body stringlengths 26 98.2k | body_hash int64 -9,222,864,604,528,158,000 9,221,803,474B | docstring stringlengths 1 16.8k | path stringlengths 5 230 | name stringlengths 1 96 | repository_name stringlengths 7 89 | lang stringclasses 1
value | body_without_docstring stringlengths 20 98.2k |
|---|---|---|---|---|---|---|---|
def load_command(self, command, flags, user_level, code, set=True):
'\n Load a command in the runtime\n\n :param command: What is the command called\n :param flags: Command flags\n :param user_level: The minimum user level to run the command\n :param code: The Lua code for the cus... | -1,585,351,775,516,527,400 | Load a command in the runtime
:param command: What is the command called
:param flags: Command flags
:param user_level: The minimum user level to run the command
:param code: The Lua code for the custom command
:param set: Should the command be set on the bot via set_command,
set this to False when loading... | bot/commandmanager.py | load_command | lietu/twitch-bot | python | def load_command(self, command, flags, user_level, code, set=True):
'\n Load a command in the runtime\n\n :param command: What is the command called\n :param flags: Command flags\n :param user_level: The minimum user level to run the command\n :param code: The Lua code for the cus... |
def run_command(self, nick, user_level, command, args=None, timestamp=None, threaded=True):
"\n Handles running of custom commands from chat\n\n :param nick: The calling user\n :param user_level: The calling user's level\n :param command: The command triggered\n :param args: The w... | 309,166,365,526,661,400 | Handles running of custom commands from chat
:param nick: The calling user
:param user_level: The calling user's level
:param command: The command triggered
:param args: The words on the line after the command
:param timestamp: The unixtime for when the event happened
:return: Any return value from the custom Lua comm... | bot/commandmanager.py | run_command | lietu/twitch-bot | python | def run_command(self, nick, user_level, command, args=None, timestamp=None, threaded=True):
"\n Handles running of custom commands from chat\n\n :param nick: The calling user\n :param user_level: The calling user's level\n :param command: The command triggered\n :param args: The w... |
def load_lua(self, code):
'\n Load Lua code in our runtime\n\n :param code: The Lua code\n :return: None\n '
self.lua.execute(code) | -9,147,439,341,931,043,000 | Load Lua code in our runtime
:param code: The Lua code
:return: None | bot/commandmanager.py | load_lua | lietu/twitch-bot | python | def load_lua(self, code):
'\n Load Lua code in our runtime\n\n :param code: The Lua code\n :return: None\n '
self.lua.execute(code) |
def _parse_func(self, args):
'\n Process the given arguments into a function definition\n\n :param args: List of the words after the "def" command\n :return: Function name, if it wants the caller\'s user name,\n the required user level, and the function\'s Lua code\n :rai... | -3,807,910,362,400,559,000 | Process the given arguments into a function definition
:param args: List of the words after the "def" command
:return: Function name, if it wants the caller's user name,
the required user level, and the function's Lua code
:raise argparse.ArgumentError: There was something wrong with the args | bot/commandmanager.py | _parse_func | lietu/twitch-bot | python | def _parse_func(self, args):
'\n Process the given arguments into a function definition\n\n :param args: List of the words after the "def" command\n :return: Function name, if it wants the caller\'s user name,\n the required user level, and the function\'s Lua code\n :rai... |
def _parse_simple_func(self, args):
'\n Process the given arguments into a simple function definition\n\n :param args: List of the words after the "com" command\n :return: Function name, if it wants the caller\'s user name,\n the required user level, and the function\'s Lua code... | -820,046,322,053,778,800 | Process the given arguments into a simple function definition
:param args: List of the words after the "com" command
:return: Function name, if it wants the caller's user name,
the required user level, and the function's Lua code
:raise argparse.ArgumentError: There was something wrong with the args | bot/commandmanager.py | _parse_simple_func | lietu/twitch-bot | python | def _parse_simple_func(self, args):
'\n Process the given arguments into a simple function definition\n\n :param args: List of the words after the "com" command\n :return: Function name, if it wants the caller\'s user name,\n the required user level, and the function\'s Lua code... |
def _is_under_cooldown(self, command, timestamp):
"\n Check if this command's cooldown period is in effect\n :param command: Which command\n :param timestamp: What is the timestamp it was issued on\n :return:\n "
if (command in self.commands_last_executed):
if ('cooldo... | 962,702,915,414,738,800 | Check if this command's cooldown period is in effect
:param command: Which command
:param timestamp: What is the timestamp it was issued on
:return: | bot/commandmanager.py | _is_under_cooldown | lietu/twitch-bot | python | def _is_under_cooldown(self, command, timestamp):
"\n Check if this command's cooldown period is in effect\n :param command: Which command\n :param timestamp: What is the timestamp it was issued on\n :return:\n "
if (command in self.commands_last_executed):
if ('cooldo... |
def _set_last_executed_time(self, command, timestamp):
'\n Save the last execution time of a command\n :param command: Which command\n :param timestamp: What is the timestamp it was issued on\n :return:\n '
self.commands_last_executed[command] = timestamp | -3,623,127,483,259,920,000 | Save the last execution time of a command
:param command: Which command
:param timestamp: What is the timestamp it was issued on
:return: | bot/commandmanager.py | _set_last_executed_time | lietu/twitch-bot | python | def _set_last_executed_time(self, command, timestamp):
'\n Save the last execution time of a command\n :param command: Which command\n :param timestamp: What is the timestamp it was issued on\n :return:\n '
self.commands_last_executed[command] = timestamp |
def _level_name_to_number(self, name):
'\n Convert the given user level to a number\n\n :param name: Level name\n :return: A number between 0 and Infinity, higher number is higher\n user level\n :raise ValueError: In case of invalid user level\n '
levels = ['us... | -4,419,965,674,233,182,700 | Convert the given user level to a number
:param name: Level name
:return: A number between 0 and Infinity, higher number is higher
user level
:raise ValueError: In case of invalid user level | bot/commandmanager.py | _level_name_to_number | lietu/twitch-bot | python | def _level_name_to_number(self, name):
'\n Convert the given user level to a number\n\n :param name: Level name\n :return: A number between 0 and Infinity, higher number is higher\n user level\n :raise ValueError: In case of invalid user level\n '
levels = ['us... |
def _can_run_command(self, user_level, command):
"\n Check if this command can be run with the given user level\n\n :param user_level: The calling user's level\n :param command: The command being called\n :return: True of False\n "
need_level = self._level_name_to_number(self.... | -2,490,286,005,795,867,600 | Check if this command can be run with the given user level
:param user_level: The calling user's level
:param command: The command being called
:return: True of False | bot/commandmanager.py | _can_run_command | lietu/twitch-bot | python | def _can_run_command(self, user_level, command):
"\n Check if this command can be run with the given user level\n\n :param user_level: The calling user's level\n :param command: The command being called\n :return: True of False\n "
need_level = self._level_name_to_number(self.... |
def _inject_globals(self):
'\n Inject some Python objects and functions into the Lua global scope _G\n\n :return: None\n '
injector = self.lua.eval('\n function (key, value)\n _G[key] = value\n end\n ')
def log(message):
'\n ... | -6,403,042,037,872,840,000 | Inject some Python objects and functions into the Lua global scope _G
:return: None | bot/commandmanager.py | _inject_globals | lietu/twitch-bot | python | def _inject_globals(self):
'\n Inject some Python objects and functions into the Lua global scope _G\n\n :return: None\n '
injector = self.lua.eval('\n function (key, value)\n _G[key] = value\n end\n ')
def log(message):
'\n ... |
def log(message):
'\n Pass a message from Lua to the Python logger\n\n :param message: The message text\n :return: None\n '
self.logger.debug((u'Lua: ' + str(message))) | 294,852,574,707,328,300 | Pass a message from Lua to the Python logger
:param message: The message text
:return: None | bot/commandmanager.py | log | lietu/twitch-bot | python | def log(message):
'\n Pass a message from Lua to the Python logger\n\n :param message: The message text\n :return: None\n '
self.logger.debug((u'Lua: ' + str(message))) |
