import torchaudio __all__ = [ \\\"spectrogram\\\", \\\"griffinlim\\\", \\\"amplitude_to_DB\\\", \\\"DB_to_amplitude\\\", \\\"compute_deltas\\\", \\\"compute_kaldi_pitch\\\", \\\"create_fb_matrix\\\", \\\"create_dct\\\",\",\n \"dimension of `(..., freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length = 1025, 512\",\n \"true, the function will output features that correspond to what an online decoder\",\n \"* b[0] indices = mask * a[1] + ~mask * b[1] return values,\",\n \"algorithm assumes the signal has been scaled to between -1 and 1 and\",\n \"int ) -> Tensor: r\\\"\\\"\\\"Encode signal based on mu-law companding. For more info\",\n \"# (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not None\",\n \"signal based on mu-law companding. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_\",\n \"phase_advance = torch.linspace( >>> 0, math.pi * hop_length, freq)[..., None] >>> x =\",\n \"freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0\",\n \"first pass of decoding -- not the final version of the features, which\",\n \"+ complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float, axis:\",\n \"to clamp ``x`` db_multiplier (float): Log10(max(reference value and amin)) top_db (float or None,\",\n \"for LowPass filter (Hz) (default: 1000) resample_frequency (float, optional): Frequency that we down-sample\",\n \"the waveform (Hz) frame_time (float, optional): Duration of a frame (Default: ``10 **\",\n \"python in science conference, pp. 18-25. 2015. * [2] <NAME>., <NAME>., & <NAME>.\",\n \"(int, default = 100) center (bool, optional): If true, use a window centered\",\n \"# And now the nonlinear scale min_log_hz = 1000.0 min_log_mel = (min_log_hz -\",\n \"of None or 'slaney'\\\") # freq bins # Equivalent filterbank construction by Librosa\",\n \"device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate to 0 rebuilt\",\n \"is ``True``. Default: ``\\\"reflect\\\"`` onesided (bool, optional): controls whether to return half of\",\n \"(int or None): Array length of the expected output. rand_init (bool): Initializes phase\",\n \"(min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0 if freq >=\",\n \"r\\\"\\\"\\\"Create a DCT transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized depending on norm.\",\n \"numbers to frequencies. Args: mels (Tensor): Mel frequencies mel_scale (str, optional): Scale to\",\n \"> 0) e.g., 1 for energy, 2 for power, etc. normalized (bool): Whether\",\n \"the normed input tensor. Shape of `(..., )` \\\"\\\"\\\" # Replace by torch.norm\",\n \"applied/multiplied to each frame/window n_fft (int): Size of FFT hop_length (int): Length of\",\n \"device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats,\",\n \"time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0\",\n \"(Tensor): Tensor of audio of dimension (..., time) sample_rate (int): Sample rate of\",\n \"- window_start, :] cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part **\",\n \"Speed up by 30% >>> phase_advance = torch.linspace( >>> 0, math.pi * hop_length,\",\n \"recompute some of the forward pointers, after revising our estimate of the signal\",\n \"length=length).float() # Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length,\",\n \"more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has ``[channel,\",\n \"Tensor: r\\\"\\\"\\\"Detect pitch frequency. It is implemented using normalized cross-correlation function and median\",\n \"frames of latency that we allow pitch tracking to introduce into the feature\",\n \"usually a spectrogram: .. math:: d_t = \\\\frac{\\\\sum_{n=1}^{\\\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\\\sum_{n=1}^{\\\\text{N}}\",\n \"torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power: float = 1.0 )\",\n \"Angle of a complex tensor. Shape of `(..., )` \\\"\\\"\\\" return torch.atan2(complex_tensor[..., 1],\",\n \"phase. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float): Power of\",\n \")` \\\"\\\"\\\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power: float\",\n \"(-1.0 * slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:, 2:]\",\n \"\\\\frac{\\\\sum_{n=1}^{\\\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\\\sum_{n=1}^{\\\\text{N}} n^2} where :math:`d_t` is the deltas at\",\n \"frame_to_remove = waveform[:, last_window_start, :] cur_sum -= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove\",\n \"= specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value\",\n \"1, 'momentum={} > 1 can be unstable'.format(momentum) assert momentum >= 0, 'momentum={} <\",\n \"number of frequencies to highlight/apply to x the number of filterbanks. Each column\",\n \"with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False,\",\n \"(float, optional): Cutoff frequency for LowPass filter (Hz) (default: 1000) resample_frequency (float, optional):\",\n \"not None: # Expand batch shape = x_db.size() packed_channels = shape[-3] if x_db.dim()\",\n \"Tensor, multiplier: float, amin: float, db_multiplier: float, top_db: Optional[float] = None ) ->\",\n \"time equals the ``length`` parameter if given. \\\"\\\"\\\" assert momentum < 1, 'momentum={}\",\n \"complex_specgrams: Tensor, rate: float, phase_advance: Tensor ) -> Tensor: r\\\"\\\"\\\"Given a STFT tensor,\",\n \"complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1,\",\n \"*= math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int )\",\n \"value for `n_freqs` ({n_freqs}) may be set too low.\\\" ) return fb def\",\n \"time) sample_rate (int): Sample rate of the audio waveform pad (int): Two sided\",\n \"the input and output Tensor have dimension ``[channel, time]``. Otherwise, they have dimension\",\n \"angles = rebuilt if momentum: angles = angles - tprev.mul_(momentum / (1 +\",\n \"to between -1 and 1 and returns a signal encoded with values from\",\n \"is the energy :math:`\\\\sum_{n=j}^{j+N-1} w^2(n)`. \\\"\\\"\\\" EPSILON = 10 ** (-9) # Number\",\n \"per utterance. Args: waveform (Tensor): Tensor of audio of dimension (..., freq, time)\",\n \"0.005) nccf_ballast (float, optional): Increasing this factor reduces NCCF for quiet frames (default:\",\n \"10 ** (-2), win_length: int = 30, freq_low: int = 85, freq_high: int\",\n \"function computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The input\",\n \"+ 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int ) -> Tensor:\",\n \"snip_edges (bool, optional): If this is set to false, the incomplete frames near\",\n \"used at start of decoding (adds latency only at start). Only applicable if\",\n \"None, then the complex spectrum is returned instead. normalized (bool): Whether to normalize\",\n \"science conference, pp. 18-25. 2015. * [2] <NAME>., <NAME>., & <NAME>. \\\"A fast\",\n \"sample_rate: int, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, )\",\n \"== ceil(300 / 1.3) torch.Size([2, 1025, 231, 2]) \\\"\\\"\\\" # pack batch shape\",\n \"delta coefficients of a tensor, usually a spectrogram: .. math:: d_t = \\\\frac{\\\\sum_{n=1}^{\\\\text{N}}\",\n \"Complex Specgrams Stretch with dimension of `(..., freq, ceil(time/rate), complex=2)` Example >>> freq,\",\n \"given window. \\\"\\\"\\\" # Centered windowed pad_length = (win_length - 1) // 2\",\n \"a tensor from the decibel scale to the power/amplitude scale. Args: x (Tensor):\",\n \"of decoding -- not the final version of the features, which is the\",\n \"for power, etc. If None, then the complex spectrum is returned instead. normalized\",\n \"/ freq_high)) # Find near enough max that is smallest best = torch.max(nccf[...,\",\n \"E(m+b_i)}}, where :math:`\\\\phi_i(m)` is the NCCF at frame :math:`i` with lag :math:`m`, :math:`w`\",\n \"return half of results to avoid redundancy. Default: ``True`` Returns: Tensor: Dimension (...,\",\n \"algorithm,\\\" IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (pp.\",\n \"by magnitude after stft center (bool, optional): whether to pad :attr:`waveform` on both\",\n \"Tensor, window: Tensor, n_fft: int, hop_length: int, win_length: int, power: float, normalized: bool,\",\n \"# (n_freqs, n_mels + 2) # create overlapping triangles zero = torch.zeros(1) down_slopes\",\n \"complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float):\",\n \"power) def _hz_to_mel(freq: float, mel_scale: str = \\\"htk\\\") -> float: r\\\"\\\"\\\"Convert Hz to\",\n \"None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch example masking specgrams\",\n \"* mask_param min_value = torch.rand(1) * (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end\",\n \"If true, use a window centered on the current frame (to the extent\",\n \"into snippets vs. a full clip. Args: x (Tensor): Input spectrogram(s) before being\",\n \"audio waveform. format (str): File format. channels_first (bool): When True, both the input\",\n \"freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor, cmn_window: int = 600,\",\n \"(float): Power of the norm. (Default: `1.0`) Returns: (Tensor, Tensor): The magnitude and\",\n \"return indices def _median_smoothing( indices: Tensor, win_length: int ) -> Tensor: r\\\"\\\"\\\" Apply\",\n \"Number of mel filterbanks sample_rate (int): Sample rate of the audio waveform norm\",\n \"* create_fb_matrix(A.size(-1), ...)``. \\\"\\\"\\\" if norm is not None and norm != \\\"slaney\\\":\",\n \"detected (Hz) (Default: ``85``). freq_high (int, optional): Highest frequency that can be detected\",\n \"normalized: warnings.warn( \\\"The argument normalized is not used in Griffin-Lim, \\\" \\\"and will\",\n \"elementwise. \\\"\\\"\\\" mask = (a[0] > thresh * b[0]) values = mask *\",\n \"is a matrix A of size (..., ``n_freqs``), the applied result would be\",\n \"Tensor: r\\\"\\\"\\\" Apply sliding-window cepstral mean (and optionally variance) normalization per utterance. Args:\",\n \"(default: 25.0) frame_shift (float, optional): Frame shift in milliseconds. (default: 10.0) min_f0 (float,\",\n \"Oct. 2013. * [3] <NAME> and <NAME>, \\\"Signal estimation from modified short-time Fourier\",\n \"for quiet frames (default: 7000) lowpass_filter_width (int, optional): Integer that determines filter width\",\n \"-1) specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end), mask_value) specgrams = specgrams.transpose(axis, -1)\",\n \"= 600, min_cmn_window: int = 100, center: bool = False, norm_vars: bool =\",\n \"(2 * math.pi)) # Compute Phase Accum phase = phase + phase_advance phase\",\n \"cur_sum / window_frames if norm_vars: if window_frames == 1: cmn_waveform[:, t, :] =\",\n \"won't be snipped, so that the number of frames is the file size\",\n \"lowpass_filter_width (int, optional): Integer that determines filter width of lowpass filter, more gives\",\n \"is the beginning of frame :math:`i`, :math:`E(j)` is the energy :math:`\\\\sum_{n=j}^{j+N-1} w^2(n)`. \\\"\\\"\\\"\",\n \"into its magnitude and phase. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)`\",\n \"Proceedings of the 14th python in science conference, pp. 18-25. 2015. * [2]\",\n \"to each frame/window n_fft (int): Size of FFT, creates ``n_fft // 2 +\",\n \"* (10.0**(mels / 2595.0) - 1.0) # Fill in the linear scale f_min\",\n \"max_f0: float = 400, soft_min_f0: float = 10.0, penalty_factor: float = 0.1, lowpass_cutoff:\",\n \"where the last dimension corresponds to pitch and NCCF. Reference: - A pitch\",\n \"specgram.dtype # pack batch shape = specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert\",\n \"ceil(300 / 1.3) torch.Size([2, 1025, 231, 2]) \\\"\\\"\\\" # pack batch shape =\",\n \"create_fb_matrix(A.size(-1), ...)``. \\\"\\\"\\\" if norm is not None and norm != \\\"slaney\\\": raise\",\n \"-1, :] else: if window_start > last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum\",\n \"other than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the\",\n \"math:: \\\\phi_i(m) = \\\\frac{\\\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\\\phi_i(m)` is the\",\n \"`(..., complex=2)` power (float): Power of the norm. (Default: `1.0`). Returns: Tensor: Power\",\n \"right-multiplied to row-wise data of size (``n_mels``, ``n_mfcc``). \\\"\\\"\\\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n =\",\n \"bins # Equivalent filterbank construction by Librosa all_freqs = torch.linspace(0, sample_rate // 2,\",\n \"`n_freqs` ({n_freqs}) may be set too low.\\\" ) return fb def create_dct( n_mfcc:\",\n \"of dimension (..., freq, frames) where freq is ``n_fft // 2 + 1``.\",\n \"Mel frequencies mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``)\",\n \"used for computing delta (Default: ``5``) mode (str, optional): Mode parameter passed to\",\n \"= waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default values are consistent with librosa.core.spectrum._spectrogram\",\n \"sample_rate / (EPSILON + indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:]))\",\n \"hop_length: int, win_length: int, ) -> Tensor: r\\\"\\\"\\\" Compute the spectral centroid for\",\n \"of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` Return:\",\n \"and <NAME>. \\\"librosa: Audio and music signal analysis in python.\\\" In Proceedings of\",\n \"Output tensor in power/amplitude scale. \\\"\\\"\\\" return ref * torch.pow(torch.pow(10.0, 0.1 * x),\",\n \"(int): Number of mfc coefficients to retain n_mels (int): Number of mel filterbanks\",\n \"tensor over the given window. \\\"\\\"\\\" # Centered windowed pad_length = (win_length -\",\n \"1000) >>> delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \\\"\\\"\\\" device = specgram.device\",\n \"bin numbers to frequencies. Args: mels (Tensor): Mel frequencies mel_scale (str, optional): Scale\",\n \"on (1 -> frequency, 2 -> time) Returns: Tensor: Masked spectrogram of dimensions\",\n \"[0, 0, 0, 2]) # (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1\",\n \"Number of mfc coefficients to retain n_mels (int): Number of mel filterbanks norm\",\n \"lags + num_of_frames * frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0, p)) #\",\n \"_combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float = 0.99 ) ->\",\n \"and amin)) top_db (float or None, optional): Minimum negative cut-off in decibels. A\",\n \"k) # size (n_mfcc, n_mels) if norm is None: dct *= 2.0 else:\",\n \"window_end = 0 if center: window_start = t - cmn_window // 2 window_end\",\n \"time :math:`t`, :math:`c_t` is the spectrogram coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``.\",\n \"```channels_first```. sample_rate (int): Sample rate of the audio waveform. format (str): File format.\",\n \"Args: x (Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input\",\n \"else: window_start = t - cmn_window window_end = t + 1 if window_start\",\n \"Optional[float] = None, encoding: Optional[str] = None, bits_per_sample: Optional[int] = None, ) ->\",\n \"* k) # size (n_mfcc, n_mels) if norm is None: dct *= 2.0\",\n \"``[v_0, v_0 + v)``, where ``v`` is sampled from ``uniform(0, mask_param)``, and ``v_0``\",\n \"ValueError('mel_scale should be one of \\\"htk\\\" or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return\",\n \"that assuming there is a matrix A of size (..., ``n_freqs``), the applied\",\n \"``\\\"reflect\\\"`` onesided (bool, optional): controls whether to return half of results to avoid\",\n \"(int, optional): Lowest frequency that can be detected (Hz) (Default: ``85``). freq_high (int,\",\n \"Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \\\"\\\"\\\" shape = waveform.shape\",\n \"\\\"amplitude_to_DB\\\", \\\"DB_to_amplitude\\\", \\\"compute_deltas\\\", \\\"compute_kaldi_pitch\\\", \\\"create_fb_matrix\\\", \\\"create_dct\\\", \\\"compute_deltas\\\", \\\"detect_pitch_frequency\\\", \\\"DB_to_amplitude\\\", \\\"mu_law_encoding\\\", \\\"mu_law_decoding\\\", \\\"complex_norm\\\", \\\"angle\\\",\",\n \"pad), \\\"constant\\\") # pack batch shape = waveform.size() waveform = waveform.reshape(-1, shape[-1]) #\",\n \"ignored if center==true (int, default = 100) center (bool, optional): If true, use\",\n \"pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:])\",\n \"* specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int, format: str,\",\n \"/ 2 * mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels:\",\n \"waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0,\",\n \"of `waveform`. frame_length (float, optional): Frame length in milliseconds. (default: 25.0) frame_shift (float,\",\n \"If power equals 1, will compute DB to power. If 0.5, will compute\",\n \"the form `(..., freq, time)`. Batched inputs should include a channel dimension and\",\n \"= torch.linspace(0, sample_rate // 2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim\",\n \"[2] <NAME>., <NAME>., & <NAME>. \\\"A fast Griffin-Lim algorithm,\\\" IEEE Workshop on Applications\",\n \"import warnings from typing import Optional, Tuple import torch from torch import Tensor\",\n \"freq >= min_log_hz: mels = min_log_mel + math.log(freq / min_log_hz) / logstep return\",\n \"near enough max that is smallest best = torch.max(nccf[..., lag_min:], -1) half_size =\",\n \"return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float = 25.0,\",\n \"so may return different values for an audio clip split into snippets vs.\",\n \"n_fft: int, hop_length: int, win_length: int, power: float, normalized: bool, n_iter: int, momentum:\",\n \"torch.tensor(0.) for _ in range(n_iter): # Store the previous iterate tprev = rebuilt\",\n \"time, complex=2) >>> complex_specgrams = torch.randn(2, freq, 300, 2) >>> rate = 1.3\",\n \"by Librosa all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) # calculate mel freq\",\n \"(float): Exponent for the magnitude spectrogram, (must be > 0) e.g., 1 for\",\n \"if mel_scale == \\\"htk\\\": return 2595.0 * math.log10(1.0 + (freq / 700.0)) #\",\n \"implemented using normalized cross-correlation function and median smoothing. Args: waveform (Tensor): Tensor of\",\n \"normalized=False, onesided=True, return_complex=True, ) ) # Update our phase estimates angles = rebuilt\",\n \"(mask < mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return specgrams def mask_along_axis( specgram:\",\n \"Tensor: r\\\"\\\"\\\"Compute the angle of complex tensor input. Args: complex_tensor (Tensor): Tensor shape\",\n \"f\\\"The value for `n_mels` ({n_mels}) may be set too high. \\\" f\\\"Or, the\",\n \"14th python in science conference, pp. 18-25. 2015. * [2] <NAME>., <NAME>., &\",\n \"window_start = t - cmn_window window_end = t + 1 if window_start <\",\n \"frequency for LowPass filter (Hz) (default: 1000) resample_frequency (float, optional): Frequency that we\",\n \"(default: 0.005) nccf_ballast (float, optional): Increasing this factor reduces NCCF for quiet frames\",\n \"a STFT tensor, speed up in time without modifying pitch by a factor\",\n \"rate: float, phase_advance: Tensor ) -> Tensor: r\\\"\\\"\\\"Given a STFT tensor, speed up\",\n \"angle of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)`\",\n \"1) * (2 * n + 1) / 3 specgram = torch.nn.functional.pad(specgram, (n,\",\n \"Sample rate of the audio waveform. format (str): File format. channels_first (bool): When\",\n \"for compatibility with online pitch extraction. A non-critical parameter; the frame at which\",\n \"optional): Smallest relative change in pitch that our algorithm measures. (default: 0.005) nccf_ballast\",\n \"specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0,\",\n \"norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1, :] else: if window_start >\",\n \"frequencies to highlight/apply f_min (float): Minimum frequency (Hz) f_max (float): Maximum frequency (Hz)\",\n \"for `n_mels` ({n_mels}) may be set too high. \\\" f\\\"Or, the value for\",\n \"_mod_utils import torchaudio __all__ = [ \\\"spectrogram\\\", \\\"griffinlim\\\", \\\"amplitude_to_DB\\\", \\\"DB_to_amplitude\\\", \\\"compute_deltas\\\", \\\"compute_kaldi_pitch\\\", \\\"create_fb_matrix\\\",\",\n \"-= window_start window_start = 0 if not center: if window_end > t: window_end\",\n \"__all__ = [ \\\"spectrogram\\\", \\\"griffinlim\\\", \\\"amplitude_to_DB\\\", \\\"DB_to_amplitude\\\", \\\"compute_deltas\\\", \\\"compute_kaldi_pitch\\\", \\\"create_fb_matrix\\\", \\\"create_dct\\\", \\\"compute_deltas\\\", \\\"detect_pitch_frequency\\\",\",\n \"min_log_hz) / logstep return mels def _mel_to_hz(mels: Tensor, mel_scale: str = \\\"htk\\\") ->\",\n \"normalization. (default: 0) simulate_first_pass_online (bool, optional): If true, the function will output features\",\n \"torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf =\",\n \"waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames,\",\n \"= waveform.reshape(-1, shape[-1]) # default values are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft(\",\n \"from the power/amplitude scale to the decibel scale. The output of each tensor\",\n \"db_multiplier (float): Log10(max(reference value and amin)) top_db (float or None, optional): Minimum negative\",\n \"(mels >= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel)) return\",\n \"waveform, sample_rate, channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file(\",\n \"0, simulate_first_pass_online: bool = False, recompute_frame: int = 500, snip_edges: bool = True,\",\n \":] cur_sum -= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove ** 2) if window_end\",\n \"signal. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input\",\n \"of size (``n_freqs``, ``n_mels``) meaning number of frequencies to highlight/apply to x the\",\n \"the masked columns axis (int): Axis to apply masking on (2 -> frequency,\",\n \"the second, elementwise. \\\"\\\"\\\" mask = (a[0] > thresh * b[0]) values =\",\n \"the decibel scale. The output of each tensor in a batch depends on\",\n \"batch shape = list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate,\",\n \"(int): Window size power (float or None): Exponent for the magnitude spectrogram, (must\",\n \"if norm_vars: if window_frames == 1: cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats,\",\n \"(float, optional): Maximum F0 to search for (Hz) (default: 400.0) soft_min_f0 (float, optional):\",\n \"\\\"htk\\\") -> Tensor: \\\"\\\"\\\"Convert mel bin numbers to frequencies. Args: mels (Tensor): Mel\",\n \"optional): Maximum F0 to search for (Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum\",\n \"the log-scale part min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp\",\n \"shape = waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default values are consistent with\",\n \"by a factor of ``rate``. Args: complex_specgrams (Tensor): Dimension of `(..., freq, time,\",\n \"sum of integer squared denom = n * (n + 1) * (2\",\n \"1 for energy, 2 for power, etc. normalized (bool): Whether to normalize by\",\n \"waveform: torch.Tensor, sample_rate: float, frame_length: float = 25.0, frame_shift: float = 10.0, min_f0:\",\n \"or 'slaney'\\\") # freq bins # Equivalent filterbank construction by Librosa all_freqs =\",\n \"torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) -\",\n \"rate = 1.3 # Speed up by 30% >>> phase_advance = torch.linspace( >>>\",\n \"of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The input waveform of shape `(...,\",\n \"* torch.round(phase / (2 * math.pi)) # Compute Phase Accum phase = phase\",\n \"+ 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) /\",\n \"if True, to zero otherwise. Returns: torch.Tensor: waveform of (..., time), where time\",\n \"= waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[...,\",\n \"window centered on the current frame (to the extent possible, modulo end effects).\",\n \"if ``frames_per_chunk > 0``. recompute_frame (int, optional): Only relevant for compatibility with online\",\n \"= _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between each mel point and each\",\n \") -> Tensor: r\\\"\\\"\\\"Turn a tensor from the decibel scale to the power/amplitude\",\n \"r\\\"\\\"\\\"Decode mu-law encoded signal. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This\",\n \"int = 85, freq_high: int = 3400, ) -> Tensor: r\\\"\\\"\\\"Detect pitch frequency.\",\n \"JIT supports it waveform = torch.nn.functional.pad(waveform, (pad, pad), \\\"constant\\\") # pack batch shape\",\n \"io import math import warnings from typing import Optional, Tuple import torch from\",\n \"and time is the number of window hops (n_frame). \\\"\\\"\\\" if pad >\",\n \"mag = alphas * norm_1 + (1 - alphas) * norm_0 real_stretch =\",\n \"mask_param] mask_value (float): Value to assign to the masked columns axis (int): Axis\",\n \"are supported') # unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def\",\n \"import module_utils as _mod_utils import torchaudio __all__ = [ \\\"spectrogram\\\", \\\"griffinlim\\\", \\\"amplitude_to_DB\\\", \\\"DB_to_amplitude\\\",\",\n \"shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) * mask_param\",\n \"= multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier if top_db is\",\n \"= torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag = alphas *\",\n \"issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor\",\n \"Cross-Correlation Function (NCCF). .. math:: \\\\phi_i(m) = \\\\frac{\\\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\\\sqrt{E(b_i) E(m+b_i)}},\",\n \"norm is None: dct *= 2.0 else: assert norm == \\\"ortho\\\" dct[0] *=\",\n \"dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames,\",\n \"4000) delta_pitch( float, optional): Smallest relative change in pitch that our algorithm measures.\",\n \"part min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep =\",\n \"what an online decoder would see in the first pass of decoding --\",\n \"is 80. (Default: ``None``) Returns: Tensor: Output tensor in decibel scale \\\"\\\"\\\" x_db\",\n \":math:`t`-th frame is centered at time :math:`t \\\\times \\\\text{hop\\\\_length}`. Default: ``True`` pad_mode (string,\",\n \"rand_init: angles = 2 * math.pi * torch.rand(batch, freq, frames) else: angles =\",\n \"shape[-3] if x_db.dim() > 2 else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1])\",\n \"(int): Window size. (Default: ``n_fft``) power (float): Exponent for the magnitude spectrogram, (must\",\n \"and returns a signal encoded with values from 0 to quantization_channels - 1.\",\n \"phase = angle_1 - angle_0 - phase_advance phase = phase - 2 *\",\n \"the norm. (Default: `1.0`). Returns: Tensor: Power of the normed input tensor. Shape\",\n \"waveform: Tensor, pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, power:\",\n \"and music signal analysis in python.\\\" In Proceedings of the 14th python in\",\n \"spectrograms (batch, channel, freq, time) mask_param (int): Number of columns to be masked\",\n \"factor for FO change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency for LowPass\",\n \"lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result\",\n \"center==true (int, default = 100) center (bool, optional): If true, use a window\",\n \"number of filterbanks. Each column is a filterbank so that assuming there is\",\n \"rebuilt # Invert with our current estimate of the phases inverse = torch.istft(specgram\",\n \"multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier if top_db is not\",\n \"the power/amplitude scale to the decibel scale. The output of each tensor in\",\n \"to use (either 'ortho' or None) Returns: Tensor: The transformation matrix, to be\",\n \"band (area normalization). (Default: ``None``) mel_scale (str, optional): Scale to use: ``htk`` or\",\n \"cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0)\",\n \"specgrams def mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float, axis: int ) ->\",\n \"'slaney'\\\") # freq bins # Equivalent filterbank construction by Librosa all_freqs = torch.linspace(0,\",\n \"(min_log_hz - f_min) / f_sp logstep = math.log(6.4) / 27.0 log_t = (mels\",\n \"For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with\",\n \"Hz \\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be one\",\n \"window_start last_window_end = window_end cmn_waveform[:, t, :] = waveform[:, t, :] - cur_sum\",\n \"f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not\",\n \"f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels)\",\n \"``10 ** (-2)``). win_length (int, optional): The window length for median smoothing (in\",\n \"pp.236–243, Apr. 1984. Args: specgram (Tensor): A magnitude-only STFT spectrogram of dimension (...,\",\n \"Example >>> freq, hop_length = 1025, 512 >>> # (channel, freq, time, complex=2)\",\n \"num_frames, num_feats, dtype=dtype, device=device) for t in range(num_frames): window_start = 0 window_end =\",\n \"!= \\\"slaney\\\": raise ValueError(\\\"norm must be one of None or 'slaney'\\\") # freq\",\n \"-1 and 1. Args: x_mu (Tensor): Input tensor quantization_channels (int): Number of channels\",\n \"# pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram =\",\n \"number of Fourier bins, and time is the number of window hops (n_frame).\",\n \"supported') # unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas(\",\n \"= torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch waveform\",\n \"delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \\\"\\\"\\\" device = specgram.device dtype =\",\n \"device = specgram.device dtype = specgram.dtype # pack batch shape = specgram.size() specgram\",\n \"pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, ) -> Tensor:\",\n \"freq_high: int = 3400, ) -> Tensor: r\\\"\\\"\\\"Detect pitch frequency. It is implemented\",\n \"num_channels, num_feats, dtype=dtype, device=device) else: variance = cur_sumsq variance = variance / window_frames\",\n \"return x def complex_norm( complex_tensor: Tensor, power: float = 1.0 ) -> Tensor:\",\n \"an online decoder would see in the first pass of decoding -- not\",\n \"2 + 1`` and ``n_fft`` is the number of Fourier bins, and time\",\n \"window_end cmn_waveform[:, t, :] = waveform[:, t, :] - cur_sum / window_frames if\",\n \"(str, optional): Mode parameter passed to padding (Default: ``\\\"replicate\\\"``) Returns: Tensor: Tensor of\",\n \"frequency that can be detected (Hz) (Default: ``85``). freq_high (int, optional): Highest frequency\",\n \"norm_1 + (1 - alphas) * norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch\",\n \"that can be detected (Hz) (Default: ``3400``). Returns: Tensor: Tensor of freq of\",\n \"in Hz \\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be\",\n \"torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu + 1) / 2 * mu +\",\n \"2 for power, etc. normalized (bool): Whether to normalize by magnitude after stft.\",\n \"* math.pi * torch.round(phase / (2 * math.pi)) # Compute Phase Accum phase\",\n \"using the Griffin-Lim transformation. Implementation ported from `librosa`. * [1] McFee, Brian, <NAME>,\",\n \"angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram rebuilt = torch.view_as_real(\",\n \"return waveform def amplitude_to_DB( x: Tensor, multiplier: float, amin: float, db_multiplier: float, top_db:\",\n \"< 1, 'momentum={} > 1 can be unstable'.format(momentum) assert momentum >= 0, 'momentum={}\",\n \"= min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs def create_fb_matrix( n_freqs:\",\n \"num_of_frames = int(math.ceil(waveform_length / frame_size)) p = lags + num_of_frames * frame_size -\",\n \"sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. Args: specgrams\",\n \"(s1 * s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2,\",\n \"2 - 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) /\",\n \"/ (2 * math.pi)) # Compute Phase Accum phase = phase + phase_advance\",\n \"+ shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high)\",\n \"and Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \\\"\\\"\\\" shape =\",\n \"2013. * [3] <NAME> and <NAME>, \\\"Signal estimation from modified short-time Fourier transform,\\\"\",\n \"of frequencies to highlight/apply to x the number of filterbanks. Each column is\",\n \"a[0] + ~mask * b[0] indices = mask * a[1] + ~mask *\",\n \"stft. n_iter (int): Number of iteration for phase recovery process. momentum (float): The\",\n \"Replace by torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power)\",\n \"-> Tensor: r\\\"\\\"\\\" Compute Normalized Cross-Correlation Function (NCCF). .. math:: \\\\phi_i(m) = \\\\frac{\\\\sum_{n=b_i}^{b_i\",\n \"-2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate:\",\n \"dimension ``[time, channel]``. compression (float): Used for formats other than WAV. For mor\",\n \"Processing to Audio and Acoustics (pp. 1-4), Oct. 2013. * [3] <NAME> and\",\n \"cmn_window (int, optional): Window in frames for running average CMN computation (int, default\",\n \"`(..., freq, time, complex=2)` rate (float): Speed-up factor phase_advance (Tensor): Expected phase advance\",\n \"/ (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates\",\n \"last_window_start: frame_to_remove = waveform[:, last_window_start, :] cur_sum -= frame_to_remove if norm_vars: cur_sumsq -=\",\n \"is the number of Fourier bins, and time is the number of window\",\n \"mel_scale == \\\"htk\\\": return 2595.0 * math.log10(1.0 + (freq / 700.0)) # Fill\",\n \"dim=-1) \\\\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate\",\n \"float, freq_low: int ) -> Tensor: r\\\"\\\"\\\" Compute Normalized Cross-Correlation Function (NCCF). ..\",\n \"n_mels: int, sample_rate: int, norm: Optional[str] = None, mel_scale: str = \\\"htk\\\", )\",\n \"specgram def compute_deltas( specgram: Tensor, win_length: int = 5, mode: str = \\\"replicate\\\"\",\n \"_find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length) # Convert indices to frequency EPSILON\",\n \"(int): Size of FFT, creates ``n_fft // 2 + 1`` bins hop_length (int):\",\n \"# Update our phase estimates angles = rebuilt if momentum: angles = angles\",\n \"in range(n_iter): # Store the previous iterate tprev = rebuilt # Invert with\",\n \"Signal Processing to Audio and Acoustics (pp. 1-4), Oct. 2013. * [3] <NAME>\",\n \"= 10 ** (-2), win_length: int = 30, freq_low: int = 85, freq_high:\",\n \"2 * mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int\",\n \"mag, phase def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor ) -> Tensor:\",\n \"sample_rate: int, frame_time: float = 10 ** (-2), win_length: int = 30, freq_low:\",\n \") -> Tensor: r\\\"\\\"\\\"Create a DCT transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized\",\n \"# Store the previous iterate tprev = rebuilt # Invert with our current\",\n \"40, 1000) >>> delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \\\"\\\"\\\" device =\",\n \"optional): Cutoff frequency for LowPass filter (Hz) (default: 1000) resample_frequency (float, optional): Frequency\",\n \"True, both the input and output Tensor have dimension ``[channel, time]``. Otherwise, they\",\n \"of the complex tensor \\\"\\\"\\\" mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor) return\",\n \"a frame (Default: ``10 ** (-2)``). win_length (int, optional): The window length for\",\n \"onesided: bool = True ) -> Tensor: r\\\"\\\"\\\"Create a spectrogram or a batch\",\n \"tensor that is applied/multiplied to each frame/window n_fft (int): Size of FFT hop_length\",\n \"window_frames variance -= ((cur_sum ** 2) / (window_frames ** 2)) variance = torch.pow(variance,\",\n \"= waveform.shape[0] dtype = waveform.dtype device = waveform.device last_window_start = last_window_end = -1\",\n \"2, 1)[:, -1, :] else: if window_start > last_window_start: frame_to_remove = waveform[:, last_window_start,\",\n \"where freq is ``n_fft // 2 + 1``. window (Tensor): Window tensor that\",\n \"frame at which we recompute some of the forward pointers, after revising our\",\n \"split into snippets vs. a full clip. Args: x (Tensor): Input spectrogram(s) before\",\n \"f_max (float): Maximum frequency (Hz) n_mels (int): Number of mel filterbanks sample_rate (int):\",\n \"the frequency values, weighted by their magnitude. Args: waveform (Tensor): Tensor of audio\",\n \"'sliding_window_cmn', \\\"spectral_centroid\\\", \\\"apply_codec\\\", ] def spectrogram( waveform: Tensor, pad: int, window: Tensor, n_fft:\",\n \"output def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float, freq_low: int ) ->\",\n \"3 n = (win_length - 1) // 2 # twice sum of integer\",\n \"# \\\"replicate\\\" padding in any dimension indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\\\"constant\\\",\",\n \"= \\\"replicate\\\" ) -> Tensor: r\\\"\\\"\\\"Compute delta coefficients of a tensor, usually a\",\n \"current frame (to the extent possible, modulo end effects). If false, window is\",\n \"(default: 7000) lowpass_filter_width (int, optional): Integer that determines filter width of lowpass filter,\",\n \"channels_first: bool = True, compression: Optional[float] = None, encoding: Optional[str] = None, bits_per_sample:\",\n \"quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law encoding \\\"\\\"\\\" mu\",\n \"Time masking are supported') # unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return\",\n \"* torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu + 1) / 2 * mu\",\n \"the number of window hops (n_frame). \\\"\\\"\\\" if pad > 0: # TODO\",\n \"the width of the mel band (area normalization). (Default: ``None``) mel_scale (str, optional):\",\n \"= False, ) -> Tensor: r\\\"\\\"\\\" Apply sliding-window cepstral mean (and optionally variance)\",\n \"to frequency EPSILON = 10 ** (-9) freq = sample_rate / (EPSILON +\",\n \"x: Tensor, multiplier: float, amin: float, db_multiplier: float, top_db: Optional[float] = None )\",\n \"int, f_min: float, f_max: float, n_mels: int, sample_rate: int, norm: Optional[str] = None,\",\n \"Griffin-Lim algorithm,\\\" IEEE Workshop on Applications of Signal Processing to Audio and Acoustics\",\n \"2 and axis != 3: raise ValueError('Only Frequency and Time masking are supported')\",\n \"= slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes))\",\n \"time) \\\"\\\"\\\" # pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:]))\",\n \"be applied from indices ``[v_0, v_0 + v)``, where ``v`` is sampled from\",\n \"> 0) e.g., 1 for energy, 2 for power, etc. If None, then\",\n \"dimensional. See also ```channels_first```. sample_rate (int): Sample rate of the audio waveform. format\",\n \"with shape `(..., 2)` into its magnitude and phase. Args: complex_tensor (Tensor): Tensor\",\n \"of (freq, 1) Returns: Tensor: Complex Specgrams Stretch with dimension of `(..., freq,\",\n \"that the number of frames is the file size divided by the frame-shift.\",\n \"scale. Args: x (Tensor): Input tensor before being converted to power/amplitude scale. ref\",\n \"cur_sumsq += (frame_to_add ** 2) window_frames = window_end - window_start last_window_start = window_start\",\n \"vs. a full clip. Args: x (Tensor): Input spectrogram(s) before being converted to\",\n \"torch.linspace( >>> 0, math.pi * hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate,\",\n \"norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames = window_end - window_start last_window_start =\",\n \"freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with 231\",\n \"then the complex spectrum is returned instead. normalized (bool): Whether to normalize by\",\n \"spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if power is not None: if power\",\n \"freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\\\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles)\",\n \"return fb def create_dct( n_mfcc: int, n_mels: int, norm: Optional[str] ) -> Tensor:\",\n \"w^2(n)`. \\\"\\\"\\\" EPSILON = 10 ** (-9) # Number of lags to check\",\n \"of the waveform (Hz) frame_time (float, optional): Duration of a frame (Default: ``10\",\n \"clamp ``x`` db_multiplier (float): Log10(max(reference value and amin)) top_db (float or None, optional):\",\n \") -> Tensor: r\\\"\\\"\\\"Compute waveform from a linear scale magnitude spectrogram using the\",\n \"min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep = math.log(6.4)\",\n \"\\\"\\\"\\\" assert momentum < 1, 'momentum={} > 1 can be unstable'.format(momentum) assert momentum\",\n \"the spectrogram coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor\",\n \"freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor, cmn_window: int\",\n \"back when JIT supports it waveform = torch.nn.functional.pad(waveform, (pad, pad), \\\"constant\\\") # pack\",\n \"(freq - f_min) / f_sp # Fill in the log-scale part min_log_hz =\",\n \"3 freqs = f_min + f_sp * mels # And now the nonlinear\",\n \"= torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2,\",\n \"controls the padding method used when :attr:`center` is ``True``. Default: ``\\\"reflect\\\"`` onesided (bool,\",\n \"2494-2498, doi: 10.1109/ICASSP.2014.6854049. \\\"\\\"\\\" shape = waveform.shape waveform = waveform.reshape(-1, shape[-1]) result =\",\n \"that is smallest best = torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] // 2\",\n \"** 2) if window_end > last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum +=\",\n \"down-sample the signal to. Must be more than twice lowpass-cutoff. (default: 4000) delta_pitch(\",\n \"@_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int, format: str, channels_first: bool = True,\",\n \"(string, optional): controls the padding method used when :attr:`center` is ``True``. Default: ``\\\"reflect\\\"``\",\n \"bytes, effects=[[\\\"rate\\\", f\\\"{sample_rate}\\\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate:\",\n \"(float or None): Exponent for the magnitude spectrogram, (must be > 0) e.g.,\",\n \"warnings.warn( \\\"The argument normalized is not used in Griffin-Lim, \\\" \\\"and will be\",\n \"of the norm. (Default: `1.0`). Returns: Tensor: Power of the normed input tensor.\",\n \"/ window_frames variance -= ((cur_sum ** 2) / (window_frames ** 2)) variance =\",\n \"Optional[float] = None ) -> Tensor: r\\\"\\\"\\\"Turn a spectrogram from the power/amplitude scale\",\n \"(Tensor): Tensor of audio of dimension (..., freq, time) cmn_window (int, optional): Window\",\n \"Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi:\",\n \"power (float or None): Exponent for the magnitude spectrogram, (must be > 0)\",\n \"A non-critical parameter; the frame at which we recompute some of the forward\",\n \"= last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels,\",\n \"the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect',\",\n \"Mode parameter passed to padding (Default: ``\\\"replicate\\\"``) Returns: Tensor: Tensor of deltas of\",\n \"# http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels)\",\n \"= int(math.ceil(waveform_length / frame_size)) p = lags + num_of_frames * frame_size - waveform_length\",\n \"Must be 2 dimensional. See also ```channels_first```. sample_rate (int): Sample rate of the\",\n \"* s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2,\",\n \"-= (frame_to_remove ** 2) if window_end > last_window_end: frame_to_add = waveform[:, last_window_end, :]\",\n \"along ``axis``. Mask will be applied from indices ``[v_0, v_0 + v)``, where\",\n \"(pad_length, 0), mode=\\\"constant\\\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1)\",\n \"+ (num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def\",\n \"audio clip split into snippets vs. a full clip. Args: x (Tensor): Input\",\n \"( Default: ``win_length // 2``) win_length (int): Window size. (Default: ``n_fft``) power (float):\",\n \"min_cmn_window: int = 100, center: bool = False, norm_vars: bool = False, )\",\n \"more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes the signal has\",\n \"mean (and optionally variance) normalization per utterance. Args: waveform (Tensor): Tensor of audio\",\n \"= 2 * math.pi * torch.rand(batch, freq, frames) else: angles = torch.zeros(batch, freq,\",\n \"``A * create_fb_matrix(A.size(-1), ...)``. \\\"\\\"\\\" if norm is not None and norm !=\",\n \"float = 10.0, min_f0: float = 50, max_f0: float = 400, soft_min_f0: float\",\n \"specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor, win_length: int = 5,\",\n \"torch.rand(batch, freq, frames) else: angles = torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()],\",\n \"a mask along ``axis``. Mask will be applied from indices ``[v_0, v_0 +\",\n \"(int): Number of frequencies to highlight/apply f_min (float): Minimum frequency (Hz) f_max (float):\",\n \"500, snip_edges: bool = True, ) -> torch.Tensor: \\\"\\\"\\\"Extract pitch based on method\",\n \"optional): Increasing this factor reduces NCCF for quiet frames (default: 7000) lowpass_filter_width (int,\",\n \"1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x =\",\n \"= specgram.reshape([-1] + list(shape[-2:])) value = torch.rand(1) * mask_param min_value = torch.rand(1) *\",\n \"+= 1 return indices def _median_smoothing( indices: Tensor, win_length: int ) -> Tensor:\",\n \"= waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p = lags + num_of_frames *\",\n \"values = mask * a[0] + ~mask * b[0] indices = mask *\",\n \"waveform (Tensor): Tensor of audio of dimension (..., freq, time) sample_rate (int): The\",\n \"quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Encode signal based on mu-law companding. For more\",\n \"Tensor from torchaudio._internal import module_utils as _mod_utils import torchaudio __all__ = [ \\\"spectrogram\\\",\",\n \"Input tensor before being converted to power/amplitude scale. ref (float): Reference which the\",\n \"into the feature processing (affects output only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``)\",\n \"specgram.pow(1 / power) # randomly initialize the phase batch, freq, frames = specgram.size()\",\n \"Number of columns to be masked will be uniformly sampled from [0, mask_param]\",\n \"batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram def compute_deltas( specgram: Tensor, win_length:\",\n \"lag_min # Add 1 empirical calibration offset indices += 1 return indices def\",\n \"= waveform[:, window_start: window_end - window_start, :] cur_sum += torch.sum(input_part, 1) if norm_vars:\",\n \"torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value) # Create broadcastable mask mask_start =\",\n \"/ logstep return mels def _mel_to_hz(mels: Tensor, mel_scale: str = \\\"htk\\\") -> Tensor:\",\n \"<NAME>., & <NAME>. \\\"A fast Griffin-Lim algorithm,\\\" IEEE Workshop on Applications of Signal\",\n \"(int): Length of hop between STFT windows win_length (int): Window size Returns: Tensor:\",\n \"complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0,\",\n \"of augmentation. Args: waveform (Tensor): Audio data. Must be 2 dimensional. See also\",\n \"The input waveform of shape `(..., time)`. sample_rate (float): Sample rate of `waveform`.\",\n \"or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 700.0 * (10.0**(mels / 2595.0) -\",\n \"way, must not exceed min-f0 (default: 10.0) penalty_factor (float, optional): Cost factor for\",\n \"of a complex tensor. Shape of `(..., )` \\\"\\\"\\\" return torch.atan2(complex_tensor[..., 1], complex_tensor[...,\",\n \"supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit\",\n \"per channel enorm = 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *=\",\n \"`(..., freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length = 1025, 512 >>> #\",\n \"In Proceedings of the 14th python in science conference, pp. 18-25. 2015. *\",\n \"(Default: ``None``) Returns: Tensor: Output tensor in decibel scale \\\"\\\"\\\" x_db = multiplier\",\n \"high. \\\" f\\\"Or, the value for `n_freqs` ({n_freqs}) may be set too low.\\\"\",\n \"def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor ) -> Tensor: r\\\"\\\"\\\"Given a\",\n \"with 231 == ceil(300 / 1.3) torch.Size([2, 1025, 231, 2]) \\\"\\\"\\\" # pack\",\n \"2: specgram[:, :, mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency and Time masking\",\n \"values are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window,\",\n \"``htk``) Returns: freqs (Tensor): Mels converted in Hz \\\"\\\"\\\" if mel_scale not in\",\n \"mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency and Time masking are supported') #\",\n \"Window tensor that is applied/multiplied to each frame/window n_fft (int): Size of FFT\",\n \"pack batch shape = waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default values are\",\n \"or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels converted in Hz \\\"\\\"\\\" if\",\n \"Mels converted in Hz \\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale\",\n \"+ waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor, multiplier: float, amin: float, db_multiplier:\",\n \"== 0.).any(): warnings.warn( \\\"At least one mel filterbank has all zero values. \\\"\",\n \"lags is very close to the first half of lags, then the latter\",\n \"Fill in the log-scale part min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min)\",\n \"matrix, to be right-multiplied to row-wise data of size (``n_mels``, ``n_mfcc``). \\\"\\\"\\\" #\",\n \"channel, freq, time) mask_param (int): Number of columns to be masked will be\",\n \"= torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis)\",\n \"math.pi * hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape\",\n \"``uniform(0, max_v - v)``. Args: specgrams (Tensor): Real spectrograms (batch, channel, freq, time)\",\n \"win_length, 1) values, _ = torch.median(roll, -1) return values def detect_pitch_frequency( waveform: Tensor,\",\n \"window_frames = window_end - window_start last_window_start = window_start last_window_end = window_end cmn_waveform[:, t,\",\n \"def sliding_window_cmn( waveform: Tensor, cmn_window: int = 600, min_cmn_window: int = 100, center:\",\n \"dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 - angle_0 - phase_advance\",\n \"value) # Create broadcastable mask mask_start = min_value[..., None, None] mask_end = (min_value\",\n \"t - cmn_window window_end = t + 1 if window_start < 0: window_end\",\n \"our algorithm measures. (default: 0.005) nccf_ballast (float, optional): Increasing this factor reduces NCCF\",\n \"nccf_ballast (float, optional): Increasing this factor reduces NCCF for quiet frames (default: 7000)\",\n \"a signal encoded with values from 0 to quantization_channels - 1. Args: x\",\n \"NCCF. Reference: - A pitch extraction algorithm tuned for automatic speech recognition <NAME>,\",\n \"returned instead. normalized (bool): Whether to normalize by magnitude after stft center (bool,\",\n \"2, n_freqs) # calculate mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max =\",\n \"-> time) Returns: Tensor: Masked spectrogram of dimensions (channel, freq, time) \\\"\\\"\\\" #\",\n \"number of frames of latency that we allow pitch tracking to introduce into\",\n \"complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float, axis: int ) ->\",\n \"constant energy per channel enorm = 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels])\",\n \"latency only at start). Only applicable if center == false, ignored if center==true\",\n \"of lowpass filter, more gives sharper filter. (default: 1) upsample_filter_width (int, optional): Integer\",\n \"Tensor: Dimension (..., freq, time), freq is ``n_fft // 2 + 1`` and\",\n \"specgram.reshape(1, -1, shape[-1]) assert win_length >= 3 n = (win_length - 1) //\",\n \"= mask * a[0] + ~mask * b[0] indices = mask * a[1]\",\n \"cur_sumsq variance = variance / window_frames variance -= ((cur_sum ** 2) / (window_frames\",\n \"> last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum += frame_to_add if norm_vars: cur_sumsq\",\n \"phase recovery process. momentum (float): The momentum parameter for fast Griffin-Lim. Setting this\",\n \"\\\"compute_deltas\\\", \\\"compute_kaldi_pitch\\\", \\\"create_fb_matrix\\\", \\\"create_dct\\\", \\\"compute_deltas\\\", \\\"detect_pitch_frequency\\\", \\\"DB_to_amplitude\\\", \\\"mu_law_encoding\\\", \\\"mu_law_decoding\\\", \\\"complex_norm\\\", \\\"angle\\\", \\\"magphase\\\", \\\"phase_vocoder\\\",\",\n \"include a channel dimension and have the form `(batch, channel, freq, time)`. multiplier\",\n \"complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:])\",\n \"output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf def _combine_max( a: Tuple[Tensor, Tensor], b:\",\n \"frames. (default: True) Returns: Tensor: Pitch feature. Shape: ``(batch, frames 2)`` where the\",\n \"utf-8 -*- import io import math import warnings from typing import Optional, Tuple\",\n \"Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor): A magnitude-only STFT\",\n \"e.g., 1 for energy, 2 for power, etc. normalized (bool): Whether to normalize\",\n \"= 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values\",\n \"pack batch shape = specgram.size() specgram = specgram.reshape(1, -1, shape[-1]) assert win_length >=\",\n \"Apply sliding-window cepstral mean (and optionally variance) normalization per utterance. Args: waveform (Tensor):\",\n \"by the width of the mel band (area normalization). (Default: ``None``) mel_scale (str,\",\n \"the :math:`t`-th frame is centered at time :math:`t \\\\times \\\\text{hop\\\\_length}`. Default: ``True`` pad_mode\",\n \"false, window is to the left. (bool, default = false) norm_vars (bool, optional):\",\n \"Hz to Mels. Args: freqs (float): Frequencies in Hz mel_scale (str, optional): Scale\",\n \"= specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 / power) # randomly initialize the\",\n \"encoding (str, optional): Changes the encoding for the supported formats. For more details\",\n \"size divided by the frame-shift. This makes different types of features give the\",\n \"slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:, 2:] / f_diff[1:]\",\n \"that can be detected (Hz) (Default: ``85``). freq_high (int, optional): Highest frequency that\",\n \"sliding_window_cmn( waveform: Tensor, cmn_window: int = 600, min_cmn_window: int = 100, center: bool\",\n \"r\\\"\\\"\\\"Separate a complex-valued spectrogram with shape `(..., 2)` into its magnitude and phase.\",\n \"n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1])\",\n \"length in milliseconds. (default: 25.0) frame_shift (float, optional): Frame shift in milliseconds. (default:\",\n \"- f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \\\"At least one\",\n \"optional): Integer that determines filter width when upsampling NCCF. (default: 5) max_frames_latency (int,\",\n \"complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power: float = 1.0 ) -> Tuple[Tensor,\",\n \"optional): If true, the function will output features that correspond to what an\",\n \"last_window_end, :] cur_sum += frame_to_add if norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames\",\n \"bool, n_iter: int, momentum: float, length: Optional[int], rand_init: bool ) -> Tensor: r\\\"\\\"\\\"Compute\",\n \"of FFT hop_length (int): Length of hop between STFT windows win_length (int): Window\",\n \"if top_db is not None: # Expand batch shape = x_db.size() packed_channels =\",\n \"Specgrams Stretch with dimension of `(..., freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length\",\n \"sample_rate: int, frame_time: float, freq_low: int ) -> Tensor: r\\\"\\\"\\\" Compute Normalized Cross-Correlation\",\n \"thresh * b[0]) values = mask * a[0] + ~mask * b[0] indices\",\n \"# Add 1 empirical calibration offset indices += 1 return indices def _median_smoothing(\",\n \"return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor, n_fft:\",\n \"dimension (..., freq, time) cmn_window (int, optional): Window in frames for running average\",\n \"frequency bin conversion matrix. Args: n_freqs (int): Number of frequencies to highlight/apply f_min\",\n \"mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. All examples will have the\",\n \"optional): Minimum F0 to search for (Hz) (default: 50.0) max_f0 (float, optional): Maximum\",\n \"final version of the features, which is the default. (default: False) Relevant if\",\n \"specgram = torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta)\",\n \"def mu_law_decoding( x_mu: Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Decode mu-law encoded signal.\",\n \"frame/window n_fft (int): Size of FFT, creates ``n_fft // 2 + 1`` bins\",\n \"complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0\",\n \"weighted average of the frequency values, weighted by their magnitude. Args: waveform (Tensor):\",\n \"linear scale magnitude spectrogram using the Griffin-Lim transformation. Implementation ported from `librosa`. *\",\n \"\\\"\\\"\\\" return ref * torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq: float, mel_scale:\",\n \"with values between 0 and quantization_channels - 1 and returns a signal scaled\",\n \"1.3) torch.Size([2, 1025, 231, 2]) \\\"\\\"\\\" # pack batch shape = complex_specgrams.size() complex_specgrams\",\n \"n_fft (int): Size of FFT hop_length (int): Length of hop between STFT windows\",\n \"in decibel scale \\\"\\\"\\\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier\",\n \"EPSILON = 10 ** (-9) # Number of lags to check lags =\",\n \"Args: waveform (Tensor): Tensor of audio of dimension (..., freq, time) cmn_window (int,\",\n \"optional): Integer that determines filter width of lowpass filter, more gives sharper filter.\",\n \"** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance cmn_waveform =\",\n \"/ 3 freqs = f_min + f_sp * mels # And now the\",\n \"return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor, n_fft: int, hop_length:\",\n \"complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float): Power of the norm.