def test_basic_constants(self):
'\n Check that the basic constants are imported and visible.\n '
self.assertIsNotNone(ck.SEEK_TO_BEGINNING)
self.assertIsNotNone(ck.DONT_SEEK)
self.assertIsNotNone(ck.SEEK_TO_END)
self.assertIsNotNone(ck.ALL_PARTITIONS_SEEK_TO_BEGINNING)
self.assertI... | -8,485,359,525,170,984,000 | Check that the basic constants are imported and visible. | py/server/tests/test_kafka_consumer.py | test_basic_constants | lbooker42/deephaven-core | python | def test_basic_constants(self):
'\n \n '
self.assertIsNotNone(ck.SEEK_TO_BEGINNING)
self.assertIsNotNone(ck.DONT_SEEK)
self.assertIsNotNone(ck.SEEK_TO_END)
self.assertIsNotNone(ck.ALL_PARTITIONS_SEEK_TO_BEGINNING)
self.assertIsNotNone(ck.ALL_PARTITIONS_SEEK_TO_END)
self.assertI... |
def test_simple_spec(self):
'\n Check a simple Kafka subscription creates the right table.\n '
t = ck.consume({'bootstrap.servers': 'redpanda:29092'}, 'orders', key_spec=KeyValueSpec.IGNORE, value_spec=ck.simple_spec('Price', dtypes.double))
cols = t.columns
self.assertEqual(4, len(cols))
... | 5,960,851,227,852,433,000 | Check a simple Kafka subscription creates the right table. | py/server/tests/test_kafka_consumer.py | test_simple_spec | lbooker42/deephaven-core | python | def test_simple_spec(self):
'\n \n '
t = ck.consume({'bootstrap.servers': 'redpanda:29092'}, 'orders', key_spec=KeyValueSpec.IGNORE, value_spec=ck.simple_spec('Price', dtypes.double))
cols = t.columns
self.assertEqual(4, len(cols))
self._assert_common_cols(cols)
self.assertEqual('P... |
def test_json_spec(self):
'\n Check a JSON Kafka subscription creates the right table.\n '
t = ck.consume({'bootstrap.servers': 'redpanda:29092'}, 'orders', key_spec=KeyValueSpec.IGNORE, value_spec=ck.json_spec([('Symbol', dtypes.string), ('Side', dtypes.string), ('Price', dtypes.double), ('Qty', ... | 2,342,120,107,655,886,300 | Check a JSON Kafka subscription creates the right table. | py/server/tests/test_kafka_consumer.py | test_json_spec | lbooker42/deephaven-core | python | def test_json_spec(self):
'\n \n '
t = ck.consume({'bootstrap.servers': 'redpanda:29092'}, 'orders', key_spec=KeyValueSpec.IGNORE, value_spec=ck.json_spec([('Symbol', dtypes.string), ('Side', dtypes.string), ('Price', dtypes.double), ('Qty', dtypes.int_), ('Tstamp', dtypes.DateTime)], mapping={'js... |
def test_avro_spec(self):
'\n Check an Avro Kafka subscription creates the right table.\n '
schema = '\n { "type" : "record",\n "namespace" : "io.deephaven.examples",\n "name" : "share_price",\n "fields" : [\n { "name" : "Symbol", "t... | 485,627,723,911,774,850 | Check an Avro Kafka subscription creates the right table. | py/server/tests/test_kafka_consumer.py | test_avro_spec | lbooker42/deephaven-core | python | def test_avro_spec(self):
'\n \n '
schema = '\n { "type" : "record",\n "namespace" : "io.deephaven.examples",\n "name" : "share_price",\n "fields" : [\n { "name" : "Symbol", "type" : "string" },\n { "name" : "Side", ... |
@unittest.skip('https://github.com/deephaven/deephaven-core/pull/2277')
def test_deprecated_table_types(self):
'\n Tests to make sure deprecated TableTypes are equivalent\n '
self.assertEqual(TableType.append(), TableType.Append)
self.assertEqual(TableType.stream(), TableType.Stream) | -4,242,480,715,210,158,600 | Tests to make sure deprecated TableTypes are equivalent | py/server/tests/test_kafka_consumer.py | test_deprecated_table_types | lbooker42/deephaven-core | python | @unittest.skip('https://github.com/deephaven/deephaven-core/pull/2277')
def test_deprecated_table_types(self):
'\n \n '
self.assertEqual(TableType.append(), TableType.Append)
self.assertEqual(TableType.stream(), TableType.Stream) |
def test_table_types(self):
'\n Tests TableType construction\n '
_ = TableType.append()
_ = TableType.stream()
_ = TableType.ring(4096) | 2,499,055,364,101,107,700 | Tests TableType construction | py/server/tests/test_kafka_consumer.py | test_table_types | lbooker42/deephaven-core | python | def test_table_types(self):
'\n \n '
_ = TableType.append()
_ = TableType.stream()
_ = TableType.ring(4096) |
@classmethod
def from_dict(cls, dict_obj):
' Creates an Agent object from parameters stored in a dict. AgentSchema is used to validate inputs.'
return cls(**cls.AgentSchema().load(dict_obj, partial=['paw'])) | -4,173,985,643,143,858,000 | Creates an Agent object from parameters stored in a dict. AgentSchema is used to validate inputs. | app/objects/c_agent.py | from_dict | zaphodef/caldera | python | @classmethod
def from_dict(cls, dict_obj):
' '
return cls(**cls.AgentSchema().load(dict_obj, partial=['paw'])) |
def parse_duration(value: str) -> datetime.timedelta:
"Parse a duration string and return a datetime.timedelta.\n\n Args:\n value (str): A time duration given as text. The preferred format for\n durations is '%d %H:%M:%S.%f'. This function also supports ISO 8601\n representation and ... | -5,307,280,787,856,276,000 | Parse a duration string and return a datetime.timedelta.
Args:
value (str): A time duration given as text. The preferred format for
durations is '%d %H:%M:%S.%f'. This function also supports ISO 8601
representation and PostgreSQL's day-time interval format.
Returns:
datetime.timedelta: An inst... | pde/tools/parse_duration.py | parse_duration | lmenou/py-pde | python | def parse_duration(value: str) -> datetime.timedelta:
"Parse a duration string and return a datetime.timedelta.\n\n Args:\n value (str): A time duration given as text. The preferred format for\n durations is '%d %H:%M:%S.%f'. This function also supports ISO 8601\n representation and ... |
@query_many_property
def local_modules(self):
'Load local modules. Return SQLAlchemy query'
return self.modules.filter(Module.m.path.like('%{}%'.format(persistence_config.base_path))) | 34,532,395,116,731,730 | Load local modules. Return SQLAlchemy query | capture/noworkflow/now/persistence/models/trial.py | local_modules | raffaelfoidl/noworkflow | python | @query_many_property
def local_modules(self):
return self.modules.filter(Module.m.path.like('%{}%'.format(persistence_config.base_path))) |
@query_many_property
def modules(self):
'Load modules. Return SQLAlchemy query'
if self.inherited:
return self.inherited.modules
return self.dmodules | -2,528,479,259,529,810,400 | Load modules. Return SQLAlchemy query | capture/noworkflow/now/persistence/models/trial.py | modules | raffaelfoidl/noworkflow | python | @query_many_property
def modules(self):
if self.inherited:
return self.inherited.modules
return self.dmodules |
@query_many_property
def dependencies(self):
'Load modules. Return SQLAlchemy query'
if self.inherited:
return self.inherited.dependencies
return self.module_dependencies | -7,273,323,766,861,591,000 | Load modules. Return SQLAlchemy query | capture/noworkflow/now/persistence/models/trial.py | dependencies | raffaelfoidl/noworkflow | python | @query_many_property
def dependencies(self):
if self.inherited:
return self.inherited.dependencies
return self.module_dependencies |
@query_many_property
def initial_activations(self):
'Return initial activation as a SQLAlchemy query'
return self.activations.filter(is_none(Activation.m.caller_id)) | -7,233,818,596,856,919,000 | Return initial activation as a SQLAlchemy query | capture/noworkflow/now/persistence/models/trial.py | initial_activations | raffaelfoidl/noworkflow | python | @query_many_property
def initial_activations(self):
return self.activations.filter(is_none(Activation.m.caller_id)) |
@property
def prolog_variables(self):
'Return filtered prolog variables'
if (not self._prolog_visitor):
self.dependency_filter.run()
self._prolog_visitor = PrologVisitor(self.dependency_filter)
self._prolog_visitor.visit(self.dependency_filter.main_cluster)
return self._prolog_visito... | -397,316,024,569,532,600 | Return filtered prolog variables | capture/noworkflow/now/persistence/models/trial.py | prolog_variables | raffaelfoidl/noworkflow | python | @property
def prolog_variables(self):
if (not self._prolog_visitor):
self.dependency_filter.run()
self._prolog_visitor = PrologVisitor(self.dependency_filter)
self._prolog_visitor.visit(self.dependency_filter.main_cluster)
return self._prolog_visitor |
@property
def script_content(self):
'Return the "main" script content of the trial'
return PrettyLines(content.get(self.code_hash).decode('utf-8').split('/n')) | 5,959,198,191,165,273,000 | Return the "main" script content of the trial | capture/noworkflow/now/persistence/models/trial.py | script_content | raffaelfoidl/noworkflow | python | @property
def script_content(self):
return PrettyLines(content.get(self.code_hash).decode('utf-8').split('/n')) |
@property
def finished(self):
'Check if trial has finished'
return bool(self.finish) | 4,549,426,415,557,629,400 | Check if trial has finished | capture/noworkflow/now/persistence/models/trial.py | finished | raffaelfoidl/noworkflow | python | @property
def finished(self):
return bool(self.finish) |
@property
def status(self):
'Check trial status\n Possible statuses: finished, unfinished, backup'
if (not self.run):