\",\n \"1. Args: x_mu (Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor:\",\n \"return 700.0 * (10.0**(mels / 2595.0) - 1.0) # Fill in the linear\",\n \"+ 1``. window (Tensor): Window tensor that is applied/multiplied to each frame/window n_fft\",\n \"- window_start last_window_start = window_start last_window_end = window_end cmn_waveform[:, t, :] = waveform[:,\",\n \"-1)) - top_db).view(-1, 1, 1, 1)) # Repack batch x_db = x_db.reshape(shape) return\",\n \"frequency EPSILON = 10 ** (-9) freq = sample_rate / (EPSILON + indices.to(torch.float))\",\n \"2]) \\\"\\\"\\\" # pack batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:]))\",\n \"batch shape = waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default values are consistent\",\n \"center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) # Update our phase estimates angles\",\n \"power/amplitude scale to the decibel scale. The output of each tensor in a\",\n \"STFT windows. ( Default: ``win_length // 2``) win_length (int): Window size. (Default: ``n_fft``)\",\n \"``htk``) Returns: Tensor: Triangular filter banks (fb matrix) of size (``n_freqs``, ``n_mels``) meaning\",\n \"phase advance in each bin. Dimension of (freq, 1) Returns: Tensor: Complex Specgrams\",\n \"are supported') device = specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype)\",\n \"in frames for running average CMN computation (int, default = 600) min_cmn_window (int,\",\n \"of dimension (..., time) sample_rate (int): Sample rate of the audio waveform pad\",\n \"formats other than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes\",\n \"last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats,\",\n \"the beginning of frame :math:`i`, :math:`E(j)` is the energy :math:`\\\\sum_{n=j}^{j+N-1} w^2(n)`. \\\"\\\"\\\" EPSILON\",\n \"the original Griffin-Lim method. Values near 1 can lead to faster convergence, but\",\n \"= torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram,\",\n \"be detected (Hz) (Default: ``85``). freq_high (int, optional): Highest frequency that can be\",\n \"Tensor of freq of dimension (..., frame) \\\"\\\"\\\" # pack batch shape =\",\n \"Stretch with dimension of `(..., freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length =\",\n \"size. (Default: ``n_fft``) power (float): Exponent for the magnitude spectrogram, (must be >\",\n \"1 if window_start < 0: window_end -= window_start window_start = 0 if not\",\n \"which we recompute some of the forward pointers, after revising our estimate of\",\n \"(bool, optional): whether to pad :attr:`waveform` on both sides so that the :math:`t`-th\",\n \"power (float): If power equals 1, will compute DB to power. If 0.5,\",\n \"``\\\"replicate\\\"``) Returns: Tensor: Tensor of deltas of dimension (..., freq, time) Example >>>\",\n \"r\\\"\\\"\\\" Compute Normalized Cross-Correlation Function (NCCF). .. math:: \\\\phi_i(m) = \\\\frac{\\\\sum_{n=b_i}^{b_i + N-1}\",\n \"/ (window_frames ** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance\",\n \"sample_rate: int, format: str, channels_first: bool = True, compression: Optional[float] = None, encoding:\",\n \"the Griffin-Lim transformation. Implementation ported from `librosa`. * [1] McFee, Brian, <NAME>, <NAME>,\",\n \":] - cur_sum / window_frames if norm_vars: if window_frames == 1: cmn_waveform[:, t,\",\n \"to highlight/apply to x the number of filterbanks. Each column is a filterbank\",\n \"-> Tensor: r\\\"\\\"\\\"Create a DCT transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized depending\",\n \"for automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE\",\n \"formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit depth\",\n \"converted to decibel scale. Input should take the form `(..., freq, time)`. Batched\",\n \"(default: False) Relevant if ``frames_per_chunk > 0``. recompute_frame (int, optional): Only relevant for\",\n \"fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor ) ->\",\n \"2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values ==\",\n \"by. power (float): If power equals 1, will compute DB to power. If\",\n \"Tensor shape of `(..., complex=2)` power (float): Power of the norm. (Default: `1.0`)\",\n \"``v_0`` from ``uniform(0, max_v - v)``. Args: specgrams (Tensor): Real spectrograms (batch, channel,\",\n \"= torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2]) / f_diff[:-1] # (n_freqs, n_mels)\",\n \"onesided=True, return_complex=True, ) ) # Update our phase estimates angles = rebuilt if\",\n \"dct[0] *= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return dct.t() def\",\n \"Mels \\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be one\",\n \"A reasonable number is 80. (Default: ``None``) Returns: Tensor: Output tensor in decibel\",\n \"(EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf\",\n \"difference between each mel point and each stft freq point in hertz f_diff\",\n \"n_mfcc: int, n_mels: int, norm: Optional[str] ) -> Tensor: r\\\"\\\"\\\"Create a DCT transformation\",\n \"Args: waveform (Tensor): Audio data. Must be 2 dimensional. See also ```channels_first```. sample_rate\",\n \"Tensor: Tensor of deltas of dimension (..., freq, time) Example >>> specgram =\",\n \"depending on norm. Args: n_mfcc (int): Number of mfc coefficients to retain n_mels\",\n \"window_frames if norm_vars: if window_frames == 1: cmn_waveform[:, t, :] = torch.zeros( num_channels,\",\n \"the incomplete frames near the ending edge won't be snipped, so that the\",\n \"waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor,\",\n \"# -*- coding: utf-8 -*- import io import math import warnings from typing\",\n \"penalty_factor: float = 0.1, lowpass_cutoff: float = 1000, resample_frequency: float = 4000, delta_pitch:\",\n \"\\\"\\\"\\\" mask = (a[0] > thresh * b[0]) values = mask * a[0]\",\n \"= -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype,\",\n \"pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate // 2,\",\n \"sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices, win_length) #\",\n \"is to the left. (bool, default = false) norm_vars (bool, optional): If true,\",\n \"of dimension (..., freq, time) win_length (int, optional): The window length used for\",\n \"padding in any dimension indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\\\"constant\\\", value=0. )\",\n \"power is not None: if power == 1.0: return spec_f.abs() return spec_f.abs().pow(power) return\",\n \"(-9) freq = sample_rate / (EPSILON + indices.to(torch.float)) # unpack batch freq =\",\n \"divided by the frame-shift. This makes different types of features give the same\",\n \"# Equivalent filterbank construction by Librosa all_freqs = torch.linspace(0, sample_rate // 2, n_freqs)\",\n \"Sample rate of the audio waveform pad (int): Two sided padding of signal\",\n \"(bool, optional): If true, the function will output features that correspond to what\",\n \"= spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if power is not\",\n \"the output will be scaled by. power (float): If power equals 1, will\",\n \"Frequency and Time masking are supported') # unpack batch specgram = specgram.reshape(shape[:-2] +\",\n \"// 2, steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return\",\n \"specgram[:, mask_start:mask_end] = mask_value elif axis == 2: specgram[:, :, mask_start:mask_end] = mask_value\",\n \"of the mel band (area normalization). (Default: ``None``) mel_scale (str, optional): Scale to\",\n \"quantization_channels - 1. Args: x (Tensor): Input tensor quantization_channels (int): Number of channels\",\n \"an input with values between 0 and quantization_channels - 1 and returns a\",\n \"= True ) -> Tensor: r\\\"\\\"\\\"Create a spectrogram or a batch of spectrograms\",\n \"half = torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best) indices = best[1] #\",\n \"(Tensor): Dimension of `(..., freq, time, complex=2)` rate (float): Speed-up factor phase_advance (Tensor):\",\n \"the signal energy. Relevant if ``frames_per_chunk > 0``. (default: 500) snip_edges (bool, optional):\",\n \"= 30, freq_low: int = 85, freq_high: int = 3400, ) -> Tensor:\",\n \"/ math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor,\",\n \"def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length: float = 25.0, frame_shift: float =\",\n \"n_freqs: int, f_min: float, f_max: float, n_mels: int, sample_rate: int, norm: Optional[str] =\",\n \"encoding \\\"\\\"\\\" mu = quantization_channels - 1.0 if not x.is_floating_point(): x = x.to(torch.float)\",\n \"Returns: Tensor: Tensor of freq of dimension (..., frame) \\\"\\\"\\\" input_shape = waveform.shape\",\n \"frame (Default: ``10 ** (-2)``). win_length (int, optional): The window length for median\",\n \"after mu-law encoding \\\"\\\"\\\" mu = quantization_channels - 1.0 if not x.is_floating_point(): x\",\n \"check lags = int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length =\",\n \"time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio of dimension\",\n \"nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half, best) indices\",\n \"``30``). freq_low (int, optional): Lowest frequency that can be detected (Hz) (Default: ``85``).\",\n \"# (new_bins, freq, 2) complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps +\",\n \"# pack batch shape = waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default values\",\n \"Tensor. If ``channels_first=True``, it has ``[channel, time]`` else ``[time, channel]``. \\\"\\\"\\\" bytes =\",\n \"1``. window (Tensor): Window tensor that is applied/multiplied to each frame/window n_fft (int):\",\n \"int = 3400, ) -> Tensor: r\\\"\\\"\\\"Detect pitch frequency. It is implemented using\",\n \"(float): Speed-up factor phase_advance (Tensor): Expected phase advance in each bin. Dimension of\",\n \"between each mel point and each stft freq point in hertz f_diff =\",\n \"Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins, freq, 2) complex_specgrams_0\",\n \"/ frame_size)) p = lags + num_of_frames * frame_size - waveform_length waveform =\",\n \"80. (Default: ``None``) Returns: Tensor: Output tensor in decibel scale \\\"\\\"\\\" x_db =\",\n \"Tensor: Input after mu-law encoding \\\"\\\"\\\" mu = quantization_channels - 1.0 if not\",\n \"compression (float): Used for formats other than WAV. For mor details see :py:func:`torchaudio.backend.sox_io_backend.save`.\",\n \"(bool, optional): If true, use a window centered on the current frame (to\",\n \"Dimension (..., time) \\\"\\\"\\\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1.,\",\n \"= torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1) values, _\",\n \"shift in milliseconds. (default: 10.0) min_f0 (float, optional): Minimum F0 to search for\",\n \"\\\"replicate\\\" ) -> Tensor: r\\\"\\\"\\\"Compute delta coefficients of a tensor, usually a spectrogram:\",\n \"fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not None and norm ==\",\n \"Tensor: r\\\"\\\"\\\"Decode mu-law encoded signal. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_\",\n \"\\\"The argument normalized is not used in Griffin-Lim, \\\" \\\"and will be removed\",\n \"hop between STFT windows win_length (int): Window size Returns: Tensor: Dimension (..., time)\",\n \"not converge. length (int or None): Array length of the expected output. rand_init\",\n \"input tensor. Shape of `(..., )` \\\"\\\"\\\" # Replace by torch.norm once issue\",\n \"10 ** (-9) freq = sample_rate / (EPSILON + indices.to(torch.float)) # unpack batch\",\n \"-> Tensor: r\\\"\\\"\\\"Detect pitch frequency. It is implemented using normalized cross-correlation function and\",\n \"1, upsample_filter_width: int = 5, max_frames_latency: int = 0, frames_per_chunk: int = 0,\",\n \"feature. Shape: ``(batch, frames 2)`` where the last dimension corresponds to pitch and\",\n \"return_complex=True, ) # unpack batch spec_f = spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f\",\n \"if window_end > last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum += frame_to_add if\",\n \"<https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values between 0 and quantization_channels - 1\",\n \"= 25.0, frame_shift: float = 10.0, min_f0: float = 50, max_f0: float =\",\n \"(2 -> frequency, 3 -> time) Returns: Tensor: Masked spectrograms of dimensions (batch,\",\n \">= 0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \\\"The argument normalized is not\",\n \"db_multiplier if top_db is not None: # Expand batch shape = x_db.size() packed_channels\",\n \"- v)``. Args: specgrams (Tensor): Real spectrograms (batch, channel, freq, time) mask_param (int):\",\n \"!= 2 and axis != 3: raise ValueError('Only Frequency and Time masking are\",\n \"hop_length (int): Length of hop between STFT windows win_length (int): Window size power\",\n \"return specgrams def mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float, axis: int )\",\n \"2 dimensional. See also ```channels_first```. sample_rate (int): Sample rate of the audio waveform.\",\n \"Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values between 0 and quantization_channels -\",\n \"normalized cross-correlation function and median smoothing. Args: waveform (Tensor): Tensor of audio of\",\n \"(Default: ``3400``). Returns: Tensor: Tensor of freq of dimension (..., frame) \\\"\\\"\\\" #\",\n \"(n_frame). \\\"\\\"\\\" if pad > 0: # TODO add \\\"with torch.no_grad():\\\" back when\",\n \"Tensor], b: Tuple[Tensor, Tensor], thresh: float = 0.99 ) -> Tuple[Tensor, Tensor]: \\\"\\\"\\\"\",\n \"cmn_window else: window_start = t - cmn_window window_end = t + 1 if\",\n \"Maximum F0 to search for (Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum f0,\",\n \"torch.stack([angles.cos(), angles.sin()], dim=-1) \\\\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the\",\n \":] cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:,\",\n \"dtype=dtype, device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for t in\",\n \"(float): Maximum frequency (Hz) n_mels (int): Number of mel filterbanks sample_rate (int): Sample\",\n \"mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding( x_mu: Tensor, quantization_channels: int ) ->\",\n \"\\\"htk\\\", ) -> Tensor: r\\\"\\\"\\\"Create a frequency bin conversion matrix. Args: n_freqs (int):\",\n \"be one of \\\"htk\\\" or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 700.0 *\",\n \"slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) fb = torch.max(zero, torch.min(down_slopes, up_slopes)) if\",\n \"has been scaled to between -1 and 1 and returns a signal encoded\",\n \"Values near 1 can lead to faster convergence, but above 1 may not\",\n \"to be masked will be uniformly sampled from [0, mask_param] mask_value (float): Value\",\n \"where :math:`\\\\phi_i(m)` is the NCCF at frame :math:`i` with lag :math:`m`, :math:`w` is\",\n \"indices = best[1] # Add back minimal lag indices += lag_min # Add\",\n \"_compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float, freq_low: int ) -> Tensor: r\\\"\\\"\\\"\",\n \"shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices\",\n \"bits_per_sample (int, optional): Changes the bit depth for the supported formats. For more\",\n \"quantization_channels - 1.0 if not x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype)\",\n \"1000) resample_frequency (float, optional): Frequency that we down-sample the signal to. Must be\",\n \"t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) ==\",\n \"cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform\",\n \"/ f_sp logstep = math.log(6.4) / 27.0 log_t = (mels >= min_log_mel) freqs[log_t]\",\n \"Implementation ported from `librosa`. * [1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>,\",\n \"f_min (float): Minimum frequency (Hz) f_max (float): Maximum frequency (Hz) n_mels (int): Number\",\n \"would be ``A * create_fb_matrix(A.size(-1), ...)``. \\\"\\\"\\\" if norm is not None and\",\n \"-*- import io import math import warnings from typing import Optional, Tuple import\",\n \"dtype=dtype, device=device) for t in range(num_frames): window_start = 0 window_end = 0 if\",\n \"1: cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance =\",\n \"optional): Mode parameter passed to padding (Default: ``\\\"replicate\\\"``) Returns: Tensor: Tensor of deltas\",\n \"1.0 ) -> Tensor: r\\\"\\\"\\\"Compute the norm of complex tensor input. Args: complex_tensor\",\n \"(n, n), mode=mode) kernel = torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1,\",\n \"# Number of lags to check lags = int(math.ceil(sample_rate / freq_low)) frame_size =\",\n \"masking are supported') # unpack batch specgram = specgram.reshape(shape[:-2] + specgram.shape[-2:]) return specgram\",\n \"lag :math:`m`, :math:`w` is the waveform, :math:`N` is the length of a frame,\",\n \"frame) \\\"\\\"\\\" # pack batch shape = list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:])\",\n \"they have dimension ``[time, channel]``. compression (float): Used for formats other than WAV.\",\n \"list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0\",\n \"Number to clamp ``x`` db_multiplier (float): Log10(max(reference value and amin)) top_db (float or\",\n \"in a batch depends on the maximum value of that tensor, and so\",\n \"(..., time) sample_rate (int): Sample rate of the audio waveform pad (int): Two\",\n \"file size divided by the frame-shift. This makes different types of features give\",\n \"* db_multiplier if top_db is not None: # Expand batch shape = x_db.size()\",\n \"enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \\\"At least one mel filterbank has all\",\n \"spec_f /= window.pow(2.).sum().sqrt() if power is not None: if power == 1.0: return\",\n \"mode: str = \\\"replicate\\\" ) -> Tensor: r\\\"\\\"\\\"Compute delta coefficients of a tensor,\",\n \"- value) # Create broadcastable mask mask_start = min_value[..., None, None] mask_end =\",\n \"centered at time :math:`t \\\\times \\\\text{hop\\\\_length}`. Default: ``True`` pad_mode (string, optional): controls the\",\n \"the number of Fourier bins, and time is the number of window hops\",\n \"r\\\"\\\"\\\" Apply median smoothing to the 1D tensor over the given window. \\\"\\\"\\\"\",\n \"previous iterate tprev = rebuilt # Invert with our current estimate of the\",\n \"freq, time) \\\"\\\"\\\" # pack batch shape = specgram.size() specgram = specgram.reshape([-1] +\",\n \"Changes the bit depth for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`.\",\n \"\\\"\\\"\\\" # pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) value\",\n \"the final version of the features, which is the default. (default: False) Relevant\",\n \"\\\"\\\"\\\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs =\",\n \"steps=1 + n_fft // 2, device=specgram.device).reshape((-1, 1)) freq_dim = -2 return (freqs *\",\n \"x_mu (Tensor): Input tensor quantization_channels (int): Number of channels Returns: Tensor: Input after\",\n \"\\\"reflect\\\", onesided: bool = True ) -> Tensor: r\\\"\\\"\\\"Create a spectrogram or a\",\n \"and phase. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float): Power\",\n \"to amplitude. Returns: Tensor: Output tensor in power/amplitude scale. \\\"\\\"\\\" return ref *\",\n \"= complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams: Tensor,\",\n \"scale magnitude spectrogram using the Griffin-Lim transformation. Implementation ported from `librosa`. * [1]\",\n \"== 1: specgram[:, mask_start:mask_end] = mask_value elif axis == 2: specgram[:, :, mask_start:mask_end]\",\n \"Tensor: r\\\"\\\"\\\"Compute the norm of complex tensor input. Args: complex_tensor (Tensor): Tensor shape\",\n \"specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 / power) # randomly\",\n \"Return: Tensor: Angle of a complex tensor. Shape of `(..., )` \\\"\\\"\\\" return\",\n \"waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch\",\n \"torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps % 1.0 phase_0 = angle(complex_specgrams[...,\",\n \"d_t = \\\\frac{\\\\sum_{n=1}^{\\\\text{N}} n (c_{t+n} - c_{t-n})}{2 \\\\sum_{n=1}^{\\\\text{N}} n^2} where :math:`d_t` is the\",\n \"\\\"\\\"\\\" Take value from first if bigger than a multiplicative factor of the\",\n \"window_start -= (window_end - num_frames) window_end = num_frames if window_start < 0: window_start\",\n \"= angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates waveform = torch.istft(specgram * angles,\",\n \"27.0 if freq >= min_log_hz: mels = min_log_mel + math.log(freq / min_log_hz) /\",\n \"signal has been scaled to between -1 and 1 and returns a signal\",\n \"one of \\\"htk\\\" or \\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 2595.0 * math.log10(1.0\",\n \"sampled from [0, mask_param] mask_value (float): Value to assign to the masked columns\",\n \"waveform pad (int): Two sided padding of signal window (Tensor): Window tensor that\",\n \"Shape of `(..., )` \\\"\\\"\\\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0]) def magphase( complex_tensor:\",\n \"center: bool = True, pad_mode: str = \\\"reflect\\\", onesided: bool = True )\",\n \"spectrograms from a raw audio signal. The spectrogram can be either magnitude-only or\",\n \":math:`\\\\phi_i(m)` is the NCCF at frame :math:`i` with lag :math:`m`, :math:`w` is the\",\n \"= 7000, lowpass_filter_width: int = 1, upsample_filter_width: int = 5, max_frames_latency: int =\",\n \"default = 600) min_cmn_window (int, optional): Minimum CMN window used at start of\",\n \"twice sum of integer squared denom = n * (n + 1) *\",\n \"of audio of dimension (..., time) sample_rate (int): Sample rate of the audio\",\n \"for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes\",\n \"# Add back minimal lag indices += lag_min # Add 1 empirical calibration\",\n \"waveform = waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices =\",\n \"is implemented using normalized cross-correlation function and median smoothing. Args: waveform (Tensor): Tensor\",\n \"`(..., 2)` into its magnitude and phase. Args: complex_tensor (Tensor): Tensor shape of\",\n \"This function computes the equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The\",\n \"(Tensor): Tensor shape of `(..., complex=2)` Return: Tensor: Angle of a complex tensor.\",\n \"variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] +\",\n \"0: # TODO add \\\"with torch.no_grad():\\\" back when JIT supports it waveform =\",\n \"Tensor: The transformation matrix, to be right-multiplied to row-wise data of size (``n_mels``,\",\n \"/ (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return\",\n \"or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter banks (fb matrix) of size\",\n \"speed up in time without modifying pitch by a factor of ``rate``. Args:\",\n \"# https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor ) -> Tensor:\",\n \"median smoothing. Args: waveform (Tensor): Tensor of audio of dimension (..., freq, time)\",\n \"waveform[:, t, :] - cur_sum / window_frames if norm_vars: if window_frames == 1:\",\n \"(str, optional): Changes the encoding for the supported formats. For more details see\",\n \"channels_first, compression, format, encoding, bits_per_sample ) bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\\\"rate\\\",\",\n \"masking are supported') device = specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device,\",\n \"max that is smallest best = torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] //\",\n \"angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams: Tensor, rate: float, phase_advance: Tensor )\",\n \"encoded signal. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an\",\n \"from torchaudio._internal import module_utils as _mod_utils import torchaudio __all__ = [ \\\"spectrogram\\\", \\\"griffinlim\\\",\",\n \"for energy normalization. (default: 0) simulate_first_pass_online (bool, optional): If true, the function will\",\n \"by the frame-shift. This makes different types of features give the same number\",\n \"\\\"spectrogram\\\", \\\"griffinlim\\\", \\\"amplitude_to_DB\\\", \\\"DB_to_amplitude\\\", \\\"compute_deltas\\\", \\\"compute_kaldi_pitch\\\", \\\"create_fb_matrix\\\", \\\"create_dct\\\", \\\"compute_deltas\\\", \\\"detect_pitch_frequency\\\", \\\"DB_to_amplitude\\\", \\\"mu_law_encoding\\\", \\\"mu_law_decoding\\\",\",\n \"+ 1, min_cmn_window) if window_end > num_frames: window_start -= (window_end - num_frames) window_end\",\n \"waveform (Tensor): Tensor of audio of dimension (..., time) sample_rate (int): Sample rate\",\n \"windows win_length (int): Window size power (float or None): Exponent for the magnitude\",\n \"# Per batch example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) &\",\n \"_hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels + 2)\",\n \"frame is centered at time :math:`t \\\\times \\\\text{hop\\\\_length}`. Default: ``True`` pad_mode (string, optional):\",\n \"normed input tensor. Shape of `(..., )` \\\"\\\"\\\" # Replace by torch.norm once\",\n \"// 2 window_end = window_start + cmn_window else: window_start = t - cmn_window\",\n \"as a form of augmentation. Args: waveform (Tensor): Audio data. Must be 2\",\n \"pad (int): Two sided padding of signal window (Tensor): Window tensor that is\",\n \"(batch, channel, freq, time) \\\"\\\"\\\" if axis != 2 and axis != 3:\",\n \"if pad > 0: # TODO add \\\"with torch.no_grad():\\\" back when JIT supports\",\n \"of signal window (Tensor): Window tensor that is applied/multiplied to each frame/window n_fft\",\n \"the weighted average of the frequency values, weighted by their magnitude. Args: waveform\",\n \"compute_deltas( specgram: Tensor, win_length: int = 5, mode: str = \\\"replicate\\\" ) ->\",\n \"the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the\",\n \"complex_specgrams_0 = complex_specgrams.index_select(-2, time_steps.long()) complex_specgrams_1 = complex_specgrams.index_select(-2, (time_steps + 1).long()) angle_0 = angle(complex_specgrams_0)\",\n \"window_start window_start = 0 if not center: if window_end > t: window_end =\",\n \"highlight/apply f_min (float): Minimum frequency (Hz) f_max (float): Maximum frequency (Hz) n_mels (int):\",\n \"b[0]) values = mask * a[0] + ~mask * b[0] indices = mask\",\n \"\\\"\\\"\\\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier if\",\n \"of mel filterbanks norm (str or None): Norm to use (either 'ortho' or\",\n \"Axis to apply masking on (2 -> frequency, 3 -> time) Returns: Tensor:\",\n \"optional): Frame shift in milliseconds. (default: 10.0) min_f0 (float, optional): Minimum F0 to\",\n \"cur_sumsq -= (frame_to_remove ** 2) if window_end > last_window_end: frame_to_add = waveform[:, last_window_end,\",\n \"raw audio signal. The spectrogram can be either magnitude-only or complex. Args: waveform\",\n \"angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase =\",\n \"= indices.unfold(-1, win_length, 1) values, _ = torch.median(roll, -1) return values def detect_pitch_frequency(\",\n \"10 ** (-9) # Number of lags to check lags = int(math.ceil(sample_rate /\",\n \"Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float = 0.99 ) -> Tuple[Tensor, Tensor]:\",\n \"= _combine_max(half, best) indices = best[1] # Add back minimal lag indices +=\",\n \"0 window_end = 0 if center: window_start = t - cmn_window // 2\",\n \"\\\"apply_codec\\\", ] def spectrogram( waveform: Tensor, pad: int, window: Tensor, n_fft: int, hop_length:\",\n \"return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int, mask_value: float, axis: int )\",\n \"Compute Phase Accum phase = phase + phase_advance phase = torch.cat([phase_0, phase[..., :-1]],\",\n \"int, momentum: float, length: Optional[int], rand_init: bool ) -> Tensor: r\\\"\\\"\\\"Compute waveform from\",\n \"(default: 5) max_frames_latency (int, optional): Maximum number of frames of latency that we\",\n \"median smoothing (in number of frames) (Default: ``30``). freq_low (int, optional): Lowest frequency\",\n \"of audio of dimension (..., time) pad (int): Two sided padding of signal\",\n \"+ 1 if window_start < 0: window_end -= window_start window_start = 0 if\",\n \"\\\"\\\"\\\" # pack batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps\",\n \"window_end > last_window_end: frame_to_add = waveform[:, last_window_end, :] cur_sum += frame_to_add if norm_vars:\",\n \"to the left. (bool, default = false) norm_vars (bool, optional): If true, normalize\",\n \"(freq / 700.0)) # Fill in the linear part f_min = 0.0 f_sp\",\n \"torch.nn.functional.pad(waveform, (pad, pad), \\\"constant\\\") # pack batch shape = waveform.size() waveform = waveform.reshape(-1,\",\n \"optional): Window in frames for running average CMN computation (int, default = 600)\",\n \"dimension (..., freq, time) sample_rate (int): The sample rate of the waveform (Hz)\",\n \"in pitch that our algorithm measures. (default: 0.005) nccf_ballast (float, optional): Increasing this\",\n \"\\\"angle\\\", \\\"magphase\\\", \\\"phase_vocoder\\\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \\\"spectral_centroid\\\", \\\"apply_codec\\\", ] def spectrogram( waveform: Tensor,\",\n \"True ) -> Tensor: r\\\"\\\"\\\"Create a spectrogram or a batch of spectrograms from\",\n \"normalized (bool): Whether to normalize by magnitude after stft. n_iter (int): Number of\",\n \"Tensor: Power of the normed input tensor. Shape of `(..., )` \\\"\\\"\\\" #\",\n \"freq, ceil(time/rate), complex=2)` Example >>> freq, hop_length = 1025, 512 >>> # (channel,\",\n \"0 if center: window_start = t - cmn_window // 2 window_end = window_start\",\n \"(int): Size of FFT hop_length (int): Length of hop between STFT windows win_length\",\n \"iterate to 0 rebuilt = torch.tensor(0.) for _ in range(n_iter): # Store the\",\n \"if (fb.max(dim=0).values == 0.).any(): warnings.warn( \\\"At least one mel filterbank has all zero\",\n \"with our current estimate of the phases inverse = torch.istft(specgram * angles, n_fft=n_fft,\",\n \"= output.reshape(shape) return output def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float, freq_low:\",\n \"the norm of complex tensor input. Args: complex_tensor (Tensor): Tensor shape of `(...,\",\n \"def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float, freq_low: int ) -> Tensor:\",\n \"columns to be masked will be uniformly sampled from [0, mask_param] mask_value (float):\",\n \"= 100) center (bool, optional): If true, use a window centered on the\",\n \"cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform\",\n \"factor of ``rate``. Args: complex_specgrams (Tensor): Dimension of `(..., freq, time, complex=2)` rate\",\n \"num_feats, dtype=dtype, device=device) else: variance = cur_sumsq variance = variance / window_frames variance\",\n \"\\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']: raise ValueError('mel_scale should be one of\",\n \"Returns: Tensor: Dimension (..., time) \\\"\\\"\\\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length,\",\n \"_ in range(n_iter): # Store the previous iterate tprev = rebuilt # Invert\",\n \"Optional[int] = None, ) -> Tensor: r\\\"\\\"\\\" Apply codecs as a form of\",\n \"angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2,\",\n \"indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll = indices.unfold(-1, win_length, 1)\",\n \"hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate // 2, steps=1 + n_fft\",\n \"Fill in the linear part f_min = 0.0 f_sp = 200.0 / 3\",\n \"if bigger than a multiplicative factor of the second, elementwise. \\\"\\\"\\\" mask =\",\n \"= rebuilt # Invert with our current estimate of the phases inverse =\",\n \"mel bin numbers to frequencies. Args: mels (Tensor): Mel frequencies mel_scale (str, optional):\",\n \"\\\"mu_law_decoding\\\", \\\"complex_norm\\\", \\\"angle\\\", \\\"magphase\\\", \\\"phase_vocoder\\\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \\\"spectral_centroid\\\", \\\"apply_codec\\\", ] def spectrogram(\",\n \"is sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. All\",\n \"= math.log(6.4) / 27.0 if freq >= min_log_hz: mels = min_log_mel + math.log(freq\",\n \"value.long()).squeeze() assert mask_end - mask_start < mask_param if axis == 1: specgram[:, mask_start:mask_end]\",\n \"the length of a frame, :math:`b_i` is the beginning of frame :math:`i`, :math:`E(j)`\",\n \"window_start < 0: window_end -= window_start window_start = 0 if not center: if\",\n \"r\\\"\\\"\\\"Detect pitch frequency. It is implemented using normalized cross-correlation function and median smoothing.\",\n \"* torch.log1p(mu * torch.abs(x)) / torch.log1p(mu) x_mu = ((x_mu + 1) / 2\",\n \"soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges,\",\n \"creates ``n_fft // 2 + 1`` bins hop_length (int): Length of hop between\",\n \":math:`w` is the waveform, :math:`N` is the length of a frame, :math:`b_i` is\",\n \"the 14th python in science conference, pp. 18-25. 2015. * [2] <NAME>., <NAME>.,\",\n \"scale f_min = 0.0 f_sp = 200.0 / 3 freqs = f_min +\",\n \"will have the same mask interval. Args: specgram (Tensor): Real spectrogram (channel, freq,\",\n \"of `(..., complex=2)` Return: Tensor: Angle of a complex tensor. Shape of `(...,\",\n \"* frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size)) p = lags\",\n \"float = 10.0, penalty_factor: float = 0.1, lowpass_cutoff: float = 1000, resample_frequency: float\",\n \"indices += lag_min # Add 1 empirical calibration offset indices += 1 return\",\n \"of a tensor, usually a spectrogram: .. math:: d_t = \\\\frac{\\\\sum_{n=1}^{\\\\text{N}} n (c_{t+n}\",\n \"def DB_to_amplitude( x: Tensor, ref: float, power: float ) -> Tensor: r\\\"\\\"\\\"Turn a\",\n \"frame) \\\"\\\"\\\" input_shape = waveform.shape num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames,\",\n \"function will output features that correspond to what an online decoder would see\",\n \"Args: x (Tensor): Input spectrogram(s) before being converted to decibel scale. Input should\",\n \"== \\\"ortho\\\" dct[0] *= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return\",\n \"float, normalized: bool, n_iter: int, momentum: float, length: Optional[int], rand_init: bool ) ->\",\n \"** (-2), win_length: int = 30, freq_low: int = 85, freq_high: int =\",\n \"= 85, freq_high: int = 3400, ) -> Tensor: r\\\"\\\"\\\"Detect pitch frequency. It\",\n \"list(shape[-2:])) specgram = specgram.pow(1 / power) # randomly initialize the phase batch, freq,\",\n \"frequencies. Args: mels (Tensor): Mel frequencies mel_scale (str, optional): Scale to use: ``htk``\",\n \"norm != \\\"slaney\\\": raise ValueError(\\\"norm must be one of None or 'slaney'\\\") #\",\n \"The window length used for computing delta (Default: ``5``) mode (str, optional): Mode\",\n \"(float, optional): Frequency that we down-sample the signal to. Must be more than\",\n \"The output of each tensor in a batch depends on the maximum value\",\n \"online pitch extraction. A non-critical parameter; the frame at which we recompute some\",\n \"-1) mag = alphas * norm_1 + (1 - alphas) * norm_0 real_stretch\",\n \"used for energy normalization. (default: 0) simulate_first_pass_online (bool, optional): If true, the function\",\n \"else: raise ValueError('Only Frequency and Time masking are supported') # unpack batch specgram\",\n \"['slaney', 'htk']: raise ValueError('mel_scale should be one of \\\"htk\\\" or \\\"slaney\\\".') if mel_scale\",\n \"\\\"spectral_centroid\\\", \\\"apply_codec\\\", ] def spectrogram( waveform: Tensor, pad: int, window: Tensor, n_fft: int,\",\n \"spec_f.reshape(shape[:-1] + spec_f.shape[-2:]) if normalized: spec_f /= window.pow(2.).sum().sqrt() if power is not None:\",\n \"optional): Changes the bit depth for the supported formats. For more details see\",\n \"Tensor: Complex Specgrams Stretch with dimension of `(..., freq, ceil(time/rate), complex=2)` Example >>>\",\n \"angle_1 - angle_0 - phase_advance phase = phase - 2 * math.pi *\",\n \"-> Tensor: r\\\"\\\"\\\" Compute the spectral centroid for each channel along the time\",\n \"float, optional): Smallest relative change in pitch that our algorithm measures. (default: 0.005)\",\n \"input_part = waveform[:, window_start: window_end - window_start, :] cur_sum += torch.sum(input_part, 1) if\",\n \"Tensor: r\\\"\\\"\\\"Create a spectrogram or a batch of spectrograms from a raw audio\",\n \":attr:`center` is ``True``. Default: ``\\\"reflect\\\"`` onesided (bool, optional): controls whether to return half\",\n \"Returns: Tensor: Triangular filter banks (fb matrix) of size (``n_freqs``, ``n_mels``) meaning number\",\n \"at start of decoding (adds latency only at start). Only applicable if center\",\n \"1D tensor over the given window. \\\"\\\"\\\" # Centered windowed pad_length = (win_length\",\n \"cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1,\",\n \"Tensor, rate: float, phase_advance: Tensor ) -> Tensor: r\\\"\\\"\\\"Given a STFT tensor, speed\",\n \"STFT windows win_length (int): Window size Returns: Tensor: Dimension (..., time) \\\"\\\"\\\" specgram\",\n \"``slaney``. (Default: ``htk``) Returns: mels (float): Frequency in Mels \\\"\\\"\\\" if mel_scale not\",\n \"variance / window_frames variance -= ((cur_sum ** 2) / (window_frames ** 2)) variance\",\n \"dtype=dtype) # Per batch example masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start)\",\n \"size power (float or None): Exponent for the magnitude spectrogram, (must be >\",\n \"of dimensions (channel, freq, time) \\\"\\\"\\\" # pack batch shape = specgram.size() specgram\",\n \"assumes the signal has been scaled to between -1 and 1 and returns\",\n \"alphas = time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1, :]) # Time Padding\",\n \"mode (str, optional): Mode parameter passed to padding (Default: ``\\\"replicate\\\"``) Returns: Tensor: Tensor\",\n \"Acoustics (pp. 1-4), Oct. 2013. * [3] <NAME> and <NAME>, \\\"Signal estimation from\",\n \"unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor,\",\n \"spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor, n_fft: int, hop_length: int,\",\n \"cmn_window: int = 600, min_cmn_window: int = 100, center: bool = False, norm_vars:\",\n \"== \\\"slaney\\\": # Slaney-style mel is scaled to be approx constant energy per\",\n \"device=device) cmn_waveform = torch.zeros( num_channels, num_frames, num_feats, dtype=dtype, device=device) for t in range(num_frames):\",\n \":attr:`waveform` on both sides so that the :math:`t`-th frame is centered at time\",\n \"# Create broadcastable mask mask_start = min_value[..., None, None] mask_end = (min_value +\",\n \"- mask_start < mask_param if axis == 1: specgram[:, mask_start:mask_end] = mask_value elif\",\n \"pad: int, window: Tensor, n_fft: int, hop_length: int, win_length: int, power: Optional[float], normalized:\",\n \"0), mode=\\\"constant\\\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length * [indices[..., pad_length].unsqueeze(-1)], dim=-1) roll\",\n \"create_dct( n_mfcc: int, n_mels: int, norm: Optional[str] ) -> Tensor: r\\\"\\\"\\\"Create a DCT\",\n \"the current frame (to the extent possible, modulo end effects). If false, window\",\n \"= waveform.device last_window_start = last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device)\",\n \"def complex_norm( complex_tensor: Tensor, power: float = 1.0 ) -> Tensor: r\\\"\\\"\\\"Compute the\",\n \"if normalized: spec_f /= window.pow(2.).sum().sqrt() if power is not None: if power ==\",\n \"specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end), mask_value) specgrams\",\n \"(area normalization). (Default: ``None``) mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``.\",\n \"+ 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0) if (fb.max(dim=0).values == 0.).any(): warnings.warn( \\\"At\",\n \"Create broadcastable mask mask_start = min_value[..., None, None] mask_end = (min_value + value)[...,\",\n \"is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def angle( complex_tensor: Tensor )\",\n \"Args: n_freqs (int): Number of frequencies to highlight/apply f_min (float): Minimum frequency (Hz)\",\n \"batch output = output.reshape(shape) return output def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time:\",\n \"+ 1`` and ``n_fft`` is the number of Fourier bins, and time is\",\n \"= ( (s1 * s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON\",\n \"window_end = window_start + cmn_window else: window_start = t - cmn_window window_end =\",\n \"milliseconds. (default: 10.0) min_f0 (float, optional): Minimum F0 to search for (Hz) (default:\",\n \"Optional, Tuple import torch from torch import Tensor from torchaudio._internal import module_utils as\",\n \"scale. \\\"\\\"\\\" return ref * torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq: float,\",\n \"= quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu,\",\n \"None: # Expand batch shape = x_db.size() packed_channels = shape[-3] if x_db.dim() >\",\n \"Tuple import torch from torch import Tensor from torchaudio._internal import module_utils as _mod_utils\",\n \"empirical calibration offset indices += 1 return indices def _median_smoothing( indices: Tensor, win_length:\",\n \"variance = cur_sumsq variance = variance / window_frames variance -= ((cur_sum ** 2)\",\n \"torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu) * 2 - 1.0 x =\",\n \"power) phase = angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams: Tensor, rate: float,\",\n \"+ indices.to(torch.float)) # unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def\",\n \"shape[-1]) # default values are consistent with librosa.core.spectrum._spectrogram spec_f = torch.stft( input=waveform, n_fft=n_fft,\",\n \"one of None or 'slaney'\\\") # freq bins # Equivalent filterbank construction by\",\n \"Tuple[Tensor, Tensor]: \\\"\\\"\\\" Take value from first if bigger than a multiplicative factor\",\n \"calibration offset indices += 1 return indices def _median_smoothing( indices: Tensor, win_length: int\",\n \"``rate``. Args: complex_specgrams (Tensor): Dimension of `(..., freq, time, complex=2)` rate (float): Speed-up\",\n \"= waveform.shape num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels =\",\n \"may be set too high. \\\" f\\\"Or, the value for `n_freqs` ({n_freqs}) may\",\n \"torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor, n_fft: int, hop_length: int, win_length: int,\",\n \"amplitude amin (float): Number to clamp ``x`` db_multiplier (float): Log10(max(reference value and amin))\",\n \"\\\"\\\"\\\" # Replace by torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5\",\n \"dtype = specgram.dtype # pack batch shape = specgram.size() specgram = specgram.reshape(1, -1,\",\n \"(``n_mels``, ``n_mfcc``), normalized depending on norm. Args: n_mfcc (int): Number of mfc coefficients\",\n \"* [2] <NAME>., <NAME>., & <NAME>. \\\"A fast Griffin-Lim algorithm,\\\" IEEE Workshop on\",\n \"<NAME> 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence,\",\n \"data. Must be 2 dimensional. See also ```channels_first```. sample_rate (int): Sample rate of\",\n \"be right-multiplied to row-wise data of size (``n_mels``, ``n_mfcc``). \\\"\\\"\\\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n\",\n \"= [] for lag in range(1, lags + 1): s1 = waveform[..., :-lag].unfold(-1,\",\n \"default. (default: False) Relevant if ``frames_per_chunk > 0``. recompute_frame (int, optional): Only relevant\",\n \"f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between each mel point and\",\n \"shape = x_db.size() packed_channels = shape[-3] if x_db.dim() > 2 else 1 x_db\",\n \"= torch.zeros( num_channels, num_feats, dtype=dtype, device=device) else: variance = cur_sumsq variance = variance\",\n \"Use 10. for power and 20. for amplitude amin (float): Number to clamp\",\n \"phase of the complex tensor \\\"\\\"\\\" mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor)\",\n \"phase - 2 * math.pi * torch.round(phase / (2 * math.pi)) # Compute\",\n \"If true, normalize variance to one. (bool, default = false) Returns: Tensor: Tensor\",\n \"optional): Only relevant for compatibility with online pitch extraction. A non-critical parameter; the\",\n \"relevant for compatibility with online pitch extraction. A non-critical parameter; the frame at\",\n \"/ 3 specgram = torch.nn.functional.pad(specgram, (n, n), mode=mode) kernel = torch.arange(-n, n +\",\n \"squared denom = n * (n + 1) * (2 * n +\",\n \"None): Exponent for the magnitude spectrogram, (must be > 0) e.g., 1 for\",\n \"bool ) -> Tensor: r\\\"\\\"\\\"Compute waveform from a linear scale magnitude spectrogram using\",\n \"win_length: int = 5, mode: str = \\\"replicate\\\" ) -> Tensor: r\\\"\\\"\\\"Compute delta\",\n \"Tensor of audio of dimension (..., freq, time) cmn_window (int, optional): Window in\",\n \"= torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\\\"rate\\\", f\\\"{sample_rate}\\\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform:\",\n \"a complex-valued spectrogram with shape `(..., 2)` into its magnitude and phase. Args:\",\n \"float, n_mels: int, sample_rate: int, norm: Optional[str] = None, mel_scale: str = \\\"htk\\\",\",\n \"``v`` is sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``.\",\n \"not None and norm == \\\"slaney\\\": # Slaney-style mel is scaled to be\",\n \"0: window_end -= window_start window_start = 0 if not center: if window_end >\",\n \"specgram = specgram.reshape([-1] + list(shape[-2:])) specgram = specgram.pow(1 / power) # randomly initialize\",\n \"/ float(n_mels) * (n + 0.5) * k) # size (n_mfcc, n_mels) if\",\n \"Shape of `(..., )` \\\"\\\"\\\" # Replace by torch.norm once issue is fixed\",\n \"``n_freqs``), the applied result would be ``A * create_fb_matrix(A.size(-1), ...)``. \\\"\\\"\\\" if norm\",\n \"return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window: Tensor, n_fft: int, hop_length: int, win_length:\",\n \"specgram: Tensor, win_length: int = 5, mode: str = \\\"replicate\\\" ) -> Tensor:\",\n \"the first half of lags, then the latter is taken. \\\"\\\"\\\" lag_min =\",\n \"and output Tensor have dimension ``[channel, time]``. Otherwise, they have dimension ``[time, channel]``.\",\n \"Tensor have dimension ``[channel, time]``. Otherwise, they have dimension ``[time, channel]``. compression (float):\",\n \"float = 0.005, nccf_ballast: float = 7000, lowpass_filter_width: int = 1, upsample_filter_width: int\",\n \"``True`` Returns: Tensor: Dimension (..., freq, time), freq is ``n_fft // 2 +\",\n \"1) Returns: Tensor: Complex Specgrams Stretch with dimension of `(..., freq, ceil(time/rate), complex=2)`\",\n \"redundancy. Default: ``True`` Returns: Tensor: Dimension (..., freq, time), freq is ``n_fft //\",\n \"(int): Length of hop between STFT windows win_length (int): Window size power (float\",\n \"utterance. Args: waveform (Tensor): Tensor of audio of dimension (..., freq, time) cmn_window\",\n \"power and 20. for amplitude amin (float): Number to clamp ``x`` db_multiplier (float):\",\n \"freq, time, complex=2) >>> complex_specgrams = torch.randn(2, freq, 300, 2) >>> rate =\",\n \"input_shape = waveform.shape num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels\",\n \"in soft way, must not exceed min-f0 (default: 10.0) penalty_factor (float, optional): Cost\",\n \"the spectral centroid for each channel along the time axis. The spectral centroid\",\n \"max_v - v)``. All examples will have the same mask interval. Args: specgram\",\n \"* [1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \\\"librosa: Audio\",\n \"to the first half of lags, then the latter is taken. \\\"\\\"\\\" lag_min\",\n \"Shape: ``(batch, frames 2)`` where the last dimension corresponds to pitch and NCCF.\",\n \"details see :py:func:`torchaudio.backend.sox_io_backend.save`. encoding (str, optional): Changes the encoding for the supported formats.\",\n \"1)[:, -1, :] else: if window_start > last_window_start: frame_to_remove = waveform[:, last_window_start, :]\",\n \"in any dimension indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\\\"constant\\\", value=0. ) indices[...,\",\n \"create_fb_matrix( n_freqs: int, f_min: float, f_max: float, n_mels: int, sample_rate: int, norm: Optional[str]\",\n \"measures. (default: 0.005) nccf_ballast (float, optional): Increasing this factor reduces NCCF for quiet\",\n \"recovers the original Griffin-Lim method. Values near 1 can lead to faster convergence,\",\n \"half of results to avoid redundancy. Default: ``True`` Returns: Tensor: Dimension (..., freq,\",\n \"if window_frames == 1: cmn_waveform[:, t, :] = torch.zeros( num_channels, num_feats, dtype=dtype, device=device)\",\n \"Tensor, sample_rate: int, freq_high: int ) -> Tensor: r\\\"\\\"\\\" For each frame, take\",\n \"(specgrams.size(axis) - value) # Create broadcastable mask mask_start = min_value[..., None, None] mask_end\",\n \"\\\"slaney\\\".') if mel_scale == \\\"htk\\\": return 2595.0 * math.log10(1.0 + (freq / 700.0))\",\n \"each frame/window n_fft (int): Size of FFT, creates ``n_fft // 2 + 1``\",\n \"power) def angle( complex_tensor: Tensor ) -> Tensor: r\\\"\\\"\\\"Compute the angle of complex\",\n \"freqs (Tensor): Mels converted in Hz \\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']:\",\n \"momentum < 1, 'momentum={} > 1 can be unstable'.format(momentum) assert momentum >= 0,\",\n \"(..., freq, time) sample_rate (int): The sample rate of the waveform (Hz) frame_time\",\n \"-1) best = _combine_max(half, best) indices = best[1] # Add back minimal lag\",\n \"Power of the norm. (Default: `1.0`). Returns: Tensor: Power of the normed input\",\n \"is ``n_fft // 2 + 1`` and ``n_fft`` is the number of Fourier\",\n \"/ specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int, format: str, channels_first: bool\",\n \"frames (default: 7000) lowpass_filter_width (int, optional): Integer that determines filter width of lowpass\",\n \"nccf = _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices =\",\n \"complex=2) >>> complex_specgrams = torch.randn(2, freq, 300, 2) >>> rate = 1.3 #\",\n \"= torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1, p=2, dim=-1) phase = angle_1 -\",\n \"waveform: Tensor, sample_rate: int, format: str, channels_first: bool = True, compression: Optional[float] =\",\n \"norm is not None and norm == \\\"slaney\\\": # Slaney-style mel is scaled\",\n \"(..., freq, time) win_length (int, optional): The window length used for computing delta\",\n \"1 return indices def _median_smoothing( indices: Tensor, win_length: int ) -> Tensor: r\\\"\\\"\\\"\",\n \"corresponds to pitch and NCCF. Reference: - A pitch extraction algorithm tuned for\",\n \"f_min + f_sp * mels # And now the nonlinear scale min_log_hz =\",\n \"= angles - tprev.mul_(momentum / (1 + momentum)) angles = angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return\",\n \"= -2 return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor,\",\n \"to be right-multiplied to row-wise data of size (``n_mels``, ``n_mfcc``). \\\"\\\"\\\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II\",\n \"in range(num_frames): window_start = 0 window_end = 0 if center: window_start = t\",\n \"int, frame_time: float, freq_low: int ) -> Tensor: r\\\"\\\"\\\" Compute Normalized Cross-Correlation Function\",\n \"to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter banks (fb\",\n \"- value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert mask_end -\",\n \"input=waveform, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack\",\n \"`(..., time)`. sample_rate (float): Sample rate of `waveform`. frame_length (float, optional): Frame length\",\n \"Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins, freq, 2)\",\n \"Maximum frequency (Hz) n_mels (int): Number of mel filterbanks sample_rate (int): Sample rate\",\n \"mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch example masking specgrams =\",\n \"mu_law_decoding( x_mu: Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Decode mu-law encoded signal. For\",\n \"(float, optional): Minimum F0 to search for (Hz) (default: 50.0) max_f0 (float, optional):\",\n \"-= multiplier * db_multiplier if top_db is not None: # Expand batch shape\",\n \"values, _ = torch.median(roll, -1) return values def detect_pitch_frequency( waveform: Tensor, sample_rate: int,\",\n \"be masked will be uniformly sampled from [0, mask_param] mask_value (float): Value to\",\n \"Integer that determines filter width when upsampling NCCF. (default: 5) max_frames_latency (int, optional):\",\n \"optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: mels (float): Frequency\",\n \"max among all the lags is very close to the first half of\",\n \") -> Tensor: r\\\"\\\"\\\" Apply codecs as a form of augmentation. Args: waveform\",\n \"scaled between -1 and 1. Args: x_mu (Tensor): Input tensor quantization_channels (int): Number\",\n \"(Tensor): A magnitude-only STFT spectrogram of dimension (..., freq, frames) where freq is\",\n \"- f_min) / f_sp logstep = math.log(6.4) / 27.0 log_t = (mels >=\",\n \"int, frame_time: float = 10 ** (-2), win_length: int = 30, freq_low: int\",\n \"audio of dimension (..., time) sample_rate (int): Sample rate of the audio waveform\",\n \"Default: ``\\\"reflect\\\"`` onesided (bool, optional): controls whether to return half of results to\",\n \"frames for running average CMN computation (int, default = 600) min_cmn_window (int, optional):\",\n \"some of the forward pointers, after revising our estimate of the signal energy.\",\n \"1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack batch output\",\n \"automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE International\",\n \"[0, mask_param] mask_value (float): Value to assign to the masked columns axis (int):\",\n \"coefficients to retain n_mels (int): Number of mel filterbanks norm (str or None):\",\n \"min_value[..., None, None] mask_end = (min_value + value)[..., None, None] mask = torch.arange(0,\",\n \"\\\"constant\\\") # pack batch shape = waveform.size() waveform = waveform.reshape(-1, shape[-1]) # default\",\n \"/ f_sp # Fill in the log-scale part min_log_hz = 1000.0 min_log_mel =\",\n \"(-9) # Number of lags to check lags = int(math.ceil(sample_rate / freq_low)) frame_size\",\n \"specgram.device dtype = specgram.dtype # pack batch shape = specgram.size() specgram = specgram.reshape(1,\",\n \"None, optional): Minimum negative cut-off in decibels. A reasonable number is 80. (Default:\",\n \"a factor of ``rate``. Args: complex_specgrams (Tensor): Dimension of `(..., freq, time, complex=2)`\",\n \"of lags to check lags = int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate *\",\n \"None: dct *= 2.0 else: assert norm == \\\"ortho\\\" dct[0] *= 1.0 /\",\n \"** 2, 1)[:, -1, :] else: if window_start > last_window_start: frame_to_remove = waveform[:,\",\n \"bool = False, recompute_frame: int = 500, snip_edges: bool = True, ) ->\",\n \"that correspond to what an online decoder would see in the first pass\",\n \"if norm is None: dct *= 2.0 else: assert norm == \\\"ortho\\\" dct[0]\",\n \"mel weights by the width of the mel band (area normalization). (Default: ``None``)\",\n \"torch.nn.functional.pad( indices, (pad_length, 0), mode=\\\"constant\\\", value=0. ) indices[..., :pad_length] = torch.cat(pad_length * [indices[...,\",\n \"near the ending edge won't be snipped, so that the number of frames\",\n \"half_size = nccf.shape[-1] // 2 half = torch.max(nccf[..., lag_min:half_size], -1) best = _combine_max(half,\",\n \"output features that correspond to what an online decoder would see in the\",\n \"time, complex=2)` rate (float): Speed-up factor phase_advance (Tensor): Expected phase advance in each\",\n \">>> complex_specgrams = torch.randn(2, freq, 300, 2) >>> rate = 1.3 # Speed\",\n \"Phase Accum phase = phase + phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1)\",\n \"mask_param min_value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * (specgrams.size(axis) - value) # Create broadcastable\",\n \"to search for (Hz) (default: 50.0) max_f0 (float, optional): Maximum F0 to search\",\n \"time) Example >>> specgram = torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram) >>>\",\n \"1 can be unstable'.format(momentum) assert momentum >= 0, 'momentum={} < 0'.format(momentum) if normalized:\",\n \"all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) # create overlapping triangles zero = torch.zeros(1)\",\n \"* [3] <NAME> and <NAME>, \\\"Signal estimation from modified short-time Fourier transform,\\\" IEEE\",\n \"str, channels_first: bool = True, compression: Optional[float] = None, encoding: Optional[str] = None,\",\n \"in science conference, pp. 18-25. 2015. * [2] <NAME>., <NAME>., & <NAME>. \\\"A\",\n \"Equivalent filterbank construction by Librosa all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) #\",\n \"output = output.reshape(shape) return output def _compute_nccf( waveform: Tensor, sample_rate: int, frame_time: float,\",\n \"slopes = f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) # create overlapping\",\n \"soft_min_f0: float = 10.0, penalty_factor: float = 0.1, lowpass_cutoff: float = 1000, resample_frequency:\",\n \"of Signal Processing to Audio and Acoustics (pp. 1-4), Oct. 2013. * [3]\",\n \"= cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return\",\n \"one. (bool, default = false) Returns: Tensor: Tensor of freq of dimension (...,\",\n \"str = \\\"htk\\\") -> float: r\\\"\\\"\\\"Convert Hz to Mels. Args: freqs (float): Frequencies\",\n \"rand_init (bool): Initializes phase randomly if True, to zero otherwise. Returns: torch.Tensor: waveform\",\n \"to retain n_mels (int): Number of mel filterbanks norm (str or None): Norm\",\n \"k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) * (n + 0.5) *\",\n \"= torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu return x def\",\n \"(Tensor): Tensor shape of `(..., complex=2)` power (float): Power of the norm. (Default:\",\n \"axis (int): Axis to apply masking on (1 -> frequency, 2 -> time)\",\n \"Tensor, n_fft: int, hop_length: int, win_length: int, ) -> Tensor: r\\\"\\\"\\\" Compute the\",\n \"-1: input_part = waveform[:, window_start: window_end - window_start, :] cur_sum += torch.sum(input_part, 1)\",\n \"center (bool, optional): If true, use a window centered on the current frame\",\n \"of window hops (n_frame). \\\"\\\"\\\" if pad > 0: # TODO add \\\"with\",\n \"more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values\",\n \"v)``, where ``v`` is sampled from ``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v\",\n \"Args: waveform (Tensor): Tensor of audio of dimension (..., freq, time) sample_rate (int):\",\n \"p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag,\",\n \"(float, optional): Cost factor for FO change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff\",\n \"+= torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2, 1)[:, -1, :]\",\n \"scale. The output of each tensor in a batch depends on the maximum\",\n \"to what an online decoder would see in the first pass of decoding\",\n \"Frame length in milliseconds. (default: 25.0) frame_shift (float, optional): Frame shift in milliseconds.\",\n \"# pack batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps =\",\n \"+ phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag\",\n \"``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter banks (fb matrix) of\",\n \"# Centered windowed pad_length = (win_length - 1) // 2 # \\\"replicate\\\" padding\",\n \"== false, ignored if center==true (int, default = 100) center (bool, optional): If\",\n \">>> 0, math.pi * hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance)\",\n \"dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2],\",\n \"window_start, :] cur_sum += torch.sum(input_part, 1) if norm_vars: cur_sumsq += torch.cumsum(input_part ** 2,\",\n \"waveform.device last_window_start = last_window_end = -1 cur_sum = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq\",\n \"momentum parameter for fast Griffin-Lim. Setting this to 0 recovers the original Griffin-Lim\",\n \"window_start last_window_start = window_start last_window_end = window_end cmn_waveform[:, t, :] = waveform[:, t,\",\n \"``frames_per_chunk > 0``. recompute_frame (int, optional): Only relevant for compatibility with online pitch\",\n \"compatibility with online pitch extraction. A non-critical parameter; the frame at which we\",\n \"~mask * b[0] indices = mask * a[1] + ~mask * b[1] return\",\n \"1.0 if not x.is_floating_point(): x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu =\",\n \"a window centered on the current frame (to the extent possible, modulo end\",\n \"len(input_shape) == 2: cmn_waveform = cmn_waveform.squeeze(0) return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate:\",\n \"Centered windowed pad_length = (win_length - 1) // 2 # \\\"replicate\\\" padding in\",\n \"= \\\"reflect\\\", onesided: bool = True ) -> Tensor: r\\\"\\\"\\\"Create a spectrogram or\",\n \"= waveform[:, t, :] - cur_sum / window_frames if norm_vars: if window_frames ==\",\n \"value from first if bigger than a multiplicative factor of the second, elementwise.\",\n \"frames used for energy normalization. (default: 0) simulate_first_pass_online (bool, optional): If true, the\",\n \"all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) # calculate mel freq bins m_min\",\n \"torch.rand(1) * (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze()\",\n \"( (s1 * s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON +\",\n \"best[1] # Add back minimal lag indices += lag_min # Add 1 empirical\",\n \"filterbank has all zero values. \\\" f\\\"The value for `n_mels` ({n_mels}) may be\",\n \") -> Tensor: r\\\"\\\"\\\" For each frame, take the highest value of NCCF,\",\n \"``85``). freq_high (int, optional): Highest frequency that can be detected (Hz) (Default: ``3400``).\",\n \"randomly if True, to zero otherwise. Returns: torch.Tensor: waveform of (..., time), where\",\n \"hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with\",\n \"return ref * torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq: float, mel_scale: str\",\n \"- min_log_mel)) return freqs def create_fb_matrix( n_freqs: int, f_min: float, f_max: float, n_mels:\",\n \"coeffcients at time :math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio\",\n \"International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498,\",\n \"of spectrograms from a raw audio signal. The spectrogram can be either magnitude-only\",\n \"\\\"htk\\\": return 2595.0 * math.log10(1.0 + (freq / 700.0)) # Fill in the\",\n \"def create_fb_matrix( n_freqs: int, f_min: float, f_max: float, n_mels: int, sample_rate: int, norm:\",\n \"mu_law_encoding( x: Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Encode signal based on mu-law\",\n \"Tensor, win_length: int = 5, mode: str = \\\"replicate\\\" ) -> Tensor: r\\\"\\\"\\\"Compute\",\n \"and 1. Args: x_mu (Tensor): Input tensor quantization_channels (int): Number of channels Returns:\",\n \"the linear part f_min = 0.0 f_sp = 200.0 / 3 mels =\",\n \"form `(..., freq, time)`. Batched inputs should include a channel dimension and have\",\n \"max_v - v)``. Args: specgrams (Tensor): Real spectrograms (batch, channel, freq, time) mask_param\",\n \"Each column is a filterbank so that assuming there is a matrix A\",\n \"clip. Args: x (Tensor): Input spectrogram(s) before being converted to decibel scale. Input\",\n \"(float): Log10(max(reference value and amin)) top_db (float or None, optional): Minimum negative cut-off\",\n \"-> frequency, 3 -> time) Returns: Tensor: Masked spectrograms of dimensions (batch, channel,\",\n \"5, mode: str = \\\"replicate\\\" ) -> Tensor: r\\\"\\\"\\\"Compute delta coefficients of a\",\n \"(Default: ``30``). freq_low (int, optional): Lowest frequency that can be detected (Hz) (Default:\",\n \"with lag :math:`m`, :math:`w` is the waveform, :math:`N` is the length of a\",\n \"ref * torch.pow(torch.pow(10.0, 0.1 * x), power) def _hz_to_mel(freq: float, mel_scale: str =\",\n \"filter. (default: 1) upsample_filter_width (int, optional): Integer that determines filter width when upsampling\",\n \"-> Tensor: \\\"\\\"\\\"Convert mel bin numbers to frequencies. Args: mels (Tensor): Mel frequencies\",\n \"best = torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] // 2 half = torch.max(nccf[...,\",\n \"a channel dimension and have the form `(batch, channel, freq, time)`. multiplier (float):\",\n \"= ((x_mu) / mu) * 2 - 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x)\",\n \">>> delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \\\"\\\"\\\" device = specgram.device dtype\",\n \"shape = list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf = _compute_nccf(waveform, sample_rate, frame_time,\",\n \"> 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The number of frames\",\n \"Griffin-Lim transformation. Implementation ported from `librosa`. * [1] McFee, Brian, <NAME>, <NAME>, <NAME>,\",\n \"= time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams\",\n \"<NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \\\"librosa: Audio and music signal analysis in\",\n \"float = 4000, delta_pitch: float = 0.005, nccf_ballast: float = 7000, lowpass_filter_width: int\",\n \"see in the first pass of decoding -- not the final version of\",\n \"batch, freq, frames = specgram.size() if rand_init: angles = 2 * math.pi *\",\n \"examples will have the same mask interval. Args: specgram (Tensor): Real spectrogram (channel,\",\n \"specgram = specgram.pow(1 / power) # randomly initialize the phase batch, freq, frames\",\n \"\\\"Signal estimation from modified short-time Fourier transform,\\\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243,\",\n \"= torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform =\",\n \"window_start = t - cmn_window // 2 window_end = window_start + cmn_window else:\",\n \"for each channel along the time axis. The spectral centroid is defined as\",\n \"2 * math.pi * torch.round(phase / (2 * math.pi)) # Compute Phase Accum\",\n \"depends on the maximum value of that tensor, and so may return different\",\n \"== 1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim( specgram: Tensor, window:\",\n \"mel_scale: str = \\\"htk\\\") -> Tensor: \\\"\\\"\\\"Convert mel bin numbers to frequencies. Args:\",\n \"power, etc. normalized (bool): Whether to normalize by magnitude after stft. n_iter (int):\",\n \"from a linear scale magnitude spectrogram using the Griffin-Lim transformation. Implementation ported from\",\n \"mask_start < mask_param if axis == 1: specgram[:, mask_start:mask_end] = mask_value elif axis\",\n \"Optional[float], normalized: bool, center: bool = True, pad_mode: str = \\\"reflect\\\", onesided: bool\",\n \"0.1, lowpass_cutoff: float = 1000, resample_frequency: float = 4000, delta_pitch: float = 0.005,\",\n \"Length of hop between STFT windows win_length (int): Window size power (float or\",\n \"compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \\\"\\\"\\\" device = specgram.device dtype = specgram.dtype #\",\n \"phase estimates angles = rebuilt if momentum: angles = angles - tprev.mul_(momentum /\",\n \"Window size power (float or None): Exponent for the magnitude spectrogram, (must be\",\n \"same number of frames. (default: True) Returns: Tensor: Pitch feature. Shape: ``(batch, frames\",\n \"Setting this to 0 recovers the original Griffin-Lim method. Values near 1 can\",\n \"elif axis == 2: specgram[:, :, mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency\",\n \"transformation matrix with shape (``n_mels``, ``n_mfcc``), normalized depending on norm. Args: n_mfcc (int):\",\n \"2015. * [2] <NAME>., <NAME>., & <NAME>. \\\"A fast Griffin-Lim algorithm,\\\" IEEE Workshop\",\n \"of channels Returns: Tensor: Input after mu-law encoding \\\"\\\"\\\" mu = quantization_channels -\",\n \"be > 0) e.g., 1 for energy, 2 for power, etc. normalized (bool):\",\n \"True, ) -> torch.Tensor: \\\"\\\"\\\"Extract pitch based on method described in [1]. This\",\n \"== \\\"htk\\\": return 2595.0 * math.log10(1.0 + (freq / 700.0)) # Fill in\",\n \"- 1.0) / mu return x def complex_norm( complex_tensor: Tensor, power: float =\",\n \"(freq, 1) Returns: Tensor: Complex Specgrams Stretch with dimension of `(..., freq, ceil(time/rate),\",\n \"Tensor, cmn_window: int = 600, min_cmn_window: int = 100, center: bool = False,\",\n \"energy, 2 for power, etc. If None, then the complex spectrum is returned\",\n \"* b[1] return values, indices def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high: int\",\n \"phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag = alphas\",\n \"time)`. multiplier (float): Use 10. for power and 20. for amplitude amin (float):\",\n \"specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end), mask_value) specgrams = specgrams.transpose(axis, -1) return\",\n \"= window_start last_window_end = window_end cmn_waveform[:, t, :] = waveform[:, t, :] -\",\n \"be 2 dimensional. See also ```channels_first```. sample_rate (int): Sample rate of the audio\",\n \"The sample rate of the waveform (Hz) frame_time (float, optional): Duration of a\",\n \"magnitude spectrogram, (must be > 0) e.g., 1 for energy, 2 for power,\",\n \"/ mu return x def complex_norm( complex_tensor: Tensor, power: float = 1.0 )\",\n \"masked columns axis (int): Axis to apply masking on (2 -> frequency, 3\",\n \"dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf def _combine_max( a: Tuple[Tensor,\",\n \"median smoothing, and convert to frequency. Note: If the max among all the\",\n \"extent possible, modulo end effects). If false, window is to the left. (bool,\",\n \"momentum >= 0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \\\"The argument normalized is\",\n \"values. \\\" f\\\"The value for `n_mels` ({n_mels}) may be set too high. \\\"\",\n \"Tensor: r\\\"\\\"\\\"Compute delta coefficients of a tensor, usually a spectrogram: .. math:: d_t\",\n \") -> Tensor: r\\\"\\\"\\\"Turn a spectrogram from the power/amplitude scale to the decibel\",\n \"<NAME>, <NAME>, and <NAME>. \\\"librosa: Audio and music signal analysis in python.\\\" In\",\n \"x (Tensor): Input spectrogram(s) before being converted to decibel scale. Input should take\",\n \"rate, phase_advance) >>> x.shape # with 231 == ceil(300 / 1.3) torch.Size([2, 1025,\",\n \"\\\"\\\"\\\" lag_min = int(math.ceil(sample_rate / freq_high)) # Find near enough max that is\",\n \"we down-sample the signal to. Must be more than twice lowpass-cutoff. (default: 4000)\",\n \"(..., freq, time), freq is ``n_fft // 2 + 1`` and ``n_fft`` is\",\n \"num_frames: window_start -= (window_end - num_frames) window_end = num_frames if window_start < 0:\",\n \"equals 1, will compute DB to power. If 0.5, will compute DB to\",\n \"math.log(freq / min_log_hz) / logstep return mels def _mel_to_hz(mels: Tensor, mel_scale: str =\",\n \"= torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames,\",\n \"torch.randn(2, freq, 300, 2) >>> rate = 1.3 # Speed up by 30%\",\n \"+ torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf def\",\n \"= phase + phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase,\",\n \"with values from 0 to quantization_channels - 1. Args: x (Tensor): Input tensor\",\n \"sample_rate: int, norm: Optional[str] = None, mel_scale: str = \\\"htk\\\", ) -> Tensor:\",\n \"center: bool = False, norm_vars: bool = False, ) -> Tensor: r\\\"\\\"\\\" Apply\",\n \"Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True,\",\n \"complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams: Tensor, mask_param: int,\",\n \"window_start = 0 if not center: if window_end > t: window_end = max(t\",\n \"top_db is not None: # Expand batch shape = x_db.size() packed_channels = shape[-3]\",\n \"from 0 to quantization_channels - 1. Args: x (Tensor): Input tensor quantization_channels (int):\",\n \"modulo end effects). If false, window is to the left. (bool, default =\",\n \"r\\\"\\\"\\\"Turn a spectrogram from the power/amplitude scale to the decibel scale. The output\",\n \"nonlinear scale min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep\",\n \"resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result =\",\n \"\\\\text{hop\\\\_length}`. Default: ``True`` pad_mode (string, optional): controls the padding method used when :attr:`center`\",\n \"Tensor: Masked spectrogram of dimensions (channel, freq, time) \\\"\\\"\\\" # pack batch shape\",\n \"optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor): Mels\",\n \"mask_value (float): Value to assign to the masked columns axis (int): Axis to\",\n \"batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor, multiplier:\",\n \"Apr. 1984. Args: specgram (Tensor): A magnitude-only STFT spectrogram of dimension (..., freq,\",\n \"A of size (..., ``n_freqs``), the applied result would be ``A * create_fb_matrix(A.size(-1),\",\n \"freq def sliding_window_cmn( waveform: Tensor, cmn_window: int = 600, min_cmn_window: int = 100,\",\n \"Increasing this factor reduces NCCF for quiet frames (default: 7000) lowpass_filter_width (int, optional):\",\n \"(0, p)) # Compute lags output_lag = [] for lag in range(1, lags\",\n \"be set too high. \\\" f\\\"Or, the value for `n_freqs` ({n_freqs}) may be\",\n \"r\\\"\\\"\\\"Compute waveform from a linear scale magnitude spectrogram using the Griffin-Lim transformation. Implementation\",\n \"1 and returns a signal scaled between -1 and 1. Args: x_mu (Tensor):\",\n \"_hz_to_mel(f_max, mel_scale=mel_scale) m_pts = torch.linspace(m_min, m_max, n_mels + 2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale)\",\n \"// 2, n_freqs) # calculate mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max\",\n \"def mask_along_axis( specgram: Tensor, mask_param: int, mask_value: float, axis: int ) -> Tensor:\",\n \"= (min_value.long()).squeeze() mask_end = (min_value.long() + value.long()).squeeze() assert mask_end - mask_start < mask_param\",\n \":, mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency and Time masking are supported')\",\n \"1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom\",\n \"= 50, max_f0: float = 400, soft_min_f0: float = 10.0, penalty_factor: float =\",\n \"resample_frequency: float = 4000, delta_pitch: float = 0.005, nccf_ballast: float = 7000, lowpass_filter_width:\",\n \"Tensor, n_fft: int, hop_length: int, win_length: int, power: float, normalized: bool, n_iter: int,\",\n \"int, hop_length: int, win_length: int, power: float, normalized: bool, n_iter: int, momentum: float,\",\n \"width when upsampling NCCF. (default: 5) max_frames_latency (int, optional): Maximum number of frames\",\n \"introduce into the feature processing (affects output only if ``frames_per_chunk > 0`` and\",\n \"norm: Optional[str] ) -> Tensor: r\\\"\\\"\\\"Create a DCT transformation matrix with shape (``n_mels``,\",\n \"(``n_freqs``, ``n_mels``) meaning number of frequencies to highlight/apply to x the number of\",\n \"(Default: ``n_fft``) power (float): Exponent for the magnitude spectrogram, (must be > 0)\",\n \"0``. recompute_frame (int, optional): Only relevant for compatibility with online pitch extraction. A\",\n \"Number of mel filterbanks norm (str or None): Norm to use (either 'ortho'\",\n \"(int, optional): The window length for median smoothing (in number of frames) (Default:\",\n \"bool = False, norm_vars: bool = False, ) -> Tensor: r\\\"\\\"\\\" Apply sliding-window\",\n \"= f_pts.unsqueeze(0) - all_freqs.unsqueeze(1) # (n_freqs, n_mels + 2) # create overlapping triangles\",\n \"Tensor: r\\\"\\\"\\\"Given a STFT tensor, speed up in time without modifying pitch by\",\n \"conference, pp. 18-25. 2015. * [2] <NAME>., <NAME>., & <NAME>. \\\"A fast Griffin-Lim\",\n \"torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch example masking specgrams = specgrams.transpose(axis, -1)\",\n \"= torch.randn(2, freq, 300, 2) >>> rate = 1.3 # Speed up by\",\n \"Tensor: Masked spectrograms of dimensions (batch, channel, freq, time) \\\"\\\"\\\" if axis !=\",\n \"same mask interval. Args: specgram (Tensor): Real spectrogram (channel, freq, time) mask_param (int):\",\n \"Default: ``win_length // 2``) win_length (int): Window size. (Default: ``n_fft``) power (float): Exponent\",\n \"mask = (a[0] > thresh * b[0]) values = mask * a[0] +\",\n \"angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\\\ .to(dtype=specgram.dtype, device=specgram.device) specgram = specgram.unsqueeze(-1).expand_as(angles) # And\",\n \"This algorithm assumes the signal has been scaled to between -1 and 1\",\n \"and convert to frequency. Note: If the max among all the lags is\",\n \"(n_mfcc, n_mels) if norm is None: dct *= 2.0 else: assert norm ==\",\n \"by their magnitude. Args: waveform (Tensor): Tensor of audio of dimension (..., time)\",\n \"cross-correlation function and median smoothing. Args: waveform (Tensor): Tensor of audio of dimension\",\n \"use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: mels (float): Frequency in Mels \\\"\\\"\\\"\",\n \"width of the mel band (area normalization). (Default: ``None``) mel_scale (str, optional): Scale\",\n \"last_window_start = window_start last_window_end = window_end cmn_waveform[:, t, :] = waveform[:, t, :]\",\n \"point and each stft freq point in hertz f_diff = f_pts[1:] - f_pts[:-1]\",\n \"speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE International Conference\",\n \"power (float): Power of the norm. (Default: `1.0`) Returns: (Tensor, Tensor): The magnitude\",\n \"- v)``. All examples will have the same mask interval. Args: specgram (Tensor):\",\n \"max_f0 (float, optional): Maximum F0 to search for (Hz) (default: 400.0) soft_min_f0 (float,\",\n \"# Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window,\",\n \"hops (n_frame). \\\"\\\"\\\" if pad > 0: # TODO add \\\"with torch.no_grad():\\\" back\",\n \") -> Tensor: r\\\"\\\"\\\"Create a frequency bin conversion matrix. Args: n_freqs (int): Number\",\n \"a linear scale magnitude spectrogram using the Griffin-Lim transformation. Implementation ported from `librosa`.\",\n \"lead to faster convergence, but above 1 may not converge. length (int or\",\n \"r\\\"\\\"\\\" For each frame, take the highest value of NCCF, apply centered median\",\n \"lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest relative change in pitch that our\",\n \"than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest relative change in pitch\",\n \"if norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames = window_end - window_start last_window_start\",\n \"phase_advance phase = torch.cat([phase_0, phase[..., :-1]], dim=-1) phase_acc = torch.cumsum(phase, -1) mag =\",\n \"norm_vars: cur_sumsq -= (frame_to_remove ** 2) if window_end > last_window_end: frame_to_add = waveform[:,\",\n \"= rebuilt if momentum: angles = angles - tprev.mul_(momentum / (1 + momentum))\",\n \"(int): Two sided padding of signal window (Tensor): Window tensor that is applied/multiplied\",\n \"complex tensor \\\"\\\"\\\" mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag, phase\",\n \"Number of channels Returns: Tensor: Input after mu-law decoding \\\"\\\"\\\" mu = quantization_channels\",\n \"complex_norm( complex_tensor: Tensor, power: float = 1.0 ) -> Tensor: r\\\"\\\"\\\"Compute the norm\",\n \"along the time axis. The spectral centroid is defined as the weighted average\",\n \"mu = quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu =\",\n \"of `(..., complex=2)` power (float): Power of the norm. (Default: `1.0`). Returns: Tensor:\",\n \"< 0: window_end -= window_start window_start = 0 if not center: if window_end\",\n \"apply masking on (1 -> frequency, 2 -> time) Returns: Tensor: Masked spectrogram\",\n \"time) \\\"\\\"\\\" specgram = spectrogram(waveform, pad=pad, window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs\",\n \"spectrum is returned instead. normalized (bool): Whether to normalize by magnitude after stft\",\n \"hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram rebuilt = torch.view_as_real( torch.stft( input=inverse,\",\n \"return freq def sliding_window_cmn( waveform: Tensor, cmn_window: int = 600, min_cmn_window: int =\",\n \"and each stft freq point in hertz f_diff = f_pts[1:] - f_pts[:-1] #\",\n \"is not None: if power == 1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f)\",\n \"or None, optional): Minimum negative cut-off in decibels. A reasonable number is 80.\",\n \"0.0 f_sp = 200.0 / 3 freqs = f_min + f_sp * mels\",\n \"frequency (Hz) f_max (float): Maximum frequency (Hz) n_mels (int): Number of mel filterbanks\",\n \"shape of `(..., complex=2)` power (float): Power of the norm. (Default: `1.0`) Returns:\",\n \"so that assuming there is a matrix A of size (..., ``n_freqs``), the\",\n \"+ 2) # create overlapping triangles zero = torch.zeros(1) down_slopes = (-1.0 *\",\n \"window=window, n_fft=n_fft, hop_length=hop_length, win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate // 2, steps=1\",\n \"/ f_sp logstep = math.log(6.4) / 27.0 if freq >= min_log_hz: mels =\",\n \"int, hop_length: int, win_length: int, ) -> Tensor: r\\\"\\\"\\\" Compute the spectral centroid\",\n \"\\\"detect_pitch_frequency\\\", \\\"DB_to_amplitude\\\", \\\"mu_law_encoding\\\", \\\"mu_law_decoding\\\", \\\"complex_norm\\\", \\\"angle\\\", \\\"magphase\\\", \\\"phase_vocoder\\\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \\\"spectral_centroid\\\", \\\"apply_codec\\\",\",\n \"window=window, length=length) # unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def\",\n \"frequency values, weighted by their magnitude. Args: waveform (Tensor): Tensor of audio of\",\n \"depth for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting\",\n \"that we down-sample the signal to. Must be more than twice lowpass-cutoff. (default:\",\n \"spectrogram, (must be > 0) e.g., 1 for energy, 2 for power, etc.\",\n \"2 + 1`` bins hop_length (int): Length of hop between STFT windows. (\",\n \"int ) -> Tensor: r\\\"\\\"\\\" For each frame, take the highest value of\",\n \"(Hz) (Default: ``3400``). Returns: Tensor: Tensor of freq of dimension (..., frame) \\\"\\\"\\\"\",\n \"\\\"\\\"\\\" mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag, phase def phase_vocoder(\",\n \"``uniform(0, mask_param)``, and ``v_0`` from ``uniform(0, max_v - v)``. All examples will have\",\n \"of ``rate``. Args: complex_specgrams (Tensor): Dimension of `(..., freq, time, complex=2)` rate (float):\",\n \"Update our phase estimates angles = rebuilt if momentum: angles = angles -\",\n \"- cmn_window // 2 window_end = window_start + cmn_window else: window_start = t\",\n \"(float, optional): Frame length in milliseconds. (default: 25.0) frame_shift (float, optional): Frame shift\",\n \"# Invert with our current estimate of the phases inverse = torch.istft(specgram *\",\n \"Tuple[Tensor, Tensor]: r\\\"\\\"\\\"Separate a complex-valued spectrogram with shape `(..., 2)` into its magnitude\",\n \"torch.max(zero, torch.min(down_slopes, up_slopes)) if norm is not None and norm == \\\"slaney\\\": #\",\n \"Tuple[Tensor, Tensor], thresh: float = 0.99 ) -> Tuple[Tensor, Tensor]: \\\"\\\"\\\" Take value\",\n \"power, etc. If None, then the complex spectrum is returned instead. normalized (bool):\",\n \"return nccf def _combine_max( a: Tuple[Tensor, Tensor], b: Tuple[Tensor, Tensor], thresh: float =\",\n \"``None``) Returns: Tensor: Output tensor in decibel scale \\\"\\\"\\\" x_db = multiplier *\",\n \"window_end > t: window_end = max(t + 1, min_cmn_window) if window_end > num_frames:\",\n \"width of lowpass filter, more gives sharper filter. (default: 1) upsample_filter_width (int, optional):\",\n \"if freq >= min_log_hz: mels = min_log_mel + math.log(freq / min_log_hz) / logstep\",\n \"mu) * 2 - 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) -\",\n \"= 0.99 ) -> Tuple[Tensor, Tensor]: \\\"\\\"\\\" Take value from first if bigger\",\n \"win_length=win_length, window=window, length=length) # unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform\",\n \"an audio clip split into snippets vs. a full clip. Args: x (Tensor):\",\n \"frequency (Hz) n_mels (int): Number of mel filterbanks sample_rate (int): Sample rate of\",\n \"Number of channels Returns: Tensor: Input after mu-law encoding \\\"\\\"\\\" mu = quantization_channels\",\n \"# Expand batch shape = x_db.size() packed_channels = shape[-3] if x_db.dim() > 2\",\n \"min=amin)) x_db -= multiplier * db_multiplier if top_db is not None: # Expand\",\n \"computing delta (Default: ``5``) mode (str, optional): Mode parameter passed to padding (Default:\",\n \"int, freq_high: int ) -> Tensor: r\\\"\\\"\\\" For each frame, take the highest\",\n \"from the decibel scale to the power/amplitude scale. Args: x (Tensor): Input tensor\",\n \"frame_length (float, optional): Frame length in milliseconds. (default: 25.0) frame_shift (float, optional): Frame\",\n \"None ) -> Tensor: r\\\"\\\"\\\"Turn a spectrogram from the power/amplitude scale to the\",\n \"short-time Fourier transform,\\\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args: specgram\",\n \"(n_freqs, n_mels) up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) fb =\",\n \"= torch.linspace( >>> 0, math.pi * hop_length, freq)[..., None] >>> x = phase_vocoder(complex_specgrams,\",\n \"num_channels, num_frames, num_feats, dtype=dtype, device=device) for t in range(num_frames): window_start = 0 window_end\",\n \"= (mels >= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel))\",\n \"frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove ** 2) if window_end > last_window_end: frame_to_add\",\n \"(..., freq, frames) where freq is ``n_fft // 2 + 1``. window (Tensor):\",\n \"FFT, creates ``n_fft // 2 + 1`` bins hop_length (int): Length of hop\",\n \"a matrix A of size (..., ``n_freqs``), the applied result would be ``A\",\n \"import torch from torch import Tensor from torchaudio._internal import module_utils as _mod_utils import\",\n \"is scaled to be approx constant energy per channel enorm = 2.0 /\",\n \"If ``channels_first=True``, it has ``[channel, time]`` else ``[time, channel]``. \\\"\\\"\\\" bytes = io.BytesIO()\",\n \"\\\"ortho\\\" dct[0] *= 1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return dct.t()\",\n \"Returns: Tensor: Tensor of deltas of dimension (..., freq, time) Example >>> specgram\",\n \"multiplicative factor of the second, elementwise. \\\"\\\"\\\" mask = (a[0] > thresh *\",\n \"= window_end cmn_waveform[:, t, :] = waveform[:, t, :] - cur_sum / window_frames\",\n \"= best[1] # Add back minimal lag indices += lag_min # Add 1\",\n \"bits_per_sample: Optional[int] = None, ) -> Tensor: r\\\"\\\"\\\" Apply codecs as a form\",\n \"+ list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype) alphas = time_steps %\",\n \"is smallest best = torch.max(nccf[..., lag_min:], -1) half_size = nccf.shape[-1] // 2 half\",\n \"tensor before being converted to power/amplitude scale. ref (float): Reference which the output\",\n \"False) Relevant if ``frames_per_chunk > 0``. recompute_frame (int, optional): Only relevant for compatibility\",\n \"pad > 0: # TODO add \\\"with torch.no_grad():\\\" back when JIT supports it\",\n \"int(math.ceil(sample_rate / freq_low)) frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames =\",\n \"between STFT windows. ( Default: ``win_length // 2``) win_length (int): Window size. (Default:\",\n \"not None and norm != \\\"slaney\\\": raise ValueError(\\\"norm must be one of None\",\n \"n_mels) if norm is None: dct *= 2.0 else: assert norm == \\\"ortho\\\"\",\n \"optional): The window length for median smoothing (in number of frames) (Default: ``30``).\",\n \":py:func:`torchaudio.backend.sox_io_backend.save`. Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has ``[channel, time]`` else ``[time,\",\n \"Returns: torch.Tensor: waveform of (..., time), where time equals the ``length`` parameter if\",\n \"min_log_mel + math.log(freq / min_log_hz) / logstep return mels def _mel_to_hz(mels: Tensor, mel_scale:\",\n \"None: if power == 1.0: return spec_f.abs() return spec_f.abs().pow(power) return torch.view_as_real(spec_f) def griffinlim(\",\n \"else: angles = torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\\\ .to(dtype=specgram.dtype,\",\n \"angles.div(complex_norm(angles).add(1e-16).unsqueeze(-1).expand_as(angles)) # Return the final phase estimates waveform = torch.istft(specgram * angles, n_fft=n_fft,\",\n \"the form `(batch, channel, freq, time)`. multiplier (float): Use 10. for power and\",\n \"dtype=x_mu.dtype) x = ((x_mu) / mu) * 2 - 1.0 x = torch.sign(x)\",\n \"If the max among all the lags is very close to the first\",\n \":math:`i` with lag :math:`m`, :math:`w` is the waveform, :math:`N` is the length of\",\n \"pad :attr:`waveform` on both sides so that the :math:`t`-th frame is centered at\",\n \"min_log_mel)) return freqs def create_fb_matrix( n_freqs: int, f_min: float, f_max: float, n_mels: int,\",\n \"input=inverse, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) #\",\n \"bin. Dimension of (freq, 1) Returns: Tensor: Complex Specgrams Stretch with dimension of\",\n \"frequency, 2 -> time) Returns: Tensor: Masked spectrogram of dimensions (channel, freq, time)\",\n \"= \\\\frac{\\\\sum_{n=b_i}^{b_i + N-1} w(n) w(m+n)}{\\\\sqrt{E(b_i) E(m+b_i)}}, where :math:`\\\\phi_i(m)` is the NCCF at\",\n \"window: Tensor, n_fft: int, hop_length: int, win_length: int, power: Optional[float], normalized: bool, center:\",\n \"value)[..., None, None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per batch example\",\n \"energy normalization. (default: 0) simulate_first_pass_online (bool, optional): If true, the function will output\",\n \"win_length: int, power: Optional[float], normalized: bool, center: bool = True, pad_mode: str =\",\n \"``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The number of\",\n \"\\\"complex_norm\\\", \\\"angle\\\", \\\"magphase\\\", \\\"phase_vocoder\\\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \\\"spectral_centroid\\\", \\\"apply_codec\\\", ] def spectrogram( waveform:\",\n \"is ``n_fft // 2 + 1``. window (Tensor): Window tensor that is applied/multiplied\",\n \"have dimension ``[channel, time]``. Otherwise, they have dimension ``[time, channel]``. compression (float): Used\",\n \"is a filterbank so that assuming there is a matrix A of size\",\n \"Integer that determines filter width of lowpass filter, more gives sharper filter. (default:\",\n \"mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag, phase def phase_vocoder( complex_specgrams:\",\n \"= specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value = torch.rand(specgrams.shape[:2], device=device,\",\n \"if center: window_start = t - cmn_window // 2 window_end = window_start +\",\n \"and ``v_0`` from ``uniform(0, max_v - v)``. Args: specgrams (Tensor): Real spectrograms (batch,\",\n \"`compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The input waveform of shape `(..., time)`.\",\n \"<NAME> and <NAME> 2014 IEEE International Conference on Acoustics, Speech and Signal Processing\",\n \"recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE International Conference on\",\n \"in the linear part f_min = 0.0 f_sp = 200.0 / 3 mels\",\n \"after mu-law decoding \\\"\\\"\\\" mu = quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu\",\n \"(float): Value to assign to the masked columns axis (int): Axis to apply\",\n \"applied from indices ``[v_0, v_0 + v)``, where ``v`` is sampled from ``uniform(0,\",\n \"0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The number of frames used\",\n \"time), where time equals the ``length`` parameter if given. \\\"\\\"\\\" assert momentum <\",\n \":] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2] + (num_frames, num_feats)) if len(input_shape) == 2:\",\n \"iteration for phase recovery process. momentum (float): The momentum parameter for fast Griffin-Lim.\",\n \"2 + 1``. window (Tensor): Window tensor that is applied/multiplied to each frame/window\",\n \"= 200.0 / 3 freqs = f_min + f_sp * mels # And\",\n \"latter is taken. \\\"\\\"\\\" lag_min = int(math.ceil(sample_rate / freq_high)) # Find near enough\",\n \"freq, frames) else: angles = torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1)\",\n \"will compute DB to power. If 0.5, will compute DB to amplitude. Returns:\",\n \"is the waveform, :math:`N` is the length of a frame, :math:`b_i` is the\",\n \"[] for lag in range(1, lags + 1): s1 = waveform[..., :-lag].unfold(-1, frame_size,\",\n \"features give the same number of frames. (default: True) Returns: Tensor: Pitch feature.\",\n \"t in range(num_frames): window_start = 0 window_end = 0 if center: window_start =\",\n \"Workshop on Applications of Signal Processing to Audio and Acoustics (pp. 1-4), Oct.\",\n \"int(math.ceil(sample_rate / freq_high)) # Find near enough max that is smallest best =\",\n \"* norm_1 + (1 - alphas) * norm_0 real_stretch = mag * torch.cos(phase_acc)\",\n \"(must be > 0) e.g., 1 for energy, 2 for power, etc. If\",\n \"= angle_1 - angle_0 - phase_advance phase = phase - 2 * math.pi\",\n \"doi: 10.1109/ICASSP.2014.6854049. \\\"\\\"\\\" shape = waveform.shape waveform = waveform.reshape(-1, shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch(\",\n \"tensor quantization_channels (int): Number of channels Returns: Tensor: Input after mu-law encoding \\\"\\\"\\\"\",\n \"``None``) mel_scale (str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns:\",\n \"time) Returns: Tensor: Masked spectrograms of dimensions (batch, channel, freq, time) \\\"\\\"\\\" if\",\n \"NCCF at frame :math:`i` with lag :math:`m`, :math:`w` is the waveform, :math:`N` is\",\n \"math.pi * torch.round(phase / (2 * math.pi)) # Compute Phase Accum phase =\",\n \"num_frames, num_feats = input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype\",\n \"dimension ``[channel, time]``. Otherwise, they have dimension ``[time, channel]``. compression (float): Used for\",\n \"Tensor: Angle of a complex tensor. Shape of `(..., )` \\\"\\\"\\\" return torch.atan2(complex_tensor[...,\",\n \"weights by the width of the mel band (area normalization). (Default: ``None``) mel_scale\",\n \"has all zero values. \\\" f\\\"The value for `n_mels` ({n_mels}) may be set\",\n \":-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :]\",\n \"mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu) * 2 - 1.0\",\n \"= (a[0] > thresh * b[0]) values = mask * a[0] + ~mask\",\n \"# Convert indices to frequency EPSILON = 10 ** (-9) freq = sample_rate\",\n \"x_mu.is_floating_point(): x_mu = x_mu.to(torch.float) mu = torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu)\",\n \"if window_end > t: window_end = max(t + 1, min_cmn_window) if window_end >\",\n \"audio waveform norm (Optional[str]): If 'slaney', divide the triangular mel weights by the\",\n \"windowed pad_length = (win_length - 1) // 2 # \\\"replicate\\\" padding in any\",\n \") -> Tensor: r\\\"\\\"\\\"Decode mu-law encoded signal. For more info see the `Wikipedia\",\n \"-1 and 1 and returns a signal encoded with values from 0 to\",\n \"window length for median smoothing (in number of frames) (Default: ``30``). freq_low (int,\",\n \"r\\\"\\\"\\\"Compute delta coefficients of a tensor, usually a spectrogram: .. math:: d_t =\",\n \"\\\"DB_to_amplitude\\\", \\\"mu_law_encoding\\\", \\\"mu_law_decoding\\\", \\\"complex_norm\\\", \\\"angle\\\", \\\"magphase\\\", \\\"phase_vocoder\\\", 'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \\\"spectral_centroid\\\", \\\"apply_codec\\\", ]\",\n \"\\\"\\\"\\\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi /\",\n \"\\\"\\\"\\\" EPSILON = 10 ** (-9) # Number of lags to check lags\",\n \"unpack batch freq = freq.reshape(shape[:-1] + list(freq.shape[-1:])) return freq def sliding_window_cmn( waveform: Tensor,\",\n \"shape[-1]) result = torch.ops.torchaudio.kaldi_ComputeKaldiPitch( waveform, sample_rate, frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff,\",\n \"a complex tensor. Shape of `(..., )` \\\"\\\"\\\" return torch.atan2(complex_tensor[..., 1], complex_tensor[..., 0])\",\n \"-> Tensor: r\\\"\\\"\\\"Create a frequency bin conversion matrix. Args: n_freqs (int): Number of\",\n \"~mask * b[1] return values, indices def _find_max_per_frame( nccf: Tensor, sample_rate: int, freq_high:\",\n \"use `normalized=False`.\\\") # pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:]))\",\n \"mu return x def complex_norm( complex_tensor: Tensor, power: float = 1.0 ) ->\",\n \"of frame :math:`i`, :math:`E(j)` is the energy :math:`\\\\sum_{n=j}^{j+N-1} w^2(n)`. \\\"\\\"\\\" EPSILON = 10\",\n \"`(..., complex=2)` Return: Tensor: Angle of a complex tensor. Shape of `(..., )`\",\n \"hop_length (int): Length of hop between STFT windows. ( Default: ``win_length // 2``)\",\n \"multiplier (float): Use 10. for power and 20. for amplitude amin (float): Number\",\n \"the complex spectrum is returned instead. normalized (bool): Whether to normalize by magnitude\",\n \"x = x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu *\",\n \"channel enorm = 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) fb *= enorm.unsqueeze(0)\",\n \":]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) # (new_bins,\",\n \":] cur_sum += frame_to_add if norm_vars: cur_sumsq += (frame_to_add ** 2) window_frames =\",\n \"``length`` parameter if given. \\\"\\\"\\\" assert momentum < 1, 'momentum={} > 1 can\",\n \"compute DB to power. If 0.5, will compute DB to amplitude. Returns: Tensor:\",\n \"torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length) # unpack batch waveform =\",\n \"rate of the audio waveform pad (int): Two sided padding of signal window\",\n \"= [ \\\"spectrogram\\\", \\\"griffinlim\\\", \\\"amplitude_to_DB\\\", \\\"DB_to_amplitude\\\", \\\"compute_deltas\\\", \\\"compute_kaldi_pitch\\\", \\\"create_fb_matrix\\\", \\\"create_dct\\\", \\\"compute_deltas\\\", \\\"detect_pitch_frequency\\\", \\\"DB_to_amplitude\\\",\",\n \"Compute Normalized Cross-Correlation Function (NCCF). .. math:: \\\\phi_i(m) = \\\\frac{\\\\sum_{n=b_i}^{b_i + N-1} w(n)\",\n \"Tensor: r\\\"\\\"\\\" Apply codecs as a form of augmentation. Args: waveform (Tensor): Audio\",\n \"indices ``[v_0, v_0 + v)``, where ``v`` is sampled from ``uniform(0, mask_param)``, and\",\n \"win_length (int, optional): The window length used for computing delta (Default: ``5``) mode\",\n \"value and amin)) top_db (float or None, optional): Minimum negative cut-off in decibels.\",\n \"that our algorithm measures. (default: 0.005) nccf_ballast (float, optional): Increasing this factor reduces\",\n \"after stft center (bool, optional): whether to pad :attr:`waveform` on both sides so\",\n \"power/amplitude scale. Args: x (Tensor): Input tensor before being converted to power/amplitude scale.\",\n \"tuned for automatic speech recognition <NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014\",\n \"in time without modifying pitch by a factor of ``rate``. Args: complex_specgrams (Tensor):\",\n \"time) pad (int): Two sided padding of signal window (Tensor): Window tensor that\",\n \"phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild\",\n \"axis == 2: specgram[:, :, mask_start:mask_end] = mask_value else: raise ValueError('Only Frequency and\",\n \"freq of dimension (..., frame) \\\"\\\"\\\" input_shape = waveform.shape num_frames, num_feats = input_shape[-2:]\",\n \"mask_end = (min_value.long() + value.long()).squeeze() assert mask_end - mask_start < mask_param if axis\",\n \"waveform: Tensor, sample_rate: int, frame_time: float, freq_low: int ) -> Tensor: r\\\"\\\"\\\" Compute\",\n \"more than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest relative change in\",\n \"= window_end - window_start last_window_start = window_start last_window_end = window_end cmn_waveform[:, t, :]\",\n \"= _compute_nccf(waveform, sample_rate, frame_time, freq_low) indices = _find_max_per_frame(nccf, sample_rate, freq_high) indices = _median_smoothing(indices,\",\n \"((cur_sum ** 2) / (window_frames ** 2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t,\",\n \"waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor, multiplier: float, amin: float, db_multiplier: float,\",\n \"(str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular\",\n \"mel_scale: str = \\\"htk\\\", ) -> Tensor: r\\\"\\\"\\\"Create a frequency bin conversion matrix.\",\n \":1, :]) # Time Padding complex_specgrams = torch.nn.functional.pad(complex_specgrams, [0, 0, 0, 2]) #\",\n \"Returns: Tensor: Input after mu-law decoding \\\"\\\"\\\" mu = quantization_channels - 1.0 if\",\n \"Tensor of audio of dimension (..., freq, time) sample_rate (int): The sample rate\",\n \"to 0 recovers the original Griffin-Lim method. Values near 1 can lead to\",\n \"(either 'ortho' or None) Returns: Tensor: The transformation matrix, to be right-multiplied to\",\n \"power. If 0.5, will compute DB to amplitude. Returns: Tensor: Output tensor in\",\n \"dct.t() def mu_law_encoding( x: Tensor, quantization_channels: int ) -> Tensor: r\\\"\\\"\\\"Encode signal based\",\n \"mu-law companding. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This algorithm assumes\",\n \"pack batch shape = complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0,\",\n \"p=2, dim=-1) phase = angle_1 - angle_0 - phase_advance phase = phase -\",\n \"angles = torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(), angles.sin()], dim=-1) \\\\ .to(dtype=specgram.dtype, device=specgram.device)\",\n \"normalization per utterance. Args: waveform (Tensor): Tensor of audio of dimension (..., freq,\",\n \"min_value = torch.rand(1) * (specgram.size(axis) - value) mask_start = (min_value.long()).squeeze() mask_end = (min_value.long()\",\n \"matrix) of size (``n_freqs``, ``n_mels``) meaning number of frequencies to highlight/apply to x\",\n \"imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1) # unpack batch\",\n \"min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep * (mels[log_t] - min_log_mel)) return freqs def\",\n \"magnitude after stft. n_iter (int): Number of iteration for phase recovery process. momentum\",\n \"decoding \\\"\\\"\\\" mu = quantization_channels - 1.0 if not x_mu.is_floating_point(): x_mu = x_mu.to(torch.float)\",\n \"* 2 - 1.0 x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0)\",\n \"(float): Power of the norm. (Default: `1.0`). Returns: Tensor: Power of the normed\",\n \"of frames of latency that we allow pitch tracking to introduce into the\",\n \"+ torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf\",\n \"= specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate to 0 rebuilt = torch.tensor(0.)\",\n \"or ``slaney``. (Default: ``htk``) Returns: mels (float): Frequency in Mels \\\"\\\"\\\" if mel_scale\",\n \"# Slaney-style mel is scaled to be approx constant energy per channel enorm\",\n \"spectrogram (channel, freq, time) mask_param (int): Number of columns to be masked will\",\n \"filter width when upsampling NCCF. (default: 5) max_frames_latency (int, optional): Maximum number of\",\n \"and so may return different values for an audio clip split into snippets\",\n \"win_length=win_length, window=window, center=True, pad_mode='reflect', normalized=False, onesided=True, return_complex=True, ) ) # Update our phase\",\n \"x_db = x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor, ref: float, power: float\",\n \"mel_scale == \\\"htk\\\": return 700.0 * (10.0**(mels / 2595.0) - 1.0) # Fill\",\n \"1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1\",\n \"centered on the current frame (to the extent possible, modulo end effects). If\",\n \"x.to(torch.float) mu = torch.tensor(mu, dtype=x.dtype) x_mu = torch.sign(x) * torch.log1p(mu * torch.abs(x)) /\",\n \"decibel scale \\\"\\\"\\\" x_db = multiplier * torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier *\",\n \"1.0 / math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding( x:\",\n \"time without modifying pitch by a factor of ``rate``. Args: complex_specgrams (Tensor): Dimension\",\n \"torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram rebuilt\",\n \"torch.randn(1, 40, 1000) >>> delta = compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \\\"\\\"\\\" device\",\n \"# pack batch shape = list(waveform.size()) waveform = waveform.reshape([-1] + shape[-1:]) nccf =\",\n \"num_frames if window_start < 0: window_start = 0 if last_window_start == -1: input_part\",\n \"Add 1 empirical calibration offset indices += 1 return indices def _median_smoothing( indices:\",\n \"waveform. format (str): File format. channels_first (bool): When True, both the input and\",\n \"false) norm_vars (bool, optional): If true, normalize variance to one. (bool, default =\",\n \"2)` into its magnitude and phase. Args: complex_tensor (Tensor): Tensor shape of `(...,\",\n \"output Tensor have dimension ``[channel, time]``. Otherwise, they have dimension ``[time, channel]``. compression\",\n \"<NAME>, <NAME>, <NAME>, <NAME>, <NAME> and <NAME> 2014 IEEE International Conference on Acoustics,\",\n \"(default: 50.0) max_f0 (float, optional): Maximum F0 to search for (Hz) (default: 400.0)\",\n \"deltas of dimension (..., freq, time) Example >>> specgram = torch.randn(1, 40, 1000)\",\n \"* x), power) def _hz_to_mel(freq: float, mel_scale: str = \\\"htk\\\") -> float: r\\\"\\\"\\\"Convert\",\n \"Tensor of audio of dimension (..., time) sample_rate (int): Sample rate of the\",\n \"torch import Tensor from torchaudio._internal import module_utils as _mod_utils import torchaudio __all__ =\",\n \"analysis in python.\\\" In Proceedings of the 14th python in science conference, pp.\",\n \"Optional[str] = None, bits_per_sample: Optional[int] = None, ) -> Tensor: r\\\"\\\"\\\" Apply codecs\",\n \"pitch by a factor of ``rate``. Args: complex_specgrams (Tensor): Dimension of `(..., freq,\",\n \"= 200.0 / 3 mels = (freq - f_min) / f_sp # Fill\",\n \"int(math.ceil(waveform_length / frame_size)) p = lags + num_of_frames * frame_size - waveform_length waveform\",\n \"frame_time (float, optional): Duration of a frame (Default: ``10 ** (-2)``). win_length (int,\",\n \"torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cur_sumsq = torch.zeros(num_channels, num_feats, dtype=dtype, device=device) cmn_waveform = torch.zeros(\",\n \"Args: waveform (Tensor): Tensor of audio of dimension (..., time) sample_rate (int): Sample\",\n \"to zero otherwise. Returns: torch.Tensor: waveform of (..., time), where time equals the\",\n \"math.sqrt(2.0) dct *= math.sqrt(2.0 / float(n_mels)) return dct.t() def mu_law_encoding( x: Tensor, quantization_channels:\",\n \"determines filter width when upsampling NCCF. (default: 5) max_frames_latency (int, optional): Maximum number\",\n \"be removed in v0.9.0 release. To suppress this warning, \\\" \\\"please use `normalized=False`.\\\")\",\n \"complex. Args: waveform (Tensor): Tensor of audio of dimension (..., time) pad (int):\",\n \"ref: float, power: float ) -> Tensor: r\\\"\\\"\\\"Turn a tensor from the decibel\",\n \":math:`t`, :math:`N` is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio of dimension (...,\",\n \"codecs as a form of augmentation. Args: waveform (Tensor): Audio data. Must be\",\n \"Fourier bins, and time is the number of window hops (n_frame). \\\"\\\"\\\" if\",\n \"c_{t-n})}{2 \\\\sum_{n=1}^{\\\\text{N}} n^2} where :math:`d_t` is the deltas at time :math:`t`, :math:`c_t` is\",\n \"unstable'.format(momentum) assert momentum >= 0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \\\"The argument\",\n \"warning, \\\" \\\"please use `normalized=False`.\\\") # pack batch shape = specgram.size() specgram =\",\n \"min_cmn_window) if window_end > num_frames: window_start -= (window_end - num_frames) window_end = num_frames\",\n \"mels (float): Frequency in Mels \\\"\\\"\\\" if mel_scale not in ['slaney', 'htk']: raise\",\n \"center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack batch spec_f = spec_f.reshape(shape[:-1] +\",\n \"-= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove ** 2) if window_end > last_window_end:\",\n \"frame_length, frame_shift, min_f0, max_f0, soft_min_f0, penalty_factor, lowpass_cutoff, resample_frequency, delta_pitch, nccf_ballast, lowpass_filter_width, upsample_filter_width, max_frames_latency,\",\n \"** (-9) freq = sample_rate / (EPSILON + indices.to(torch.float)) # unpack batch freq\",\n \"unpack batch waveform = waveform.reshape(shape[:-2] + waveform.shape[-1:]) return waveform def amplitude_to_DB( x: Tensor,\",\n \"from typing import Optional, Tuple import torch from torch import Tensor from torchaudio._internal\",\n \"x_db -= multiplier * db_multiplier if top_db is not None: # Expand batch\",\n \"the value for `n_freqs` ({n_freqs}) may be set too low.\\\" ) return fb\",\n \"# calculate mel freq bins m_min = _hz_to_mel(f_min, mel_scale=mel_scale) m_max = _hz_to_mel(f_max, mel_scale=mel_scale)\",\n \"(int): Sample rate of the audio waveform. format (str): File format. channels_first (bool):\",\n \"(Default: ``85``). freq_high (int, optional): Highest frequency that can be detected (Hz) (Default:\",\n \"* (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu return x def complex_norm( complex_tensor:\",\n \"-> Tensor: r\\\"\\\"\\\" For each frame, take the highest value of NCCF, apply\",\n \"have the same mask interval. Args: specgram (Tensor): Real spectrogram (channel, freq, time)\",\n \"Returns: torch.Tensor: Resulting Tensor. If ``channels_first=True``, it has ``[channel, time]`` else ``[time, channel]``.\",\n \"gives sharper filter. (default: 1) upsample_filter_width (int, optional): Integer that determines filter width\",\n \"85, freq_high: int = 3400, ) -> Tensor: r\\\"\\\"\\\"Detect pitch frequency. It is\",\n \"of that tensor, and so may return different values for an audio clip\",\n \"the difference between each mel point and each stft freq point in hertz\",\n \"packed_channels = shape[-3] if x_db.dim() > 2 else 1 x_db = x_db.reshape(-1, packed_channels,\",\n \"n * (n + 1) * (2 * n + 1) / 3\",\n \"\\\"htk\\\") -> float: r\\\"\\\"\\\"Convert Hz to Mels. Args: freqs (float): Frequencies in Hz\",\n \"matrix A of size (..., ``n_freqs``), the applied result would be ``A *\",\n \"= angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 = torch.norm(complex_specgrams_1,\",\n \"window.pow(2.).sum().sqrt() if power is not None: if power == 1.0: return spec_f.abs() return\",\n \"freq, time)`. multiplier (float): Use 10. for power and 20. for amplitude amin\",\n \"number of frames) (Default: ``30``). freq_low (int, optional): Lowest frequency that can be\",\n \"frequency. Note: If the max among all the lags is very close to\",\n \"log-scale part min_log_hz = 1000.0 min_log_mel = (min_log_hz - f_min) / f_sp logstep\",\n \"(..., time), where time equals the ``length`` parameter if given. \\\"\\\"\\\" assert momentum\",\n \"up in time without modifying pitch by a factor of ``rate``. Args: complex_specgrams\",\n \"complex_specgrams.size() complex_specgrams = complex_specgrams.reshape([-1] + list(shape[-3:])) time_steps = torch.arange(0, complex_specgrams.size(-2), rate, device=complex_specgrams.device, dtype=complex_specgrams.dtype)\",\n \"2)) variance = torch.pow(variance, -0.5) cmn_waveform[:, t, :] *= variance cmn_waveform = cmn_waveform.view(input_shape[:-2]\",\n \"-> Tensor: r\\\"\\\"\\\"Compute the norm of complex tensor input. Args: complex_tensor (Tensor): Tensor\",\n \"its magnitude and phase. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power\",\n \"(Default: ``htk``) Returns: freqs (Tensor): Mels converted in Hz \\\"\\\"\\\" if mel_scale not\",\n \"return cmn_waveform def spectral_centroid( waveform: Tensor, sample_rate: int, pad: int, window: Tensor, n_fft:\",\n \"frame_size = int(math.ceil(sample_rate * frame_time)) waveform_length = waveform.size()[-1] num_of_frames = int(math.ceil(waveform_length / frame_size))\",\n \"lag in range(1, lags + 1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames,\",\n \"specgram = specgram.unsqueeze(-1).expand_as(angles) # And initialize the previous iterate to 0 rebuilt =\",\n \"# Return the final phase estimates waveform = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length,\",\n \"time_steps % 1.0 phase_0 = angle(complex_specgrams[..., :1, :]) # Time Padding complex_specgrams =\",\n \"equivalent of `compute-kaldi-pitch-feats` from Kaldi. Args: waveform (Tensor): The input waveform of shape\",\n \"bool, center: bool = True, pad_mode: str = \\\"reflect\\\", onesided: bool = True\",\n \"a[1] + ~mask * b[1] return values, indices def _find_max_per_frame( nccf: Tensor, sample_rate:\",\n \"400, soft_min_f0: float = 10.0, penalty_factor: float = 0.1, lowpass_cutoff: float = 1000,\",\n \"Must be more than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest relative\",\n \"by 30% >>> phase_advance = torch.linspace( >>> 0, math.pi * hop_length, freq)[..., None]\",\n \"a tensor, usually a spectrogram: .. math:: d_t = \\\\frac{\\\\sum_{n=1}^{\\\\text{N}} n (c_{t+n} -\",\n \"[1] McFee, Brian, <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, and <NAME>. \\\"librosa: Audio and\",\n \"matrix. Args: n_freqs (int): Number of frequencies to highlight/apply f_min (float): Minimum frequency\",\n \"default = false) norm_vars (bool, optional): If true, normalize variance to one. (bool,\",\n \"shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1)) - top_db).view(-1, 1, 1, 1))\",\n \"win_length=win_length, power=1., normalized=False) freqs = torch.linspace(0, sample_rate // 2, steps=1 + n_fft //\",\n \"end effects). If false, window is to the left. (bool, default = false)\",\n \"frames_per_chunk: int = 0, simulate_first_pass_online: bool = False, recompute_frame: int = 500, snip_edges:\",\n \"= phase_vocoder(complex_specgrams, rate, phase_advance) >>> x.shape # with 231 == ceil(300 / 1.3)\",\n \"f_min) / f_sp # Fill in the log-scale part min_log_hz = 1000.0 min_log_mel\",\n \"p = lags + num_of_frames * frame_size - waveform_length waveform = torch.nn.functional.pad(waveform, (0,\",\n \"<NAME>. \\\"A fast Griffin-Lim algorithm,\\\" IEEE Workshop on Applications of Signal Processing to\",\n \"to search for (Hz) (default: 400.0) soft_min_f0 (float, optional): Minimum f0, applied in\",\n \"of NCCF, apply centered median smoothing, and convert to frequency. Note: If the\",\n \"change in pitch that our algorithm measures. (default: 0.005) nccf_ballast (float, optional): Increasing\",\n \"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, 2014, pp.\",\n \"((x_mu + 1) / 2 * mu + 0.5).to(torch.int64) return x_mu def mu_law_decoding(\",\n \"f_min: float, f_max: float, n_mels: int, sample_rate: int, norm: Optional[str] = None, mel_scale:\",\n \"decoding (adds latency only at start). Only applicable if center == false, ignored\",\n \"so that the :math:`t`-th frame is centered at time :math:`t \\\\times \\\\text{hop\\\\_length}`. Default:\",\n \"dimension indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\\\"constant\\\", value=0. ) indices[..., :pad_length] =\",\n \"100) center (bool, optional): If true, use a window centered on the current\",\n \"center == false, ignored if center==true (int, default = 100) center (bool, optional):\",\n \"+ 0.5) * k) # size (n_mfcc, n_mels) if norm is None: dct\",\n \"rate of the audio waveform. format (str): File format. channels_first (bool): When True,\",\n \"dimensions (batch, channel, freq, time) \\\"\\\"\\\" if axis != 2 and axis !=\",\n \"\\\"slaney\\\": # Slaney-style mel is scaled to be approx constant energy per channel\",\n \"(bool, optional): controls whether to return half of results to avoid redundancy. Default:\",\n \"'mask_along_axis', 'mask_along_axis_iid', 'sliding_window_cmn', \\\"spectral_centroid\\\", \\\"apply_codec\\\", ] def spectrogram( waveform: Tensor, pad: int, window:\",\n \"lags + 1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 =\",\n \"modified short-time Fourier transform,\\\" IEEE Trans. ASSP, vol.32, no.2, pp.236–243, Apr. 1984. Args:\",\n \"removed in v0.9.0 release. To suppress this warning, \\\" \\\"please use `normalized=False`.\\\") #\",\n \"Minimum F0 to search for (Hz) (default: 50.0) max_f0 (float, optional): Maximum F0\",\n \"scaled to between -1 and 1 and returns a signal encoded with values\",\n \"v0.9.0 release. To suppress this warning, \\\" \\\"please use `normalized=False`.\\\") # pack batch\",\n \"torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.0) / mu return x def complex_norm(\",\n \"the bit depth for the supported formats. For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. Returns:\",\n \"Returns: Tensor: Masked spectrogram of dimensions (channel, freq, time) \\\"\\\"\\\" # pack batch\",\n \"for power, etc. normalized (bool): Whether to normalize by magnitude after stft. n_iter\",\n \"zero values. \\\" f\\\"The value for `n_mels` ({n_mels}) may be set too high.