return 'backup'
return ('finished' if self.finished else 'unfinished') | 3,606,235,992,606,115,000 | Check trial status
Possible statuses: finished, unfinished, backup | capture/noworkflow/now/persistence/models/trial.py | status | raffaelfoidl/noworkflow | python | @property
def status(self):
'Check trial status\n Possible statuses: finished, unfinished, backup'
if (not self.run):
return 'backup'
return ('finished' if self.finished else 'unfinished') |
@property
def duration(self):
'Calculate trial duration. Return microseconds'
if self.finish:
return int(((self.finish - self.start).total_seconds() * 1000000))
return 0 | -3,282,620,830,210,900,000 | Calculate trial duration. Return microseconds | capture/noworkflow/now/persistence/models/trial.py | duration | raffaelfoidl/noworkflow | python | @property
def duration(self):
if self.finish:
return int(((self.finish - self.start).total_seconds() * 1000000))
return 0 |
@property
def duration_text(self):
'Calculate trial duration. Return formatted str'
if self.finish:
return str((self.finish - self.start))
return 'None' | -530,437,388,138,204,860 | Calculate trial duration. Return formatted str | capture/noworkflow/now/persistence/models/trial.py | duration_text | raffaelfoidl/noworkflow | python | @property
def duration_text(self):
if self.finish:
return str((self.finish - self.start))
return 'None' |
@property
def environment(self):
'Return dict: environment variables -> value'
return {e.name: e.value for e in self.environment_attrs} | 3,438,829,612,525,810,700 | Return dict: environment variables -> value | capture/noworkflow/now/persistence/models/trial.py | environment | raffaelfoidl/noworkflow | python | @property
def environment(self):
return {e.name: e.value for e in self.environment_attrs} |
def versioned_files(self, skip_script=False, skip_local=False, skip_access=False):
'Find first files accessed in a trial\n Return map with relative path -> (code_hash, type)\n\n Possible types: script, module, access\n '
files = {}
def add(path, info):
'Add file to dict'
... | 7,804,030,863,116,041,000 | Find first files accessed in a trial
Return map with relative path -> (code_hash, type)
Possible types: script, module, access | capture/noworkflow/now/persistence/models/trial.py | versioned_files | raffaelfoidl/noworkflow | python | def versioned_files(self, skip_script=False, skip_local=False, skip_access=False):
'Find first files accessed in a trial\n Return map with relative path -> (code_hash, type)\n\n Possible types: script, module, access\n '
files = {}
def add(path, info):
'Add file to dict'
... |
def iterate_accesses(self, path=None):
'Iterate on all access to a path'
if ((not path) or self.script.endswith(path)):
(yield (self.script, {'code_hash': self.code_hash, 'type': 'script'}))
for module in self.local_modules:
if ((not path) or module.path.endswith(path)):
(yield (... | 5,028,473,455,695,651,000 | Iterate on all access to a path | capture/noworkflow/now/persistence/models/trial.py | iterate_accesses | raffaelfoidl/noworkflow | python | def iterate_accesses(self, path=None):
if ((not path) or self.script.endswith(path)):
(yield (self.script, {'code_hash': self.code_hash, 'type': 'script'}))
for module in self.local_modules:
if ((not path) or module.path.endswith(path)):
(yield (module.path, {'code_hash': module... |
def create_head(self):
'Create head for this trial'
session = relational.make_session()
session.query(Head.m).filter((Head.m.script == self.script)).delete()
session.add(Head.m(trial_id=self.id, script=self.script))
session.commit() | -2,086,893,957,433,139,000 | Create head for this trial | capture/noworkflow/now/persistence/models/trial.py | create_head | raffaelfoidl/noworkflow | python | def create_head(self):
session = relational.make_session()
session.query(Head.m).filter((Head.m.script == self.script)).delete()
session.add(Head.m(trial_id=self.id, script=self.script))
session.commit() |
def query(self, query):
'Run prolog query'
return self.prolog.query(query) | 1,142,936,998,032,021,000 | Run prolog query | capture/noworkflow/now/persistence/models/trial.py | query | raffaelfoidl/noworkflow | python | def query(self, query):
return self.prolog.query(query) |
def _ipython_display_(self):
'Display history graph'
if hasattr(self, 'graph'):
return self.graph._ipython_display_()
from IPython.display import display
display({'text/plain': 'Trial {}'.format(self.id)}, raw=True) | 4,845,852,689,895,969,000 | Display history graph | capture/noworkflow/now/persistence/models/trial.py | _ipython_display_ | raffaelfoidl/noworkflow | python | def _ipython_display_(self):
if hasattr(self, 'graph'):
return self.graph._ipython_display_()
from IPython.display import display
display({'text/plain': 'Trial {}'.format(self.id)}, raw=True) |
def show(self, _print=print):
'Print trial information'
_print(' Id: {t.id}\n Inherited Id: {t.inherited_id}\n Script: {t.script}\n Code hash: {t.code_hash}\n Start: {t.start}\n Finish: {t.finish}\n Duration: {t.duration_text} ... | -3,123,170,109,015,617,500 | Print trial information | capture/noworkflow/now/persistence/models/trial.py | show | raffaelfoidl/noworkflow | python | def show(self, _print=print):
_print(' Id: {t.id}\n Inherited Id: {t.inherited_id}\n Script: {t.script}\n Code hash: {t.code_hash}\n Start: {t.start}\n Finish: {t.finish}\n Duration: {t.duration_text} '.format(t=self)) |
@classmethod
def distinct_scripts(cls):
'Return a set with distinct scripts'
return {s[0].rsplit('/', 1)[(- 1)] for s in relational.session.query(distinct(cls.m.script))} | -6,364,750,551,788,056,000 | Return a set with distinct scripts | capture/noworkflow/now/persistence/models/trial.py | distinct_scripts | raffaelfoidl/noworkflow | python | @classmethod
def distinct_scripts(cls):
return {s[0].rsplit('/', 1)[(- 1)] for s in relational.session.query(distinct(cls.m.script))} |
@classmethod
def reverse_trials(cls, limit, session=None):
'Return a generator with <limit> trials ordered by start time desc'
session = (session or relational.session)
return proxy_gen(session.query(cls.m).order_by(cls.m.start.desc()).limit(limit)) | -3,460,930,242,788,007,000 | Return a generator with <limit> trials ordered by start time desc | capture/noworkflow/now/persistence/models/trial.py | reverse_trials | raffaelfoidl/noworkflow | python | @classmethod
def reverse_trials(cls, limit, session=None):
session = (session or relational.session)
return proxy_gen(session.query(cls.m).order_by(cls.m.start.desc()).limit(limit)) |
@classmethod
def last_trial(cls, script=None, parent_required=False, session=None):
'Return last trial according to start time\n\n Keyword arguments:\n script -- specify the desired script (default=None)\n parent_required -- valid only if script exists (default=False)\n '
model = cls... | 5,395,468,279,525,787,000 | Return last trial according to start time
Keyword arguments:
script -- specify the desired script (default=None)
parent_required -- valid only if script exists (default=False) | capture/noworkflow/now/persistence/models/trial.py | last_trial | raffaelfoidl/noworkflow | python | @classmethod
def last_trial(cls, script=None, parent_required=False, session=None):
'Return last trial according to start time\n\n Keyword arguments:\n script -- specify the desired script (default=None)\n parent_required -- valid only if script exists (default=False)\n '
model = cls... |
@classmethod
def find_by_name_and_time(cls, script, timestamp, trial=None, session=None):
'Return the first trial according to script and timestamp\n\n Arguments:\n script -- specify the desired script\n timestamp -- specify the start of finish time of trial\n\n Keyword Arguments:\n ... | -5,874,113,822,201,334,000 | Return the first trial according to script and timestamp
Arguments:
script -- specify the desired script
timestamp -- specify the start of finish time of trial
Keyword Arguments:
trial -- limit query to a specific trial | capture/noworkflow/now/persistence/models/trial.py | find_by_name_and_time | raffaelfoidl/noworkflow | python | @classmethod
def find_by_name_and_time(cls, script, timestamp, trial=None, session=None):
'Return the first trial according to script and timestamp\n\n Arguments:\n script -- specify the desired script\n timestamp -- specify the start of finish time of trial\n\n Keyword Arguments:\n ... |
@classmethod
def load_trial(cls, trial_ref, session=None):
'Load trial by trial reference\n\n Find reference on trials id and tags name\n '
from .tag import Tag
session = (session or relational.session)
return session.query(cls.m).outerjoin(Tag.m).filter(((cls.m.id == trial_ref) | (Tag.m.n... | -3,829,412,513,214,292,000 | Load trial by trial reference
Find reference on trials id and tags name | capture/noworkflow/now/persistence/models/trial.py | load_trial | raffaelfoidl/noworkflow | python | @classmethod
def load_trial(cls, trial_ref, session=None):
'Load trial by trial reference\n\n Find reference on trials id and tags name\n '
from .tag import Tag
session = (session or relational.session)