\",\n \"on the current frame (to the extent possible, modulo end effects). If false,\",\n \"encoding: Optional[str] = None, bits_per_sample: Optional[int] = None, ) -> Tensor: r\\\"\\\"\\\" Apply\",\n \":num_of_frames, :] output_frames = ( (s1 * s2).sum(-1) / (EPSILON + torch.norm(s1, p=2,\",\n \"f\\\"{sample_rate}\\\"]], channels_first=channels_first, format=format) return augmented @_mod_utils.requires_kaldi() def compute_kaldi_pitch( waveform: torch.Tensor, sample_rate: float, frame_length:\",\n \"Acoustics, Speech and Signal Processing (ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \\\"\\\"\\\"\",\n \"output only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional):\",\n \"any dimension indices = torch.nn.functional.pad( indices, (pad_length, 0), mode=\\\"constant\\\", value=0. ) indices[..., :pad_length]\",\n \"float: r\\\"\\\"\\\"Convert Hz to Mels. Args: freqs (float): Frequencies in Hz mel_scale (str,\",\n \"mu-law encoded signal. For more info see the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects\",\n \"phase_advance) >>> x.shape # with 231 == ceil(300 / 1.3) torch.Size([2, 1025, 231,\",\n \"possible, modulo end effects). If false, window is to the left. (bool, default\",\n \"(float, optional): Increasing this factor reduces NCCF for quiet frames (default: 7000) lowpass_filter_width\",\n \"str = \\\"htk\\\", ) -> Tensor: r\\\"\\\"\\\"Create a frequency bin conversion matrix. Args:\",\n \"-> Tensor: r\\\"\\\"\\\"Compute the angle of complex tensor input. Args: complex_tensor (Tensor): Tensor\",\n \"negative cut-off in decibels. A reasonable number is 80. (Default: ``None``) Returns: Tensor:\",\n \"assert momentum >= 0, 'momentum={} < 0'.format(momentum) if normalized: warnings.warn( \\\"The argument normalized\",\n \"batch shape = x_db.size() packed_channels = shape[-3] if x_db.dim() > 2 else 1\",\n \"Tensor: \\\"\\\"\\\"Convert mel bin numbers to frequencies. Args: mels (Tensor): Mel frequencies mel_scale\",\n \"for power and 20. for amplitude amin (float): Number to clamp ``x`` db_multiplier\",\n \"highest value of NCCF, apply centered median smoothing, and convert to frequency. Note:\",\n \") bytes.seek(0) augmented, _ = torchaudio.sox_effects.sox_effects.apply_effects_file( bytes, effects=[[\\\"rate\\\", f\\\"{sample_rate}\\\"]], channels_first=channels_first, format=format) return augmented\",\n \"10. for power and 20. for amplitude amin (float): Number to clamp ``x``\",\n \"(1 - alphas) * norm_0 real_stretch = mag * torch.cos(phase_acc) imag_stretch = mag\",\n \"module_utils as _mod_utils import torchaudio __all__ = [ \\\"spectrogram\\\", \\\"griffinlim\\\", \\\"amplitude_to_DB\\\", \\\"DB_to_amplitude\\\", \\\"compute_deltas\\\",\",\n \"if center == false, ignored if center==true (int, default = 100) center (bool,\",\n \"torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1)) nccf = torch.cat(output_lag, -1) return nccf def _combine_max(\",\n \"Input after mu-law encoding \\\"\\\"\\\" mu = quantization_channels - 1.0 if not x.is_floating_point():\",\n \"> 2 else 1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db,\",\n \"(int, optional): The number of frames used for energy normalization. (default: 0) simulate_first_pass_online\",\n \"to the masked columns axis (int): Axis to apply masking on (2 ->\",\n \"({n_mels}) may be set too high. \\\" f\\\"Or, the value for `n_freqs` ({n_freqs})\",\n \"(bool): Initializes phase randomly if True, to zero otherwise. Returns: torch.Tensor: waveform of\",\n \"(Tensor): Expected phase advance in each bin. Dimension of (freq, 1) Returns: Tensor:\",\n \"optional): controls the padding method used when :attr:`center` is ``True``. Default: ``\\\"reflect\\\"`` onesided\",\n \"masking specgrams = specgrams.transpose(axis, -1) specgrams.masked_fill_((mask >= mask_start) & (mask < mask_end), mask_value)\",\n \"spectrogram can be either magnitude-only or complex. Args: waveform (Tensor): Tensor of audio\",\n \"Duration of a frame (Default: ``10 ** (-2)``). win_length (int, optional): The window\",\n \"`normalized=False`.\\\") # pack batch shape = specgram.size() specgram = specgram.reshape([-1] + list(shape[-2:])) specgram\",\n \"= torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi / float(n_mels) * (n +\",\n \"``n_fft // 2 + 1`` bins hop_length (int): Length of hop between STFT\",\n \"by torch.norm once issue is fixed # https://github.com/pytorch/pytorch/issues/34279 return complex_tensor.pow(2.).sum(-1).pow(0.5 * power) def\",\n \"(channel, freq, time) mask_param (int): Number of columns to be masked will be\",\n \"(fb.max(dim=0).values == 0.).any(): warnings.warn( \\\"At least one mel filterbank has all zero values.\",\n \"norm (Optional[str]): If 'slaney', divide the triangular mel weights by the width of\",\n \"(channel, freq, time, complex=2) >>> complex_specgrams = torch.randn(2, freq, 300, 2) >>> rate\",\n \"x), power) def _hz_to_mel(freq: float, mel_scale: str = \\\"htk\\\") -> float: r\\\"\\\"\\\"Convert Hz\",\n \"# unpack batch output = output.reshape(shape) return output def _compute_nccf( waveform: Tensor, sample_rate:\",\n \"create overlapping triangles zero = torch.zeros(1) down_slopes = (-1.0 * slopes[:, :-2]) /\",\n \"the extent possible, modulo end effects). If false, window is to the left.\",\n \"is very close to the first half of lags, then the latter is\",\n \"batch x_db = x_db.reshape(shape) return x_db def DB_to_amplitude( x: Tensor, ref: float, power:\",\n \"(n + 0.5) * k) # size (n_mfcc, n_mels) if norm is None:\",\n \"between STFT windows win_length (int): Window size power (float or None): Exponent for\",\n \"n_freqs (int): Number of frequencies to highlight/apply f_min (float): Minimum frequency (Hz) f_max\",\n \"return (freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int,\",\n \"shape `(..., time)`. sample_rate (float): Sample rate of `waveform`. frame_length (float, optional): Frame\",\n \"/ 27.0 log_t = (mels >= min_log_mel) freqs[log_t] = min_log_hz * torch.exp(logstep *\",\n \"0.5, will compute DB to amplitude. Returns: Tensor: Output tensor in power/amplitude scale.\",\n \"(ICASSP), Florence, 2014, pp. 2494-2498, doi: 10.1109/ICASSP.2014.6854049. \\\"\\\"\\\" shape = waveform.shape waveform =\",\n \"+= (frame_to_add ** 2) window_frames = window_end - window_start last_window_start = window_start last_window_end\",\n \"1], complex_tensor[..., 0]) def magphase( complex_tensor: Tensor, power: float = 1.0 ) ->\",\n \"input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` Return: Tensor: Angle of\",\n \"factor of the second, elementwise. \\\"\\\"\\\" mask = (a[0] > thresh * b[0])\",\n \"-> Tensor: r\\\"\\\"\\\" Apply median smoothing to the 1D tensor over the given\",\n \"* torch.rand(batch, freq, frames) else: angles = torch.zeros(batch, freq, frames) angles = torch.stack([angles.cos(),\",\n \"lag_min = int(math.ceil(sample_rate / freq_high)) # Find near enough max that is smallest\",\n \"of audio of dimension (..., freq, time) cmn_window (int, optional): Window in frames\",\n \"(min_value.long() + value.long()).squeeze() assert mask_end - mask_start < mask_param if axis == 1:\",\n \"For more details see :py:func:`torchaudio.backend.sox_io_backend.save`. bits_per_sample (int, optional): Changes the bit depth for\",\n \"(freqs * specgram).sum(dim=freq_dim) / specgram.sum(dim=freq_dim) @_mod_utils.requires_sox() def apply_codec( waveform: Tensor, sample_rate: int, format:\",\n \"1 may not converge. length (int or None): Array length of the expected\",\n \"the power/amplitude scale. Args: x (Tensor): Input tensor before being converted to power/amplitude\",\n \"Batched inputs should include a channel dimension and have the form `(batch, channel,\",\n \"return mels def _mel_to_hz(mels: Tensor, mel_scale: str = \\\"htk\\\") -> Tensor: \\\"\\\"\\\"Convert mel\",\n \"at time :math:`t`, :math:`c_t` is the spectrogram coeffcients at time :math:`t`, :math:`N` is\",\n \"indices: Tensor, win_length: int ) -> Tensor: r\\\"\\\"\\\" Apply median smoothing to the\",\n \"of mfc coefficients to retain n_mels (int): Number of mel filterbanks norm (str\",\n \"different types of features give the same number of frames. (default: True) Returns:\",\n \"`1.0`). Returns: Tensor: Power of the normed input tensor. Shape of `(..., )`\",\n \"normalize variance to one. (bool, default = false) Returns: Tensor: Tensor of freq\",\n \"= waveform[:, last_window_start, :] cur_sum -= frame_to_remove if norm_vars: cur_sumsq -= (frame_to_remove **\",\n \"is ``(win_length-1)//2``. Args: specgram (Tensor): Tensor of audio of dimension (..., freq, time)\",\n \"close to the first half of lags, then the latter is taken. \\\"\\\"\\\"\",\n \"= torch.tensor(mu, dtype=x_mu.dtype) x = ((x_mu) / mu) * 2 - 1.0 x\",\n \"1): s1 = waveform[..., :-lag].unfold(-1, frame_size, frame_size)[..., :num_of_frames, :] s2 = waveform[..., lag:].unfold(-1,\",\n \"= compute_deltas(specgram) >>> delta2 = compute_deltas(delta) \\\"\\\"\\\" device = specgram.device dtype = specgram.dtype\",\n \"the `Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_ This expects an input with values between 0 and\",\n \"to. Must be more than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional): Smallest\",\n \"# with 231 == ceil(300 / 1.3) torch.Size([2, 1025, 231, 2]) \\\"\\\"\\\" #\",\n \"2 * math.pi * torch.rand(batch, freq, frames) else: angles = torch.zeros(batch, freq, frames)\",\n \"dtype=dtype) * (specgrams.size(axis) - value) # Create broadcastable mask mask_start = min_value[..., None,\",\n \"dimensions (channel, freq, time) \\\"\\\"\\\" # pack batch shape = specgram.size() specgram =\",\n \"optional): Lowest frequency that can be detected (Hz) (Default: ``85``). freq_high (int, optional):\",\n \"1) output = torch.nn.functional.conv1d(specgram, kernel, groups=specgram.shape[1]) / denom # unpack batch output =\",\n \"the magnitude spectrogram, (must be > 0) e.g., 1 for energy, 2 for\",\n \"f_sp = 200.0 / 3 mels = (freq - f_min) / f_sp #\",\n \"warnings from typing import Optional, Tuple import torch from torch import Tensor from\",\n \">>> rate = 1.3 # Speed up by 30% >>> phase_advance = torch.linspace(\",\n \"mag * torch.cos(phase_acc) imag_stretch = mag * torch.sin(phase_acc) complex_specgrams_stretch = torch.stack([real_stretch, imag_stretch], dim=-1)\",\n \"center (bool, optional): whether to pad :attr:`waveform` on both sides so that the\",\n \"freq, time) cmn_window (int, optional): Window in frames for running average CMN computation\",\n \"float, length: Optional[int], rand_init: bool ) -> Tensor: r\\\"\\\"\\\"Compute waveform from a linear\",\n \"to power. If 0.5, will compute DB to amplitude. Returns: Tensor: Output tensor\",\n \"False, norm_vars: bool = False, ) -> Tensor: r\\\"\\\"\\\" Apply sliding-window cepstral mean\",\n \"input_shape[-2:] waveform = waveform.view(-1, num_frames, num_feats) num_channels = waveform.shape[0] dtype = waveform.dtype device\",\n \"magnitude-only STFT spectrogram of dimension (..., freq, frames) where freq is ``n_fft //\",\n \"dtype=dtype, device=device) else: variance = cur_sumsq variance = variance / window_frames variance -=\",\n \"n_mels (int): Number of mel filterbanks sample_rate (int): Sample rate of the audio\",\n \"no.2, pp.236–243, Apr. 1984. Args: specgram (Tensor): A magnitude-only STFT spectrogram of dimension\",\n \"torch.arange(-n, n + 1, 1, device=device, dtype=dtype).repeat(specgram.shape[1], 1, 1) output = torch.nn.functional.conv1d(specgram, kernel,\",\n \"delta_pitch( float, optional): Smallest relative change in pitch that our algorithm measures. (default:\",\n \"given. \\\"\\\"\\\" assert momentum < 1, 'momentum={} > 1 can be unstable'.format(momentum) assert\",\n \"...)``. \\\"\\\"\\\" if norm is not None and norm != \\\"slaney\\\": raise ValueError(\\\"norm\",\n \"shape `(..., 2)` into its magnitude and phase. Args: complex_tensor (Tensor): Tensor shape\",\n \"# unpack batch complex_specgrams_stretch = complex_specgrams_stretch.reshape(shape[:-3] + complex_specgrams_stretch.shape[1:]) return complex_specgrams_stretch def mask_along_axis_iid( specgrams:\",\n \"argument normalized is not used in Griffin-Lim, \\\" \\\"and will be removed in\",\n \"x def complex_norm( complex_tensor: Tensor, power: float = 1.0 ) -> Tensor: r\\\"\\\"\\\"Compute\",\n \"Tensor, power: float = 1.0 ) -> Tuple[Tensor, Tensor]: r\\\"\\\"\\\"Separate a complex-valued spectrogram\",\n \"window length used for computing delta (Default: ``5``) mode (str, optional): Mode parameter\",\n \"1 x_db = x_db.reshape(-1, packed_channels, shape[-2], shape[-1]) x_db = torch.max(x_db, (x_db.amax(dim=(-3, -2, -1))\",\n \"# randomly initialize the phase batch, freq, frames = specgram.size() if rand_init: angles\",\n \"(..., freq, time) Example >>> specgram = torch.randn(1, 40, 1000) >>> delta =\",\n \"float, power: float ) -> Tensor: r\\\"\\\"\\\"Turn a tensor from the decibel scale\",\n \"(EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) / (EPSILON + torch.norm(s2, p=2, dim=-1)).pow(2) ) output_lag.append(output_frames.unsqueeze(-1))\",\n \"min_log_hz: mels = min_log_mel + math.log(freq / min_log_hz) / logstep return mels def\",\n \"indices def _median_smoothing( indices: Tensor, win_length: int ) -> Tensor: r\\\"\\\"\\\" Apply median\",\n \"not used in Griffin-Lim, \\\" \\\"and will be removed in v0.9.0 release. To\",\n \"output_frames = ( (s1 * s2).sum(-1) / (EPSILON + torch.norm(s1, p=2, dim=-1)).pow(2) /\",\n \"specgrams.device dtype = specgrams.dtype value = torch.rand(specgrams.shape[:2], device=device, dtype=dtype) * mask_param min_value =\",\n \"``htk`` or ``slaney``. (Default: ``htk``) Returns: mels (float): Frequency in Mels \\\"\\\"\\\" if\",\n \":-2]) / f_diff[:-1] # (n_freqs, n_mels) up_slopes = slopes[:, 2:] / f_diff[1:] #\",\n \"``n_mfcc``). \\\"\\\"\\\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1) dct = torch.cos(math.pi\",\n \"parameter if given. \\\"\\\"\\\" assert momentum < 1, 'momentum={} > 1 can be\",\n \"* angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float() # Rebuild the spectrogram rebuilt =\",\n \"freq_high) indices = _median_smoothing(indices, win_length) # Convert indices to frequency EPSILON = 10\",\n \"of features give the same number of frames. (default: True) Returns: Tensor: Pitch\",\n \"to pitch and NCCF. Reference: - A pitch extraction algorithm tuned for automatic\",\n \"mask_start = min_value[..., None, None] mask_end = (min_value + value)[..., None, None] mask\",\n \"upsample_filter_width, max_frames_latency, frames_per_chunk, simulate_first_pass_online, recompute_frame, snip_edges, ) result = result.reshape(shape[:-1] + result.shape[-2:]) return\",\n \"the ``length`` parameter if given. \\\"\\\"\\\" assert momentum < 1, 'momentum={} > 1\",\n \"Store the previous iterate tprev = rebuilt # Invert with our current estimate\",\n \"(min_value + value)[..., None, None] mask = torch.arange(0, specgrams.size(axis), device=device, dtype=dtype) # Per\",\n \"of freq of dimension (..., frame) \\\"\\\"\\\" # pack batch shape = list(waveform.size())\",\n \"we allow pitch tracking to introduce into the feature processing (affects output only\",\n \"use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: Tensor: Triangular filter banks (fb matrix)\",\n \"** (-9) # Number of lags to check lags = int(math.ceil(sample_rate / freq_low))\",\n \"2) f_pts = _mel_to_hz(m_pts, mel_scale=mel_scale) # calculate the difference between each mel point\",\n \"+= lag_min # Add 1 empirical calibration offset indices += 1 return indices\",\n \"# And initialize the previous iterate to 0 rebuilt = torch.tensor(0.) for _\",\n \"waveform of shape `(..., time)`. sample_rate (float): Sample rate of `waveform`. frame_length (float,\",\n \"the left. (bool, default = false) norm_vars (bool, optional): If true, normalize variance\",\n \"(str, optional): Scale to use: ``htk`` or ``slaney``. (Default: ``htk``) Returns: freqs (Tensor):\",\n \"otherwise. Returns: torch.Tensor: waveform of (..., time), where time equals the ``length`` parameter\",\n \"of the second, elementwise. \\\"\\\"\\\" mask = (a[0] > thresh * b[0]) values\",\n \"of size (``n_mels``, ``n_mfcc``). \\\"\\\"\\\" # http://en.wikipedia.org/wiki/Discrete_cosine_transform#DCT-II n = torch.arange(float(n_mels)) k = torch.arange(float(n_mfcc)).unsqueeze(1)\",\n \"relative change in pitch that our algorithm measures. (default: 0.005) nccf_ballast (float, optional):\",\n \"if rand_init: angles = 2 * math.pi * torch.rand(batch, freq, frames) else: angles\",\n \"tensor input. Args: complex_tensor (Tensor): Tensor shape of `(..., complex=2)` power (float): Power\",\n \"reduces NCCF for quiet frames (default: 7000) lowpass_filter_width (int, optional): Integer that determines\",\n \"(time_steps + 1).long()) angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2,\",\n \"angle_0 = angle(complex_specgrams_0) angle_1 = angle(complex_specgrams_1) norm_0 = torch.norm(complex_specgrams_0, p=2, dim=-1) norm_1 =\",\n \"dimension (..., freq, frames) where freq is ``n_fft // 2 + 1``. window\",\n \"* torch.log10(torch.clamp(x, min=amin)) x_db -= multiplier * db_multiplier if top_db is not None:\",\n \"sliding-window cepstral mean (and optionally variance) normalization per utterance. Args: waveform (Tensor): Tensor\",\n \"tensor \\\"\\\"\\\" mag = complex_norm(complex_tensor, power) phase = angle(complex_tensor) return mag, phase def\",\n \"Cost factor for FO change. (default: 0.1) lowpass_cutoff (float, optional): Cutoff frequency for\",\n \"``frames_per_chunk > 0``. (default: 500) snip_edges (bool, optional): If this is set to\",\n \"estimates angles = rebuilt if momentum: angles = angles - tprev.mul_(momentum / (1\",\n \"filterbank so that assuming there is a matrix A of size (..., ``n_freqs``),\",\n \"int, sample_rate: int, norm: Optional[str] = None, mel_scale: str = \\\"htk\\\", ) ->\",\n \"float = 50, max_f0: float = 400, soft_min_f0: float = 10.0, penalty_factor: float\",\n \"only if ``frames_per_chunk > 0`` and ``simulate_first_pass_online=True``) (default: 0) frames_per_chunk (int, optional): The\",\n \"of FFT, creates ``n_fft // 2 + 1`` bins hop_length (int): Length of\",\n \"phase = phase - 2 * math.pi * torch.round(phase / (2 * math.pi))\",\n \"win_length=win_length, window=window, center=center, pad_mode=pad_mode, normalized=False, onesided=onesided, return_complex=True, ) # unpack batch spec_f =\",\n \"if mel_scale == \\\"htk\\\": return 700.0 * (10.0**(mels / 2595.0) - 1.0) #\",\n \"groups=specgram.shape[1]) / denom # unpack batch output = output.reshape(shape) return output def _compute_nccf(\",\n \"correspond to what an online decoder would see in the first pass of\",\n \"variance) normalization per utterance. Args: waveform (Tensor): Tensor of audio of dimension (...,\",\n \"= ((x_mu + 1) / 2 * mu + 0.5).to(torch.int64) return x_mu def\"\n]","isConversational":false}}},{"rowIdx":1498,"cells":{"ngram":{"kind":"list like","value":["mode = 'None' elif mode == 'Posctl': mode = 'Position' elif mode ==","latitude = self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f}","(XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Setpoint v = self.setpoint.velocity","ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import Rotation as R from sensor_msgs.msg","elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State:","severity in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines,","1 # GPS info satellites = 0 fix_type, color = GPS_FIX_DICT[0] for value","status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state","mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if mode","round(p.y, 2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab,","callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images =","pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row","try: rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw,","{vz:.2f} (XYZ) {yaw} (Y)') row += 1 # Cameras freqs = {c: 0","== 'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state = state_msg def extended_callback(self,","screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 # Mode color = curses.COLOR_CYAN mode","self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended =","# Default variables self.status_battery_perc = None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State,","np.isnan(frequency): return 0 return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate","queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState()","if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state ==","GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock',","= setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console","queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped()","= [] self.images = {c: deque(maxlen=10) for c in self.cameras} for camera in","lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW),","pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def","elif battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage > 0: color =","cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v))","('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def","row = 0 # Battery battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN","= rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg):","2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row,","x_indent, status_extended, get_color(color)) row += 1 # GPS info satellites = 0 fix_type,","int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ)","= mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED else:","state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self,","= 1 / np.mean(durations) if np.isnan(frequency): return 0 return frequency class StatusNode: def","absolute_import, division, print_function import curses import sys from collections import deque from datetime","sys from collections import deque from datetime import datetime import numpy as np","p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try:","= 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1","geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform","def frequency_from_messages(messages): durations = [] for i in range(len(messages) - 1): duration =","x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1 # Cameras freqs","color = curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW elif severity in","color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites","yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row,","screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0 x_indent = 14 row =","= PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back',","f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Global","Cameras freqs = {c: 0 for c in self.cameras} for cam, messages in","'{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 #","elif mode == 'Posctl': mode = 'Position' elif mode == 'Rtl': mode =","self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows - height_status, self.cols,","Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] #","x_indent, status_gps) row += 1 # Local pose p = self.local_pose.pose.position q =","color = curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage >","in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front","messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for","self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols, 1, 2)","# self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines = 0 self.text","state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg):","= NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub =","{y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Setpoint v","int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f}","(Y)') row += 1 # Cameras freqs = {c: 0 for c in","int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll}","callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback,","'right', 'back', 'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10) for c in","Armed if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN","= R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll","mode == 'Posctl': mode = 'Position' elif mode == 'Rtl': mode = 'Return'","rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1)","longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)'","rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix,","self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub","yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row,","from datetime import datetime import numpy as np import rospy from diagnostic_msgs.msg import","') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 # Armed if self.state.armed: color","0 return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate',","curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2)","+= 1 # GPS info satellites = 0 fix_type, color = GPS_FIX_DICT[0] for","# Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW]","= [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in","in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites = value.value elif value.key ==","= rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo()","('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix',","rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics',","= [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG]","elif value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info:","self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot =","(front right back left [Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self): rate","from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import Rotation as","'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row","for c in self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber =","elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state ==","= 'Position' elif mode == 'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row,","setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg):","= 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color","get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status)","DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local',","x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2","'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 #","curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE,","PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray,","== 'Satellites visible': satellites = value.value elif value.key == 'Fix type': fix_type, color","== 'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE if mode == '':","= 'Yes' else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ')","{z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Setpoint v =","} def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i in","= datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red =","altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS","0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z = round(p.x,","') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 # Mode color = curses.COLOR_CYAN","text = statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT,","severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity","left [Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try:","= round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos:","curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass if __name__","f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Setpoint","R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll =","self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended =","1 screen.refresh() def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab","in self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image,","= {c: deque(maxlen=10) for c in self.cameras} for camera in self.cameras: topic =","= 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color))","# screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen =","') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 # GPS pos","State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery',","screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 # Mode","screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row += 1 # Local","p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try:","screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch}","for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera,","curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery,","color in colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc = None self.state","return 0 return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate =","rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if","screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 # Armed","curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE),","screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row","self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera):","/ np.mean(durations) if np.isnan(frequency): return 0 return frequency class StatusNode: def __init__(self, screen):","c in self.cameras} for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr,","= 0 # Battery battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN if","x_indent, status_battery, get_color(color)) row += 1 # Armed if self.state.armed: color = curses.COLOR_RED","0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3:","- messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency): return 0 return","StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup","PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose',","x, y, z = round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll","python3 from __future__ import absolute_import, division, print_function import curses import sys from collections","f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh() def","(LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row += 1 #","+= 1 # Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion =","= curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row,","= rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback,","self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub","sat)', get_color(color)) row += 2 # GPS pos latitude = self.gps.latitude longitude =","6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations =","color setup curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1) # Default variables","= rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers =","{yaw} (Y)') row += 1 # Cameras freqs = {c: 0 for c","statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text","self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard':","'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color =","{y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Global pose","2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f}","if value.key == 'Satellites visible': satellites = value.value elif value.key == 'Fix type':","= curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED status_battery = str(battery_percentage) +","self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub =","'GPS pos: ') screen.addstr(row, x_indent, status_gps) row += 1 # Local pose p","self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass if","self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status,","in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self,","self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose","100) color = curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage","self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr() self.rows, self.cols =","= gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose =","{fb} {fl} (front right back left [Hz])') row += 1 screen.refresh() self.screen.refresh() def","elif mode == 'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode:","curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab,","pos latitude = self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps =","for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr}","__future__ import absolute_import, division, print_function import curses import sys from collections import deque","mode == 'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ')","row += 1 # GPS info satellites = 0 fix_type, color = GPS_FIX_DICT[0]","self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen =","curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED elif severity in severity_yellow: color","import deque from datetime import datetime import numpy as np import rospy from","k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb}","= round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch),","screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch}","self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for k, v","Setpoint v = self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y, 2), round(v.z,","in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps","GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row","self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended =","= int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage > 50: color =","row += 1 # Armed if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes'","Curses setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status","v = self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y, 2), round(v.z, 2)","diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget,","diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps =","curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})'","= self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text","%H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg =","# Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED","f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row","# queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose =","x_indent = 14 row = 0 # Battery battery_percentage = int(self.battery.percentage * 100)","3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK","screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep()","x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 # Mode color","= f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber)","= 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK,","color = curses.COLOR_BLUE if mode == '': mode = 'None' elif mode ==","{roll} {pitch} {yaw} (RPY)') row += 1 # Setpoint v = self.setpoint.velocity vx,","= rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx()","curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5:","self.image_subscribers = [] self.images = {c: deque(maxlen=10) for c in self.cameras} for camera","type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type}","fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key == 'Satellites visible':","PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import Rotation","[0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z =","'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row","f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1 # Cameras freqs =","ff, fr, fb, fl = [int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab,","# GPS info satellites = 0 fix_type, color = GPS_FIX_DICT[0] for value in","row += 1 # Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion","0 fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key == 'Satellites","yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ)","rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main)","f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def","# Cameras freqs = {c: 0 for c in self.cameras} for cam, messages","screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right back left [Hz])') row +=","def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str =","self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites = value.value elif value.key == 'Fix","NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2:","height_status, self.cols, 12, 2) self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) #","time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red","= int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f}","queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1)","GPS pos latitude = self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps","1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status()","= State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub =","'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 # Armed if self.state.armed:","'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg):","curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines = 0 self.text = '' self.screen.keypad(True)","color = curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED status_battery = str(battery_percentage)","rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False)","mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED else: color","+ '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1","rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x,","curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines +=","import absolute_import, division, print_function import curses import sys from collections import deque from","status_gps) row += 1 # Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation","= self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console","= status def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose =","__init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen =","self.battery = battery_msg def state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended","status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color))","> 0: color = curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery:","GPS info satellites = 0 fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values:","DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State #","status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg):","if mode == 'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE if mode","= {c: 0 for c in self.cameras} for cam, messages in self.images.items(): freqs[cam]","extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps","int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f}","if mode == '': mode = 'None' elif mode == 'Posctl': mode =","back left [Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate)","print_function import curses import sys from collections import deque from datetime import datetime","setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status =","self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED,","if battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage > 25: color =","self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended =","frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for k, v in freqs.items()] screen.addstr(row,","self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback,","local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self,","roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f}","self.status_battery_perc = None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery","'%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 #","self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint","battery_percentage > 0: color = curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab,","pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg","satellites = value.value elif value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row,","extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if","diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status","rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status","State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended","freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for k, v in","[msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED elif","degrees=True) x, y, z = round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch,","'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color =","= PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub =","curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i","self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped,","# StatusText from scipy.spatial.transform import Rotation as R from sensor_msgs.msg import BatteryState, Image,","durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency): return 0 return frequency class","import sys from collections import deque from datetime import datetime import numpy as","color = curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row,","queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery","curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color in colors:","0 for c in self.cameras} for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages)","self.cols = self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols, 1, 2) #","'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent,","gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self,","screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 # GPS","setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str","self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget,","= DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub =","R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z","color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)',","fl = [int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row,","+= 1 # Armed if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else:","rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1)","= DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint =","get_color(color)) row += 1 # Armed if self.state.armed: color = curses.COLOR_RED status_armed =","msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if","12, 2) self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor","BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1: ('No fix',","self.lines += 1 screen.refresh() def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) #","if battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state = state_msg","info satellites = 0 fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if","try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen):","battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state","import Rotation as R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = {","scipy.spatial.transform import Rotation as R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT =","severity_red: color = curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW elif severity","color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed,","color = curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED elif severity in","x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 # GPS pos latitude =","msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red: color","'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1","= rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback,","PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images","round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll)","if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed","deque from datetime import datetime import numpy as np import rospy from diagnostic_msgs.msg","{pitch} {yaw} (RPY)') row += 1 # Global pose p = self.global_pose.pose.position q","screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row +=","msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE]","DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText","-1) # Default variables self.status_battery_perc = None self.state = State() self.state_sub = rospy.Subscriber('mavros/state',","PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics","vy, vz = round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row,","= rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv',","def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def","status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row +=","= self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if mode ==","deque(maxlen=10) for c in self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber","= rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix',","get_color(color)) row += 1 # Mode color = curses.COLOR_CYAN mode = self.state.mode if","= '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1","{roll} {pitch} {yaw} (RPY)') row += 1 # Global pose p = self.global_pose.pose.position","# Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y,","callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose =","for value in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites = value.value elif","0 # Battery battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage","'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10) for c in self.cameras} for","= 'None' elif mode == 'Posctl': mode = 'Position' elif mode == 'Rtl':","msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color =","screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1 # Cameras","= statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL,","1 / np.mean(durations) if np.isnan(frequency): return 0 return frequency class StatusNode: def __init__(self,","= curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize()","callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended =","self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 **","screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 # GPS pos latitude","statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral =","str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row +=","= rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback,","{vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1 # Cameras freqs = {c:","# Curses color setup curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1) #","x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 # GPS info","curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color","curses.init_pair(color, color, -1) # Default variables self.status_battery_perc = None self.state = State() self.state_sub","= [] for i in range(len(messages) - 1): duration = messages[i + 1].header.stamp","= f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps)","4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def","row += 1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air'","{c: 0 for c in self.cameras} for cam, messages in self.images.items(): freqs[cam] =","x_indent, f'{ff} {fr} {fb} {fl} (front right back left [Hz])') row += 1","# Battery battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage >","statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING,","# Mode color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1]","2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ')","def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self,","{fl} (front right back left [Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self):","severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red: color =","curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row","status def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg","callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0':","'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 # Extended status if","({satellites} sat)', get_color(color)) row += 2 # GPS pos latitude = self.gps.latitude longitude","'back', 'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10) for c in self.cameras}","['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10) for c","== '': mode = 'None' elif mode == 'Posctl': mode = 'Position' elif","+= 1 # Setpoint v = self.setpoint.velocity vx, vy, vz = round(v.x, 2),","self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub","fr, fb, fl = [int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras:","1 # Cameras freqs = {c: 0 for c in self.cameras} for cam,","buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery =","({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen","def state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def","2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f}","= PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps =","battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state = state_msg def","import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1: ('No","satellites = 0 fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key","not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def","import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg","elif severity in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' #","GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D","'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 #","status_armed, get_color(color)) row += 1 # Mode color = curses.COLOR_CYAN mode = self.state.mode","2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK","curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if","x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row +=","[] self.images = {c: deque(maxlen=10) for c in self.cameras} for camera in self.cameras:","mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode,","rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1)","[q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx',","q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0,","round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos:","'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 # Mode color =","callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose","height_status = 15 self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows","durations = [] for i in range(len(messages) - 1): duration = messages[i +","Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif","frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) #","def run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException:","Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location","') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 # GPS info satellites =","def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def","gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg):","subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self,","pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg):","14 row = 0 # Battery battery_percentage = int(self.battery.percentage * 100) color =","curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab,","topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24)","datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY,","status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed:","screen.addstr(row, x_indent, status_gps) row += 1 # Local pose p = self.local_pose.pose.position q","int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ)","datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg","from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState,","[] for i in range(len(messages) - 1): duration = messages[i + 1].header.stamp -","return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i in range(len(messages) - 1):","mode = mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED else: color =","StatusText from scipy.spatial.transform import Rotation as R from sensor_msgs.msg import BatteryState, Image, NavSatFix","= self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0 x_indent = 14","Default variables self.status_battery_perc = None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback,","(XYZ) {yaw} (Y)') row += 1 # Cameras freqs = {c: 0 for","mode = mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED","= 0 x_indent = 14 row = 0 # Battery battery_percentage = int(self.battery.percentage","row += 1 # Setpoint v = self.setpoint.velocity vx, vy, vz = round(v.x,","curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color in colors: curses.init_pair(color,","fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA),","image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S')","value in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites = value.value elif value.key","'Posctl': mode = 'Position' elif mode == 'Rtl': mode = 'Return' status_mode =","'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent,","for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl =","battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED","f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 # GPS pos latitude = self.gps.latitude","[curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors()","Mode color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode","round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos:","int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)')","curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass if __name__ == '__main__':","= messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if","{altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row += 1","[msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red:","self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF:","# Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y,","1): duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 /","if severity in severity_red: color = curses.COLOR_RED elif severity in severity_yellow: color =","mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import Rotation as R","= 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color))","def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen","(RPY)') row += 1 # Setpoint v = self.setpoint.velocity vx, vy, vz =","self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING:","= curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row,","else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent,","for color in colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc = None","elif battery_percentage > 0: color = curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row,","self.state = state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for","{z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Global pose p","colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc = None self.state = State()","{longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row +=","rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1)","0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2),","queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped()","# callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1)","= curses.COLOR_BLUE if mode == '': mode = 'None' elif mode == 'Posctl':","'Yes' else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row,","= curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif","= StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps =","color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color))","self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10)","rospy.loginfo(status) # print(status) x_tab = 0 x_indent = 14 row = 0 #","') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right back left [Hz])') row","color, -1) # Default variables self.status_battery_perc = None self.state = State() self.state_sub =","x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right back left","('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D","== self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended","('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS',","log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen = self.status screen.clear() #","pos: ') screen.addstr(row, x_indent, status_gps) row += 1 # Local pose p =","= curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif","messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency): return 0 return frequency","np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from","self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right',","= 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color","severity = statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow","+= 1 # Cameras freqs = {c: 0 for c in self.cameras} for","NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose","ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, #","frequency_from_messages(messages): durations = [] for i in range(len(messages) - 1): duration = messages[i","msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN","') screen.addstr(row, x_indent, status_gps) row += 1 # Local pose p = self.local_pose.pose.position","get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i in range(len(messages) -","i in range(len(messages) - 1): duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec())","2 # GPS pos latitude = self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude,","self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in","in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for k,","State # StatusText from scipy.spatial.transform import Rotation as R from sensor_msgs.msg import BatteryState,","curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 #","screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 # Extended","value.value elif value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS","callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location ==","curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return","BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) #","0, log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen = self.status screen.clear()","row += 1 # Mode color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'):","self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub","self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError:","{fr} {fb} {fl} (front right back left [Hz])') row += 1 screen.refresh() self.screen.refresh()","right back left [Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self): rate =","self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try:","#!