return session.query(cls.m).outerjoin(Tag.m).filter(((cls.m.id == trial_ref) | (Tag.m.n... |
@classmethod
def load_parent(cls, script, remove=True, parent_required=False, session=None):
'Load head trial by script\n\n\n Keyword arguments:\n remove -- remove from head, after loading (default=True)\n parent_required -- valid only if script exists (default=False)\n session -- specif... | -5,441,716,824,521,170,000 | Load head trial by script
Keyword arguments:
remove -- remove from head, after loading (default=True)
parent_required -- valid only if script exists (default=False)
session -- specify session for loading (default=relational.session) | capture/noworkflow/now/persistence/models/trial.py | load_parent | raffaelfoidl/noworkflow | python | @classmethod
def load_parent(cls, script, remove=True, parent_required=False, session=None):
'Load head trial by script\n\n\n Keyword arguments:\n remove -- remove from head, after loading (default=True)\n parent_required -- valid only if script exists (default=False)\n session -- specif... |
@classmethod
def fast_last_trial_id(cls, session=None):
'Load last trial id that did not bypass modules\n\n\n Compile SQLAlchemy core query into string for optimization\n\n Keyword arguments:\n session -- specify session for loading (default=relational.session)\n '
session = (session... | 3,566,533,528,998,085,000 | Load last trial id that did not bypass modules
Compile SQLAlchemy core query into string for optimization
Keyword arguments:
session -- specify session for loading (default=relational.session) | capture/noworkflow/now/persistence/models/trial.py | fast_last_trial_id | raffaelfoidl/noworkflow | python | @classmethod
def fast_last_trial_id(cls, session=None):
'Load last trial id that did not bypass modules\n\n\n Compile SQLAlchemy core query into string for optimization\n\n Keyword arguments:\n session -- specify session for loading (default=relational.session)\n '
session = (session... |
@classmethod
def fast_update(cls, trial_id, finish, docstring, session=None):
'Update finish time of trial\n\n Use core sqlalchemy\n\n Arguments:\n trial_id -- trial id\n finish -- finish time as a datetime object\n\n\n Keyword arguments:\n session -- specify session for lo... | 7,144,367,229,818,227,000 | Update finish time of trial
Use core sqlalchemy
Arguments:
trial_id -- trial id
finish -- finish time as a datetime object
Keyword arguments:
session -- specify session for loading (default=relational.session) | capture/noworkflow/now/persistence/models/trial.py | fast_update | raffaelfoidl/noworkflow | python | @classmethod
def fast_update(cls, trial_id, finish, docstring, session=None):
'Update finish time of trial\n\n Use core sqlalchemy\n\n Arguments:\n trial_id -- trial id\n finish -- finish time as a datetime object\n\n\n Keyword arguments:\n session -- specify session for lo... |
@classmethod
def store(cls, start, script, code_hash, arguments, bypass_modules, command, run, docstring, session=None):
'Create trial and assign a new id to it\n\n Use core sqlalchemy\n\n Arguments:\n start -- trial start time\n script -- script name\n code_hash -- script hash co... | -5,175,056,888,793,935,000 | Create trial and assign a new id to it
Use core sqlalchemy
Arguments:
start -- trial start time
script -- script name
code_hash -- script hash code
arguments -- trial arguments
bypass_modules -- whether it captured modules or not
command -- the full command line with noWorkflow parametes
run -- trial created by the r... | capture/noworkflow/now/persistence/models/trial.py | store | raffaelfoidl/noworkflow | python | @classmethod
def store(cls, start, script, code_hash, arguments, bypass_modules, command, run, docstring, session=None):
'Create trial and assign a new id to it\n\n Use core sqlalchemy\n\n Arguments:\n start -- trial start time\n script -- script name\n code_hash -- script hash co... |
@classmethod
def all(cls, session=None):
'Return all trials\n\n Keyword arguments:\n session -- specify session for loading (default=relational.session)\n '
session = (session or relational.session)
return proxy_gen(session.query(cls.m)) | -5,441,857,363,821,957,000 | Return all trials
Keyword arguments:
session -- specify session for loading (default=relational.session) | capture/noworkflow/now/persistence/models/trial.py | all | raffaelfoidl/noworkflow | python | @classmethod
def all(cls, session=None):
'Return all trials\n\n Keyword arguments:\n session -- specify session for loading (default=relational.session)\n '
session = (session or relational.session)
return proxy_gen(session.query(cls.m)) |
def match_status(self, status):
'Check if trial statuses matches\n '
if (status == '*'):
return True
return (self.status == status) | 3,859,083,279,929,322,000 | Check if trial statuses matches | capture/noworkflow/now/persistence/models/trial.py | match_status | raffaelfoidl/noworkflow | python | def match_status(self, status):
'\n '
if (status == '*'):
return True
return (self.status == status) |
def match_script(self, script):
'Check if trial scripts matches\n '
if (script == '*'):
return True
return (self.script == script) | 2,700,283,920,835,461,000 | Check if trial scripts matches | capture/noworkflow/now/persistence/models/trial.py | match_script | raffaelfoidl/noworkflow | python | def match_script(self, script):
'\n '
if (script == '*'):
return True
return (self.script == script) |
@property
def str_start(self):
'Return start date as string'
return str(self.start) | 6,990,337,085,220,348,000 | Return start date as string | capture/noworkflow/now/persistence/models/trial.py | str_start | raffaelfoidl/noworkflow | python | @property
def str_start(self):
return str(self.start) |
@property
def str_finish(self):
'Return start date as string'
return str(self.finish) | -4,390,467,911,824,953,000 | Return start date as string | capture/noworkflow/now/persistence/models/trial.py | str_finish | raffaelfoidl/noworkflow | python | @property
def str_finish(self):
return str(self.finish) |
@classmethod
def count(cls, session=None):
'Count number of trials on database\n '
session = (session or relational.session)
return session.query(cls.m).count() | -3,095,270,125,073,085,000 | Count number of trials on database | capture/noworkflow/now/persistence/models/trial.py | count | raffaelfoidl/noworkflow | python | @classmethod
def count(cls, session=None):
'\n '
session = (session or relational.session)
return session.query(cls.m).count() |
def add(path, info):
'Add file to dict'
if os.path.isabs(path):
if (not (persistence_config.base_path in path)):
return
path = os.path.relpath(path, persistence_config.base_path)
files[path] = info | 1,143,074,063,093,067,000 | Add file to dict | capture/noworkflow/now/persistence/models/trial.py | add | raffaelfoidl/noworkflow | python | def add(path, info):
if os.path.isabs(path):
if (not (persistence_config.base_path in path)):
return
path = os.path.relpath(path, persistence_config.base_path)
files[path] = info |
def __init__(self, init_state_idx=None, init_state_idx_type='obs', policy_array=None, policy_idx_type='obs', p_diabetes=0.2):
'\n initialize the simulator\n '
assert ((p_diabetes >= 0) and (p_diabetes <= 1)), 'Invalid p_diabetes: {}'.format(p_diabetes)
assert (policy_idx_type in ['obs', 'full'... | 7,739,463,211,233,123,000 | initialize the simulator | sepsisSimDiabetes/MDP.py | __init__ | GuyLor/gumbel_max_causal_gadgets_part2 | python | def __init__(self, init_state_idx=None, init_state_idx_type='obs', policy_array=None, policy_idx_type='obs', p_diabetes=0.2):
'\n \n '
assert ((p_diabetes >= 0) and (p_diabetes <= 1)), 'Invalid p_diabetes: {}'.format(p_diabetes)
assert (policy_idx_type in ['obs', 'full', 'proj_obs'])
if (p... |
def get_new_state(self, state_idx=None, idx_type='obs', diabetic_idx=None):
"\n use to start MDP over. A few options:\n\n Full specification:\n 1. Provide state_idx with idx_type = 'obs' + diabetic_idx\n 2. Provide state_idx with idx_type = 'full', diabetic_idx is ignored\n 3. Pr... | 5,995,413,871,458,844,000 | use to start MDP over. A few options:
Full specification:
1. Provide state_idx with idx_type = 'obs' + diabetic_idx
2. Provide state_idx with idx_type = 'full', diabetic_idx is ignored
3. Provide state_idx with idx_type = 'proj_obs' + diabetic_idx*
* This option will set glucose to a normal level
Random specificati... | sepsisSimDiabetes/MDP.py | get_new_state | GuyLor/gumbel_max_causal_gadgets_part2 | python | def get_new_state(self, state_idx=None, idx_type='obs', diabetic_idx=None):
"\n use to start MDP over. A few options:\n\n Full specification:\n 1. Provide state_idx with idx_type = 'obs' + diabetic_idx\n 2. Provide state_idx with idx_type = 'full', diabetic_idx is ignored\n 3. Pr... |
def transition_antibiotics_on(self):
'\n antibiotics state on\n heart rate, sys bp: hi -> normal w.p. .5\n '
self.state.antibiotic_state = 1
if ((self.state.hr_state == 2) and (np.random.uniform(0, 1) < 0.5)):
self.state.hr_state = 1
if ((self.state.sysbp_state == 2) and (np... | 8,961,013,802,412,358,000 | antibiotics state on