/usr/bin/env python3 from __future__ import absolute_import, division, print_function import curses import sys from","float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages):","cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses","queue_size=1) # self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, #","self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent,","= rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback,","x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw}","curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state","= ['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10) for","status_battery, get_color(color)) row += 1 # Armed if self.state.armed: color = curses.COLOR_RED status_armed","= 'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color","severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log,","15 self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows - height_status,","elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state ==","pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w]","int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN","self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot =","'Satellites visible': satellites = value.value elif value.key == 'Fix type': fix_type, color =","screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 # Armed if self.state.armed: color =","battery_msg def state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended = extended_msg","variables self.status_battery_perc = None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1)","= mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE","# Setpoint v = self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y, 2),","= self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw","fb, fl = [int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ')","= 14 row = 0 # Battery battery_percentage = int(self.battery.percentage * 100) color","rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException:","curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations","color = curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage >","curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage > 0: color","self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError:","self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab,","class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses","sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1:","self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose","value.key == 'Satellites visible': satellites = value.value elif value.key == 'Fix type': fix_type,","from __future__ import absolute_import, division, print_function import curses import sys from collections import","Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED),","= rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2), round(p.y, 2), round(p.z, 2)","rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main():","get_color(color)) row += 1 # GPS info satellites = 0 fix_type, color =","round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent,","= 15 self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows -","self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND:","{ 0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE),","lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN)","self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState,","from collections import deque from datetime import datetime import numpy as np import","= statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral","= curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows - height_status, self.cols, 12,","self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps","print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0 x_indent","'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)')","in severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE self.text","duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations)","# Curses setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15","24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg def","'None' elif mode == 'Posctl': mode = 'Position' elif mode == 'Rtl': mode","'' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA,","row += 2 # GPS pos latitude = self.gps.latitude longitude = self.gps.longitude altitude","= self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot","status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff'","curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for","status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground'","NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose',","self.images = {c: deque(maxlen=10) for c in self.cameras} for camera in self.cameras: topic","pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg,","= 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color","elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state ==","= curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif","= curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text}","pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent,","= int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f}","except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except","rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText,","50: color = curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage","'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right back left [Hz])')","f'{ff} {fr} {fb} {fl} (front right back left [Hz])') row += 1 screen.refresh()","import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import Rotation as R from","get_color(color)) row += 1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended =","= GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites =","freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right","x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw}","range(len(messages) - 1): duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency =","1 # Armed if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else: color","yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2), round(p.y,","= None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery =","battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage > 50: color","x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 #","pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2), round(p.y, 2),","= BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub =","= datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity","== 'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row,","1 # Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x,","self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1","('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float',","0 x_indent = 14 row = 0 # Battery battery_percentage = int(self.battery.percentage *","[int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff}","battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state =","PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left']","mode = 'Position' elif mode == 'Rtl': mode = 'Return' status_mode = '{}'.format(mode)","import datetime import numpy as np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus","def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i in range(len(messages)","self.cols, 1, 2) # self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines","q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion)","'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)')","for c in self.cameras} for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff,","2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global","in self.cameras} for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb,","ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub","curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass","pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent,","PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus()","= curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED elif severity in severity_yellow:","= curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color))","run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak()","collections import deque from datetime import datetime import numpy as np import rospy","') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1 #","2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ')","# self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1)","Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z,","frequency = 1 / np.mean(durations) if np.isnan(frequency): return 0 return frequency class StatusNode:","import numpy as np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg","if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard': color","color = curses.COLOR_RED else: color = curses.COLOR_BLUE if mode == '': mode =","== self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended","def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def","+ 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency): return","self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint","x_indent, status_armed, get_color(color)) row += 1 # Mode color = curses.COLOR_CYAN mode =","color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN","0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE,","1, 2) # self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines =","np.mean(durations) if np.isnan(frequency): return 0 return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node',","int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll}","colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color","1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency): return 0","c in self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic,","state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status in","= R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y,","rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def","DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras","self.cameras} for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl","rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1)","return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0)","get_color(color)) row += 2 # GPS pos latitude = self.gps.latitude longitude = self.gps.longitude","roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f}","= round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint:","while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run()","curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols, 1,","extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS'","1 # Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x,","from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED),","- 1): duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1","{yaw} (RPY)') row += 1 # Setpoint v = self.setpoint.velocity vx, vy, vz","value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ')","status_extended, get_color(color)) row += 1 # GPS info satellites = 0 fix_type, color","vz = round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab,","image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d","screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1","numpy as np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import","2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row,","None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState()","import curses import sys from collections import deque from datetime import datetime import","'': mode = 'None' elif mode == 'Posctl': mode = 'Position' elif mode","def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass if __name__ ==","DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget()","** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg","+= 1 # Mode color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode","if 'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps = gps_msg","= ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() #","setup curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc","self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps","status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined'","round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ')","vx, vy, vz = round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw))","status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed'","self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState,","# time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg = statustext_msg","row += 1 # Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion","1 # Mode color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode =","statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time)","1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color =","== self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended","screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen = self.status","= pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint =","severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE self.text =","screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr()","mode == '': mode = 'None' elif mode == 'Posctl': mode = 'Position'","callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext","{pitch} {yaw} (RPY)') row += 1 # Setpoint v = self.setpoint.velocity vx, vy,","curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1)","datetime import numpy as np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from","2) self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors","screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 # Extended status if self.extended.landed_state ==","self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub","= curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines = 0 self.text = ''","') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 # Extended status if self.extended.landed_state","default=1.0) # Curses setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status =","(XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Global pose p =","y, z = round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll =","from scipy.spatial.transform import Rotation as R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT","datetime import datetime import numpy as np import rospy from diagnostic_msgs.msg import DiagnosticArray,","== 'Posctl': mode = 'Position' elif mode == 'Rtl': mode = 'Return' status_mode","'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 # GPS info satellites","def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status:","= GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color))","= [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED","except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx',","ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True)","in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0,","in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2","self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED:","def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps =","status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent,","x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row += 1 # Local pose","+= 1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown():","setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen","= curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1","x_indent, status_mode, get_color(color)) row += 1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR:","queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext =","R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS',","self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN,","# GPS pos latitude = self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2)","self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors =","self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped,","severity in severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE","color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row +=","= curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines","= curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral:","import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State","round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f}","curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage > 25: color","fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for","2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local","Curses color setup curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1) # Default","5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color)","PositionTarget, State # StatusText from scipy.spatial.transform import Rotation as R from sensor_msgs.msg import","import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import","Battery battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage > 50:","= { 0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock',","curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state","self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw =","('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = []","self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except","self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self,","curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color in colors: curses.init_pair(color, color,","= rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback,","curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc =","= curses.COLOR_RED else: color = curses.COLOR_BLUE if mode == '': mode = 'None'","elif severity in severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral: color =","screen.refresh() def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab =","curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color in","Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z,","color = curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed = 'No'","mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE if","'Position' elif mode == 'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab,","') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row +=","curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) }","x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 # Armed if","pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w]","x_tab = 0 x_indent = 14 row = 0 # Battery battery_percentage =","= 0 fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key ==","= frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for k, v in freqs.items()]","print(status) x_tab = 0 x_indent = 14 row = 0 # Battery battery_percentage","screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text =","x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 # Extended status","callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics =","StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix()","diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status def","color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN","('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color):","callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras =","color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED","[Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while","for status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self,","queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray()","- height_status, self.cols, 12, 2) self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False)","> 25: color = curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED status_battery","screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right back","q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion)","status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row +=","for i in range(len(messages) - 1): duration = messages[i + 1].header.stamp - messages[i].header.stamp","color = curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}:","= [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError: rot =","# Armed if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else: color =","status_mode, get_color(color)) row += 1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended","= battery_msg def state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended =","screen = self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0 x_indent =","'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color =","def statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str =","self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f}","row += 1 # Cameras freqs = {c: 0 for c in self.cameras}","= [int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent,","self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText()","= curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent,","self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity","= curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage > 25:","in range(len(messages) - 1): duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency","severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO,","color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN","= curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage > 0:","0: color = curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ')","info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 # GPS","q.w] try: rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0])","= int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw}","'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps = gps_msg def","gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg","{c: deque(maxlen=10) for c in self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw'","in colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc = None self.state =","= f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh()","argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr() self.rows, self.cols","status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg):","= state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status","BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state',","camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') #","= str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row","q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0,","else: color = curses.COLOR_BLUE if mode == '': mode = 'None' elif mode","row += 1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while not","curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral: color","# rospy.loginfo(status) # print(status) x_tab = 0 x_indent = 14 row = 0","as R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No","= rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub =","StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass if __name__ == '__main__': main()","'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE if mode == '': mode","Rotation as R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0:","callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback,","# print(status) x_tab = 0 x_indent = 14 row = 0 # Battery","color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode =","division, print_function import curses import sys from collections import deque from datetime import","self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ')","self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines = 0 self.text =","curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state","status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended,","+= 1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color","freqs = {c: 0 for c in self.cameras} for cam, messages in self.images.items():","curses.COLOR_RED else: color = curses.COLOR_BLUE if mode == '': mode = 'None' elif","GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites = value.value","= '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN,","curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6:","{yaw} (RPY)') row += 1 # Global pose p = self.global_pose.pose.position q =","as np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped","self.cols, 12, 2) self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide","v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl}","self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub =","self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console =","z = round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll = int(yaw),","visible': satellites = value.value elif value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)]","= self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row,","= pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg)","StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback,","self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers","queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images = {c:","= self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except","screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 # GPS info satellites = 0","= extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in status.name:","= [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup","curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED status_battery = str(battery_percentage) + '%'","self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str","[msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color","1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4:","= curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols,","global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self,","> 50: color = curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW elif","+= 1 screen.refresh() def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) # print(status)","rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw,","= value.value elif value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab,","(RPY)') row += 1 # Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation","== 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row,","camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1,","= self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f}","2) # self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines = 0","2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row,","+= 2 # GPS pos latitude = self.gps.latitude longitude = self.gps.longitude altitude =","curses import sys from collections import deque from datetime import datetime import numpy","in severity_red: color = curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW elif","time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity =","{text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self):","self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0 x_indent = 14 row","mode == 'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE if mode ==","quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError: rot","queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front',","curses.COLOR_BLUE if mode == '': mode = 'None' elif mode == 'Posctl': mode","+= 1 # Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion =","1 # Setpoint v = self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y,","if np.isnan(frequency): return 0 return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv)","self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub","def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self, state_msg):","round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ')","* 100) color = curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN elif","mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard': color =","== self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row,","# self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub","25: color = curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED status_battery =","battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW","rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import","statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR]","== self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended","rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr() self.rows,","= statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow =","def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0","severity in severity_red: color = curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW","fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites}","from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from","curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i in range(len(messages) - 1): duration","self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed =","messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency):","rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers = []","'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color =","roll = rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2), round(p.y, 2), round(p.z,","= self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except","= self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot","msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED elif severity","rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch,"],"string":"[\n \"mode = 'None' elif mode == 'Posctl': mode = 'Position' elif mode ==\",\n \"latitude = self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f}\",\n \"(XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Setpoint v = self.setpoint.velocity\",\n \"ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import Rotation as R from sensor_msgs.msg\",\n \"elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State:\",\n \"severity in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines,\",\n \"1 # GPS info satellites = 0 fix_type, color = GPS_FIX_DICT[0] for value\",\n \"status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state\",\n \"mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if mode\",\n \"round(p.y, 2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab,\",\n \"callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images =\",\n \"pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row\",\n \"try: rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw,\",\n \"{vz:.2f} (XYZ) {yaw} (Y)') row += 1 # Cameras freqs = {c: 0\",\n \"== 'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state = state_msg def extended_callback(self,\",\n \"screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 # Mode color = curses.COLOR_CYAN mode\",\n \"self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended =\",\n \"# Default variables self.status_battery_perc = None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State,\",\n \"np.isnan(frequency): return 0 return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate\",\n \"queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState()\",\n \"if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state ==\",\n \"GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock',\",\n \"= setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console\",\n \"queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped()\",\n \"= [] self.images = {c: deque(maxlen=10) for c in self.cameras} for camera in\",\n \"lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW),\",\n \"pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def\",\n \"elif battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage > 0: color =\",\n \"cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v))\",\n \"('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def\",\n \"row = 0 # Battery battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN\",\n \"= rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg):\",\n \"2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row,\",\n \"x_indent, status_extended, get_color(color)) row += 1 # GPS info satellites = 0 fix_type,\",\n \"int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ)\",\n \"= mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED else:\",\n \"state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self,\",\n \"= 1 / np.mean(durations) if np.isnan(frequency): return 0 return frequency class StatusNode: def\",\n \"absolute_import, division, print_function import curses import sys from collections import deque from datetime\",\n \"sys from collections import deque from datetime import datetime import numpy as np\",\n \"p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try:\",\n \"= 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1\",\n \"geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform\",\n \"def frequency_from_messages(messages): durations = [] for i in range(len(messages) - 1): duration =\",\n \"x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1 # Cameras freqs\",\n \"color = curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW elif severity in\",\n \"color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites\",\n \"yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row,\",\n \"screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0 x_indent = 14 row =\",\n \"= PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back',\",\n \"f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Global\",\n \"Cameras freqs = {c: 0 for c in self.cameras} for cam, messages in\",\n \"'{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 #\",\n \"elif mode == 'Posctl': mode = 'Position' elif mode == 'Rtl': mode =\",\n \"self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows - height_status, self.cols,\",\n \"Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] #\",\n \"x_indent, status_gps) row += 1 # Local pose p = self.local_pose.pose.position q =\",\n \"color = curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage >\",\n \"in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front\",\n \"messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for\",\n \"self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols, 1, 2)\",\n \"# self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines = 0 self.text\",\n \"state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg):\",\n \"= NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub =\",\n \"{y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Setpoint v\",\n \"int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f}\",\n \"(Y)') row += 1 # Cameras freqs = {c: 0 for c in\",\n \"int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll}\",\n \"callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback,\",\n \"'right', 'back', 'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10) for c in\",\n \"Armed if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN\",\n \"= R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll\",\n \"mode == 'Posctl': mode = 'Position' elif mode == 'Rtl': mode = 'Return'\",\n \"rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1)\",\n \"longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)'\",\n \"rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix,\",\n \"self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub\",\n \"yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row,\",\n \"from datetime import datetime import numpy as np import rospy from diagnostic_msgs.msg import\",\n \"') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 # Armed if self.state.armed: color\",\n \"0 return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate',\",\n \"curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2)\",\n \"+= 1 # GPS info satellites = 0 fix_type, color = GPS_FIX_DICT[0] for\",\n \"# Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW]\",\n \"= [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in\",\n \"in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites = value.value elif value.key ==\",\n \"= rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo()\",\n \"('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix',\",\n \"rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics',\",\n \"= [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG]\",\n \"elif value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info:\",\n \"self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot =\",\n \"(front right back left [Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self): rate\",\n \"from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import Rotation as\",\n \"'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row\",\n \"for c in self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber =\",\n \"elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state ==\",\n \"= 'Position' elif mode == 'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row,\",\n \"setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg):\",\n \"= 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color\",\n \"get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status)\",\n \"DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local',\",\n \"x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2\",\n \"'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 #\",\n \"curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE,\",\n \"PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray,\",\n \"== 'Satellites visible': satellites = value.value elif value.key == 'Fix type': fix_type, color\",\n \"== 'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE if mode == '':\",\n \"= 'Yes' else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ')\",\n \"{z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Setpoint v =\",\n \"} def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i in\",\n \"= datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red =\",\n \"altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS\",\n \"0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z = round(p.x,\",\n \"') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 # Mode color = curses.COLOR_CYAN\",\n \"text = statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT,\",\n \"severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity\",\n \"left [Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try:\",\n \"= round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos:\",\n \"curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass if __name__\",\n \"f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Setpoint\",\n \"R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll =\",\n \"self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended =\",\n \"1 screen.refresh() def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab\",\n \"in self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image,\",\n \"= {c: deque(maxlen=10) for c in self.cameras} for camera in self.cameras: topic =\",\n \"= 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color))\",\n \"# screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen =\",\n \"') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 # GPS pos\",\n \"State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery',\",\n \"screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 # Mode\",\n \"screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row += 1 # Local\",\n \"p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try:\",\n \"screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch}\",\n \"for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera,\",\n \"curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery,\",\n \"color in colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc = None self.state\",\n \"return 0 return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate =\",\n \"rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if\",\n \"screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 # Armed\",\n \"curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE),\",\n \"screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row\",\n \"self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera):\",\n \"/ np.mean(durations) if np.isnan(frequency): return 0 return frequency class StatusNode: def __init__(self, screen):\",\n \"c in self.cameras} for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr,\",\n \"= 0 # Battery battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN if\",\n \"x_indent, status_battery, get_color(color)) row += 1 # Armed if self.state.armed: color = curses.COLOR_RED\",\n \"0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3:\",\n \"- messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency): return 0 return\",\n \"StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup\",\n \"PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose',\",\n \"x, y, z = round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll\",\n \"python3 from __future__ import absolute_import, division, print_function import curses import sys from collections\",\n \"f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh() def\",\n \"(LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row += 1 #\",\n \"+= 1 # Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion =\",\n \"= curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row,\",\n \"= rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback,\",\n \"self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub\",\n \"sat)', get_color(color)) row += 2 # GPS pos latitude = self.gps.latitude longitude =\",\n \"6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations =\",\n \"color setup curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1) # Default variables\",\n \"= rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers =\",\n \"{yaw} (Y)') row += 1 # Cameras freqs = {c: 0 for c\",\n \"statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text\",\n \"self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard':\",\n \"'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color =\",\n \"{y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Global pose\",\n \"2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f}\",\n \"if value.key == 'Satellites visible': satellites = value.value elif value.key == 'Fix type':\",\n \"= curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED status_battery = str(battery_percentage) +\",\n \"self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub =\",\n \"'GPS pos: ') screen.addstr(row, x_indent, status_gps) row += 1 # Local pose p\",\n \"self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass if\",\n \"self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status,\",\n \"in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self,\",\n \"self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose\",\n \"100) color = curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage\",\n \"self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr() self.rows, self.cols =\",\n \"= gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose =\",\n \"{fb} {fl} (front right back left [Hz])') row += 1 screen.refresh() self.screen.refresh() def\",\n \"elif mode == 'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode:\",\n \"curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab,\",\n \"pos latitude = self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps =\",\n \"for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr}\",\n \"__future__ import absolute_import, division, print_function import curses import sys from collections import deque\",\n \"mode == 'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ')\",\n \"row += 1 # GPS info satellites = 0 fix_type, color = GPS_FIX_DICT[0]\",\n \"self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen =\",\n \"curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED elif severity in severity_yellow: color\",\n \"import deque from datetime import datetime import numpy as np import rospy from\",\n \"k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb}\",\n \"= round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch),\",\n \"screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch}\",\n \"self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for k, v\",\n \"Setpoint v = self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y, 2), round(v.z,\",\n \"in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps\",\n \"GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row\",\n \"self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended =\",\n \"= int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage > 50: color =\",\n \"row += 1 # Armed if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes'\",\n \"Curses setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status\",\n \"v = self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y, 2), round(v.z, 2)\",\n \"diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget,\",\n \"diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps =\",\n \"curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})'\",\n \"= self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text\",\n \"%H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg =\",\n \"# Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED\",\n \"f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row\",\n \"# queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose =\",\n \"x_indent = 14 row = 0 # Battery battery_percentage = int(self.battery.percentage * 100)\",\n \"3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK\",\n \"screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep()\",\n \"x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 # Mode color\",\n \"= f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber)\",\n \"= 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK,\",\n \"color = curses.COLOR_BLUE if mode == '': mode = 'None' elif mode ==\",\n \"{roll} {pitch} {yaw} (RPY)') row += 1 # Setpoint v = self.setpoint.velocity vx,\",\n \"= rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx()\",\n \"curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5:\",\n \"self.image_subscribers = [] self.images = {c: deque(maxlen=10) for c in self.cameras} for camera\",\n \"type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type}\",\n \"fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key == 'Satellites visible':\",\n \"PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import Rotation\",\n \"[0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z =\",\n \"'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row\",\n \"f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1 # Cameras freqs =\",\n \"ff, fr, fb, fl = [int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab,\",\n \"# GPS info satellites = 0 fix_type, color = GPS_FIX_DICT[0] for value in\",\n \"row += 1 # Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion\",\n \"0 fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key == 'Satellites\",\n \"yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ)\",\n \"rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main)\",\n \"f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def\",\n \"# Cameras freqs = {c: 0 for c in self.cameras} for cam, messages\",\n \"screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right back left [Hz])') row +=\",\n \"def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str =\",\n \"self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites = value.value elif value.key == 'Fix\",\n \"NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2:\",\n \"height_status, self.cols, 12, 2) self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) #\",\n \"time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red\",\n \"= int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f}\",\n \"queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1)\",\n \"GPS pos latitude = self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps\",\n \"1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status()\",\n \"= State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub =\",\n \"'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 # Armed if self.state.armed:\",\n \"'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg):\",\n \"curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines = 0 self.text = '' self.screen.keypad(True)\",\n \"color = curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED status_battery = str(battery_percentage)\",\n \"rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False)\",\n \"mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED else: color\",\n \"+ '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1\",\n \"rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x,\",\n \"curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines +=\",\n \"import absolute_import, division, print_function import curses import sys from collections import deque from\",\n \"status_gps) row += 1 # Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation\",\n \"= self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console\",\n \"= status def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose =\",\n \"__init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen =\",\n \"self.battery = battery_msg def state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended\",\n \"status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color))\",\n \"> 0: color = curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery:\",\n \"GPS info satellites = 0 fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values:\",\n \"DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State #\",\n \"status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg):\",\n \"if mode == 'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE if mode\",\n \"= {c: 0 for c in self.cameras} for cam, messages in self.images.items(): freqs[cam]\",\n \"extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps\",\n \"int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f}\",\n \"if mode == '': mode = 'None' elif mode == 'Posctl': mode =\",\n \"back left [Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate)\",\n \"print_function import curses import sys from collections import deque from datetime import datetime\",\n \"setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status =\",\n \"self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED,\",\n \"if battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage > 25: color =\",\n \"self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended =\",\n \"frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for k, v in freqs.items()] screen.addstr(row,\",\n \"self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback,\",\n \"local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self,\",\n \"roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f}\",\n \"self.status_battery_perc = None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery\",\n \"'%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 #\",\n \"self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint\",\n \"battery_percentage > 0: color = curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab,\",\n \"pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg\",\n \"satellites = value.value elif value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row,\",\n \"extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if\",\n \"diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status\",\n \"rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status\",\n \"State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended\",\n \"freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for k, v in\",\n \"[msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED elif\",\n \"degrees=True) x, y, z = round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch,\",\n \"'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color =\",\n \"= PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub =\",\n \"curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i\",\n \"self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped,\",\n \"# StatusText from scipy.spatial.transform import Rotation as R from sensor_msgs.msg import BatteryState, Image,\",\n \"durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency): return 0 return frequency class\",\n \"import sys from collections import deque from datetime import datetime import numpy as\",\n \"color = curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row,\",\n \"queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery\",\n \"curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color in colors:\",\n \"0 for c in self.cameras} for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages)\",\n \"self.cols = self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols, 1, 2) #\",\n \"'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent,\",\n \"gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self,\",\n \"screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 # GPS\",\n \"setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str\",\n \"self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget,\",\n \"= DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub =\",\n \"R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z\",\n \"color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)',\",\n \"fl = [int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row,\",\n \"+= 1 # Armed if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else:\",\n \"rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1)\",\n \"= DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint =\",\n \"get_color(color)) row += 1 # Armed if self.state.armed: color = curses.COLOR_RED status_armed =\",\n \"msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if\",\n \"12, 2) self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor\",\n \"BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1: ('No fix',\",\n \"self.lines += 1 screen.refresh() def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) #\",\n \"if battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state = state_msg\",\n \"info satellites = 0 fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if\",\n \"try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen):\",\n \"battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state\",\n \"import Rotation as R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = {\",\n \"scipy.spatial.transform import Rotation as R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT =\",\n \"severity_red: color = curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW elif severity\",\n \"color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed,\",\n \"color = curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED elif severity in\",\n \"x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 # GPS pos latitude =\",\n \"msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red: color\",\n \"'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1\",\n \"= rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback,\",\n \"PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images\",\n \"round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll)\",\n \"if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed\",\n \"deque from datetime import datetime import numpy as np import rospy from diagnostic_msgs.msg\",\n \"{pitch} {yaw} (RPY)') row += 1 # Global pose p = self.global_pose.pose.position q\",\n \"screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row +=\",\n \"msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE]\",\n \"DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText\",\n \"-1) # Default variables self.status_battery_perc = None self.state = State() self.state_sub = rospy.Subscriber('mavros/state',\",\n \"PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics\",\n \"vy, vz = round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row,\",\n \"= rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv',\",\n \"def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def\",\n \"status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row +=\",\n \"= self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if mode ==\",\n \"deque(maxlen=10) for c in self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber\",\n \"= rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix',\",\n \"get_color(color)) row += 1 # Mode color = curses.COLOR_CYAN mode = self.state.mode if\",\n \"= '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1\",\n \"{roll} {pitch} {yaw} (RPY)') row += 1 # Global pose p = self.global_pose.pose.position\",\n \"# Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y,\",\n \"callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose =\",\n \"for value in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites = value.value elif\",\n \"0 # Battery battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage\",\n \"'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10) for c in self.cameras} for\",\n \"= 'None' elif mode == 'Posctl': mode = 'Position' elif mode == 'Rtl':\",\n \"msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color =\",\n \"screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1 # Cameras\",\n \"= statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL,\",\n \"1 / np.mean(durations) if np.isnan(frequency): return 0 return frequency class StatusNode: def __init__(self,\",\n \"= curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize()\",\n \"callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended =\",\n \"self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 **\",\n \"screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 # GPS pos latitude\",\n \"statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral =\",\n \"str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row +=\",\n \"= rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback,\",\n \"{vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1 # Cameras freqs = {c:\",\n \"# Curses color setup curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1) #\",\n \"x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 # GPS info\",\n \"curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color\",\n \"curses.init_pair(color, color, -1) # Default variables self.status_battery_perc = None self.state = State() self.state_sub\",\n \"= [] for i in range(len(messages) - 1): duration = messages[i + 1].header.stamp\",\n \"= f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps)\",\n \"4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def\",\n \"row += 1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air'\",\n \"{c: 0 for c in self.cameras} for cam, messages in self.images.items(): freqs[cam] =\",\n \"x_indent, f'{ff} {fr} {fb} {fl} (front right back left [Hz])') row += 1\",\n \"# Battery battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage >\",\n \"statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING,\",\n \"# Mode color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1]\",\n \"2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ')\",\n \"def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self,\",\n \"{fl} (front right back left [Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self):\",\n \"severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red: color =\",\n \"curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row\",\n \"status def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg\",\n \"callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0':\",\n \"'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 # Extended status if\",\n \"({satellites} sat)', get_color(color)) row += 2 # GPS pos latitude = self.gps.latitude longitude\",\n \"'back', 'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10) for c in self.cameras}\",\n \"['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10) for c\",\n \"== '': mode = 'None' elif mode == 'Posctl': mode = 'Position' elif\",\n \"+= 1 # Setpoint v = self.setpoint.velocity vx, vy, vz = round(v.x, 2),\",\n \"self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub\",\n \"fr, fb, fl = [int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras:\",\n \"1 # Cameras freqs = {c: 0 for c in self.cameras} for cam,\",\n \"buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery =\",\n \"({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen\",\n \"def state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def\",\n \"2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f}\",\n \"= PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps =\",\n \"battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state = state_msg def\",\n \"import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1: ('No\",\n \"satellites = 0 fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key\",\n \"not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def\",\n \"import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg\",\n \"elif severity in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' #\",\n \"GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D\",\n \"'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 #\",\n \"status_armed, get_color(color)) row += 1 # Mode color = curses.COLOR_CYAN mode = self.state.mode\",\n \"2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK\",\n \"curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if\",\n \"x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row +=\",\n \"[] self.images = {c: deque(maxlen=10) for c in self.cameras} for camera in self.cameras:\",\n \"mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode,\",\n \"rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1)\",\n \"[q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx',\",\n \"q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0,\",\n \"round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos:\",\n \"'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row += 1 # Mode color =\",\n \"callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose\",\n \"height_status = 15 self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows\",\n \"durations = [] for i in range(len(messages) - 1): duration = messages[i +\",\n \"Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif\",\n \"frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) #\",\n \"def run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException:\",\n \"Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location\",\n \"') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 # GPS info satellites =\",\n \"def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def\",\n \"gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg):\",\n \"subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self,\",\n \"pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg):\",\n \"14 row = 0 # Battery battery_percentage = int(self.battery.percentage * 100) color =\",\n \"curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab,\",\n \"topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24)\",\n \"datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY,\",\n \"status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed:\",\n \"screen.addstr(row, x_indent, status_gps) row += 1 # Local pose p = self.local_pose.pose.position q\",\n \"int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ)\",\n \"datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg\",\n \"from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState,\",\n \"[] for i in range(len(messages) - 1): duration = messages[i + 1].header.stamp -\",\n \"return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i in range(len(messages) - 1):\",\n \"mode = mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED else: color =\",\n \"StatusText from scipy.spatial.transform import Rotation as R from sensor_msgs.msg import BatteryState, Image, NavSatFix\",\n \"= self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0 x_indent = 14\",\n \"Default variables self.status_battery_perc = None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback,\",\n \"(XYZ) {yaw} (Y)') row += 1 # Cameras freqs = {c: 0 for\",\n \"mode = mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED\",\n \"= 0 x_indent = 14 row = 0 # Battery battery_percentage = int(self.battery.percentage\",\n \"row += 1 # Setpoint v = self.setpoint.velocity vx, vy, vz = round(v.x,\",\n \"curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color in colors: curses.init_pair(color,\",\n \"fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA),\",\n \"image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S')\",\n \"value in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites = value.value elif value.key\",\n \"'Posctl': mode = 'Position' elif mode == 'Rtl': mode = 'Return' status_mode =\",\n \"'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent,\",\n \"for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl =\",\n \"battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED\",\n \"f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 # GPS pos latitude = self.gps.latitude\",\n \"[curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors()\",\n \"Mode color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode\",\n \"round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos:\",\n \"int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)')\",\n \"curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass if __name__ == '__main__':\",\n \"= messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if\",\n \"{altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row += 1\",\n \"[msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red:\",\n \"self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF:\",\n \"# Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y,\",\n \"1): duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 /\",\n \"if severity in severity_red: color = curses.COLOR_RED elif severity in severity_yellow: color =\",\n \"mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import Rotation as R\",\n \"= 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color))\",\n \"def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen\",\n \"(RPY)') row += 1 # Setpoint v = self.setpoint.velocity vx, vy, vz =\",\n \"self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING:\",\n \"= curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row,\",\n \"else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent,\",\n \"for color in colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc = None\",\n \"elif battery_percentage > 0: color = curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row,\",\n \"self.state = state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for\",\n \"{z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Global pose p\",\n \"colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc = None self.state = State()\",\n \"{longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row +=\",\n \"rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1)\",\n \"0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2),\",\n \"queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped()\",\n \"# callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1)\",\n \"= curses.COLOR_BLUE if mode == '': mode = 'None' elif mode == 'Posctl':\",\n \"'Yes' else: color = curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row,\",\n \"= curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif\",\n \"= StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps =\",\n \"color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color))\",\n \"self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10)\",\n \"rospy.loginfo(status) # print(status) x_tab = 0 x_indent = 14 row = 0 #\",\n \"') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right back left [Hz])') row\",\n \"color, -1) # Default variables self.status_battery_perc = None self.state = State() self.state_sub =\",\n \"x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right back left\",\n \"('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D\",\n \"== self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended\",\n \"('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS',\",\n \"log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen = self.status screen.clear() #\",\n \"pos: ') screen.addstr(row, x_indent, status_gps) row += 1 # Local pose p =\",\n \"= curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif\",\n \"messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency): return 0 return frequency\",\n \"np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from\",\n \"self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right',\",\n \"= 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color\",\n \"severity = statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow\",\n \"+= 1 # Cameras freqs = {c: 0 for c in self.cameras} for\",\n \"NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose\",\n \"ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, #\",\n \"frequency_from_messages(messages): durations = [] for i in range(len(messages) - 1): duration = messages[i\",\n \"msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN\",\n \"') screen.addstr(row, x_indent, status_gps) row += 1 # Local pose p = self.local_pose.pose.position\",\n \"get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i in range(len(messages) -\",\n \"i in range(len(messages) - 1): duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec())\",\n \"2 # GPS pos latitude = self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude,\",\n \"self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in\",\n \"in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for k,\",\n \"State # StatusText from scipy.spatial.transform import Rotation as R from sensor_msgs.msg import BatteryState,\",\n \"curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 #\",\n \"screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 # Extended\",\n \"value.value elif value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS\",\n \"callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2 ** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location ==\",\n \"curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return\",\n \"BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) #\",\n \"0, log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen = self.status screen.clear()\",\n \"row += 1 # Mode color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'):\",\n \"self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub\",\n \"self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError:\",\n \"{fr} {fb} {fl} (front right back left [Hz])') row += 1 screen.refresh() self.screen.refresh()\",\n \"right back left [Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self): rate =\",\n \"self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try:\",\n \"#!/usr/bin/env python3 from __future__ import absolute_import, division, print_function import curses import sys from\",\n \"float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages):\",\n \"cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses\",\n \"queue_size=1) # self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, #\",\n \"self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent,\",\n \"= rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback,\",\n \"x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw}\",\n \"curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state\",\n \"= ['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images = {c: deque(maxlen=10) for\",\n \"status_battery, get_color(color)) row += 1 # Armed if self.state.armed: color = curses.COLOR_RED status_armed\",\n \"= 'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color\",\n \"severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log,\",\n \"15 self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows - height_status,\",\n \"elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state ==\",\n \"pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w]\",\n \"int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN\",\n \"self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot =\",\n \"'Satellites visible': satellites = value.value elif value.key == 'Fix type': fix_type, color =\",\n \"screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 # Armed if self.state.armed: color =\",\n \"battery_msg def state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended = extended_msg\",\n \"variables self.status_battery_perc = None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1)\",\n \"= mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE\",\n \"# Setpoint v = self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y, 2),\",\n \"= self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw\",\n \"fb, fl = [int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ')\",\n \"= 14 row = 0 # Battery battery_percentage = int(self.battery.percentage * 100) color\",\n \"rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException:\",\n \"curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations\",\n \"color = curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage >\",\n \"curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage > 0: color\",\n \"self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError:\",\n \"self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab,\",\n \"class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses\",\n \"sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1:\",\n \"self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg): self.local_pose\",\n \"value.key == 'Satellites visible': satellites = value.value elif value.key == 'Fix type': fix_type,\",\n \"from __future__ import absolute_import, division, print_function import curses import sys from collections import\",\n \"Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED),\",\n \"= rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2), round(p.y, 2), round(p.z, 2)\",\n \"rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main():\",\n \"get_color(color)) row += 1 # GPS info satellites = 0 fix_type, color =\",\n \"round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent,\",\n \"= 15 self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows -\",\n \"self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND:\",\n \"{ 0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE),\",\n \"lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN)\",\n \"self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState,\",\n \"from collections import deque from datetime import datetime import numpy as np import\",\n \"= statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral\",\n \"= curses.newwin(height_status, self.cols, 1, 2) # self.console = curses.newwin(self.rows - height_status, self.cols, 12,\",\n \"self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps\",\n \"print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0 x_indent\",\n \"'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)')\",\n \"in severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE self.text\",\n \"duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations)\",\n \"# Curses setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15\",\n \"24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg def\",\n \"'None' elif mode == 'Posctl': mode = 'Position' elif mode == 'Rtl': mode\",\n \"'' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA,\",\n \"row += 2 # GPS pos latitude = self.gps.latitude longitude = self.gps.longitude altitude\",\n \"= self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot\",\n \"status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff'\",\n \"curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for\",\n \"status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground'\",\n \"NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose',\",\n \"self.images = {c: deque(maxlen=10) for c in self.cameras} for camera in self.cameras: topic\",\n \"pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg,\",\n \"= 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color\",\n \"elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state ==\",\n \"= curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif\",\n \"= curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text}\",\n \"pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent,\",\n \"= int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f}\",\n \"except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except\",\n \"rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText,\",\n \"50: color = curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage\",\n \"'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right back left [Hz])')\",\n \"f'{ff} {fr} {fb} {fl} (front right back left [Hz])') row += 1 screen.refresh()\",\n \"import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import Rotation as R from\",\n \"get_color(color)) row += 1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended =\",\n \"= GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites =\",\n \"freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right\",\n \"x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw}\",\n \"range(len(messages) - 1): duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency =\",\n \"1 # Armed if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else: color\",\n \"yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2), round(p.y,\",\n \"= None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery =\",\n \"battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage > 50: color\",\n \"x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 #\",\n \"pitch, roll = rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2), round(p.y, 2),\",\n \"= BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub =\",\n \"= datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity\",\n \"== 'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab, 'Mode: ') screen.addstr(row,\",\n \"1 # Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x,\",\n \"self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1\",\n \"('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float',\",\n \"0 x_indent = 14 row = 0 # Battery battery_percentage = int(self.battery.percentage *\",\n \"[int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff}\",\n \"battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self, state_msg): self.state =\",\n \"PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left']\",\n \"mode = 'Position' elif mode == 'Rtl': mode = 'Return' status_mode = '{}'.format(mode)\",\n \"import datetime import numpy as np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus\",\n \"def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i in range(len(messages)\",\n \"self.cols, 1, 2) # self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines\",\n \"q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion)\",\n \"'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)')\",\n \"for c in self.cameras} for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff,\",\n \"2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global\",\n \"in self.cameras} for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb,\",\n \"ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() # self.statustext_sub\",\n \"curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass\",\n \"pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent,\",\n \"PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus()\",\n \"= curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED elif severity in severity_yellow:\",\n \"= curses.COLOR_GREEN status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color))\",\n \"run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak()\",\n \"collections import deque from datetime import datetime import numpy as np import rospy\",\n \"') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw} (Y)') row += 1 #\",\n \"2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ')\",\n \"# self.statustext = StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1)\",\n \"Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z,\",\n \"frequency = 1 / np.mean(durations) if np.isnan(frequency): return 0 return frequency class StatusNode:\",\n \"import numpy as np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg\",\n \"if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard': color\",\n \"color = curses.COLOR_RED else: color = curses.COLOR_BLUE if mode == '': mode =\",\n \"== self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended\",\n \"def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def\",\n \"+ 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency): return\",\n \"self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint\",\n \"x_indent, status_armed, get_color(color)) row += 1 # Mode color = curses.COLOR_CYAN mode =\",\n \"color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN\",\n \"0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE,\",\n \"1, 2) # self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines =\",\n \"np.mean(durations) if np.isnan(frequency): return 0 return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node',\",\n \"int(roll) screen.addstr(row, x_tab, 'Global pos: ') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll}\",\n \"colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color\",\n \"1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency): return 0\",\n \"c in self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic,\",\n \"state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status in\",\n \"= R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True) x, y,\",\n \"rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def\",\n \"DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras\",\n \"self.cameras} for cam, messages in self.images.items(): freqs[cam] = frequency_from_messages(messages) ff, fr, fb, fl\",\n \"rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1)\",\n \"return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0)\",\n \"get_color(color)) row += 2 # GPS pos latitude = self.gps.latitude longitude = self.gps.longitude\",\n \"roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local pos: ') screen.addstr(row, x_indent, f'{x:.2f}\",\n \"= round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint:\",\n \"while not rospy.is_shutdown(): self.print_status() rate.sleep() except rospy.ROSInterruptException: curses.nocbreak() self.screen.keypad(False) curses.echo() def curses_main(screen): StatusNode(screen).run()\",\n \"curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols, 1,\",\n \"extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS'\",\n \"1 # Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x,\",\n \"from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS', curses.COLOR_RED),\",\n \"- 1): duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1\",\n \"{yaw} (RPY)') row += 1 # Setpoint v = self.setpoint.velocity vx, vy, vz\",\n \"value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ')\",\n \"status_extended, get_color(color)) row += 1 # GPS info satellites = 0 fix_type, color\",\n \"vz = round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab,\",\n \"image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d\",\n \"screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row += 1\",\n \"numpy as np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import\",\n \"2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row,\",\n \"None self.state = State() self.state_sub = rospy.Subscriber('mavros/state', State, callback=self.state_callback, queue_size=1) self.battery = BatteryState()\",\n \"import curses import sys from collections import deque from datetime import datetime import\",\n \"'': mode = 'None' elif mode == 'Posctl': mode = 'Position' elif mode\",\n \"def curses_main(screen): StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass if __name__ ==\",\n \"DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget()\",\n \"** 24) self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg\",\n \"+= 1 # Mode color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode\",\n \"if 'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps = gps_msg\",\n \"= ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText() #\",\n \"setup curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc\",\n \"self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps\",\n \"status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined'\",\n \"round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ')\",\n \"vx, vy, vz = round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw))\",\n \"status_extended = 'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed'\",\n \"self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState,\",\n \"# time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity = statustext_msg.severity msg = statustext_msg\",\n \"row += 1 # Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion\",\n \"1 # Mode color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode =\",\n \"statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time)\",\n \"1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color =\",\n \"== self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended\",\n \"screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self): screen = self.status\",\n \"= pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint =\",\n \"severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE self.text =\",\n \"screen): rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr()\",\n \"mode == '': mode = 'None' elif mode == 'Posctl': mode = 'Position'\",\n \"callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext\",\n \"{pitch} {yaw} (RPY)') row += 1 # Setpoint v = self.setpoint.velocity vx, vy,\",\n \"curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1)\",\n \"datetime import numpy as np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from\",\n \"2) self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors\",\n \"screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 # Extended status if self.extended.landed_state ==\",\n \"self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub\",\n \"= curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines = 0 self.text = ''\",\n \"') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 # Extended status if self.extended.landed_state\",\n \"default=1.0) # Curses setup self.screen = curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status =\",\n \"(XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Global pose p =\",\n \"y, z = round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll =\",\n \"from scipy.spatial.transform import Rotation as R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT\",\n \"datetime import datetime import numpy as np import rospy from diagnostic_msgs.msg import DiagnosticArray,\",\n \"== 'Posctl': mode = 'Position' elif mode == 'Rtl': mode = 'Return' status_mode\",\n \"'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 # GPS info satellites\",\n \"def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status:\",\n \"= GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color))\",\n \"= [msg.INFO, msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED\",\n \"except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx',\",\n \"ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch, roll = rot.as_euler('zyx', degrees=True)\",\n \"in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0,\",\n \"in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1, buff_size=2\",\n \"self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED:\",\n \"def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps =\",\n \"status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row, x_tab, 'GPS pos: ') screen.addstr(row, x_indent,\",\n \"x_tab, 'GPS pos: ') screen.addstr(row, x_indent, status_gps) row += 1 # Local pose\",\n \"+= 1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown():\",\n \"setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen\",\n \"= curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1\",\n \"x_indent, status_mode, get_color(color)) row += 1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR:\",\n \"queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext =\",\n \"R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No GPS',\",\n \"self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN,\",\n \"# GPS pos latitude = self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2)\",\n \"self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors =\",\n \"self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped,\",\n \"severity in severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE\",\n \"color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended, get_color(color)) row +=\",\n \"= curses.COLOR_WHITE self.text = f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines\",\n \"= curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral:\",\n \"import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State\",\n \"round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f}\",\n \"curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage > 25: color\",\n \"fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = [] for\",\n \"2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row, x_tab, 'Local\",\n \"Curses color setup curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1) # Default\",\n \"5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color)\",\n \"PositionTarget, State # StatusText from scipy.spatial.transform import Rotation as R from sensor_msgs.msg import\",\n \"import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from scipy.spatial.transform import\",\n \"Battery battery_percentage = int(self.battery.percentage * 100) color = curses.COLOR_CYAN if battery_percentage > 50:\",\n \"= { 0: ('No GPS', curses.COLOR_RED), 1: ('No fix', curses.COLOR_RED), 2: ('2D lock',\",\n \"curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED elif self.extended.landed_state\",\n \"self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw =\",\n \"('RTK fix', curses.COLOR_GREEN) } def get_color(color): return curses.color_pair(color) def frequency_from_messages(messages): durations = []\",\n \"self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while not rospy.is_shutdown(): self.print_status() rate.sleep() except\",\n \"self.image_subscribers.append(subscriber) def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self,\",\n \"curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color in colors: curses.init_pair(color, color,\",\n \"= rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback, queue_size=1) self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback,\",\n \"curses.use_default_colors() for color in colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc =\",\n \"= curses.COLOR_RED else: color = curses.COLOR_BLUE if mode == '': mode = 'None'\",\n \"elif severity in severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral: color =\",\n \"screen.refresh() def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab =\",\n \"curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup curses.use_default_colors() for color in\",\n \"Local pose p = self.local_pose.pose.position q = self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z,\",\n \"color = curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed = 'No'\",\n \"mode.capitalize() if mode == 'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE if\",\n \"'Position' elif mode == 'Rtl': mode = 'Return' status_mode = '{}'.format(mode) screen.addstr(row, x_tab,\",\n \"') screen.addstr(row, x_indent, f'{x:.2f} {y:.2f} {z:.2f} (XYZ) {roll} {pitch} {yaw} (RPY)') row +=\",\n \"curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) }\",\n \"x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row += 1 # Armed if\",\n \"pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w]\",\n \"x_tab = 0 x_indent = 14 row = 0 # Battery battery_percentage =\",\n \"= 0 fix_type, color = GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key ==\",\n \"= frequency_from_messages(messages) ff, fr, fb, fl = [int(round(v)) for k, v in freqs.items()]\",\n \"print(status) x_tab = 0 x_indent = 14 row = 0 # Battery battery_percentage\",\n \"screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text =\",\n \"x_tab, 'Mode: ') screen.addstr(row, x_indent, status_mode, get_color(color)) row += 1 # Extended status\",\n \"callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics =\",\n \"StatusText() # self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix()\",\n \"diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status def\",\n \"color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color = curses.COLOR_GREEN\",\n \"('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6: ('RTK fix', curses.COLOR_GREEN) } def get_color(color):\",\n \"callback=self.diagnostics_callback, queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras =\",\n \"color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color = curses.COLOR_RED\",\n \"[Hz])') row += 1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while\",\n \"for status in diagnostics_msg.status: if 'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self,\",\n \"queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub = rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray()\",\n \"- height_status, self.cols, 12, 2) self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False)\",\n \"> 25: color = curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED status_battery\",\n \"screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl} (front right back\",\n \"q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion)\",\n \"status_armed = 'No' screen.addstr(row, x_tab, 'Armed: ') screen.addstr(row, x_indent, status_armed, get_color(color)) row +=\",\n \"for i in range(len(messages) - 1): duration = messages[i + 1].header.stamp - messages[i].header.stamp\",\n \"color = curses.COLOR_YELLOW elif severity in severity_neutral: color = curses.COLOR_WHITE self.text = f'{time_str}:\",\n \"= [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError: rot =\",\n \"# Armed if self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else: color =\",\n \"status_mode, get_color(color)) row += 1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended\",\n \"= battery_msg def state_callback(self, state_msg): self.state = state_msg def extended_callback(self, extended_msg): self.extended =\",\n \"screen = self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0 x_indent =\",\n \"'Air' color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_LANDING: status_extended = 'Landed' color =\",\n \"def statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str =\",\n \"self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f}\",\n \"row += 1 # Cameras freqs = {c: 0 for c in self.cameras}\",\n \"= [int(round(v)) for k, v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent,\",\n \"self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state', ExtendedState, callback=self.extended_callback, queue_size=1) # self.statustext = StatusText()\",\n \"= curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent,\",\n \"self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity\",\n \"= curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage > 25:\",\n \"in range(len(messages) - 1): duration = messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency\",\n \"severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO,\",\n \"color = curses.COLOR_RED elif self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN\",\n \"= curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW elif battery_percentage > 0:\",\n \"0: color = curses.COLOR_RED status_battery = str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ')\",\n \"info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites} sat)', get_color(color)) row += 2 # GPS\",\n \"q.w] try: rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0])\",\n \"= int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ') screen.addstr(row, x_indent, f'{vx:.2f} {vy:.2f} {vz:.2f} (XYZ) {yaw}\",\n \"'GPS' in status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps = gps_msg def\",\n \"gps_msg def local_pose_callback(self, pose_msg): self.local_pose = pose_msg def global_pose_callback(self, pose_msg): self.global_pose = pose_msg\",\n \"{c: deque(maxlen=10) for c in self.cameras} for camera in self.cameras: topic = f'camera_{camera}/image_raw'\",\n \"in colors: curses.init_pair(color, color, -1) # Default variables self.status_battery_perc = None self.state =\",\n \"= f'{time_str}: {text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh()\",\n \"argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr() self.rows, self.cols\",\n \"status.name: self.diagnostic_gps = status def gps_callback(self, gps_msg): self.gps = gps_msg def local_pose_callback(self, pose_msg):\",\n \"= state_msg def extended_callback(self, extended_msg): self.extended = extended_msg def diagnostics_callback(self, diagnostics_msg): for status\",\n \"BatteryState() self.battery_sub = rospy.Subscriber('mavros/battery', BatteryState, callback=self.battery_callback, queue_size=1) self.extended = ExtendedState() self.extended_sub = rospy.Subscriber('mavros/extended_state',\",\n \"camera): self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') #\",\n \"= str(battery_percentage) + '%' screen.addstr(row, x_tab, 'Battery: ') screen.addstr(row, x_indent, status_battery, get_color(color)) row\",\n \"q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0,\",\n \"else: color = curses.COLOR_BLUE if mode == '': mode = 'None' elif mode\",\n \"row += 1 screen.refresh() self.screen.refresh() def run(self): rate = rospy.Rate(self.rate) try: while not\",\n \"curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW elif severity in severity_neutral: color\",\n \"# rospy.loginfo(status) # print(status) x_tab = 0 x_indent = 14 row = 0\",\n \"as R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0: ('No\",\n \"= rospy.Subscriber('global_position/pose', PoseStamped, callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub =\",\n \"StatusNode(screen).run() def main(): try: curses.wrapper(curses_main) except rospy.ROSInterruptException: pass if __name__ == '__main__': main()\",\n \"'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE if mode == '': mode\",\n \"Rotation as R from sensor_msgs.msg import BatteryState, Image, NavSatFix GPS_FIX_DICT = { 0:\",\n \"callback=self.global_pose_callback, queue_size=1) self.diagnostics = DiagnosticArray() self.diagnostic_gps = DiagnosticStatus() self.diagnostics_sub = rospy.Subscriber('/diagnostics', DiagnosticArray, callback=self.diagnostics_callback,\",\n \"# print(status) x_tab = 0 x_indent = 14 row = 0 # Battery\",\n \"color = curses.COLOR_CYAN mode = self.state.mode if mode.startswith('AUTO'): mode = mode.split('.')[-1] mode =\",\n \"division, print_function import curses import sys from collections import deque from datetime import\",\n \"self.extended.landed_state == self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ')\",\n \"self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines = 0 self.text =\",\n \"curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state\",\n \"status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row, x_indent, status_extended,\",\n \"+= 1 # Extended status if self.extended.landed_state == self.extended.LANDED_STATE_IN_AIR: status_extended = 'Air' color\",\n \"freqs = {c: 0 for c in self.cameras} for cam, messages in self.images.items():\",\n \"curses.COLOR_RED else: color = curses.COLOR_BLUE if mode == '': mode = 'None' elif\",\n \"GPS_FIX_DICT[0] for value in self.diagnostic_gps.values: if value.key == 'Satellites visible': satellites = value.value\",\n \"= '' self.screen.keypad(True) curses.curs_set(False) # Hide cursor colors = [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN,\",\n \"curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4: ('DGPS', curses.COLOR_MAGENTA), 5: ('RTK float', curses.COLOR_YELLOW), 6:\",\n \"{yaw} (RPY)') row += 1 # Global pose p = self.global_pose.pose.position q =\",\n \"as np import rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped\",\n \"self.cols, 12, 2) self.lines = 0 self.text = '' self.screen.keypad(True) curses.curs_set(False) # Hide\",\n \"v in freqs.items()] screen.addstr(row, x_tab, 'Cameras: ') screen.addstr(row, x_indent, f'{ff} {fr} {fb} {fl}\",\n \"self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub =\",\n \"self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols, 1, 2) # self.console =\",\n \"z = round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll = int(yaw),\",\n \"visible': satellites = value.value elif value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)]\",\n \"= self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f} {altitude:.2f} (LLA)' screen.addstr(row,\",\n \"= pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self, image_msg, camera): self.images[camera].append(image_msg)\",\n \"StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub = rospy.Subscriber('mavros/global_position/raw/fix', NavSatFix, callback=self.gps_callback,\",\n \"self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers\",\n \"queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers = [] self.images = {c:\",\n \"= self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except\",\n \"screen.addstr(row, x_indent, status_extended, get_color(color)) row += 1 # GPS info satellites = 0\",\n \"= extended_msg def diagnostics_callback(self, diagnostics_msg): for status in diagnostics_msg.status: if 'GPS' in status.name:\",\n \"= [curses.COLOR_BLACK, curses.COLOR_BLUE, curses.COLOR_CYAN, curses.COLOR_GREEN, curses.COLOR_MAGENTA, curses.COLOR_RED, curses.COLOR_WHITE, curses.COLOR_YELLOW] # Curses color setup\",\n \"curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED status_battery = str(battery_percentage) + '%'\",\n \"self.images[camera].append(image_msg) def statustext_callback(self, statustext_msg): screen = self.console time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str\",\n \"[msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow = [msg.WARNING, msg.NOTICE] severity_neutral = [msg.INFO, msg.DEBUG] color\",\n \"1: ('No fix', curses.COLOR_RED), 2: ('2D lock', curses.COLOR_BLUE), 3: ('3D lock', curses.COLOR_BLUE), 4:\",\n \"= curses.initscr() self.rows, self.cols = self.screen.getmaxyx() height_status = 15 self.status = curses.newwin(height_status, self.cols,\",\n \"global_pose_callback(self, pose_msg): self.global_pose = pose_msg def setpoint_callback(self, setpoint_msg): self.setpoint = setpoint_msg def image_callback(self,\",\n \"> 50: color = curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW elif\",\n \"+= 1 screen.refresh() def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) # print(status)\",\n \"rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2), round(p.y, 2), round(p.z, 2) yaw,\",\n \"= value.value elif value.key == 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab,\",\n \"(RPY)') row += 1 # Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation\",\n \"== 'Fix type': fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row,\",\n \"camera in self.cameras: topic = f'camera_{camera}/image_raw' subscriber = rospy.Subscriber(topic, Image, callback=self.image_callback, callback_args=camera, queue_size=1,\",\n \"= self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f} {longitude:.7f}\",\n \"2) # self.console = curses.newwin(self.rows - height_status, self.cols, 12, 2) self.lines = 0\",\n \"2), round(p.y, 2), round(p.z, 2) yaw, pitch, roll = int(yaw), int(pitch), int(roll) screen.addstr(row,\",\n \"+= 2 # GPS pos latitude = self.gps.latitude longitude = self.gps.longitude altitude =\",\n \"curses import sys from collections import deque from datetime import datetime import numpy\",\n \"in severity_red: color = curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW elif\",\n \"time_str = datetime.now().strftime('%Y-%m-%d %H:%M:%S') # time_str = datetime.datetime.fromtimestamp(unix_time) text = statustext_msg.text severity =\",\n \"{text} ({color})' # screen.addstr(self.lines, 0, log, get_color(color)) self.lines += 1 screen.refresh() def print_status(self):\",\n \"self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0 x_indent = 14 row\",\n \"mode == 'Offboard': color = curses.COLOR_RED else: color = curses.COLOR_BLUE if mode ==\",\n \"quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except ValueError: rot\",\n \"queue_size=1) self.setpoint = PositionTarget() self.setpoint_sub = rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front',\",\n \"curses.COLOR_BLUE if mode == '': mode = 'None' elif mode == 'Posctl': mode\",\n \"+= 1 # Global pose p = self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion =\",\n \"1 # Setpoint v = self.setpoint.velocity vx, vy, vz = round(v.x, 2), round(v.y,\",\n \"if np.isnan(frequency): return 0 return frequency class StatusNode: def __init__(self, screen): rospy.init_node('status_node', argv=sys.argv)\",\n \"self.local_pose = PoseStamped() self.local_pose_sub = rospy.Subscriber('mavros/local_position/pose', PoseStamped, callback=self.local_pose_callback, queue_size=1) self.global_pose = PoseStamped() self.global_pose_sub\",\n \"def battery_callback(self, battery_msg): if battery_msg.location == 'id0': self.battery = battery_msg def state_callback(self, state_msg):\",\n \"round(v.x, 2), round(v.y, 2), round(v.z, 2) yaw = int(np.rad2deg(self.setpoint.yaw)) screen.addstr(row, x_tab, 'Setpoint: ')\",\n \"* 100) color = curses.COLOR_CYAN if battery_percentage > 50: color = curses.COLOR_GREEN elif\",\n \"mode.startswith('AUTO'): mode = mode.split('.')[-1] mode = mode.capitalize() if mode == 'Offboard': color =\",\n \"== self.extended.LANDED_STATE_UNDEFINED: status_extended = 'Undefined' color = curses.COLOR_CYAN screen.addstr(row, x_tab, 'State: ') screen.addstr(row,\",\n \"# self.statustext_sub = rospy.Subscriber('mavros/statustext/recv', StatusText, # callback=self.statustext_callback, # queue_size=1) self.gps = NavSatFix() self.gps_sub\",\n \"25: color = curses.COLOR_YELLOW elif battery_percentage > 0: color = curses.COLOR_RED status_battery =\",\n \"battery_percentage > 50: color = curses.COLOR_GREEN elif battery_percentage > 25: color = curses.COLOR_YELLOW\",\n \"rospy from diagnostic_msgs.msg import DiagnosticArray, DiagnosticStatus from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import\",\n \"statustext_msg.text severity = statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR]\",\n \"== self.extended.LANDED_STATE_ON_GROUND: status_extended = 'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended\",\n \"rospy.init_node('status_node', argv=sys.argv) self.rate = rospy.get_param('~rate', default=1.0) # Curses setup self.screen = curses.initscr() self.rows,\",\n \"= statustext_msg.severity msg = statustext_msg severity_red = [msg.EMERGENCY, msg.ALERT, msg.CRITICAL, msg.ERROR] severity_yellow =\",\n \"def print_status(self): screen = self.status screen.clear() # rospy.loginfo(status) # print(status) x_tab = 0\",\n \"severity in severity_red: color = curses.COLOR_RED elif severity in severity_yellow: color = curses.COLOR_YELLOW\",\n \"fix_type, color = GPS_FIX_DICT[int(value.value)] screen.addstr(row, x_tab, 'GPS info: ') screen.addstr(row, x_indent, f'{fix_type} ({satellites}\",\n \"from geometry_msgs.msg import PoseStamped from mavros_msgs.msg import ExtendedState, PositionTarget, State # StatusText from\",\n \"curses.color_pair(color) def frequency_from_messages(messages): durations = [] for i in range(len(messages) - 1): duration\",\n \"self.state.armed: color = curses.COLOR_RED status_armed = 'Yes' else: color = curses.COLOR_GREEN status_armed =\",\n \"messages[i + 1].header.stamp - messages[i].header.stamp durations.append(duration.to_sec()) frequency = 1 / np.mean(durations) if np.isnan(frequency):\",\n \"rospy.Subscriber('mavros/setpoint_raw/local', PositionTarget, callback=self.setpoint_callback, queue_size=1) self.cameras = ['front', 'right', 'back', 'left'] self.image_subscribers = []\",\n \"'Ground' color = curses.COLOR_GREEN elif self.extended.landed_state == self.extended.LANDED_STATE_TAKEOFF: status_extended = 'Takeoff' color =\",\n \"roll = rot.as_euler('zyx', degrees=True) x, y, z = round(p.x, 2), round(p.y, 2), round(p.z,\",\n \"= self.local_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot = R.from_quat(quaternion) except\",\n \"= self.global_pose.pose.position q = self.global_pose.pose.orientation quaternion = [q.x, q.y, q.z, q.w] try: rot\",\n \"msg.DEBUG] color = curses.COLOR_CYAN if severity in severity_red: color = curses.COLOR_RED elif severity\",\n \"rot = R.from_quat(quaternion) except ValueError: rot = R.from_euler('zyx', [0.0, 0.0, 0.0]) yaw, pitch,\"\n]","isConversational":false}}},{"rowIdx":1499,"cells":{"ngram":{"kind":"list like","value":["instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format litle,","remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and","Args: path (Path): path to the desired result file param_str (str): string containing","None and max_ > max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\"tight\") plt.close() def","the desired result file param_str (str): string containing the parameters used in the","have same length') fig = plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize defaults","widths=0.6) set_box_format(bp, '000') # set and format litle, labels, and ticks ax.set_title(title, fontweight='bold',","(Path and description) plot_dir: ath to the desired result folder to store the","not None or max_ is not None: min_original, max_original = ax.get_ylim() min_ =","str, x_label: str, y_label: str, x_ticks: tuple, min_: float = None, max_: float","color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.')","if __name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \"mia-result\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\"), \"no pp\")) results.append(ResultParam(Path(Path.cwd()","max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\"tight\") plt.close() def format_data(data, label: str, metric: str): return","methods (e.g. load different CSVs) dfs = [] methods = [] for res","bbox_inches=\"tight\") plt.close() def format_data(data, label: str, metric: str): return data[data['LABEL'] == label][metric].values def","fig = plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize defaults to (width, height)","import argparse import os import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas","18, 'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2)","and max if provided if min_ is not None or max_ is not","import matplotlib.pyplot as plt import pandas as pd from pathlib import Path class",") if __name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \"mia-result\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\"), \"no pp\"))","== '__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \"mia-result\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\"), \"no pp\")) results.append(ResultParam(Path(Path.cwd() /\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\"), \"with","of the Result Parameter Args: path (Path): path to the desired result file","axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format","not None: min_original, max_original = ax.get_ylim() min_ = min_ if min_ is not","if provided if min_ is not None or max_ is not None: min_original,","\"\"\"Result Parameter\"\"\" def __init__(self, path: Path, param_str: str): \"\"\"Initializes a new instance of","defaults to (width, height) =(6.4, 4.8), # for boxplots, we want the ratio","('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are interested in # load the","tuples of y-axis limits (min, max) for each metric. Use None if unknown","Args: results ([ResultParam]): a list of result parameters (Path and description) plot_dir: ath","ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken","load two CSV (for simplicity, it is the same here) # todo: adapt","to have same length') fig = plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize","ratio to be inversed ax = fig.add_subplot(111) # create an axes instance (nrows=ncols=index)","information about the paramter # some parameters to improve the plot's readability title","CSVs) dfs = [] methods = [] for res in results: dfs.append(pd.read_csv(res.path, sep=';'))","plot the information about the paramter # some parameters to improve the plot's","all labels Args: results ([ResultParam]): a list of result parameters (Path and description)","path self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color)","max_) plt.savefig(file_path, bbox_inches=\"tight\") plt.close() def format_data(data, label: str, metric: str): return data[data['LABEL'] ==","read parameter values from text file, use them to plot the information about","# create an axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') #","self.path = path self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color)","min_ < min_original else min_original max_ = max_ if max_ is not None","ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max if provided if min_ is not","unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \"\"\"generates box plots comparing two or more","fontweight='bold', fontsize=9.5) # we don't use the x-label since it should be clear","don't use the x-label since it should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12)","different methods (e.g. a set of different features), therefore, # we load two","'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) #","data: list, title: str, x_label: str, y_label: str, x_ticks: tuple, min_: float =","fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use the x-label since","<filename>bin/boxplot_param.py import argparse import os import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import","path (Path): path to the desired result file param_str (str): string containing the","text file, use them to plot the information about the paramter # some","# todo: read parameter values from text file, use them to plot the","in # load the CSVs. We usually want to compare different methods (e.g.","'{}' for label in labels: for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir,","as pd from pathlib import Path class ResultParam(): \"\"\"Result Parameter\"\"\" def __init__(self, path:","param_str: str): \"\"\"Initializes a new instance of the Result Parameter Args: path (Path):","length') fig = plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize defaults to (width,","set of different features), therefore, # we load two CSV (for simplicity, it","Path class ResultParam(): \"\"\"Result Parameter\"\"\" def __init__(self, path: Path, param_str: str): \"\"\"Initializes a","in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df in dfs],","labels Args: results ([ResultParam]): a list of result parameters (Path and description) plot_dir:","= ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are interested in # load","= ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format litle, labels, and ticks","is the same here) # todo: adapt to your needs to compare different","we load two CSV (for simplicity, it is the same here) # todo:","'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are interested in # load the CSVs.","'000') # set and format litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label,","to plot the information about the paramter # some parameters to improve the","box plots comparing two or more result sets for all labels Args: results","else: raise ValueError('Metric \"{}\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \"\"\"generates box plots","metric: str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if metric == 'DICE':","for each metric. Use None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the","linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list, title:","# set and format litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold',","# tuples of y-axis limits (min, max) for each metric. Use None if","is not None: min_original, max_original = ax.get_ylim() min_ = min_ if min_ is","each metric. Use None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain","from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove frame","set and format litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18)","adjust min and max if provided if min_ is not None or max_","str): if metric == 'DICE': return 'Dice coefficient' elif metric == 'HDRFDST': return","in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter values from text file,","labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are interested in #","or max_ is not None: min_original, max_original = ax.get_ylim() min_ = min_ if","float = None, max_: float = None): if len(data) != len(x_ticks): raise ValueError('arguments","min_, max_ ) if __name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \"mia-result\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\"),","[ResultParam], plot_dir: Path): \"\"\"generates box plots comparing two or more result sets for","ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\"tight\") plt.close() def format_data(data, label: str, metric: str): return data[data['LABEL']","for all labels Args: results ([ResultParam]): a list of result parameters (Path and","ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use the x-label since it should be","interested in # load the CSVs. We usually want to compare different methods","values from text file, use them to plot the information about the paramter","ax = fig.add_subplot(111) # create an axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6)","the ratio to be inversed ax = fig.add_subplot(111) # create an axes instance","the results for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) # tuples of y-axis","in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ ) if __name__ == '__main__':","# ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use the x-label since it should","fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame","boxplot(file_path: str, data: list, title: str, x_label: str, y_label: str, x_ticks: tuple, min_:","result file param_str (str): string containing the parameters used in the postprocessing \"\"\"","as plt import pandas as pd from pathlib import Path class ResultParam(): \"\"\"Result","x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False)","# we don't use the x-label since it should be clear from the","max_ if max_ is not None and max_ > max_original else max_original ax.set_ylim(min_,","\"\"\"Initializes a new instance of the Result Parameter Args: path (Path): path to","different features), therefore, # we load two CSV (for simplicity, it is the","!