heart rate, sys bp: hi -> normal w.p. .5 | sepsisSimDiabetes/MDP.py | transition_antibiotics_on | GuyLor/gumbel_max_causal_gadgets_part2 | python | def transition_antibiotics_on(self):
'\n antibiotics state on\n heart rate, sys bp: hi -> normal w.p. .5\n '
self.state.antibiotic_state = 1
if ((self.state.hr_state == 2) and (np.random.uniform(0, 1) < 0.5)):
self.state.hr_state = 1
if ((self.state.sysbp_state == 2) and (np... |
def transition_antibiotics_off(self):
'\n antibiotics state off\n if antibiotics was on: heart rate, sys bp: normal -> hi w.p. .1\n '
if (self.state.antibiotic_state == 1):
if ((self.state.hr_state == 1) and (np.random.uniform(0, 1) < 0.1)):
self.state.hr_state = 2
... | -558,963,829,897,848,400 | antibiotics state off
if antibiotics was on: heart rate, sys bp: normal -> hi w.p. .1 | sepsisSimDiabetes/MDP.py | transition_antibiotics_off | GuyLor/gumbel_max_causal_gadgets_part2 | python | def transition_antibiotics_off(self):
'\n antibiotics state off\n if antibiotics was on: heart rate, sys bp: normal -> hi w.p. .1\n '
if (self.state.antibiotic_state == 1):
if ((self.state.hr_state == 1) and (np.random.uniform(0, 1) < 0.1)):
self.state.hr_state = 2
... |
def transition_vent_on(self):
'\n ventilation state on\n percent oxygen: low -> normal w.p. .7\n '
self.state.vent_state = 1
if ((self.state.percoxyg_state == 0) and (np.random.uniform(0, 1) < 0.7)):
self.state.percoxyg_state = 1 | 4,821,546,960,925,724,000 | ventilation state on
percent oxygen: low -> normal w.p. .7 | sepsisSimDiabetes/MDP.py | transition_vent_on | GuyLor/gumbel_max_causal_gadgets_part2 | python | def transition_vent_on(self):
'\n ventilation state on\n percent oxygen: low -> normal w.p. .7\n '
self.state.vent_state = 1
if ((self.state.percoxyg_state == 0) and (np.random.uniform(0, 1) < 0.7)):
self.state.percoxyg_state = 1 |
def transition_vent_off(self):
'\n ventilation state off\n if ventilation was on: percent oxygen: normal -> lo w.p. .1\n '
if (self.state.vent_state == 1):
if ((self.state.percoxyg_state == 1) and (np.random.uniform(0, 1) < 0.1)):
self.state.percoxyg_state = 0
se... | 5,563,056,253,617,258,000 | ventilation state off
if ventilation was on: percent oxygen: normal -> lo w.p. .1 | sepsisSimDiabetes/MDP.py | transition_vent_off | GuyLor/gumbel_max_causal_gadgets_part2 | python | def transition_vent_off(self):
'\n ventilation state off\n if ventilation was on: percent oxygen: normal -> lo w.p. .1\n '
if (self.state.vent_state == 1):
if ((self.state.percoxyg_state == 1) and (np.random.uniform(0, 1) < 0.1)):
self.state.percoxyg_state = 0
se... |
def transition_vaso_on(self):
'\n vasopressor state on\n for non-diabetic:\n sys bp: low -> normal, normal -> hi w.p. .7\n for diabetic:\n raise blood pressure: normal -> hi w.p. .9,\n lo -> normal w.p. .5, lo -> hi w.p. .4\n raise blood glucose b... | -1,507,010,084,658,555,100 | vasopressor state on
for non-diabetic:
sys bp: low -> normal, normal -> hi w.p. .7
for diabetic:
raise blood pressure: normal -> hi w.p. .9,
lo -> normal w.p. .5, lo -> hi w.p. .4
raise blood glucose by 1 w.p. .5 | sepsisSimDiabetes/MDP.py | transition_vaso_on | GuyLor/gumbel_max_causal_gadgets_part2 | python | def transition_vaso_on(self):
'\n vasopressor state on\n for non-diabetic:\n sys bp: low -> normal, normal -> hi w.p. .7\n for diabetic:\n raise blood pressure: normal -> hi w.p. .9,\n lo -> normal w.p. .5, lo -> hi w.p. .4\n raise blood glucose b... |
def transition_vaso_off(self):
'\n vasopressor state off\n if vasopressor was on:\n for non-diabetics, sys bp: normal -> low, hi -> normal w.p. .1\n for diabetics, blood pressure falls by 1 w.p. .05 instead of .1\n '
if (self.state.vaso_state == 1):
if (self.st... | 4,314,229,342,329,886,000 | vasopressor state off
if vasopressor was on:
for non-diabetics, sys bp: normal -> low, hi -> normal w.p. .1
for diabetics, blood pressure falls by 1 w.p. .05 instead of .1 | sepsisSimDiabetes/MDP.py | transition_vaso_off | GuyLor/gumbel_max_causal_gadgets_part2 | python | def transition_vaso_off(self):
'\n vasopressor state off\n if vasopressor was on:\n for non-diabetics, sys bp: normal -> low, hi -> normal w.p. .1\n for diabetics, blood pressure falls by 1 w.p. .05 instead of .1\n '
if (self.state.vaso_state == 1):
if (self.st... |
def transition_fluctuate(self, hr_fluctuate, sysbp_fluctuate, percoxyg_fluctuate, glucose_fluctuate):
'\n all (non-treatment) states fluctuate +/- 1 w.p. .1\n exception: glucose flucuates +/- 1 w.p. .3 if diabetic\n '
if hr_fluctuate:
hr_prob = np.random.uniform(0, 1)
if (hr... | 1,336,593,036,583,505,400 | all (non-treatment) states fluctuate +/- 1 w.p. .1
exception: glucose flucuates +/- 1 w.p. .3 if diabetic | sepsisSimDiabetes/MDP.py | transition_fluctuate | GuyLor/gumbel_max_causal_gadgets_part2 | python | def transition_fluctuate(self, hr_fluctuate, sysbp_fluctuate, percoxyg_fluctuate, glucose_fluctuate):
'\n all (non-treatment) states fluctuate +/- 1 w.p. .1\n exception: glucose flucuates +/- 1 w.p. .3 if diabetic\n '
if hr_fluctuate:
hr_prob = np.random.uniform(0, 1)
if (hr... |
def __init__(self, score_thresh=0.05, nms=0.5, detections_per_img=100, box_coder=None, cls_agnostic_bbox_reg=False, bbox_aug_enabled=False):
'\n Arguments:\n score_thresh (float)\n nms (float)\n detections_per_img (int)\n box_coder (BoxCoder)\n '
super(P... | 2,870,374,798,669,880,000 | Arguments:
score_thresh (float)
nms (float)
detections_per_img (int)
box_coder (BoxCoder) | fcos_core/modeling/roi_heads/box_head/inference.py | __init__ | qilei123/FCOS | python | def __init__(self, score_thresh=0.05, nms=0.5, detections_per_img=100, box_coder=None, cls_agnostic_bbox_reg=False, bbox_aug_enabled=False):
'\n Arguments:\n score_thresh (float)\n nms (float)\n detections_per_img (int)\n box_coder (BoxCoder)\n '
super(P... |
def forward(self, x, boxes):
'\n Arguments:\n x (tuple[tensor, tensor]): x contains the class logits\n and the box_regression from the model.\n boxes (list[BoxList]): bounding boxes that are used as\n reference, one for ech image\n\n Returns:\n ... | -3,406,154,131,159,554,600 | Arguments:
x (tuple[tensor, tensor]): x contains the class logits
and the box_regression from the model.
boxes (list[BoxList]): bounding boxes that are used as
reference, one for ech image
Returns:
results (list[BoxList]): one BoxList for each image, containing
the extra fields labe... | fcos_core/modeling/roi_heads/box_head/inference.py | forward | qilei123/FCOS | python | def forward(self, x, boxes):
'\n Arguments:\n x (tuple[tensor, tensor]): x contains the class logits\n and the box_regression from the model.\n boxes (list[BoxList]): bounding boxes that are used as\n reference, one for ech image\n\n Returns:\n ... |
def prepare_boxlist(self, boxes, scores, image_shape):
'\n Returns BoxList from `boxes` and adds probability scores information\n as an extra field\n `boxes` has shape (#detections, 4 * #classes), where each row represents\n a list of predicted bounding boxes for each of the object class... | 6,100,855,235,390,330,000 | Returns BoxList from `boxes` and adds probability scores information
as an extra field
`boxes` has shape (#detections, 4 * #classes), where each row represents
a list of predicted bounding boxes for each of the object classes in the
dataset (including the background class). The detections in each row
originate from the... | fcos_core/modeling/roi_heads/box_head/inference.py | prepare_boxlist | qilei123/FCOS | python | def prepare_boxlist(self, boxes, scores, image_shape):
'\n Returns BoxList from `boxes` and adds probability scores information\n as an extra field\n `boxes` has shape (#detections, 4 * #classes), where each row represents\n a list of predicted bounding boxes for each of the object class... |
def filter_results(self, boxlist, num_classes):
'Returns bounding-box detection results by thresholding on scores and\n applying non-maximum suppression (NMS).\n '
boxes = boxlist.bbox.reshape((- 1), (num_classes * 4))
scores = boxlist.get_field('scores').reshape((- 1), num_classes)
device... | 3,938,484,773,227,017,700 | Returns bounding-box detection results by thresholding on scores and
applying non-maximum suppression (NMS). | fcos_core/modeling/roi_heads/box_head/inference.py | filter_results | qilei123/FCOS | python | def filter_results(self, boxlist, num_classes):
'Returns bounding-box detection results by thresholding on scores and\n applying non-maximum suppression (NMS).\n '
boxes = boxlist.bbox.reshape((- 1), (num_classes * 4))
scores = boxlist.get_field('scores').reshape((- 1), num_classes)
device... |
def _calculate_deltas(times: (((str | np.ndarray) | NDFrame) | None), halflife: ((float | TimedeltaConvertibleTypes) | None)) -> np.ndarray:
'\n Return the diff of the times divided by the half-life. These values are used in\n the calculation of the ewm mean.\n\n Parameters\n ----------\n times : str... | -5,254,744,993,093,402,000 | Return the diff of the times divided by the half-life. These values are used in
the calculation of the ewm mean.
Parameters
----------
times : str, np.ndarray, Series, default None
Times corresponding to the observations. Must be monotonically increasing
and ``datetime64[ns]`` dtype.
halflife : float, str, tim... | pandas/core/window/ewm.py | _calculate_deltas | DrGFreeman/pandas | python | def _calculate_deltas(times: (((str | np.ndarray) | NDFrame) | None), halflife: ((float | TimedeltaConvertibleTypes) | None)) -> np.ndarray:
'\n Return the diff of the times divided by the half-life. These values are used in\n the calculation of the ewm mean.\n\n Parameters\n ----------\n times : str... |
def _get_window_indexer(self) -> BaseIndexer:
'\n Return an indexer class that will compute the window start and end bounds\n '
return ExponentialMovingWindowIndexer() | 6,524,741,404,708,218,000 | Return an indexer class that will compute the window start and end bounds | pandas/core/window/ewm.py | _get_window_indexer | DrGFreeman/pandas | python | def _get_window_indexer(self) -> BaseIndexer:
'\n \n '
return ExponentialMovingWindowIndexer() |
def online(self, engine='numba', engine_kwargs=None):
"\n Return an ``OnlineExponentialMovingWindow`` object to calculate\n exponentially moving window aggregations in an online method.\n\n .. versionadded:: 1.3.0\n\n Parameters\n ----------\n engine: str, default ``'numba'... | 5,517,177,251,206,371,000 | Return an ``OnlineExponentialMovingWindow`` object to calculate
exponentially moving window aggregations in an online method.
.. versionadded:: 1.3.0
Parameters
----------
engine: str, default ``'numba'``
Execution engine to calculate online aggregations.
Applies to all supported aggregation methods.
engine_... | pandas/core/window/ewm.py | online | DrGFreeman/pandas | python | def online(self, engine='numba', engine_kwargs=None):
"\n Return an ``OnlineExponentialMovingWindow`` object to calculate\n exponentially moving window aggregations in an online method.\n\n .. versionadded:: 1.3.0\n\n Parameters\n ----------\n engine: str, default ``'numba'... |
def _get_window_indexer(self) -> GroupbyIndexer:
'\n Return an indexer class that will compute the window start and end bounds\n\n Returns\n -------\n GroupbyIndexer\n '
window_indexer = GroupbyIndexer(groupby_indicies=self._grouper.indices, window_indexer=ExponentialMovingWin... | 4,688,982,227,691,670,000 | Return an indexer class that will compute the window start and end bounds
Returns
-------
GroupbyIndexer | pandas/core/window/ewm.py | _get_window_indexer | DrGFreeman/pandas | python | def _get_window_indexer(self) -> GroupbyIndexer:
'\n Return an indexer class that will compute the window start and end bounds\n\n Returns\n -------\n GroupbyIndexer\n '
window_indexer = GroupbyIndexer(groupby_indicies=self._grouper.indices, window_indexer=ExponentialMovingWin... |
def reset(self):
'\n Reset the state captured by `update` calls.\n '
self._mean.reset() | 8,308,839,287,548,406,000 | Reset the state captured by `update` calls. | pandas/core/window/ewm.py | reset | DrGFreeman/pandas | python | def reset(self):
'\n \n '
self._mean.reset() |
def mean(self, *args, update=None, update_times=None, **kwargs):
'\n Calculate an online exponentially weighted mean.\n\n Parameters\n ----------\n update: DataFrame or Series, default None\n New values to continue calculating the\n exponentially weighted mean from ... | 581,572,148,694,043,100 | Calculate an online exponentially weighted mean.
Parameters
----------
update: DataFrame or Series, default None
New values to continue calculating the
exponentially weighted mean from the last values and weights.
Values should be float64 dtype.
``update`` needs to be ``None`` the first time the
e... | pandas/core/window/ewm.py | mean | DrGFreeman/pandas | python | def mean(self, *args, update=None, update_times=None, **kwargs):
'\n Calculate an online exponentially weighted mean.\n\n Parameters\n ----------\n update: DataFrame or Series, default None\n New values to continue calculating the\n exponentially weighted mean from ... |
def forward(self, seed_points, seed_feats):
'forward.\n\n Args:\n seed_points (torch.Tensor): Coordinate of the seed\n points in shape (B, N, 3).\n seed_feats (torch.Tensor): Features of the seed points in shape\n (B, C, N).\n\n Returns:\n ... | 6,924,099,449,724,303,000 | forward.
Args:
seed_points (torch.Tensor): Coordinate of the seed
points in shape (B, N, 3).
seed_feats (torch.Tensor): Features of the seed points in shape
(B, C, N).
Returns:
tuple[torch.Tensor]:
- vote_points: Voted xyz based on the seed points with shape (B... | mmdet3d/models/model_utils/vote_module.py | forward | BOURSa/mmdetection3d | python | def forward(self, seed_points, seed_feats):
'forward.\n\n Args:\n seed_points (torch.Tensor): Coordinate of the seed\n points in shape (B, N, 3).\n seed_feats (torch.Tensor): Features of the seed points in shape\n (B, C, N).\n\n Returns:\n ... |
def get_loss(self, seed_points, vote_points, seed_indices, vote_targets_mask, vote_targets):
'Calculate loss of voting module.\n\n Args:\n seed_points (torch.Tensor): Coordinate of the seed points.\n vote_points (torch.Tensor): Coordinate of the vote points.\n seed_indices (t... | 1,211,448,506,085,380,000 | Calculate loss of voting module.
Args:
seed_points (torch.Tensor): Coordinate of the seed points.
vote_points (torch.Tensor): Coordinate of the vote points.
seed_indices (torch.Tensor): Indices of seed points in raw points.
vote_targets_mask (torch.Tensor): Mask of valid vote targets.
vote_targets ... | mmdet3d/models/model_utils/vote_module.py | get_loss | BOURSa/mmdetection3d | python | def get_loss(self, seed_points, vote_points, seed_indices, vote_targets_mask, vote_targets):
'Calculate loss of voting module.\n\n Args:\n seed_points (torch.Tensor): Coordinate of the seed points.\n vote_points (torch.Tensor): Coordinate of the vote points.\n seed_indices (t... |
def __get_mortality_pp_increase(self, temperature: float, fish_mass: float) -> float:
'Get the mortality percentage point difference increase.\n\n :param temperature: the temperature in Celsius\n :param fish_mass: the fish mass (in grams)\n :returns: Mortality percentage point difference increa... | -3,144,523,383,826,243,000 | Get the mortality percentage point difference increase.
:param temperature: the temperature in Celsius
:param fish_mass: the fish mass (in grams)
:returns: Mortality percentage point difference increase | slim/types/TreatmentTypes.py | __get_mortality_pp_increase | magicicada/slim | python | def __get_mortality_pp_increase(self, temperature: float, fish_mass: float) -> float:
'Get the mortality percentage point difference increase.\n\n :param temperature: the temperature in Celsius\n :param fish_mass: the fish mass (in grams)\n :returns: Mortality percentage point difference increa... |
@abstractmethod
def delay(self, average_temperature: float):
'\n Delay before treatment should have a noticeable effect\n ' | -2,254,910,768,644,339,700 | Delay before treatment should have a noticeable effect | slim/types/TreatmentTypes.py | delay | magicicada/slim | python | @abstractmethod
def delay(self, average_temperature: float):
'\n \n ' |
@staticmethod
def get_allele_heterozygous_trait(alleles: Alleles):
'\n Get the allele heterozygous type\n '
if ('A' in alleles):
if ('a' in alleles):
trait = HeterozygousResistance.INCOMPLETELY_DOMINANT
else:
trait = HeterozygousResistance.DOMINANT
else:... | -8,403,997,583,842,534,000 | Get the allele heterozygous type | slim/types/TreatmentTypes.py | get_allele_heterozygous_trait | magicicada/slim | python | @staticmethod
def get_allele_heterozygous_trait(alleles: Alleles):
'\n \n '
if ('A' in alleles):
if ('a' in alleles):
trait = HeterozygousResistance.INCOMPLETELY_DOMINANT
else:
trait = HeterozygousResistance.DOMINANT
else:
trait = HeterozygousRes... |
@abstractmethod
def get_lice_treatment_mortality_rate(self, lice_population: LicePopulation, temperature: float) -> GenoTreatmentDistrib:
'\n Calculate the mortality rates of this treatment\n ' | -7,484,706,959,667,294,000 | Calculate the mortality rates of this treatment | slim/types/TreatmentTypes.py | get_lice_treatment_mortality_rate | magicicada/slim | python | @abstractmethod
def get_lice_treatment_mortality_rate(self, lice_population: LicePopulation, temperature: float) -> GenoTreatmentDistrib:
'\n \n ' |
def get_fish_mortality_occurrences(self, temperature: float, fish_mass: float, num_fish: float, efficacy_window: float, mortality_events: int):
'Get the number of fish that die due to treatment\n\n :param temperature: the temperature of the cage\n :param num_fish: the number of fish\n :param fi... | 220,058,123,522,875,100 | Get the number of fish that die due to treatment
:param temperature: the temperature of the cage
:param num_fish: the number of fish
:param fish_mass: the average fish mass (in grams)
:param efficacy_window: the length of the efficacy window
:param mortality_events: the number of fish mortality events to subtract from | slim/types/TreatmentTypes.py | get_fish_mortality_occurrences | magicicada/slim | python | def get_fish_mortality_occurrences(self, temperature: float, fish_mass: float, num_fish: float, efficacy_window: float, mortality_events: int):
'Get the number of fish that die due to treatment\n\n :param temperature: the temperature of the cage\n :param num_fish: the number of fish\n :param fi... |
def savedJSONInvariants(testCase: TestCase, savedJSON: str) -> str:
'\n Assert a few things about the result of L{eventAsJSON}, then return it.\n\n @param testCase: The L{TestCase} with which to perform the assertions.\n @param savedJSON: The result of L{eventAsJSON}.\n\n @return: C{savedJSON}\n\n @r... | -6,524,027,284,910,949,000 | Assert a few things about the result of L{eventAsJSON}, then return it.