= len(x_ticks): raise ValueError('arguments data and x_ticks need to have same length') fig","os import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas as pd from","dfs = [] methods = [] for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str)","ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use the x-label","matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas as pd from pathlib import Path","from text file, use them to plot the information about the paramter #","for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric)","features), therefore, # we load two CSV (for simplicity, it is the same","rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust","(str): string containing the parameters used in the postprocessing \"\"\" self.path = path","# the metrics we want to plot the results for metrics_yaxis_limits = ((0.0,","raise ValueError('Metric \"{}\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \"\"\"generates box plots comparing","the Result Parameter Args: path (Path): path to the desired result file param_str","parameters used in the postprocessing \"\"\" self.path = path self.param_str = param_str def","used in the postprocessing \"\"\" self.path = path self.param_str = param_str def set_box_format(bp,","litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold',","list, title: str, x_label: str, y_label: str, x_ticks: tuple, min_: float = None,","metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for","color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black')","if min_ is not None or max_ is not None: min_original, max_original =","max_ is not None and max_ > max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path,","ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format litle, labels, and ticks ax.set_title(title,","file param_str (str): string containing the parameters used in the postprocessing \"\"\" self.path","# load the CSVs. We usually want to compare different methods (e.g. a","set_box_format(bp, '000') # set and format litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20)","adapt to your needs to compare different methods (e.g. load different CSVs) dfs","== 'HDRFDST': return 'Hausdorff distance (mm)' else: raise ValueError('Metric \"{}\" unknown'.format(metric)) def main(results:","the postprocessing \"\"\" self.path = path self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'],","y_label: str, x_ticks: tuple, min_: float = None, max_: float = None): if","to the desired result file param_str (str): string containing the parameters used in","frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max","ResultParam(): \"\"\"Result Parameter\"\"\" def __init__(self, path: Path, param_str: str): \"\"\"Initializes a new instance","< min_original else min_original max_ = max_ if max_ is not None and","plot_dir: Path): \"\"\"generates box plots comparing two or more result sets for all","zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df in dfs], title.format(label),","Use None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you","ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) #","return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if metric == 'DICE': return 'Dice","want to compare different methods (e.g. a set of different features), therefore, #","[format_data(df, label, metric) for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_","desired result folder to store the qq-plots \"\"\" metrics = ('DICE', 'HDRFDST') #","'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2)","the plot's readability title = '{}' for label in labels: for metric, (min_,","and format litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) #","str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if metric == 'DICE': return","metrics we want to plot the results for metrics_yaxis_limits = ((0.0, 1.0), (0.0,","the paramter # some parameters to improve the plot's readability title = '{}'","plt import pandas as pd from pathlib import Path class ResultParam(): \"\"\"Result Parameter\"\"\"","metric. Use None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues","two CSV (for simplicity, it is the same here) # todo: adapt to","main(results: [ResultParam], plot_dir: Path): \"\"\"generates box plots comparing two or more result sets","# figsize defaults to (width, height) =(6.4, 4.8), # for boxplots, we want","5*1.5)) # figsize defaults to (width, height) =(6.4, 4.8), # for boxplots, we","title: str, x_label: str, y_label: str, x_ticks: tuple, min_: float = None, max_:","plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'],","is not None or max_ is not None: min_original, max_original = ax.get_ylim() min_","if min_ is not None and min_ < min_original else min_original max_ =","plot the results for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) # tuples of","fontsize=9.5) # we don't use the x-label since it should be clear from","limits (min, max) for each metric. Use None if unknown labels = ('WhiteMatter','GreyMatter',","'HDRFDST': return 'Hausdorff distance (mm)' else: raise ValueError('Metric \"{}\" unknown'.format(metric)) def main(results: [ResultParam],","results = [] results.append(ResultParam(Path(Path.cwd() / \"mia-result\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\"), \"no pp\")) results.append(ResultParam(Path(Path.cwd() /\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\"), \"with pp\")) main(results,","[] results.append(ResultParam(Path(Path.cwd() / \"mia-result\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\"), \"no pp\")) results.append(ResultParam(Path(Path.cwd() /\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\"), \"with pp\")) main(results, Path(Path.cwd() /","plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str,","needs to compare different methods (e.g. load different CSVs) dfs = [] methods","'{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods,","tuple, min_: float = None, max_: float = None): if len(data) != len(x_ticks):","bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format litle, labels, and","plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list, title: str, x_label: str, y_label: str,","compare different methods (e.g. a set of different features), therefore, # we load","figsize=( 2 *1.5, 5*1.5)) # figsize defaults to (width, height) =(6.4, 4.8), #","'Method', metric_to_readable_text(metric), methods, min_, max_ ) if __name__ == '__main__': results = []","linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path:","None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are","((0.0, 1.0), (0.0, 18)) # tuples of y-axis limits (min, max) for each","metric)), [format_data(df, label, metric) for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_,","we don't use the x-label since it should be clear from the x-ticks","= path self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'],","float = None): if len(data) != len(x_ticks): raise ValueError('arguments data and x_ticks need","the desired result folder to store the qq-plots \"\"\" metrics = ('DICE', 'HDRFDST')","pd from pathlib import Path class ResultParam(): \"\"\"Result Parameter\"\"\" def __init__(self, path: Path,","metric == 'DICE': return 'Dice coefficient' elif metric == 'HDRFDST': return 'Hausdorff distance","x_label: str, y_label: str, x_ticks: tuple, min_: float = None, max_: float =","boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric),","= None): if len(data) != len(x_ticks): raise ValueError('arguments data and x_ticks need to","plot_dir: ath to the desired result folder to store the qq-plots \"\"\" metrics","a new instance of the Result Parameter Args: path (Path): path to the","y-axis limits (min, max) for each metric. Use None if unknown labels =","todo: adapt to your needs to compare different methods (e.g. load different CSVs)","in the postprocessing \"\"\" self.path = path self.param_str = param_str def set_box_format(bp, color):","more result sets for all labels Args: results ([ResultParam]): a list of result","ValueError('Metric \"{}\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \"\"\"generates box plots comparing two","path: Path, param_str: str): \"\"\"Initializes a new instance of the Result Parameter Args:","ath to the desired result folder to store the qq-plots \"\"\" metrics =","(width, height) =(6.4, 4.8), # for boxplots, we want the ratio to be","min and max if provided if min_ is not None or max_ is","plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list,","todo: read parameter values from text file, use them to plot the information","= max_ if max_ is not None and max_ > max_original else max_original","if metric == 'DICE': return 'Dice coefficient' elif metric == 'HDRFDST': return 'Hausdorff","to improve the plot's readability title = '{}' for label in labels: for","and max_ > max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\"tight\") plt.close() def format_data(data,","max_ > max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\"tight\") plt.close() def format_data(data, label:","the information about the paramter # some parameters to improve the plot's readability","results.append(ResultParam(Path(Path.cwd() / \"mia-result\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\"), \"no pp\")) results.append(ResultParam(Path(Path.cwd() /\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\"), \"with pp\")) main(results, Path(Path.cwd() / 'mia-result/plot_results'))","'__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \"mia-result\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\"), \"no pp\")) results.append(ResultParam(Path(Path.cwd() /\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\"), \"with pp\"))","plt.close() def format_data(data, label: str, metric: str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric:","format litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label,","and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) #","qq-plots \"\"\" metrics = ('DICE', 'HDRFDST') # the metrics we want to plot","min_ = min_ if min_ is not None and min_ < min_original else","df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ ) if __name__ ==","height) =(6.4, 4.8), # for boxplots, we want the ratio to be inversed","if len(data) != len(x_ticks): raise ValueError('arguments data and x_ticks need to have same","comparing two or more result sets for all labels Args: results ([ResultParam]): a","CSV (for simplicity, it is the same here) # todo: adapt to your","if max_ is not None and max_ > max_original else max_original ax.set_ylim(min_, max_)","__name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \"mia-result\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\"), \"no pp\")) results.append(ResultParam(Path(Path.cwd() /\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\"),","str, y_label: str, x_ticks: tuple, min_: float = None, max_: float = None):","inversed ax = fig.add_subplot(111) # create an axes instance (nrows=ncols=index) bp = ax.boxplot(data,","or more result sets for all labels Args: results ([ResultParam]): a list of","to plot the results for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) # tuples","plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'],","None): if len(data) != len(x_ticks): raise ValueError('arguments data and x_ticks need to have","return 'Dice coefficient' elif metric == 'HDRFDST': return 'Hausdorff distance (mm)' else: raise","'HDRFDST') # the metrics we want to plot the results for metrics_yaxis_limits =","(e.g. load different CSVs) dfs = [] methods = [] for res in","x_ticks: tuple, min_: float = None, max_: float = None): if len(data) !=","import pandas as pd from pathlib import Path class ResultParam(): \"\"\"Result Parameter\"\"\" def","therefore, # we load two CSV (for simplicity, it is the same here)","== label][metric].values def metric_to_readable_text(metric: str): if metric == 'DICE': return 'Dice coefficient' elif","pathlib import Path class ResultParam(): \"\"\"Result Parameter\"\"\" def __init__(self, path: Path, param_str: str):","and min_ < min_original else min_original max_ = max_ if max_ is not","result folder to store the qq-plots \"\"\" metrics = ('DICE', 'HDRFDST') # the","max_ is not None: min_original, max_original = ax.get_ylim() min_ = min_ if min_","= ('DICE', 'HDRFDST') # the metrics we want to plot the results for","to compare different methods (e.g. load different CSVs) dfs = [] methods =","for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) # tuples of y-axis limits (min,","metrics = ('DICE', 'HDRFDST') # the metrics we want to plot the results","min_: float = None, max_: float = None): if len(data) != len(x_ticks): raise","to compare different methods (e.g. a set of different features), therefore, # we","None, max_: float = None): if len(data) != len(x_ticks): raise ValueError('arguments data and","brain structures/tissues you are interested in # load the CSVs. We usually want","import Path class ResultParam(): \"\"\"Result Parameter\"\"\" def __init__(self, path: Path, param_str: str): \"\"\"Initializes","sets for all labels Args: results ([ResultParam]): a list of result parameters (Path","fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use the x-label since it","the brain structures/tissues you are interested in # load the CSVs. We usually","you are interested in # load the CSVs. We usually want to compare","max if provided if min_ is not None or max_ is not None:","# the brain structures/tissues you are interested in # load the CSVs. We","metric_to_readable_text(metric: str): if metric == 'DICE': return 'Dice coefficient' elif metric == 'HDRFDST':","# adjust min and max if provided if min_ is not None or","containing the parameters used in the postprocessing \"\"\" self.path = path self.param_str =","> max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\"tight\") plt.close() def format_data(data, label: str,","since it should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight':","a list of result parameters (Path and description) plot_dir: ath to the desired","'Dice coefficient' elif metric == 'HDRFDST': return 'Hausdorff distance (mm)' else: raise ValueError('Metric","elif metric == 'HDRFDST': return 'Hausdorff distance (mm)' else: raise ValueError('Metric \"{}\" unknown'.format(metric))","the metrics we want to plot the results for metrics_yaxis_limits = ((0.0, 1.0),","structures/tissues you are interested in # load the CSVs. We usually want to","fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use the","title = '{}' for label in labels: for metric, (min_, max_) in zip(metrics,","fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use","of different features), therefore, # we load two CSV (for simplicity, it is","to store the qq-plots \"\"\" metrics = ('DICE', 'HDRFDST') # the metrics we","str, x_ticks: tuple, min_: float = None, max_: float = None): if len(data)","the qq-plots \"\"\" metrics = ('DICE', 'HDRFDST') # the metrics we want to","== 'DICE': return 'Dice coefficient' elif metric == 'HDRFDST': return 'Hausdorff distance (mm)'","None or max_ is not None: min_original, max_original = ax.get_ylim() min_ = min_","def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red')","min_ if min_ is not None and min_ < min_original else min_original max_","max_ = max_ if max_ is not None and max_ > max_original else","CSVs. We usually want to compare different methods (e.g. a set of different","readability title = '{}' for label in labels: for metric, (min_, max_) in","Path, param_str: str): \"\"\"Initializes a new instance of the Result Parameter Args: path","data and x_ticks need to have same length') fig = plt.figure( figsize=( 2","min_original, max_original = ax.get_ylim() min_ = min_ if min_ is not None and","__init__(self, path: Path, param_str: str): \"\"\"Initializes a new instance of the Result Parameter","same here) # todo: adapt to your needs to compare different methods (e.g.","= ax.get_ylim() min_ = min_ if min_ is not None and min_ <","metric == 'HDRFDST': return 'Hausdorff distance (mm)' else: raise ValueError('Metric \"{}\" unknown'.format(metric)) def","min_original else min_original max_ = max_ if max_ is not None and max_","ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max if","for label in labels: for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label,","methods, min_, max_ ) if __name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd() /","fig.add_subplot(111) # create an axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000')","label, metric) for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ )","param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'],","(for simplicity, it is the same here) # todo: adapt to your needs","plt.savefig(file_path, bbox_inches=\"tight\") plt.close() def format_data(data, label: str, metric: str): return data[data['LABEL'] == label][metric].values","to be inversed ax = fig.add_subplot(111) # create an axes instance (nrows=ncols=index) bp","\"\"\" metrics = ('DICE', 'HDRFDST') # the metrics we want to plot the","metric) for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ ) if","to the desired result folder to store the qq-plots \"\"\" metrics = ('DICE',","We usually want to compare different methods (e.g. a set of different features),","results for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) # tuples of y-axis limits","boxplots, we want the ratio to be inversed ax = fig.add_subplot(111) # create","result parameters (Path and description) plot_dir: ath to the desired result folder to","# remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min","from pathlib import Path class ResultParam(): \"\"\"Result Parameter\"\"\" def __init__(self, path: Path, param_str:","it should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'},","plot's readability title = '{}' for label in labels: for metric, (min_, max_)","parameter values from text file, use them to plot the information about the","use them to plot the information about the paramter # some parameters to","unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are interested in","marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list, title: str, x_label:","dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ ) if __name__ == '__main__': results","the x-label since it should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize':","a set of different features), therefore, # we load two CSV (for simplicity,","([ResultParam]): a list of result parameters (Path and description) plot_dir: ath to the","pandas as pd from pathlib import Path class ResultParam(): \"\"\"Result Parameter\"\"\" def __init__(self,","ax.get_ylim() min_ = min_ if min_ is not None and min_ < min_original","[] methods = [] for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo:","Result Parameter Args: path (Path): path to the desired result file param_str (str):","1.0), (0.0, 18)) # tuples of y-axis limits (min, max) for each metric.","same length') fig = plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize defaults to","# thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max if provided if","max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\"tight\") plt.close() def format_data(data, label: str, metric:","x-label since it should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18,","= param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1)","\"{}\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \"\"\"generates box plots comparing two or","parameters to improve the plot's readability title = '{}' for label in labels:","title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ ) if __name__ == '__main__': results =","them to plot the information about the paramter # some parameters to improve","different methods (e.g. load different CSVs) dfs = [] methods = [] for","paramter # some parameters to improve the plot's readability title = '{}' for","max_ ) if __name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \"mia-result\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\"), \"no","else min_original max_ = max_ if max_ is not None and max_ >","(nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format litle, labels,","color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data:","raise ValueError('arguments data and x_ticks need to have same length') fig = plt.figure(","be inversed ax = fig.add_subplot(111) # create an axes instance (nrows=ncols=index) bp =","labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5)","distance (mm)' else: raise ValueError('Metric \"{}\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \"\"\"generates","provided if min_ is not None or max_ is not None: min_original, max_original","= None, max_: float = None): if len(data) != len(x_ticks): raise ValueError('arguments data","use the x-label since it should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks,","(Path): path to the desired result file param_str (str): string containing the parameters","import os import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas as pd","about the paramter # some parameters to improve the plot's readability title =","should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45)","data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if metric == 'DICE': return 'Dice coefficient'","we want the ratio to be inversed ax = fig.add_subplot(111) # create an","(mm)' else: raise ValueError('Metric \"{}\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \"\"\"generates box","parameters (Path and description) plot_dir: ath to the desired result folder to store","here) # todo: adapt to your needs to compare different methods (e.g. load","not None and max_ > max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\"tight\") plt.close()","labels: for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label,","matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas as pd from pathlib import","(e.g. a set of different features), therefore, # we load two CSV (for","result sets for all labels Args: results ([ResultParam]): a list of result parameters","different CSVs) dfs = [] methods = [] for res in results: dfs.append(pd.read_csv(res.path,","of result parameters (Path and description) plot_dir: ath to the desired result folder","max_original = ax.get_ylim() min_ = min_ if min_ is not None and min_","of y-axis limits (min, max) for each metric. Use None if unknown labels","improve the plot's readability title = '{}' for label in labels: for metric,","metric_to_readable_text(metric), methods, min_, max_ ) if __name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd()","methods.append(res.param_str) # todo: read parameter values from text file, use them to plot","def __init__(self, path: Path, param_str: str): \"\"\"Initializes a new instance of the Result","= '{}' for label in labels: for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits):","argparse import os import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas as","label: str, metric: str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if metric","for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter values from","def main(results: [ResultParam], plot_dir: Path): \"\"\"generates box plots comparing two or more result","min_ is not None and min_ < min_original else min_original max_ = max_","some parameters to improve the plot's readability title = '{}' for label in","max_: float = None): if len(data) != len(x_ticks): raise ValueError('arguments data and x_ticks","min_original max_ = max_ if max_ is not None and max_ > max_original","to (width, height) =(6.4, 4.8), # for boxplots, we want the ratio to","min_ is not None or max_ is not None: min_original, max_original = ax.get_ylim()","ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we","the parameters used in the postprocessing \"\"\" self.path = path self.param_str = param_str","return 'Hausdorff distance (mm)' else: raise ValueError('Metric \"{}\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir:","markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list, title: str, x_label: str, y_label:","ValueError('arguments data and x_ticks need to have same length') fig = plt.figure( figsize=(","str, metric: str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if metric ==","the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False)","not None and min_ < min_original else min_original max_ = max_ if max_","metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df in dfs], title.format(label), 'Method',","methods = [] for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read","string containing the parameters used in the postprocessing \"\"\" self.path = path self.param_str","\"\"\" self.path = path self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'],","the CSVs. We usually want to compare different methods (e.g. a set of","compare different methods (e.g. load different CSVs) dfs = [] methods = []","sep=';')) methods.append(res.param_str) # todo: read parameter values from text file, use them to","coefficient' elif metric == 'HDRFDST': return 'Hausdorff distance (mm)' else: raise ValueError('Metric \"{}\"","= [] methods = [] for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) #","= plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize defaults to (width, height) =(6.4,","None and min_ < min_original else min_original max_ = max_ if max_ is","None: min_original, max_original = ax.get_ylim() min_ = min_ if min_ is not None","dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter values from text file, use them","load the CSVs. We usually want to compare different methods (e.g. a set","usually want to compare different methods (e.g. a set of different features), therefore,","folder to store the qq-plots \"\"\" metrics = ('DICE', 'HDRFDST') # the metrics","alpha=1) def boxplot(file_path: str, data: list, title: str, x_label: str, y_label: str, x_ticks:","res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter values from text","x_ticks need to have same length') fig = plt.figure( figsize=( 2 *1.5, 5*1.5))","\"\"\"generates box plots comparing two or more result sets for all labels Args:","set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'],","plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize defaults to (width, height) =(6.4, 4.8),","def format_data(data, label: str, metric: str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str):","len(x_ticks): raise ValueError('arguments data and x_ticks need to have same length') fig =","postprocessing \"\"\" self.path = path self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color)","format_data(data, label: str, metric: str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if","Parameter Args: path (Path): path to the desired result file param_str (str): string","def boxplot(file_path: str, data: list, title: str, x_label: str, y_label: str, x_ticks: tuple,","figsize defaults to (width, height) =(6.4, 4.8), # for boxplots, we want the","want the ratio to be inversed ax = fig.add_subplot(111) # create an axes","(0.0, 18)) # tuples of y-axis limits (min, max) for each metric. Use","file, use them to plot the information about the paramter # some parameters","new instance of the Result Parameter Args: path (Path): path to the desired","frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max if provided if min_ is","# todo: adapt to your needs to compare different methods (e.g. load different","load different CSVs) dfs = [] methods = [] for res in results:","is not None and min_ < min_original else min_original max_ = max_ if","color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1)","# we load two CSV (for simplicity, it is the same here) #","=(6.4, 4.8), # for boxplots, we want the ratio to be inversed ax","description) plot_dir: ath to the desired result folder to store the qq-plots \"\"\"","18)) # tuples of y-axis limits (min, max) for each metric. Use None","plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list, title: str, x_label: str,","desired result file param_str (str): string containing the parameters used in the postprocessing","= min_ if min_ is not None and min_ < min_original else min_original","it is the same here) # todo: adapt to your needs to compare","we want to plot the results for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18))","path to the desired result file param_str (str): string containing the parameters used","want to plot the results for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) #","ax.spines['bottom'].set_linewidth(2) # adjust min and max if provided if min_ is not None","are interested in # load the CSVs. We usually want to compare different","methods (e.g. a set of different features), therefore, # we load two CSV","def metric_to_readable_text(metric: str): if metric == 'DICE': return 'Dice coefficient' elif metric ==","# some parameters to improve the plot's readability title = '{}' for label","clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove","and description) plot_dir: ath to the desired result folder to store the qq-plots","ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max if provided","len(data) != len(x_ticks): raise ValueError('arguments data and x_ticks need to have same length')","simplicity, it is the same here) # todo: adapt to your needs to","label][metric].values def metric_to_readable_text(metric: str): if metric == 'DICE': return 'Dice coefficient' elif metric","ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't","else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\"tight\") plt.close() def format_data(data, label: str, metric: str):","str, data: list, title: str, x_label: str, y_label: str, x_ticks: tuple, min_: float","param_str (str): string containing the parameters used in the postprocessing \"\"\" self.path =","max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df in","max) for each metric. Use None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') #","plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list, title: str,","4.8), # for boxplots, we want the ratio to be inversed ax =","in labels: for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df,","Path): \"\"\"generates box plots comparing two or more result sets for all labels","create an axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set","= ((0.0, 1.0), (0.0, 18)) # tuples of y-axis limits (min, max) for","import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas as pd from pathlib","('DICE', 'HDRFDST') # the metrics we want to plot the results for metrics_yaxis_limits","thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max if provided if min_","for boxplots, we want the ratio to be inversed ax = fig.add_subplot(111) #","an axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and","[] for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter values","store the qq-plots \"\"\" metrics = ('DICE', 'HDRFDST') # the metrics we want","is not None and max_ > max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\"tight\")","self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'],","2 *1.5, 5*1.5)) # figsize defaults to (width, height) =(6.4, 4.8), # for","= [] results.append(ResultParam(Path(Path.cwd() / \"mia-result\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\"), \"no pp\")) results.append(ResultParam(Path(Path.cwd() /\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\"), \"with pp\")) main(results, Path(Path.cwd()","for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ ) if __name__","results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter values from text file, use","(min, max) for each metric. Use None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus')","the same here) # todo: adapt to your needs to compare different methods","'Hausdorff distance (mm)' else: raise ValueError('Metric \"{}\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path):","plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def","'DICE': return 'Dice coefficient' elif metric == 'HDRFDST': return 'Hausdorff distance (mm)' else:","to your needs to compare different methods (e.g. load different CSVs) dfs =","*1.5, 5*1.5)) # figsize defaults to (width, height) =(6.4, 4.8), # for boxplots,","need to have same length') fig = plt.figure( figsize=( 2 *1.5, 5*1.5)) #","Parameter\"\"\" def __init__(self, path: Path, param_str: str): \"\"\"Initializes a new instance of the","your needs to compare different methods (e.g. load different CSVs) dfs = []","# for boxplots, we want the ratio to be inversed ax = fig.add_subplot(111)","class ResultParam(): \"\"\"Result Parameter\"\"\" def __init__(self, path: Path, param_str: str): \"\"\"Initializes a new","(min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df","str): \"\"\"Initializes a new instance of the Result Parameter Args: path (Path): path","two or more result sets for all labels Args: results ([ResultParam]): a list","be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) #","list of result parameters (Path and description) plot_dir: ath to the desired result","= [] for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter","color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5)","and x_ticks need to have same length') fig = plt.figure( figsize=( 2 *1.5,","label in labels: for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)),","instance of the Result Parameter Args: path (Path): path to the desired result","plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'],","plots comparing two or more result sets for all labels Args: results ([ResultParam]):","results ([ResultParam]): a list of result parameters (Path and description) plot_dir: ath to","if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are interested","matplotlib.pyplot as plt import pandas as pd from pathlib import Path class ResultParam():","= fig.add_subplot(111) # create an axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp,","metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) # tuples of y-axis limits (min, max)"],"string":"[\n \"instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format litle,\",\n \"remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and\",\n \"Args: path (Path): path to the desired result file param_str (str): string containing\",\n \"None and max_ > max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\\\"tight\\\") plt.close() def\",\n \"the desired result file param_str (str): string containing the parameters used in the\",\n \"have same length') fig = plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize defaults\",\n \"widths=0.6) set_box_format(bp, '000') # set and format litle, labels, and ticks ax.set_title(title, fontweight='bold',\",\n \"(Path and description) plot_dir: ath to the desired result folder to store the\",\n \"not None or max_ is not None: min_original, max_original = ax.get_ylim() min_ =\",\n \"str, x_label: str, y_label: str, x_ticks: tuple, min_: float = None, max_: float\",\n \"color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.')\",\n \"if __name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \\\"mia-result\\\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\\\"), \\\"no pp\\\")) results.append(ResultParam(Path(Path.cwd()\",\n \"max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\\\"tight\\\") plt.close() def format_data(data, label: str, metric: str): return\",\n \"methods (e.g. load different CSVs) dfs = [] methods = [] for res\",\n \"bbox_inches=\\\"tight\\\") plt.close() def format_data(data, label: str, metric: str): return data[data['LABEL'] == label][metric].values def\",\n \"fig = plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize defaults to (width, height)\",\n \"import argparse import os import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas\",\n \"18, 'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2)\",\n \"and max if provided if min_ is not None or max_ is not\",\n \"import matplotlib.pyplot as plt import pandas as pd from pathlib import Path class\",\n \") if __name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \\\"mia-result\\\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\\\"), \\\"no pp\\\"))\",\n \"== '__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \\\"mia-result\\\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\\\"), \\\"no pp\\\")) results.append(ResultParam(Path(Path.cwd() /\\\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\\\"), \\\"with\",\n \"of the Result Parameter Args: path (Path): path to the desired result file\",\n \"axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format\",\n \"not None: min_original, max_original = ax.get_ylim() min_ = min_ if min_ is not\",\n \"if provided if min_ is not None or max_ is not None: min_original,\",\n \"\\\"\\\"\\\"Result Parameter\\\"\\\"\\\" def __init__(self, path: Path, param_str: str): \\\"\\\"\\\"Initializes a new instance of\",\n \"defaults to (width, height) =(6.4, 4.8), # for boxplots, we want the ratio\",\n \"('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are interested in # load the\",\n \"tuples of y-axis limits (min, max) for each metric. Use None if unknown\",\n \"Args: results ([ResultParam]): a list of result parameters (Path and description) plot_dir: ath\",\n \"ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken\",\n \"load two CSV (for simplicity, it is the same here) # todo: adapt\",\n \"to have same length') fig = plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize\",\n \"ratio to be inversed ax = fig.add_subplot(111) # create an axes instance (nrows=ncols=index)\",\n \"information about the paramter # some parameters to improve the plot's readability title\",\n \"CSVs) dfs = [] methods = [] for res in results: dfs.append(pd.read_csv(res.path, sep=';'))\",\n \"plot the information about the paramter # some parameters to improve the plot's\",\n \"all labels Args: results ([ResultParam]): a list of result parameters (Path and description)\",\n \"path self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color)\",\n \"max_) plt.savefig(file_path, bbox_inches=\\\"tight\\\") plt.close() def format_data(data, label: str, metric: str): return data[data['LABEL'] ==\",\n \"read parameter values from text file, use them to plot the information about\",\n \"# create an axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') #\",\n \"self.path = path self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color)\",\n \"min_ < min_original else min_original max_ = max_ if max_ is not None\",\n \"ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max if provided if min_ is not\",\n \"unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \\\"\\\"\\\"generates box plots comparing two or more\",\n \"fontweight='bold', fontsize=9.5) # we don't use the x-label since it should be clear\",\n \"don't use the x-label since it should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12)\",\n \"different methods (e.g. a set of different features), therefore, # we load two\",\n \"'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) #\",\n \"data: list, title: str, x_label: str, y_label: str, x_ticks: tuple, min_: float =\",\n \"fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use the x-label since\",\n \"<filename>bin/boxplot_param.py import argparse import os import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import\",\n \"path (Path): path to the desired result file param_str (str): string containing the\",\n \"text file, use them to plot the information about the paramter # some\",\n \"# todo: read parameter values from text file, use them to plot the\",\n \"in # load the CSVs. We usually want to compare different methods (e.g.\",\n \"'{}' for label in labels: for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir,\",\n \"as pd from pathlib import Path class ResultParam(): \\\"\\\"\\\"Result Parameter\\\"\\\"\\\" def __init__(self, path:\",\n \"param_str: str): \\\"\\\"\\\"Initializes a new instance of the Result Parameter Args: path (Path):\",\n \"length') fig = plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize defaults to (width,\",\n \"set of different features), therefore, # we load two CSV (for simplicity, it\",\n \"Path class ResultParam(): \\\"\\\"\\\"Result Parameter\\\"\\\"\\\" def __init__(self, path: Path, param_str: str): \\\"\\\"\\\"Initializes a\",\n \"in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df in dfs],\",\n \"labels Args: results ([ResultParam]): a list of result parameters (Path and description) plot_dir:\",\n \"= ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are interested in # load\",\n \"= ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format litle, labels, and ticks\",\n \"is the same here) # todo: adapt to your needs to compare different\",\n \"we load two CSV (for simplicity, it is the same here) # todo:\",\n \"'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are interested in # load the CSVs.\",\n \"'000') # set and format litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label,\",\n \"to plot the information about the paramter # some parameters to improve the\",\n \"box plots comparing two or more result sets for all labels Args: results\",\n \"else: raise ValueError('Metric \\\"{}\\\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \\\"\\\"\\\"generates box plots\",\n \"metric: str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if metric == 'DICE':\",\n \"for each metric. Use None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the\",\n \"linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list, title:\",\n \"# set and format litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold',\",\n \"# tuples of y-axis limits (min, max) for each metric. Use None if\",\n \"is not None: min_original, max_original = ax.get_ylim() min_ = min_ if min_ is\",\n \"each metric. Use None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain\",\n \"from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove frame\",\n \"set and format litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18)\",\n \"adjust min and max if provided if min_ is not None or max_\",\n \"str): if metric == 'DICE': return 'Dice coefficient' elif metric == 'HDRFDST': return\",\n \"in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter values from text file,\",\n \"labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are interested in #\",\n \"or max_ is not None: min_original, max_original = ax.get_ylim() min_ = min_ if\",\n \"float = None, max_: float = None): if len(data) != len(x_ticks): raise ValueError('arguments\",\n \"min_, max_ ) if __name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \\\"mia-result\\\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\\\"),\",\n \"[ResultParam], plot_dir: Path): \\\"\\\"\\\"generates box plots comparing two or more result sets for\",\n \"ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\\\"tight\\\") plt.close() def format_data(data, label: str, metric: str): return data[data['LABEL']\",\n \"for all labels Args: results ([ResultParam]): a list of result parameters (Path and\",\n \"ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use the x-label since it should be\",\n \"interested in # load the CSVs. We usually want to compare different methods\",\n \"values from text file, use them to plot the information about the paramter\",\n \"ax = fig.add_subplot(111) # create an axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6)\",\n \"the ratio to be inversed ax = fig.add_subplot(111) # create an axes instance\",\n \"the results for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) # tuples of y-axis\",\n \"in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ ) if __name__ == '__main__':\",\n \"# ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use the x-label since it should\",\n \"fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame\",\n \"boxplot(file_path: str, data: list, title: str, x_label: str, y_label: str, x_ticks: tuple, min_:\",\n \"result file param_str (str): string containing the parameters used in the postprocessing \\\"\\\"\\\"\",\n \"as plt import pandas as pd from pathlib import Path class ResultParam(): \\\"\\\"\\\"Result\",\n \"x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False)\",\n \"# we don't use the x-label since it should be clear from the\",\n \"max_ if max_ is not None and max_ > max_original else max_original ax.set_ylim(min_,\",\n \"\\\"\\\"\\\"Initializes a new instance of the Result Parameter Args: path (Path): path to\",\n \"different features), therefore, # we load two CSV (for simplicity, it is the\",\n \"!= len(x_ticks): raise ValueError('arguments data and x_ticks need to have same length') fig\",\n \"os import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas as pd from\",\n \"dfs = [] methods = [] for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str)\",\n \"ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use the x-label\",\n \"matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas as pd from pathlib import Path\",\n \"from text file, use them to plot the information about the paramter #\",\n \"for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric)\",\n \"features), therefore, # we load two CSV (for simplicity, it is the same\",\n \"rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust\",\n \"(str): string containing the parameters used in the postprocessing \\\"\\\"\\\" self.path = path\",\n \"# the metrics we want to plot the results for metrics_yaxis_limits = ((0.0,\",\n \"raise ValueError('Metric \\\"{}\\\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \\\"\\\"\\\"generates box plots comparing\",\n \"the Result Parameter Args: path (Path): path to the desired result file param_str\",\n \"parameters used in the postprocessing \\\"\\\"\\\" self.path = path self.param_str = param_str def\",\n \"used in the postprocessing \\\"\\\"\\\" self.path = path self.param_str = param_str def set_box_format(bp,\",\n \"litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold',\",\n \"list, title: str, x_label: str, y_label: str, x_ticks: tuple, min_: float = None,\",\n \"metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for\",\n \"color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black')\",\n \"if min_ is not None or max_ is not None: min_original, max_original =\",\n \"max_ is not None and max_ > max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path,\",\n \"ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format litle, labels, and ticks ax.set_title(title,\",\n \"file param_str (str): string containing the parameters used in the postprocessing \\\"\\\"\\\" self.path\",\n \"# load the CSVs. We usually want to compare different methods (e.g. a\",\n \"set_box_format(bp, '000') # set and format litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20)\",\n \"adapt to your needs to compare different methods (e.g. load different CSVs) dfs\",\n \"== 'HDRFDST': return 'Hausdorff distance (mm)' else: raise ValueError('Metric \\\"{}\\\" unknown'.format(metric)) def main(results:\",\n \"the postprocessing \\\"\\\"\\\" self.path = path self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'],\",\n \"y_label: str, x_ticks: tuple, min_: float = None, max_: float = None): if\",\n \"to the desired result file param_str (str): string containing the parameters used in\",\n \"frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max\",\n \"ResultParam(): \\\"\\\"\\\"Result Parameter\\\"\\\"\\\" def __init__(self, path: Path, param_str: str): \\\"\\\"\\\"Initializes a new instance\",\n \"< min_original else min_original max_ = max_ if max_ is not None and\",\n \"plot_dir: Path): \\\"\\\"\\\"generates box plots comparing two or more result sets for all\",\n \"zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df in dfs], title.format(label),\",\n \"Use None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you\",\n \"ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) #\",\n \"return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if metric == 'DICE': return 'Dice\",\n \"want to compare different methods (e.g. a set of different features), therefore, #\",\n \"[format_data(df, label, metric) for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_\",\n \"desired result folder to store the qq-plots \\\"\\\"\\\" metrics = ('DICE', 'HDRFDST') #\",\n \"'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2)\",\n \"the plot's readability title = '{}' for label in labels: for metric, (min_,\",\n \"and format litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) #\",\n \"str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if metric == 'DICE': return\",\n \"metrics we want to plot the results for metrics_yaxis_limits = ((0.0, 1.0), (0.0,\",\n \"the paramter # some parameters to improve the plot's readability title = '{}'\",\n \"plt import pandas as pd from pathlib import Path class ResultParam(): \\\"\\\"\\\"Result Parameter\\\"\\\"\\\"\",\n \"metric. Use None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues\",\n \"two CSV (for simplicity, it is the same here) # todo: adapt to\",\n \"main(results: [ResultParam], plot_dir: Path): \\\"\\\"\\\"generates box plots comparing two or more result sets\",\n \"# figsize defaults to (width, height) =(6.4, 4.8), # for boxplots, we want\",\n \"5*1.5)) # figsize defaults to (width, height) =(6.4, 4.8), # for boxplots, we\",\n \"title: str, x_label: str, y_label: str, x_ticks: tuple, min_: float = None, max_:\",\n \"plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'],\",\n \"is not None or max_ is not None: min_original, max_original = ax.get_ylim() min_\",\n \"if min_ is not None and min_ < min_original else min_original max_ =\",\n \"plot the results for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) # tuples of\",\n \"fontsize=9.5) # we don't use the x-label since it should be clear from\",\n \"limits (min, max) for each metric. Use None if unknown labels = ('WhiteMatter','GreyMatter',\",\n \"'HDRFDST': return 'Hausdorff distance (mm)' else: raise ValueError('Metric \\\"{}\\\" unknown'.format(metric)) def main(results: [ResultParam],\",\n \"results = [] results.append(ResultParam(Path(Path.cwd() / \\\"mia-result\\\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\\\"), \\\"no pp\\\")) results.append(ResultParam(Path(Path.cwd() /\\\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\\\"), \\\"with pp\\\")) main(results,\",\n \"[] results.append(ResultParam(Path(Path.cwd() / \\\"mia-result\\\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\\\"), \\\"no pp\\\")) results.append(ResultParam(Path(Path.cwd() /\\\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\\\"), \\\"with pp\\\")) main(results, Path(Path.cwd() /\",\n \"plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str,\",\n \"needs to compare different methods (e.g. load different CSVs) dfs = [] methods\",\n \"'{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods,\",\n \"tuple, min_: float = None, max_: float = None): if len(data) != len(x_ticks):\",\n \"bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format litle, labels, and\",\n \"plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list, title: str, x_label: str, y_label: str,\",\n \"compare different methods (e.g. a set of different features), therefore, # we load\",\n \"figsize=( 2 *1.5, 5*1.5)) # figsize defaults to (width, height) =(6.4, 4.8), #\",\n \"'Method', metric_to_readable_text(metric), methods, min_, max_ ) if __name__ == '__main__': results = []\",\n \"linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path:\",\n \"None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are\",\n \"((0.0, 1.0), (0.0, 18)) # tuples of y-axis limits (min, max) for each\",\n \"metric)), [format_data(df, label, metric) for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_,\",\n \"we don't use the x-label since it should be clear from the x-ticks\",\n \"= path self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'],\",\n \"float = None): if len(data) != len(x_ticks): raise ValueError('arguments data and x_ticks need\",\n \"the desired result folder to store the qq-plots \\\"\\\"\\\" metrics = ('DICE', 'HDRFDST')\",\n \"pd from pathlib import Path class ResultParam(): \\\"\\\"\\\"Result Parameter\\\"\\\"\\\" def __init__(self, path: Path,\",\n \"metric == 'DICE': return 'Dice coefficient' elif metric == 'HDRFDST': return 'Hausdorff distance\",\n \"x_label: str, y_label: str, x_ticks: tuple, min_: float = None, max_: float =\",\n \"boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric),\",\n \"= None): if len(data) != len(x_ticks): raise ValueError('arguments data and x_ticks need to\",\n \"plot_dir: ath to the desired result folder to store the qq-plots \\\"\\\"\\\" metrics\",\n \"a new instance of the Result Parameter Args: path (Path): path to the\",\n \"y-axis limits (min, max) for each metric. Use None if unknown labels =\",\n \"todo: adapt to your needs to compare different methods (e.g. load different CSVs)\",\n \"in the postprocessing \\\"\\\"\\\" self.path = path self.param_str = param_str def set_box_format(bp, color):\",\n \"more result sets for all labels Args: results ([ResultParam]): a list of result\",\n \"ValueError('Metric \\\"{}\\\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \\\"\\\"\\\"generates box plots comparing two\",\n \"path: Path, param_str: str): \\\"\\\"\\\"Initializes a new instance of the Result Parameter Args:\",\n \"ath to the desired result folder to store the qq-plots \\\"\\\"\\\" metrics =\",\n \"(width, height) =(6.4, 4.8), # for boxplots, we want the ratio to be\",\n \"min and max if provided if min_ is not None or max_ is\",\n \"plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list,\",\n \"todo: read parameter values from text file, use them to plot the information\",\n \"= max_ if max_ is not None and max_ > max_original else max_original\",\n \"if metric == 'DICE': return 'Dice coefficient' elif metric == 'HDRFDST': return 'Hausdorff\",\n \"to improve the plot's readability title = '{}' for label in labels: for\",\n \"and max_ > max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\\\"tight\\\") plt.close() def format_data(data,\",\n \"max_ > max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\\\"tight\\\") plt.close() def format_data(data, label:\",\n \"the information about the paramter # some parameters to improve the plot's readability\",\n \"results.append(ResultParam(Path(Path.cwd() / \\\"mia-result\\\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\\\"), \\\"no pp\\\")) results.append(ResultParam(Path(Path.cwd() /\\\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\\\"), \\\"with pp\\\")) main(results, Path(Path.cwd() / 'mia-result/plot_results'))\",\n \"'__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \\\"mia-result\\\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\\\"), \\\"no pp\\\")) results.append(ResultParam(Path(Path.cwd() /\\\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\\\"), \\\"with pp\\\"))\",\n \"plt.close() def format_data(data, label: str, metric: str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric:\",\n \"format litle, labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label,\",\n \"and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) #\",\n \"qq-plots \\\"\\\"\\\" metrics = ('DICE', 'HDRFDST') # the metrics we want to plot\",\n \"min_ = min_ if min_ is not None and min_ < min_original else\",\n \"df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ ) if __name__ ==\",\n \"height) =(6.4, 4.8), # for boxplots, we want the ratio to be inversed\",\n \"if len(data) != len(x_ticks): raise ValueError('arguments data and x_ticks need to have same\",\n \"comparing two or more result sets for all labels Args: results ([ResultParam]): a\",\n \"CSV (for simplicity, it is the same here) # todo: adapt to your\",\n \"if max_ is not None and max_ > max_original else max_original ax.set_ylim(min_, max_)\",\n \"__name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \\\"mia-result\\\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\\\"), \\\"no pp\\\")) results.append(ResultParam(Path(Path.cwd() /\\\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\\\"),\",\n \"str, y_label: str, x_ticks: tuple, min_: float = None, max_: float = None):\",\n \"inversed ax = fig.add_subplot(111) # create an axes instance (nrows=ncols=index) bp = ax.boxplot(data,\",\n \"or more result sets for all labels Args: results ([ResultParam]): a list of\",\n \"to plot the results for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) # tuples\",\n \"plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'],\",\n \"None): if len(data) != len(x_ticks): raise ValueError('arguments data and x_ticks need to have\",\n \"return 'Dice coefficient' elif metric == 'HDRFDST': return 'Hausdorff distance (mm)' else: raise\",\n \"'HDRFDST') # the metrics we want to plot the results for metrics_yaxis_limits =\",\n \"(e.g. load different CSVs) dfs = [] methods = [] for res in\",\n \"x_ticks: tuple, min_: float = None, max_: float = None): if len(data) !