@param testCase: The L{TestCase} with which to perform the assertions.
@param savedJSON: The result of L{eventAsJSON}.
@return: C{savedJSON}
@raise AssertionError: If any of the preconditions fail. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | savedJSONInvariants | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def savedJSONInvariants(testCase: TestCase, savedJSON: str) -> str:
'\n Assert a few things about the result of L{eventAsJSON}, then return it.\n\n @param testCase: The L{TestCase} with which to perform the assertions.\n @param savedJSON: The result of L{eventAsJSON}.\n\n @return: C{savedJSON}\n\n @r... |
def savedEventJSON(self, event: LogEvent) -> str:
'\n Serialize some an events, assert some things about it, and return the\n JSON.\n\n @param event: An event.\n\n @return: JSON.\n '
return savedJSONInvariants(self, eventAsJSON(event)) | 3,940,816,593,613,317,600 | Serialize some an events, assert some things about it, and return the
JSON.
@param event: An event.
@return: JSON. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | savedEventJSON | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def savedEventJSON(self, event: LogEvent) -> str:
'\n Serialize some an events, assert some things about it, and return the\n JSON.\n\n @param event: An event.\n\n @return: JSON.\n '
return savedJSONInvariants(self, eventAsJSON(event)) |
def test_simpleSaveLoad(self) -> None:
'\n Saving and loading an empty dictionary results in an empty dictionary.\n '
self.assertEqual(eventFromJSON(self.savedEventJSON({})), {}) | 158,441,858,065,887,970 | Saving and loading an empty dictionary results in an empty dictionary. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_simpleSaveLoad | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_simpleSaveLoad(self) -> None:
'\n \n '
self.assertEqual(eventFromJSON(self.savedEventJSON({})), {}) |
def test_saveLoad(self) -> None:
"\n Saving and loading a dictionary with some simple values in it results\n in those same simple values in the output; according to JSON's rules,\n though, all dictionary keys must be L{str} and any non-L{str}\n keys will be converted.\n "
self... | -5,613,583,833,805,194,000 | Saving and loading a dictionary with some simple values in it results
in those same simple values in the output; according to JSON's rules,
though, all dictionary keys must be L{str} and any non-L{str}
keys will be converted. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_saveLoad | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_saveLoad(self) -> None:
"\n Saving and loading a dictionary with some simple values in it results\n in those same simple values in the output; according to JSON's rules,\n though, all dictionary keys must be L{str} and any non-L{str}\n keys will be converted.\n "
self... |
def test_saveUnPersistable(self) -> None:
'\n Saving and loading an object which cannot be represented in JSON will\n result in a placeholder.\n '
self.assertEqual(eventFromJSON(self.savedEventJSON({'1': 2, '3': object()})), {'1': 2, '3': {'unpersistable': True}}) | 1,832,279,315,044,509,000 | Saving and loading an object which cannot be represented in JSON will
result in a placeholder. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_saveUnPersistable | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_saveUnPersistable(self) -> None:
'\n Saving and loading an object which cannot be represented in JSON will\n result in a placeholder.\n '
self.assertEqual(eventFromJSON(self.savedEventJSON({'1': 2, '3': object()})), {'1': 2, '3': {'unpersistable': True}}) |
def test_saveNonASCII(self) -> None:
'\n Non-ASCII keys and values can be saved and loaded.\n '
self.assertEqual(eventFromJSON(self.savedEventJSON({'ሴ': '䌡', '3': object()})), {'ሴ': '䌡', '3': {'unpersistable': True}}) | 2,038,994,471,241,656,300 | Non-ASCII keys and values can be saved and loaded. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_saveNonASCII | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_saveNonASCII(self) -> None:
'\n \n '
self.assertEqual(eventFromJSON(self.savedEventJSON({'ሴ': '䌡', '3': object()})), {'ሴ': '䌡', '3': {'unpersistable': True}}) |
def test_saveBytes(self) -> None:
'\n Any L{bytes} objects will be saved as if they are latin-1 so they can\n be faithfully re-loaded.\n '
inputEvent = {'hello': bytes(range(255))}
inputEvent.update({b'skipped': 'okay'})
self.assertEqual(eventFromJSON(self.savedEventJSON(inputEvent)... | 536,017,709,974,603,460 | Any L{bytes} objects will be saved as if they are latin-1 so they can
be faithfully re-loaded. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_saveBytes | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_saveBytes(self) -> None:
'\n Any L{bytes} objects will be saved as if they are latin-1 so they can\n be faithfully re-loaded.\n '
inputEvent = {'hello': bytes(range(255))}
inputEvent.update({b'skipped': 'okay'})
self.assertEqual(eventFromJSON(self.savedEventJSON(inputEvent)... |
def test_saveUnPersistableThenFormat(self) -> None:
'\n Saving and loading an object which cannot be represented in JSON, but\n has a string representation which I{can} be saved as JSON, will result\n in the same string formatting; any extractable fields will retain their\n data types.\n... | -7,824,544,873,663,906,000 | Saving and loading an object which cannot be represented in JSON, but
has a string representation which I{can} be saved as JSON, will result
in the same string formatting; any extractable fields will retain their
data types. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_saveUnPersistableThenFormat | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_saveUnPersistableThenFormat(self) -> None:
'\n Saving and loading an object which cannot be represented in JSON, but\n has a string representation which I{can} be saved as JSON, will result\n in the same string formatting; any extractable fields will retain their\n data types.\n... |
def test_extractingFieldsPostLoad(self) -> None:
"\n L{extractField} can extract fields from an object that's been saved and\n loaded from JSON.\n "
class Obj():
def __init__(self) -> None:
self.value = 345
inputEvent = dict(log_format='{object.value}', object=Obj(... | -2,728,139,371,617,195,000 | L{extractField} can extract fields from an object that's been saved and
loaded from JSON. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_extractingFieldsPostLoad | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_extractingFieldsPostLoad(self) -> None:
"\n L{extractField} can extract fields from an object that's been saved and\n loaded from JSON.\n "
class Obj():
def __init__(self) -> None:
self.value = 345
inputEvent = dict(log_format='{object.value}', object=Obj(... |
def test_failureStructurePreserved(self) -> None:
'\n Round-tripping a failure through L{eventAsJSON} preserves its class and\n structure.\n '
events: List[LogEvent] = []
log = Logger(observer=cast(ILogObserver, events.append))
try:
(1 / 0)
except ZeroDivisionError:
... | 5,266,929,867,749,554,000 | Round-tripping a failure through L{eventAsJSON} preserves its class and
structure. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_failureStructurePreserved | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_failureStructurePreserved(self) -> None:
'\n Round-tripping a failure through L{eventAsJSON} preserves its class and\n structure.\n '
events: List[LogEvent] = []
log = Logger(observer=cast(ILogObserver, events.append))
try:
(1 / 0)
except ZeroDivisionError:
... |
def test_saveLoadLevel(self) -> None:
"\n It's important that the C{log_level} key remain a\n L{constantly.NamedConstant} object.\n "
inputEvent = dict(log_level=LogLevel.warn)
loadedEvent = eventFromJSON(self.savedEventJSON(inputEvent))
self.assertIs(loadedEvent['log_level'], LogLe... | 2,264,376,178,710,008,000 | It's important that the C{log_level} key remain a
L{constantly.NamedConstant} object. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_saveLoadLevel | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_saveLoadLevel(self) -> None:
"\n It's important that the C{log_level} key remain a\n L{constantly.NamedConstant} object.\n "
inputEvent = dict(log_level=LogLevel.warn)
loadedEvent = eventFromJSON(self.savedEventJSON(inputEvent))
self.assertIs(loadedEvent['log_level'], LogLe... |
def test_saveLoadUnknownLevel(self) -> None:
"\n If a saved bit of JSON (let's say, from a future version of Twisted)\n were to persist a different log_level, it will resolve as None.\n "
loadedEvent = eventFromJSON('{"log_level": {"name": "other", "__class_uuid__": "02E59486-F24D-46AD-8224... | -8,522,714,585,909,203,000 | If a saved bit of JSON (let's say, from a future version of Twisted)
were to persist a different log_level, it will resolve as None. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_saveLoadUnknownLevel | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_saveLoadUnknownLevel(self) -> None:
"\n If a saved bit of JSON (let's say, from a future version of Twisted)\n were to persist a different log_level, it will resolve as None.\n "
loadedEvent = eventFromJSON('{"log_level": {"name": "other", "__class_uuid__": "02E59486-F24D-46AD-8224... |
def test_interface(self) -> None:
'\n A L{FileLogObserver} returned by L{jsonFileLogObserver} is an\n L{ILogObserver}.\n '
with StringIO() as fileHandle:
observer = jsonFileLogObserver(fileHandle)
try:
verifyObject(ILogObserver, observer)
except BrokenMet... | 3,291,993,695,110,113,000 | A L{FileLogObserver} returned by L{jsonFileLogObserver} is an
L{ILogObserver}. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_interface | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_interface(self) -> None:
'\n A L{FileLogObserver} returned by L{jsonFileLogObserver} is an\n L{ILogObserver}.\n '
with StringIO() as fileHandle:
observer = jsonFileLogObserver(fileHandle)
try:
verifyObject(ILogObserver, observer)
except BrokenMet... |
def assertObserverWritesJSON(self, recordSeparator: str='\x1e') -> None:
'\n Asserts that an observer created by L{jsonFileLogObserver} with the\n given arguments writes events serialized as JSON text, using the given\n record separator.\n\n @param recordSeparator: C{recordSeparator} arg... | -8,549,672,763,853,330,000 | Asserts that an observer created by L{jsonFileLogObserver} with the
given arguments writes events serialized as JSON text, using the given
record separator.