=\",\n \"import pandas as pd from pathlib import Path class ResultParam(): \\\"\\\"\\\"Result Parameter\\\"\\\"\\\" def\",\n \"therefore, # we load two CSV (for simplicity, it is the same here)\",\n \"== label][metric].values def metric_to_readable_text(metric: str): if metric == 'DICE': return 'Dice coefficient' elif\",\n \"pathlib import Path class ResultParam(): \\\"\\\"\\\"Result Parameter\\\"\\\"\\\" def __init__(self, path: Path, param_str: str):\",\n \"and min_ < min_original else min_original max_ = max_ if max_ is not\",\n \"result folder to store the qq-plots \\\"\\\"\\\" metrics = ('DICE', 'HDRFDST') # the\",\n \"max_ is not None: min_original, max_original = ax.get_ylim() min_ = min_ if min_\",\n \"= ('DICE', 'HDRFDST') # the metrics we want to plot the results for\",\n \"to compare different methods (e.g. load different CSVs) dfs = [] methods =\",\n \"for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) # tuples of y-axis limits (min,\",\n \"metrics = ('DICE', 'HDRFDST') # the metrics we want to plot the results\",\n \"min_: float = None, max_: float = None): if len(data) != len(x_ticks): raise\",\n \"to compare different methods (e.g. a set of different features), therefore, # we\",\n \"None, max_: float = None): if len(data) != len(x_ticks): raise ValueError('arguments data and\",\n \"brain structures/tissues you are interested in # load the CSVs. We usually want\",\n \"import Path class ResultParam(): \\\"\\\"\\\"Result Parameter\\\"\\\"\\\" def __init__(self, path: Path, param_str: str): \\\"\\\"\\\"Initializes\",\n \"sets for all labels Args: results ([ResultParam]): a list of result parameters (Path\",\n \"fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use the x-label since it\",\n \"the brain structures/tissues you are interested in # load the CSVs. We usually\",\n \"you are interested in # load the CSVs. We usually want to compare\",\n \"max if provided if min_ is not None or max_ is not None:\",\n \"# the brain structures/tissues you are interested in # load the CSVs. We\",\n \"metric_to_readable_text(metric: str): if metric == 'DICE': return 'Dice coefficient' elif metric == 'HDRFDST':\",\n \"# adjust min and max if provided if min_ is not None or\",\n \"containing the parameters used in the postprocessing \\\"\\\"\\\" self.path = path self.param_str =\",\n \"> max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\\\"tight\\\") plt.close() def format_data(data, label: str,\",\n \"since it should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight':\",\n \"a list of result parameters (Path and description) plot_dir: ath to the desired\",\n \"'Dice coefficient' elif metric == 'HDRFDST': return 'Hausdorff distance (mm)' else: raise ValueError('Metric\",\n \"elif metric == 'HDRFDST': return 'Hausdorff distance (mm)' else: raise ValueError('Metric \\\"{}\\\" unknown'.format(metric))\",\n \"the metrics we want to plot the results for metrics_yaxis_limits = ((0.0, 1.0),\",\n \"structures/tissues you are interested in # load the CSVs. We usually want to\",\n \"fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use the\",\n \"title = '{}' for label in labels: for metric, (min_, max_) in zip(metrics,\",\n \"fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't use\",\n \"of different features), therefore, # we load two CSV (for simplicity, it is\",\n \"to store the qq-plots \\\"\\\"\\\" metrics = ('DICE', 'HDRFDST') # the metrics we\",\n \"str, x_ticks: tuple, min_: float = None, max_: float = None): if len(data)\",\n \"the qq-plots \\\"\\\"\\\" metrics = ('DICE', 'HDRFDST') # the metrics we want to\",\n \"== 'DICE': return 'Dice coefficient' elif metric == 'HDRFDST': return 'Hausdorff distance (mm)'\",\n \"None or max_ is not None: min_original, max_original = ax.get_ylim() min_ = min_\",\n \"def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red')\",\n \"min_ if min_ is not None and min_ < min_original else min_original max_\",\n \"max_ = max_ if max_ is not None and max_ > max_original else\",\n \"CSVs. We usually want to compare different methods (e.g. a set of different\",\n \"readability title = '{}' for label in labels: for metric, (min_, max_) in\",\n \"Path, param_str: str): \\\"\\\"\\\"Initializes a new instance of the Result Parameter Args: path\",\n \"data and x_ticks need to have same length') fig = plt.figure( figsize=( 2\",\n \"min_original, max_original = ax.get_ylim() min_ = min_ if min_ is not None and\",\n \"__init__(self, path: Path, param_str: str): \\\"\\\"\\\"Initializes a new instance of the Result Parameter\",\n \"same here) # todo: adapt to your needs to compare different methods (e.g.\",\n \"= ax.get_ylim() min_ = min_ if min_ is not None and min_ <\",\n \"metric == 'HDRFDST': return 'Hausdorff distance (mm)' else: raise ValueError('Metric \\\"{}\\\" unknown'.format(metric)) def\",\n \"min_original else min_original max_ = max_ if max_ is not None and max_\",\n \"ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max if\",\n \"for label in labels: for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label,\",\n \"methods, min_, max_ ) if __name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd() /\",\n \"fig.add_subplot(111) # create an axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000')\",\n \"label, metric) for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ )\",\n \"param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'],\",\n \"(for simplicity, it is the same here) # todo: adapt to your needs\",\n \"plt.savefig(file_path, bbox_inches=\\\"tight\\\") plt.close() def format_data(data, label: str, metric: str): return data[data['LABEL'] == label][metric].values\",\n \"to be inversed ax = fig.add_subplot(111) # create an axes instance (nrows=ncols=index) bp\",\n \"\\\"\\\"\\\" metrics = ('DICE', 'HDRFDST') # the metrics we want to plot the\",\n \"metric) for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ ) if\",\n \"to the desired result folder to store the qq-plots \\\"\\\"\\\" metrics = ('DICE',\",\n \"We usually want to compare different methods (e.g. a set of different features),\",\n \"results for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) # tuples of y-axis limits\",\n \"boxplots, we want the ratio to be inversed ax = fig.add_subplot(111) # create\",\n \"result parameters (Path and description) plot_dir: ath to the desired result folder to\",\n \"# remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min\",\n \"from pathlib import Path class ResultParam(): \\\"\\\"\\\"Result Parameter\\\"\\\"\\\" def __init__(self, path: Path, param_str:\",\n \"it should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'},\",\n \"plot's readability title = '{}' for label in labels: for metric, (min_, max_)\",\n \"parameter values from text file, use them to plot the information about the\",\n \"use them to plot the information about the paramter # some parameters to\",\n \"unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are interested in\",\n \"marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list, title: str, x_label:\",\n \"dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ ) if __name__ == '__main__': results\",\n \"the x-label since it should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize':\",\n \"a set of different features), therefore, # we load two CSV (for simplicity,\",\n \"([ResultParam]): a list of result parameters (Path and description) plot_dir: ath to the\",\n \"pandas as pd from pathlib import Path class ResultParam(): \\\"\\\"\\\"Result Parameter\\\"\\\"\\\" def __init__(self,\",\n \"ax.get_ylim() min_ = min_ if min_ is not None and min_ < min_original\",\n \"[] methods = [] for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo:\",\n \"Result Parameter Args: path (Path): path to the desired result file param_str (str):\",\n \"1.0), (0.0, 18)) # tuples of y-axis limits (min, max) for each metric.\",\n \"same length') fig = plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize defaults to\",\n \"# thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max if provided if\",\n \"max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\\\"tight\\\") plt.close() def format_data(data, label: str, metric:\",\n \"x-label since it should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18,\",\n \"= param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1)\",\n \"\\\"{}\\\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \\\"\\\"\\\"generates box plots comparing two or\",\n \"parameters to improve the plot's readability title = '{}' for label in labels:\",\n \"title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ ) if __name__ == '__main__': results =\",\n \"them to plot the information about the paramter # some parameters to improve\",\n \"different methods (e.g. load different CSVs) dfs = [] methods = [] for\",\n \"paramter # some parameters to improve the plot's readability title = '{}' for\",\n \"max_ ) if __name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd() / \\\"mia-result\\\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\\\"), \\\"no\",\n \"else min_original max_ = max_ if max_ is not None and max_ >\",\n \"(nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format litle, labels,\",\n \"color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data:\",\n \"raise ValueError('arguments data and x_ticks need to have same length') fig = plt.figure(\",\n \"be inversed ax = fig.add_subplot(111) # create an axes instance (nrows=ncols=index) bp =\",\n \"labels, and ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5)\",\n \"distance (mm)' else: raise ValueError('Metric \\\"{}\\\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \\\"\\\"\\\"generates\",\n \"provided if min_ is not None or max_ is not None: min_original, max_original\",\n \"= None, max_: float = None): if len(data) != len(x_ticks): raise ValueError('arguments data\",\n \"use the x-label since it should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks,\",\n \"(Path): path to the desired result file param_str (str): string containing the parameters\",\n \"import os import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas as pd\",\n \"about the paramter # some parameters to improve the plot's readability title =\",\n \"should be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45)\",\n \"data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if metric == 'DICE': return 'Dice coefficient'\",\n \"we want the ratio to be inversed ax = fig.add_subplot(111) # create an\",\n \"(mm)' else: raise ValueError('Metric \\\"{}\\\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path): \\\"\\\"\\\"generates box\",\n \"parameters (Path and description) plot_dir: ath to the desired result folder to store\",\n \"here) # todo: adapt to your needs to compare different methods (e.g. load\",\n \"not None and max_ > max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\\\"tight\\\") plt.close()\",\n \"labels: for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label,\",\n \"matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas as pd from pathlib import\",\n \"(e.g. a set of different features), therefore, # we load two CSV (for\",\n \"result sets for all labels Args: results ([ResultParam]): a list of result parameters\",\n \"different CSVs) dfs = [] methods = [] for res in results: dfs.append(pd.read_csv(res.path,\",\n \"of result parameters (Path and description) plot_dir: ath to the desired result folder\",\n \"max_original = ax.get_ylim() min_ = min_ if min_ is not None and min_\",\n \"of y-axis limits (min, max) for each metric. Use None if unknown labels\",\n \"improve the plot's readability title = '{}' for label in labels: for metric,\",\n \"metric_to_readable_text(metric), methods, min_, max_ ) if __name__ == '__main__': results = [] results.append(ResultParam(Path(Path.cwd()\",\n \"methods.append(res.param_str) # todo: read parameter values from text file, use them to plot\",\n \"def __init__(self, path: Path, param_str: str): \\\"\\\"\\\"Initializes a new instance of the Result\",\n \"= '{}' for label in labels: for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits):\",\n \"argparse import os import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas as\",\n \"label: str, metric: str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if metric\",\n \"for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter values from\",\n \"def main(results: [ResultParam], plot_dir: Path): \\\"\\\"\\\"generates box plots comparing two or more result\",\n \"min_ is not None and min_ < min_original else min_original max_ = max_\",\n \"some parameters to improve the plot's readability title = '{}' for label in\",\n \"max_: float = None): if len(data) != len(x_ticks): raise ValueError('arguments data and x_ticks\",\n \"min_original max_ = max_ if max_ is not None and max_ > max_original\",\n \"to (width, height) =(6.4, 4.8), # for boxplots, we want the ratio to\",\n \"min_ is not None or max_ is not None: min_original, max_original = ax.get_ylim()\",\n \"ticks ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we\",\n \"the parameters used in the postprocessing \\\"\\\"\\\" self.path = path self.param_str = param_str\",\n \"return 'Hausdorff distance (mm)' else: raise ValueError('Metric \\\"{}\\\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir:\",\n \"markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list, title: str, x_label: str, y_label:\",\n \"ValueError('arguments data and x_ticks need to have same length') fig = plt.figure( figsize=(\",\n \"str, metric: str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if metric ==\",\n \"the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove frame ax.spines['top'].set_visible(False)\",\n \"not None and min_ < min_original else min_original max_ = max_ if max_\",\n \"metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df in dfs], title.format(label), 'Method',\",\n \"methods = [] for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read\",\n \"string containing the parameters used in the postprocessing \\\"\\\"\\\" self.path = path self.param_str\",\n \"\\\"\\\"\\\" self.path = path self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'],\",\n \"the CSVs. We usually want to compare different methods (e.g. a set of\",\n \"compare different methods (e.g. load different CSVs) dfs = [] methods = []\",\n \"sep=';')) methods.append(res.param_str) # todo: read parameter values from text file, use them to\",\n \"coefficient' elif metric == 'HDRFDST': return 'Hausdorff distance (mm)' else: raise ValueError('Metric \\\"{}\\\"\",\n \"= [] methods = [] for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) #\",\n \"= plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize defaults to (width, height) =(6.4,\",\n \"None and min_ < min_original else min_original max_ = max_ if max_ is\",\n \"None: min_original, max_original = ax.get_ylim() min_ = min_ if min_ is not None\",\n \"dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter values from text file, use them\",\n \"load the CSVs. We usually want to compare different methods (e.g. a set\",\n \"usually want to compare different methods (e.g. a set of different features), therefore,\",\n \"folder to store the qq-plots \\\"\\\"\\\" metrics = ('DICE', 'HDRFDST') # the metrics\",\n \"alpha=1) def boxplot(file_path: str, data: list, title: str, x_label: str, y_label: str, x_ticks:\",\n \"res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter values from text\",\n \"x_ticks need to have same length') fig = plt.figure( figsize=( 2 *1.5, 5*1.5))\",\n \"\\\"\\\"\\\"generates box plots comparing two or more result sets for all labels Args:\",\n \"set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'],\",\n \"plt.figure( figsize=( 2 *1.5, 5*1.5)) # figsize defaults to (width, height) =(6.4, 4.8),\",\n \"def format_data(data, label: str, metric: str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str):\",\n \"len(x_ticks): raise ValueError('arguments data and x_ticks need to have same length') fig =\",\n \"postprocessing \\\"\\\"\\\" self.path = path self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color)\",\n \"format_data(data, label: str, metric: str): return data[data['LABEL'] == label][metric].values def metric_to_readable_text(metric: str): if\",\n \"Parameter Args: path (Path): path to the desired result file param_str (str): string\",\n \"def boxplot(file_path: str, data: list, title: str, x_label: str, y_label: str, x_ticks: tuple,\",\n \"figsize defaults to (width, height) =(6.4, 4.8), # for boxplots, we want the\",\n \"want the ratio to be inversed ax = fig.add_subplot(111) # create an axes\",\n \"(0.0, 18)) # tuples of y-axis limits (min, max) for each metric. Use\",\n \"file, use them to plot the information about the paramter # some parameters\",\n \"new instance of the Result Parameter Args: path (Path): path to the desired\",\n \"frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max if provided if min_ is\",\n \"# todo: adapt to your needs to compare different methods (e.g. load different\",\n \"load different CSVs) dfs = [] methods = [] for res in results:\",\n \"is not None and min_ < min_original else min_original max_ = max_ if\",\n \"color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1)\",\n \"# we load two CSV (for simplicity, it is the same here) #\",\n \"=(6.4, 4.8), # for boxplots, we want the ratio to be inversed ax\",\n \"description) plot_dir: ath to the desired result folder to store the qq-plots \\\"\\\"\\\"\",\n \"18)) # tuples of y-axis limits (min, max) for each metric. Use None\",\n \"plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list, title: str, x_label: str,\",\n \"desired result file param_str (str): string containing the parameters used in the postprocessing\",\n \"= min_ if min_ is not None and min_ < min_original else min_original\",\n \"it is the same here) # todo: adapt to your needs to compare\",\n \"we want to plot the results for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18))\",\n \"path to the desired result file param_str (str): string containing the parameters used\",\n \"want to plot the results for metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) #\",\n \"ax.spines['bottom'].set_linewidth(2) # adjust min and max if provided if min_ is not None\",\n \"are interested in # load the CSVs. We usually want to compare different\",\n \"methods (e.g. a set of different features), therefore, # we load two CSV\",\n \"def metric_to_readable_text(metric: str): if metric == 'DICE': return 'Dice coefficient' elif metric ==\",\n \"# some parameters to improve the plot's readability title = '{}' for label\",\n \"clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) # remove\",\n \"and description) plot_dir: ath to the desired result folder to store the qq-plots\",\n \"ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max if provided\",\n \"len(data) != len(x_ticks): raise ValueError('arguments data and x_ticks need to have same length')\",\n \"simplicity, it is the same here) # todo: adapt to your needs to\",\n \"label][metric].values def metric_to_readable_text(metric: str): if metric == 'DICE': return 'Dice coefficient' elif metric\",\n \"ax.set_title(title, fontweight='bold', fontsize=20) ax.set_ylabel(y_label, fontweight='bold', fontsize=18) # ax.set_xlabel(x_label, fontweight='bold', fontsize=9.5) # we don't\",\n \"else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\\\"tight\\\") plt.close() def format_data(data, label: str, metric: str):\",\n \"str, data: list, title: str, x_label: str, y_label: str, x_ticks: tuple, min_: float\",\n \"param_str (str): string containing the parameters used in the postprocessing \\\"\\\"\\\" self.path =\",\n \"max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df in\",\n \"max) for each metric. Use None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') #\",\n \"plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def boxplot(file_path: str, data: list, title: str,\",\n \"4.8), # for boxplots, we want the ratio to be inversed ax =\",\n \"in labels: for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df,\",\n \"Path): \\\"\\\"\\\"generates box plots comparing two or more result sets for all labels\",\n \"create an axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set\",\n \"= ((0.0, 1.0), (0.0, 18)) # tuples of y-axis limits (min, max) for\",\n \"import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import pandas as pd from pathlib\",\n \"('DICE', 'HDRFDST') # the metrics we want to plot the results for metrics_yaxis_limits\",\n \"thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and max if provided if min_\",\n \"for boxplots, we want the ratio to be inversed ax = fig.add_subplot(111) #\",\n \"an axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and\",\n \"[] for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter values\",\n \"store the qq-plots \\\"\\\"\\\" metrics = ('DICE', 'HDRFDST') # the metrics we want\",\n \"is not None and max_ > max_original else max_original ax.set_ylim(min_, max_) plt.savefig(file_path, bbox_inches=\\\"tight\\\")\",\n \"self.param_str = param_str def set_box_format(bp, color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'],\",\n \"2 *1.5, 5*1.5)) # figsize defaults to (width, height) =(6.4, 4.8), # for\",\n \"= [] results.append(ResultParam(Path(Path.cwd() / \\\"mia-result\\\\gridsearch_PKF/2020-12-11-09-51-54/no_PP/results.csv\\\"), \\\"no pp\\\")) results.append(ResultParam(Path(Path.cwd() /\\\"mia-result/gridsearch_PKF/2020-12-11-09-51-54/with_PP/PP-V-20_0-BG-True/results.csv\\\"), \\\"with pp\\\")) main(results, Path(Path.cwd()\",\n \"for df in dfs], title.format(label), 'Method', metric_to_readable_text(metric), methods, min_, max_ ) if __name__\",\n \"results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter values from text file, use\",\n \"(min, max) for each metric. Use None if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus')\",\n \"the same here) # todo: adapt to your needs to compare different methods\",\n \"'Hausdorff distance (mm)' else: raise ValueError('Metric \\\"{}\\\" unknown'.format(metric)) def main(results: [ResultParam], plot_dir: Path):\",\n \"plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'], marker='.') plt.setp(bp['fliers'], markerfacecolor='black') plt.setp(bp['fliers'], alpha=1) def\",\n \"'DICE': return 'Dice coefficient' elif metric == 'HDRFDST': return 'Hausdorff distance (mm)' else:\",\n \"to your needs to compare different methods (e.g. load different CSVs) dfs =\",\n \"*1.5, 5*1.5)) # figsize defaults to (width, height) =(6.4, 4.8), # for boxplots,\",\n \"need to have same length') fig = plt.figure( figsize=( 2 *1.5, 5*1.5)) #\",\n \"Parameter\\\"\\\"\\\" def __init__(self, path: Path, param_str: str): \\\"\\\"\\\"Initializes a new instance of the\",\n \"your needs to compare different methods (e.g. load different CSVs) dfs = []\",\n \"# for boxplots, we want the ratio to be inversed ax = fig.add_subplot(111)\",\n \"class ResultParam(): \\\"\\\"\\\"Result Parameter\\\"\\\"\\\" def __init__(self, path: Path, param_str: str): \\\"\\\"\\\"Initializes a new\",\n \"(min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)), [format_data(df, label, metric) for df\",\n \"str): \\\"\\\"\\\"Initializes a new instance of the Result Parameter Args: path (Path): path\",\n \"two or more result sets for all labels Args: results ([ResultParam]): a list\",\n \"be clear from the x-ticks ax.yaxis.set_tick_params(labelsize=12) ax.set_xticklabels(x_ticks, fontdict={'fontsize': 18, 'fontweight': 'bold'}, rotation=45) #\",\n \"list of result parameters (Path and description) plot_dir: ath to the desired result\",\n \"= [] for res in results: dfs.append(pd.read_csv(res.path, sep=';')) methods.append(res.param_str) # todo: read parameter\",\n \"color): plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5)\",\n \"and x_ticks need to have same length') fig = plt.figure( figsize=( 2 *1.5,\",\n \"label in labels: for metric, (min_, max_) in zip(metrics, metrics_yaxis_limits): boxplot(os.path.join(plot_dir, '{}_{}.png'.format(label, metric)),\",\n \"instance of the Result Parameter Args: path (Path): path to the desired result\",\n \"plt.setp(bp['boxes'], color=color) plt.setp(bp['whiskers'], color=color) plt.setp(bp['caps'], color=color) plt.setp(bp['caps'], linewidth=1) plt.setp(bp['medians'], color='red') plt.setp(bp['medians'], linewidth=1.5) plt.setp(bp['fliers'],\",\n \"plots comparing two or more result sets for all labels Args: results ([ResultParam]):\",\n \"results ([ResultParam]): a list of result parameters (Path and description) plot_dir: ath to\",\n \"if unknown labels = ('WhiteMatter','GreyMatter', 'Hippocampus','Amygdala','Thalamus') # the brain structures/tissues you are interested\",\n \"matplotlib.pyplot as plt import pandas as pd from pathlib import Path class ResultParam():\",\n \"= fig.add_subplot(111) # create an axes instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp,\",\n \"metrics_yaxis_limits = ((0.0, 1.0), (0.0, 18)) # tuples of y-axis limits (min, max)\"\n]","isConversational":false}}}],"truncated":false,"partial":false},"paginationData":{"pageIndex":14,"numItemsPerPage":100,"numTotalItems":12866649,"offset":1400,"length":100}},"jwt":"eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc3NTAwNTgyMSwic3ViIjoiL2RhdGFzZXRzL3RlcnJ5eXovc3RhcmNvZGVyZGF0YV9uZ3JhbV8xMyIsImV4cCI6MTc3NTAwOTQyMSwiaXNzIjoiaHR0cHM6Ly9odWdnaW5nZmFjZS5jbyJ9.tCJwQ9IkcfwZmFufDn8u4crl0O-O02DIZHBI8qla2DjsGVVwL7FAl0KNlt1mZlB4n9F1wUqpqU87qIWhOPWMAQ","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":12866649,"numBytesParquet":149232926747}]},"discussionsStats":{"closed":0,"open":0,"total":0},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
ngram listlengths 0 67.8k |
|---|
[
"parser = feedparser.parse(content) # Set the root parser = parser[\"entries\"] # Get the",
"hashlib.sha256(bytes(description, \"utf-8\", errors=\"ignore\")).hexdigest() # Return the check of the query return not self.database.isNewsExists(root,",
"to discord. @param => str: `root`: Name of the Website. @param ... |
[
"such as changing avatar and low-level message handling. \"\"\" def __init__( self, player_configuration:",
"None, server_configuration: ServerConfiguration, start_listening: bool = True, ) -> None: \"\"\" :param player_configuration:",
"e: self.logger.critical(\"CancelledError intercepted. %s\", e) except Exce... |
[
"'scheduling', 'september', 'special', 'student', 'programs', 'capacitated', 'balancing', 'assembly', 'aspect', 'model', 'inc', 'psychological', 'psychology',",
"bin_ngrams(authors, n=15, max_bin_size=30): bins = defaultdict(set) for i, (id, a) in enumerate(authors.iteritems()): if",
"(id, a) in enumerate(autho... |
[
"signature unknown pass def currentFilePath(self, *args, **kwargs): # real signature unknown pass def",
"# module PySide.QtCore # from C:\\Python27\\lib\\site-packages\\PySide\\QtCore.pyd # by generator 1.147 # no doc",
"real signature unknown pass def currentFileName(self, *args, **kwargs): # real signature un... |
[
"iss_tle): orb = iss_tle.orbit() if request.param == \"tle\": return orb elif request.param ==",
"timedelta(minutes=1) return orb.ephem(start=start, stop=stop, step=step) @fixture def jplfiles(): config['env'] = { 'jpl': [",
"of the library, but merely a convenience \"\"\" try: import matplotlib.pyplot as plt",... |
[
"for arg in expr.args if arg.has(x) ]) else: return expr f = (x**7",
"0.5*x*sqrt(0.25*x**2 + 1) + 1.0*asinh(0.5*x) # TODO: convert the rest of PMINT tests:",
"assert heurisch(1/(x + sqrt(2)), x) == log(x + sqrt(2)) assert simplify(diff(heurisch(log(x + y",
"C = 5*pi*I/12, Mathematica gives identical # result ... |
[
"> pi)).any(): raise ValueError(f\"Hue-factor must be in the range [-PI, PI]. Got {hue_factor}\")",
"super(AdjustHue, self).__init__() self.hue_factor: Union[float, torch.Tensor] = hue_factor def forward(self, input: torch.Tensor) -> torch.Tensor:",
"saturation_factor (float): How much to adjust the saturation.... |
[
"{}\".format(config_id, REGISTRY) env = gym.make(config_id) for id_, agent in enumerate(agent_list): assert isinstance(agent, agents.BaseAgent)",
"gym.make(config_id) for id_, agent in enumerate(agent_list): assert isinstance(agent, agents.BaseAgent) # NOTE: This is",
"continue config = f() gym.envs.registratio... |
[
"import path from .views import ProfileView urlpatterns = [ path('', ProfileView.as_view(), name='user-profile'), ]",
"django.urls import path from .views import ProfileView urlpatterns = [ path('', ProfileView.as_view(), name='user-profile'),",
"from django.urls import path from .views import ProfileView urlpa... |
[
"BaseClassificationComponentTest class PassiveAggressiveComponentTest(BaseClassificationComponentTest): __test__ = True res = dict() res[\"default_iris\"] = 0.92 res[\"iris_n_calls\"]",
"from autosklearn.pipeline.components.classification.passive_aggressive import \\ PassiveAggressive from .test_base import BaseC... |
[
"# # Licensed under the Apache License, Version 2.0 (the \"License\"); # you",
"writing, software # distributed under the License is distributed on an \"AS IS\"",
"# limitations under the License. \"\"\"Dart dataset tests.\"\"\" import json import mock import",
"KIND, either express or implied. # See the Lice... |
[
"# encoder - decoder outputs = self.model(batch_x, batch_x_mark, dec_inp, batch_y_mark) batch_y = batch_y[:,-self.args.pred_len:,:].to(self.device)",
"= 'val') test_data, test_loader = self._get_data(flag = 'test') path = './checkpoints/'+setting if not",
"print('\\tspeed: {:.4f}s/iter; left time: {:.4f}s'.form... |
[
"the power sensor state.\"\"\" return load_nodes_state(\"mysensors/power_sensor_state.json\") @pytest.fixture def power_sensor(gateway_nodes: dict[int, Sensor], power_sensor_state: dict)",
"\"\"\"Receive a message for the gateway.\"\"\" def receive_message_callback(message_string: str) -> None: \"\"\"Receive a",
... |
[
"point in points: if point[0] != 'p' and point[0] != 'v' and point[0]",
"import Edges import INTPoint eps = 1e-7 votes = {} Groups = []",
"Centers = [] Cluster = [] voters = {} image = cv.imread(inputname) edges",
"K = 3 ret = [] count = count / num * 0.1",
"num * 0.1 if p1 > count: K -= 1 ret.append(ret1) ... |
[
"== 200 data = response.get_json() assert 'annotations' in data assert 'tags' in data",
"'02.png' def test_get_example_image(client): response = client.get(\"/api/files/image/x.jpg\") assert response.status_code == 404 response = client.get(\"/api/files/image/image.jpg\")",
"response = client.get(\"/api/files/i... |
[
"models.ManyToManyField(help_text='Who is in this group?', related_name='course_groups', to=settings.AUTH_USER_MODEL, db_index=True)), ], ), migrations.CreateModel( name='CourseUserGroupPartitionGroup', fields=[",
"models.DateTimeField(auto_now_add=True)), ('updated_at', models.DateTimeField(auto_now=True)), ('co... |
[
"= { 'CustomerID': int(customer_id), 'AcquisitionSource': random.choices(ACQUISITION_SOURCES).pop() } writer.writerow(record) if __name__ == '__main__': main()",
"'SocialMedia', 'Display', 'Affiliate' 'Referral' ] def main(): with open('customers.csv', 'w') as fout: writer",
"fout: writer = csv.DictWriter(fout,... |
[
"executors[label] break assert isinstance(executor, WorkQueueExecutor) if __name__ == '__main__': local_config = config parsl.load(local_config)",
"2, 'memory': '1GiB'} fut = double(n, parsl_resource_specification=spec) try: fut.result() except Exception as e:",
"executors = parsl.dfk().executors executor = Non... |
[
"based on a pattern\"\"\" def __init__(self, match_string: str, include: bool): self.match_string = match_string",
"When filename contains potentially spaces, were are only interested about absolute path #",
"argument, not dividing it pieces yet for further analysis if a_name: self.command_args.append(a_name) c... |
[
"'groups', 'login_method']: body['error'] = error.FORBIDDEN_MODIFICATION return body else: user[field] = value resource.db_update_item(user_id, user)",
"'value?': 'str', }, 'output_format': { 'user_id?': 'str', }, 'description': 'Set my information' }",
"'field': 'str', 'value?': 'str', }, 'output_format': { 'u... |
[
"is so pervasive that it made it into the framework. \"\"\" from armi.reactor.tests",
"= r.core.getBlocks(Flags.FUEL)[0] for ci, component in enumerate(bFuel, start=1): ndens = component.getNumberDensities() # convert",
"import test_reactors from armi.reactor.flags import Flags from armi.utils.densityTools impo... |
[
"\"+family_id + '\\n' db[wife_id]['string'] += \"1 FAMS \"+family_id + '\\n' generate_recursive_family(db, generations=8, max_children=4)",
"font_size=22, pos=(15, 40), size=(100, 100), color=(160, 160, 160)): img = Image.new('RGB', size, color=color)",
"int(random()*5), sex='M') else: print('reused {}'.format(... |
[
"frame. # Position the start at the enemy's current location start_x = enemy.center_x",
"title): super().__init__(width, height, title) # Set the working directory (where we expect to",
"delta_x, delta_y): \"\"\"Called whenever the mouse moves. \"\"\" self.player.center_x = x self.player.center_y =",
"bullet ... |
[
"gather Infos and demonstrate the use of Variables. usrName = input(\"What is your",
"will gather Infos and demonstrate the use of Variables. usrName = input(\"What is",
"to improve your GPA by %f points to have a perfect score.\" %",
"get a new line print (\"Hello, %s\" % (usrName)) print (\"Did you know",
... |
[
"<reponame>AmitHasanShuvo/Programming a = input() a = a.replace('--', '2') a = a.replace('-.', '1') a",
"= input() a = a.replace('--', '2') a = a.replace('-.', '1') a = a.replace('.',",
"a = a.replace('--', '2') a = a.replace('-.', '1') a = a.replace('.', '0') print(a)",
"a = input() a = a.replace('--', '2') ... |
[
"class Message: def __init__(self, from_channel=None, **kwargs): self._channel = from_channel if kwargs is not",
"from_channel=None, **kwargs): self._channel = from_channel if kwargs is not None: for key, value",
"for key, value in kwargs.items(): setattr(self, key, value) @property def carrier(self): return se... |
[
"stacks', extra={'stack': True}) self.assertEquals(len(self.client.events), 1) event = self.client.events.pop(0) self.assertTrue('stacktrace' in event) frames =",
"event['exception'] self.assertEquals(exc['type'], 'ValueError') self.assertEquals(exc['value'], 'This is a test ValueError') self.assertTrue('param_me... |
[
"@property def full(self): return '{0}/{1}'.format(self.major.name, self.name) @staticmethod def q_major_minor(dbsession, major, minor): cond =",
"= name class Mime(Base): def __init__(self, name, template, major): super().__init__() self.name = name",
"== major) if minor and minor != '*': cond.append(Mime.name... |
[
"json_data = json.loads(json_data) from django.http import HttpResponse, JsonResponse # jsonResponse做的工作也就是加上了dumps和content_type # return HttpResponse(json.dumps(json_data),",
"return HttpResponse(json.dumps(json_list),content_type=\"application/json\") from django.forms.models import model_to_dict for good in go... |
[
"classpath] command += jvm_properties + system_properties command += [main_class] command += options.arguments if",
"pathjoin(options.data_dir, 'etc')) if options.install_path != options.data_dir: create_symlink( pathjoin(options.install_path, 'plugin'), pathjoin(options.data_dir, 'plugin')) def build_java_execut... |
[
"from direct.task import Task from direct.actor.Actor import Actor import numpy as np class",
"__init__(self): ShowBase.__init__(self) # Load environment model self.scene = self.loader.loadModel(\"models/environment\") # Reparent model to",
"self.pandaActor.reparentTo(self.render) # Loop animation self.pandaAct... |
[] |
[
"your data. - package: package details. \"\"\" if df is None: raise ValueError(\"Can",
"variables: descriptions per series. - correlations: correlation matrices. - missing: missing value diagrams.",
"not isinstance(df, pd.DataFrame): warnings.warn(\"df is not of type pandas.DataFrame\") disable_progress_bar = n... |
[
"== \"__main__\": campers = ['PKUxk','THUsz_ai','THUsz_cs','THUsz_data','USTC_cs'] for camper in campers: filename = camper +",
"= index index += 1 if camper not in stds[stdsDict[name]].offers: stds[stdsDict[name]].offers.append(camper) stds[stdsDict[name]].offerNum +=",
"1 if camper not in stds[stdsDict[name]]... |
[
"keywords=KEYWORDS, entry_points={ 'console_scripts': [ 'futurize = libfuturize.main:main', 'pasteurize = libpasteurize.main:main' ] }, package_dir={'':",
"his/her Python 3 install, depending on the folder order in # sys.path. (Running",
"try: # If the user happens to run: # python2 setup.py build #",
"single... |
[
"from flask import Flask from .extensions import db from .routes import short from",
"import config def create_app(): \"\"\" Creates Flask App, connect to Database and register",
"routes\"\"\" app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = config.DATABASE_CONNECTION_URI app.config['SQLALCHEMY_TRA... |
[
"def html(url): user_agents = [ 'Mozilla/5.0 (Windows; U; Windows NT 5.1; it; rv:1.8.1.11)",
".NET CLR 2.0.50727)', 'Mozilla/5.0 (compatible; Konqueror/3.5; Linux) KHTML/3.5.5 (like Gecko) (Kubuntu)', 'Mozilla/5.0 (X11;",
"# title views answersnum asked_time tag_str active_time quest_content_ text answer_conten... |
[
"angl = np.array([np.full(shape=(75, 75), fill_value=angel).astype(np.float32) for angel in angl]) X_band_1 = (X_band_1 -",
"= np.array([np.array(band).astype(np.float32).reshape(75, 75) for band in df[\"band_1\"]]) X_band_2 = np.array([np.array(band).astype(np.float32).reshape(75, 75) for band",
"train_test_sp... |
[
"PolyaxonClient().experiment.resume( user, project_name, _experiment, config=config, update_code=update_code) Printer.print_success('Experiment was resumed with id {}'.format(response.id)) except",
"help=\"The job id.\") @click.option('--past', '-p', is_flag=True, help=\"Show the past logs.\") @click.option('--fo... |
[
"for which a + b + c = 1000. Find the product abc.",
"range(1, 1000): for b in range(1, 1000): for c in range(1, 1000): if",
"c in range(1, 1000): if a < b < c: if a +",
"c == 1000: if a**2 + b**2 == c**2: solved = True break",
"1000): for c in range(1, 1000): if a < b < c: if",
"solved = False for a in r... |
[
"import os from django.test import TestCase from unipath import Path from ....utils import",
"django.test import TestCase from unipath import Path from ....utils import refresh from ...media",
"os from django.test import TestCase from unipath import Path from ....utils import refresh",
"= t.fragments.all() se... |
[
"= entries[0].find(\"a\").next_sibling.text #We do next_sibling here because the source puts PFS links first,",
"requests.get(link) res.raise_for_status() soup = BeautifulSoup(res.text, 'lxml') feat = soup.find_all(\"div\", {'class':'main'}) detailraw = soup.find(\"meta\",",
"'Pathfinder 2.0 Ancestry feat list'... |
[
"some kind of structure with numbers of question and space to answer. print",
"# randomly selecting from strings within each question list for each_question in range",
"don't understand. #printing some kind of structure with numbers of question and space",
"def Randomise(questions_lists): import random import... |
[
"TestScrapeFunctions(unittest.TestCase): def test_build_url(self): url = scrape.build_url(\"indeed\", \"/jobs?q=Data+Scientist&l=Texas&start=10\", join_next=True) expected = (\"https://www.indeed.com/\" \"jobs?q=Data+Scientist&l=Texas&start=10\") url2",
"def test_fetch_page(self): fpl = scrape.fetch_page_listings... |
[
"print(\"|q p| /}\") print(\"( 0 )\\\"\\\"\\\"\\\\\") print(\"|\\\"^\\\"` |\") print(\"||_/=\\\\\\\\__|\") if __name__ == \"__main__\":",
"def main(): print(\"|\\_/|\") print(\"|q p| /}\") print(\"( 0 )\\\"\\\"\\\"\\\\\") print(\"|\\\"^\\\"` |\") print(\"||_/=\\\\\\\\__|\") if",
"main(): print(\"|\\_/|\") print... |
[
"tf-idf model and classifiers ClassificationUtils.save_classifier(\"ada_bag_cook.pickle\",adaboost) ClassificationUtils.save_classifier(\"rf_bag_cook.pickle\",randomforest) ClassificationUtils.save_classifier(\"extree_bag_cook.pickle\",extratrees) ClassificationUtils.save_classifier(\"bagging_bag_cook.pickle\",bagg... |
[
"range(52)] # Create suits and ranks lists suits = [\"Spades\", \"Hearts\", \"Diamonds\", \"Clubs\"]",
"\"8\", \"9\", \"10\", \"Jack\", \"Queen\", \"King\"] # Shuffle the cards random.shuffle(deck) # Display",
"of cards deck = [x for x in range(52)] # Create suits and",
"[\"Ace\", \"2\", \"3\", \"4\", \"5\", ... |
[
"self.built = True def message_function(self, edge_source_states, edge_target_states, num_incoming_to_node_per_message, num_outing_to_node_per_message, edge_type_idx): \"\"\" :param edge_source_states:",
"True def message_function(self, edge_source_states, edge_target_states, num_incoming_to_node_per_message, num... |
[
"\"\"\" Deletes a model. If a model is already deployed, this only deletes",
"Unless required by applicable law or agreed to in writing, software # distributed",
"name = client.model_path('[PROJECT]', '[LOCATION]', '[MODEL]') >>> >>> response = client.get_model(name) Args: name (str):",
"default_timeout=self.... |
[
"user_names)) def _compute_attachment_ids(self): for task in self: attachment_ids = self.env['ir.attachment'].search([('res_id', '=', task.id), ('res_model',",
"= self.env.context.get('default_project_id', False) if project_id: name = self.env['project.project'].browse(project_id).label_tasks if name: tname = nam... |
[
"import import_module class Config(object): \"\"\" Base class for all config variables \"\"\" DEBUG",
"class Config(object): \"\"\" Base class for all config variables \"\"\" DEBUG = False",
"Config File for enviroment variables \"\"\" import os from importlib import import_module class",
"True KEY_ON_TEST = ... |
[
"as MysqlSelectDao from postgres_dao.ddl_dao import DdlDao from postgres_dao.dml_dao import DmlDao as PsqlDmlDao psql_ddl_dao",
"import SelectDao as MysqlSelectDao from postgres_dao.ddl_dao import DdlDao from postgres_dao.dml_dao import DmlDao as",
"postgres_dao.ddl_dao import DdlDao from postgres_dao.dml_dao i... |
[
"BlobGenerator class DocsTests(BaseTestCase): def setUp(self): super(DocsTests, self).setUp() def tearDown(self): super(DocsTests, self).tearDown() def test_docs_int_big_values(self):",
"self.fail(\"Able to create documents with value: %s\" % str(number)) #docs.docs.DocsTests.test_load_memory,nodes_init=3,standar... |
[
"URL!!!') excel_url = get_excel_url(url) excel_url = excel_url.replace(' ','%20') print('Download excel file!!!') save_at =",
"str(td_tag.a['href']).replace('..', ROOT) def get_excel_url(url): r = requests.get(url) soup = BeautifulSoup(r.text,'lxml') list_span_tags = soup.find_all('span',class_='txt_l4')",
"req... |
[
"request. Returns: The list of items loaded from BigQuery. \"\"\" table_id = f'process_items_to_{operation.value}_{task.timestamp}'",
"item_failures = [ failure.Failure(str(item_row.get('item_id', 'Missing ID')), error_reason) for item_row in item_rows ] api_result",
"if not items: logging.error( 'Batch #%d, op... |
[
"lifted = _loop_lift_modify_blocks(func_ir, loopinfo, blocks, typingctx, targetctx, flags, locals) loops.append(lifted) # Make main",
"blocks[loopinfo.callfrom] scope = entry_block.scope loc = entry_block.loc # Lowering assumes the first block",
"object and extra info. The extra contains the arguments if the co... |
[
"mask = np.zeros((WIDTH // 2, HEIGHT // 2)) mask[100, 100] = 1 np.save(MASK1,",
"[ [[243, 243], [243, 243]], [[243, 243], [243, 243]], [[243, 243], [243, 243]],",
"@skipUnless(has_osl, \"Requires OpenSlide\") @skip_if_quick def test_read_patches_openslide(self, input_parameters, expected): dataset = MaskedInfer... |
[
"[b''] def get_files(self): items = self.document_fromstring(self.content, self.img_selector) return [i.get('data-file').replace('&', '&') for i in",
"from .helpers.std import Std class DoujinsCom(Provider, Std): img_selector = '#image-container img.doujin' def get_archive_name(self)",
"DoujinsCom(Provider,... |
[
"import QItemDelegate, QWidget, QStyleOptionViewItem, QCheckBox class CheckBoxDelegate(QItemDelegate): def __init__(self, parent=None): super().__init__(parent) self.enabled =",
"parent=None): super().__init__(parent) self.enabled = True def createEditor(self, parent: QWidget, option: QStyleOptionViewItem, index:... |
[
"= tflearn.embedding(net, input_dim=10000, output_dim=128) net = tflearn.simple_rnn(net, neurons_num, dropout=keep_prob) net = tflearn.fully_connected(net, 2,",
"to_categorical(Y, 2) #Build the network net = tflearn.input_data([None, 5]) net = tflearn.embedding(net, input_dim=10000,",
"32 # Batch size n_epoch =... |
[
"real data in logits, 0 where there's padding dim: int. dimension over which",
"2 M = 3 BS = 10 def my_softmax(arr): max_elements = np.reshape(np.max(arr, axis",
"but with 1e30 subtracted (i.e. very large negative number) in the padding locations.",
"M = 3 BS = 10 def my_softmax(arr): max_elements = np.reshap... |
[
"median_smooth(spec1, width) compare_flux(spec1_smoothed.flux.value, flux_smoothed_astropy, flux_original.value, rtol=0.15) # Check the input and output units",
"difficult as smoothing will make a difference for median filter, but less so",
"(area under the kernel = 1). In this second case the rtol (relative",
... |
[
"a mathematical function from a given set of points using either linear, polynomial",
"method (string): name of the interpolation method to be used Returns: intfunc: interpolated",
"name of the interpolation method to be used Returns: intfunc: interpolated function \"\"\"",
"intfunc: interpolated function \"\... |
[
"<filename>frappe/patches/v13_0/remove_web_view.py import frappe def execute(): frappe.delete_doc_if_exists(\"DocType\", \"Web View\") frappe.delete_doc_if_exists(\"DocType\", \"Web View Component\") frappe.delete_doc_if_exists(\"DocType\",",
"import frappe def execute(): frappe.delete_doc_if_exists(\"DocType\", ... |
[
"= lambda x: x*slope + intercept fit_y = [f(min(X)), f(max(X))] plt.xlabel('Free Throw Attempts')",
"X.append(ft_dif) y.append(pt_dif) c = 0 for f, p in zip(X, y): if f",
"as f: df = json.load(f) X, y = [], [] for match, stats",
"away['mp'] != '240': continue try: ft_dif = float(home['fta']) - float(away['fta... |
[
"y_tr), (ID_val, X_num_val, X_img_val, y_val) def load_test_data(): ID, X_num_test = load_numeric_test() X_img_test =",
"h1, h2, w1, w2 = 0, h, 0, w X[i][h1:h2, w1:w2][:] = x",
"load_test_data(): ID, X_num_test = load_numeric_test() X_img_test = load_img_data(ID) return ID, X_num_test, X_img_test print('Loading... |
[
"coding: utf-8 -*- n, w = map(int, input().split()) for _ in range(n): entrada",
"n, w = map(int, input().split()) for _ in range(n): entrada = input() last_space",
"_ in range(n): entrada = input() last_space = entrada.rfind(' ') if int(entrada[last_space:]) >",
"-*- n, w = map(int, input().split()) for _ in... |
[
"ast.CompExpr( ast.FeatureRef(0), ast.NumVal(1.5), ast.CompOpType.LTE), ast.NumVal(1.0), ast.NumVal(2.0)), ast.BinNumOpType.ADD), ast.NumVal(0.5), ast.BinNumOpType.MUL) assert utils.cmp_exprs(actual, expected) def",
"from tests import utils def test_single_condition(): estimator = ensemble.RandomForestRegressor(n... |
[
"import os from setuptools import setup, find_packages, Extension import pynumenc_meta # pylint: disable=redefined-builtin",
"pylint: disable=invalid-name with open(os.path.join(here, 'README.rst'), encoding='utf-8') as f: long_description = f.read() # pylint:",
"License', 'Programming Language :: Python :: 3.5... |
[
"analysis and labelling were used Parameters: ----------- a_license_plate: 2D numpy binary image of",
"else: roismall = resize(roi, (20,20)) samples = np.concatenate((samples[:,:,:], roismall[None,:,:]), axis=0) cord.append(regions.bbox) column_list.append(minimumCol) if",
"where the license plate charcters are... |
[
":return: string \"\"\" try: payload = { 'exp': datetime.datetime.utcnow() + datetime.timedelta(days=0, seconds=5), 'iat':",
"def check_blacklist(auth_token): # Check whether auth token has been blacklisted res = BlacklistToken.query.filter_by(token=str(auth_token)).first()",
"unique=True, nullable=False) black... |
[
"import setup from setuptools import find_packages def read_file(filename, encoding='utf8'): \"\"\"Read unicode from given",
"= os.path.abspath(os.path.dirname(__file__)) readme = read_file(os.path.join(here, 'README.rst')) # This package is a simple shim",
"Python :: 2', 'Programming Language :: Python :: 2.6'... |
[
"jira_ part. Convert underscores to spaces normalized_jira_field = jira_field[5:].replace('_', ' ').lower() # All",
"%s at %s:' % (self.rule['name'], match[qk], lookup_es_key(match, self.rule['timestamp_field'])) ) fullmessage['match'] = match[qk] else:",
"a query_key, use that in the title if 'query_key' in se... |
[
"in args assert 'OMF to PI north' in args assert 'North Readings to",
"scheduler._schedule_executions[sch_id] # WHEN scheduler._schedule_first_task(sch, current_time) time_after_call = sch_execution.next_start_time # THEN assert time_after_call >",
"log_info.assert_has_calls(calls, any_order=True) assert 1 == a... |
[
"you solve based on the highest calorie to lowest calorie cupcake Args: calorie",
"\"__main__\": assert marcs_cakewalk([5, 10, 7]) == 44 assert marcs_cakewalk([1, 3, 2]) == 11",
"highest calorie to lowest calorie cupcake Args: calorie (list): List of integers denoting",
"the highest calorie to lowest calorie ... |
[
"context = { 'corona_info': info, 'data': sorted(corona_info, key=lambda i: int(''.join(i['confirm_case'].replace(',', ''))), reverse=True) }",
"state.find_all('div', class_='tick-death')[0].find_all('small')[0].string } for state in state_wise_data ] context = { 'corona_info': info,",
"info = { 'update_data': ... |
[
"[] model_out = [] comp_out = [] for etype in ['EQS','EQP','SUS','SUP','THS','THP','SNS','SNP','PXS','PXP']: arrival =",
"= open(comp_out, 'w') truth_arr = read_arrivals_to_arr(arrival) # read in the arrival times to",
"= 'P' times = key_lookup(event, phase, model_dict) if len(times) == 0: phase =",
"model_di... |
[
"chunk_multiplier + frame_number def insert_images( img_raw_paths, img_types, img_metadatas, game_id, frame_numbers ): command =",
"Pool from ultitrackerapi import get_backend, get_logger, get_s3Client, video backend_instance = get_backend() logger =",
"os.remove(video_filename) os.remove(thumbnail_filename) sh... |
[
"Predict the most probable class hard_predictions = voting.predict(x_test) # --- SECTION 6 ---",
"# --- SECTION 1 --- # Import the required libraries import matplotlib as",
"Import the required libraries import matplotlib as mpl import matplotlib.pyplot as plt mpl.style.use('seaborn-paper')",
"2 --- # Get the... |
[
"] operations = [ migrations.AlterField( model_name='news', name='date_time', field=models.DateTimeField(default=datetime.datetime(2022, 3, 23, 17, 31, 17,",
"django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('API', '0004_alter_news_date_time_alter_news_headline'), ] ope... |
[
"1)).fit(samples) sample_train = minmax_scale.transform(sample_train) sample_test = minmax_scale.transform(sample_test) # Pick training size number of",
"from sklearn.preprocessing import StandardScaler, MinMaxScaler from sklearn.decomposition import PCA from qiskit.aqua import MissingOptionalLibraryError",
"sa... |
[
"controller.oauth.validate_authorization_request.assert_called_once_with( pyramid_request.url) @pytest.mark.parametrize('view_name', ['get', 'get_web_message']) def test_get_raises_for_invalid_request(self, controller, view_name): controller.oauth.validate_authorization_request.side_effect = InvalidRequestFatalErro... |
[
"file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) # Test conditional properties. import BoostBuild",
"Arrange a project which will build only if 'a.cpp' is compiled with \"STATIC\"",
"if 'a.cpp' is compiled with \"STATIC\" # define. t.write(\"a.cpp\", \"\"\"\\ #ifdef STATIC int",
"int m... |
[
"<gh_stars>1-10 from setuptools_rust_starter import PythonClass, ExampleClass def test_python_class() -> None: py_class = PythonClass(value=10)",
"= PythonClass(value=10) assert py_class.value == 10 def test_example_class() -> None: example = ExampleClass(value=11)",
"PythonClass, ExampleClass def test_python_c... |
[
"self._login_uid: Optional[str] = None self._login_client_id: Optional[str] = None self._response_data = None self._blogs_data: List",
"login_params if \"uid\" in d][ 0 ].replace(\"uid=\", \"\") self._login_token = [d for d",
"next_page_variable = personal_blog[\"verifyCreatedAt\"] if self._response_data[\"d\"]... |
[
"36, 40, 44, 48, 52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48,",
"52, 56, 60, 64]) # channel_optional.append([36, 40, 44, 48, 52, 56,60, 64]) else:",
"ResNet20(100, channel_list) net2 = ResNet20(100, channel_list) net2.set_state_dict(paddle.load('./pretrained_model/resnet20.pdparams')) channel_opt... |
[
"AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,",
"a Pastebin link. \"\"\" await self.create_slash_tag(ctx, tag_name, link, is_global=False) @commands.mod_or_permissions(manage_guild=True) @slashtag.group(\"edit\", aliases=[\"e\"], invoke_without_command=True)",
"@classmethod ... |
[
"str1 [::-1]: l1 = i+l1 print(l1) if str1 == l1: print(\"string is a",
"== l1: print(\"string is a palindrome\") else : print(\"string is not a palindrome\")",
"string :\") l1 =\"\" for i in str1 [::-1]: l1 = i+l1 print(l1)",
"= i+l1 print(l1) if str1 == l1: print(\"string is a palindrome\") else :",
"str1 ... |
[
"div.xpath('.//a[@class=\"name\"]/@href').get() img_url = div.xpath('.//img/@src').get() d = { 'brand': brand.replace('-', '') or None, \"purity\":",
"for package_obj in packages: catalog_price = package_obj.get(\"CatalogPrice\", {}) dd = { 'brand': d.get('brand'),",
"rel_url), 'img_url': img_url and urljoin(re... |
[
"todo check if rational def updateObservation(self): self.observation[0] = self.ego.lanePos self.observation[1] = self.ego.speed self.observation[2]",
"if not self.is_success: if action_lateral == 1: # and abs(self.ego.pos_lat - (0.5+self.ego.targetLane)*self.rd.laneWidth) >",
"self.ego = self.veh_dict[self.ego... |
[
"True ) def handler(event, context): r = requests.get('https://endpoints.office.com/version?clientrequestid='+str(uuid.uuid4())) logger.info('Link Status Code: '+str(r.status_code)) if",
"== 200: for cidr in cidrs: try: if len(cidr['ips']) != 0: for ip",
"r.json() logger.info(versions) for version in versions: ... |
[
"= Company(\"Example Inc\") c.add_flow(FixedCost(\"Initial Cash\", -500000)) c.add_flow(FixedCost(\"Incorporation\", 500)) c.add_flow(ConstantCost(\"Office\", 50000)) c.add_flow(PeriodicCost(\"Subscription\", 4000, \"2012-01-05\",",
"ConstantCost(\"Office\", 50000))) c.add_flow(DelayedCost(\"2012-02-01\", FixedCo... |
[
"ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1', address), stdout=subprocess.PIPE, stderr=subprocess.PIPE)",
"= logging.getLogger(__name__) class ValidatorError(Exception): pass def ping(address): try: subprocess.check_call(('ping', '-c 1', '-W 1',",
"addre... |
[
"<reponame>Open-EO/openeo-geopyspark-driver from openeo.udf import XarrayDataCube def apply_datacube(cube: XarrayDataCube, context: dict) -> XarrayDataCube: return",
"from openeo.udf import XarrayDataCube def apply_datacube(cube: XarrayDataCube, context: dict) -> XarrayDataCube: return cube"
] |
[
"gave the resource home, look 4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player)",
"look 4 resources again if(not self.player.hasResources()): self.player.state = StateLook4Resources(self.player) return create_purchase_action(0) return create_move_action(mov... |
[
"same velocity along +x for 3 steps. It will bounce back in y",
"self.assertAlmostEqual(slit.H, 2.) self.assertAlmostEqual(slit.V, 0.) self.assertEqual(slit.boundary, \"no_slip\") self.assertAlmostEqual(slit._cpp.geometry.getH(), 2.) self.assertAlmostEqual(slit._cpp.geometry.getVelocity(), 0.) self.assertEqual(sl... |
[
"models.QuestionGroupDTO( self.second_question_group_id, {'description': self.second_question_group_description, 'items': [{'question': str(self.used_twice_question_id)}]}) self.third_question_group_description = 'third_question_group' self.third_question_group_id = 6",
"'user_id' student = models.Student(key_nam... |
[
"signal to. Must be more than twice lowpass-cutoff. (default: 4000) delta_pitch( float, optional):",
"of the phases inverse = torch.istft(specgram * angles, n_fft=n_fft, hop_length=hop_length, win_length=win_length, window=window, length=length).float()",
"int = 100, center: bool = False, norm_vars: bool = Fals... |
[
"mode = 'None' elif mode == 'Posctl': mode = 'Position' elif mode ==",
"latitude = self.gps.latitude longitude = self.gps.longitude altitude = round(self.gps.altitude, 2) status_gps = f'{latitude:.7f}",
"(XYZ) {roll} {pitch} {yaw} (RPY)') row += 1 # Setpoint v = self.setpoint.velocity",
"ExtendedState, Positi... |
[
"instance (nrows=ncols=index) bp = ax.boxplot(data, widths=0.6) set_box_format(bp, '000') # set and format litle,",
"remove frame ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False) # thicken frame ax.spines['left'].set_linewidth(2) ax.spines['bottom'].set_linewidth(2) # adjust min and",
"... |