@param recordSeparator: C{recordSeparator} argument to
L{jsonFileLogObserver} | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | assertObserverWritesJSON | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def assertObserverWritesJSON(self, recordSeparator: str='\x1e') -> None:
'\n Asserts that an observer created by L{jsonFileLogObserver} with the\n given arguments writes events serialized as JSON text, using the given\n record separator.\n\n @param recordSeparator: C{recordSeparator} arg... |
def test_observeWritesDefaultRecordSeparator(self) -> None:
'\n A L{FileLogObserver} created by L{jsonFileLogObserver} writes events\n serialzed as JSON text to a file when it observes events.\n By default, the record separator is C{"\\x1e"}.\n '
self.assertObserverWritesJSON() | 747,158,194,430,973,300 | A L{FileLogObserver} created by L{jsonFileLogObserver} writes events
serialzed as JSON text to a file when it observes events.
By default, the record separator is C{"\x1e"}. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_observeWritesDefaultRecordSeparator | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_observeWritesDefaultRecordSeparator(self) -> None:
'\n A L{FileLogObserver} created by L{jsonFileLogObserver} writes events\n serialzed as JSON text to a file when it observes events.\n By default, the record separator is C{"\\x1e"}.\n '
self.assertObserverWritesJSON() |
def test_observeWritesEmptyRecordSeparator(self) -> None:
'\n A L{FileLogObserver} created by L{jsonFileLogObserver} writes events\n serialzed as JSON text to a file when it observes events.\n This test sets the record separator to C{""}.\n '
self.assertObserverWritesJSON(recordSepar... | 5,725,957,345,564,703,000 | A L{FileLogObserver} created by L{jsonFileLogObserver} writes events
serialzed as JSON text to a file when it observes events.
This test sets the record separator to C{""}. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_observeWritesEmptyRecordSeparator | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_observeWritesEmptyRecordSeparator(self) -> None:
'\n A L{FileLogObserver} created by L{jsonFileLogObserver} writes events\n serialzed as JSON text to a file when it observes events.\n This test sets the record separator to C{}.\n '
self.assertObserverWritesJSON(recordSeparat... |
def test_failureFormatting(self) -> None:
'\n A L{FileLogObserver} created by L{jsonFileLogObserver} writes failures\n serialized as JSON text to a file when it observes events.\n '
io = StringIO()
publisher = LogPublisher()
logged: List[LogEvent] = []
publisher.addObserver(cast... | -7,563,002,394,003,736,000 | A L{FileLogObserver} created by L{jsonFileLogObserver} writes failures
serialized as JSON text to a file when it observes events. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_failureFormatting | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_failureFormatting(self) -> None:
'\n A L{FileLogObserver} created by L{jsonFileLogObserver} writes failures\n serialized as JSON text to a file when it observes events.\n '
io = StringIO()
publisher = LogPublisher()
logged: List[LogEvent] = []
publisher.addObserver(cast... |
def _readEvents(self, inFile: IO[Any], recordSeparator: Optional[str]=None, bufferSize: int=4096) -> None:
'\n Test that L{eventsFromJSONLogFile} reads two pre-defined events from a\n file: C{{"x": 1}} and C{{"y": 2}}.\n\n @param inFile: C{inFile} argument to L{eventsFromJSONLogFile}\n @... | -2,322,267,403,128,152,600 | Test that L{eventsFromJSONLogFile} reads two pre-defined events from a
file: C{{"x": 1}} and C{{"y": 2}}.
@param inFile: C{inFile} argument to L{eventsFromJSONLogFile}
@param recordSeparator: C{recordSeparator} argument to
L{eventsFromJSONLogFile}
@param bufferSize: C{bufferSize} argument to L{eventsFromJSONLogFil... | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | _readEvents | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def _readEvents(self, inFile: IO[Any], recordSeparator: Optional[str]=None, bufferSize: int=4096) -> None:
'\n Test that L{eventsFromJSONLogFile} reads two pre-defined events from a\n file: C{{"x": 1}} and C{{"y": 2}}.\n\n @param inFile: C{inFile} argument to L{eventsFromJSONLogFile}\n @... |
def test_readEventsAutoWithRecordSeparator(self) -> None:
'\n L{eventsFromJSONLogFile} reads events from a file and automatically\n detects use of C{"\\x1e"} as the record separator.\n '
with StringIO('\x1e{"x": 1}\n\x1e{"y": 2}\n') as fileHandle:
self._readEvents(fileHandle)
... | 1,436,743,086,405,439,500 | L{eventsFromJSONLogFile} reads events from a file and automatically
detects use of C{"\x1e"} as the record separator. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_readEventsAutoWithRecordSeparator | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_readEventsAutoWithRecordSeparator(self) -> None:
'\n L{eventsFromJSONLogFile} reads events from a file and automatically\n detects use of C{"\\x1e"} as the record separator.\n '
with StringIO('\x1e{"x": 1}\n\x1e{"y": 2}\n') as fileHandle:
self._readEvents(fileHandle)
... |
def test_readEventsAutoEmptyRecordSeparator(self) -> None:
'\n L{eventsFromJSONLogFile} reads events from a file and automatically\n detects use of C{""} as the record separator.\n '
with StringIO('{"x": 1}\n{"y": 2}\n') as fileHandle:
self._readEvents(fileHandle)
self.asser... | -5,958,368,649,329,142,000 | L{eventsFromJSONLogFile} reads events from a file and automatically
detects use of C{""} as the record separator. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_readEventsAutoEmptyRecordSeparator | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_readEventsAutoEmptyRecordSeparator(self) -> None:
'\n L{eventsFromJSONLogFile} reads events from a file and automatically\n detects use of C{} as the record separator.\n '
with StringIO('{"x": 1}\n{"y": 2}\n') as fileHandle:
self._readEvents(fileHandle)
self.assertE... |
def test_readEventsExplicitRecordSeparator(self) -> None:
'\n L{eventsFromJSONLogFile} reads events from a file and is told to use\n a specific record separator.\n '
with StringIO('\x08{"x": 1}\n\x08{"y": 2}\n') as fileHandle:
self._readEvents(fileHandle, recordSeparator='\x08')
... | 4,865,284,781,638,233,000 | L{eventsFromJSONLogFile} reads events from a file and is told to use
a specific record separator. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_readEventsExplicitRecordSeparator | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_readEventsExplicitRecordSeparator(self) -> None:
'\n L{eventsFromJSONLogFile} reads events from a file and is told to use\n a specific record separator.\n '
with StringIO('\x08{"x": 1}\n\x08{"y": 2}\n') as fileHandle:
self._readEvents(fileHandle, recordSeparator='\x08')
... |
def test_readEventsPartialBuffer(self) -> None:
'\n L{eventsFromJSONLogFile} handles buffering a partial event.\n '
with StringIO('\x1e{"x": 1}\n\x1e{"y": 2}\n') as fileHandle:
self._readEvents(fileHandle, bufferSize=1)
self.assertEqual(len(self.errorEvents), 0) | 19,513,616,301,660,430 | L{eventsFromJSONLogFile} handles buffering a partial event. | SCRAPE/Lib/site-packages/twisted/logger/test/test_json.py | test_readEventsPartialBuffer | Chinmoy-Prasad-Dutta/scrapy_scraper | python | def test_readEventsPartialBuffer(self) -> None:
'\n \n '
with StringIO('\x1e{"x": 1}\n\x1e{"y": 2}\n') as fileHandle:
self._readEvents(fileHandle, bufferSize=1)
self.assertEqual(len(self.errorEvents), 0) |
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