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def return_response(self, method, path, data, headers, response): req_data = None if method == "POST" and path == "/": req_data = urlparse.parse_qs(to_str(data)) action = req_data.get("Action")[0] if req_data: if action == "DescribeStackResources": if response.status_code < 300: response_dict = xmltodict.parse(response.content)[ "DescribeStackResourcesResponse" ] resources = response_dict["DescribeStackResourcesResult"][ "StackResources" ] if not resources: # Check if stack exists stack_name = req_data.get("StackName")[0] cloudformation_client = aws_stack.connect_to_service( "cloudformation" ) try: cloudformation_client.describe_stacks(StackName=stack_name) except Exception: return error_response( "Stack with id %s does not exist" % stack_name, code=404 ) if action == "DescribeStackResource": if response.status_code >= 500: # fix an error in moto where it fails with 500 if the stack does not exist return error_response("Stack resource does not exist", code=404) elif action == "CreateStack" or action == "UpdateStack": if response.status_code >= 400 and response.status_code < 500: return response # run the actual deployment template = template_deployer.template_to_json( req_data.get("TemplateBody")[0] ) template_deployer.deploy_template(template, req_data.get("StackName")[0])
def return_response(self, method, path, data, headers, response): req_data = None if method == "POST" and path == "/": req_data = urlparse.parse_qs(to_str(data)) action = req_data.get("Action")[0] if req_data: if action == "DescribeStackResources": if response.status_code < 300: response_dict = xmltodict.parse(response.content)[ "DescribeStackResourcesResponse" ] resources = response_dict["DescribeStackResourcesResult"][ "StackResources" ] if not resources: # Check if stack exists stack_name = req_data.get("StackName")[0] cloudformation_client = aws_stack.connect_to_service( "cloudformation" ) try: cloudformation_client.describe_stacks(StackName=stack_name) except Exception: return error_response( "Stack with id %s does not exist" % stack_name, code=404 ) if action == "DescribeStackResource": if response.status_code >= 500: # fix an error in moto where it fails with 500 if the stack does not exist return error_response("Stack resource does not exist", code=404) elif action == "CreateStack" or action == "UpdateStack": # run the actual deployment template = template_deployer.template_to_json( req_data.get("TemplateBody")[0] ) template_deployer.deploy_template(template, req_data.get("StackName")[0]) if response.status_code >= 400: return make_response(action)
https://github.com/localstack/localstack/issues/395
2017-10-11T05:49:47:INFO:werkzeug: 192.168.99.1 - - [11/Oct/2017 05:49:47] "GET / HTTP/1.1" 200 - 2017-10-11T05:49:47:INFO:werkzeug: 192.168.99.1 - - [11/Oct/2017 05:49:47] "GET //192.168.99.103:8080/swagger.json HTTP/1.1" 200 - 2017-10-11T05:49:48:INFO:werkzeug: 192.168.99.1 - - [11/Oct/2017 05:49:48] "GET /img/localstack_icon.png HTTP/1.1" 200 - 2017-10-11T05:49:49:INFO:werkzeug: 192.168.99.1 - - [11/Oct/2017 05:49:49] "POST /graph HTTP/1.1" 500 - Traceback (most recent call last): File "/opt/code/localstack/.venv/lib/python2.7/site-packages/flask/app.py", line 1836, in __call__ return self.wsgi_app(environ, start_response) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/flask/app.py", line 1820, in wsgi_app response = self.make_response(self.handle_exception(e)) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/flask/app.py", line 1403, in handle_exception reraise(exc_type, exc_value, tb) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/flask/app.py", line 1817, in wsgi_app response = self.full_dispatch_request() File "/opt/code/localstack/.venv/lib/python2.7/site-packages/flask/app.py", line 1477, in full_dispatch_request rv = self.handle_user_exception(e) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/flask/app.py", line 1381, in handle_user_exception reraise(exc_type, exc_value, tb) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/flask/app.py", line 1475, in full_dispatch_request rv = self.dispatch_request() File "/opt/code/localstack/.venv/lib/python2.7/site-packages/flask/app.py", line 1461, in dispatch_request return self.view_functions[rule.endpoint](**req.view_args) File "/opt/code/localstack/localstack/dashboard/api.py", line 37, in get_graph graph = infra.get_graph(name_filter=data['nameFilter'], env=env) File "/opt/code/localstack/localstack/dashboard/infra.py", line 432, in get_graph domains = get_elasticsearch_domains(name_filter, pool=pool, env=env) File "/opt/code/localstack/localstack/dashboard/infra.py", line 312, in get_elasticsearch_domains parallelize(handle, out['DomainNames']) File "/opt/code/localstack/localstack/utils/common.py", line 698, in parallelize result = pool.map(func, list) File "/usr/lib/python2.7/multiprocessing/pool.py", line 251, in map return self.map_async(func, iterable, chunksize).get() File "/usr/lib/python2.7/multiprocessing/pool.py", line 567, in get raise self._value KeyError: 'Endpoint'
KeyError
def forward_request(self, method, path, data, headers): modified_data = None # If this request contains streaming v4 authentication signatures, strip them from the message # Related isse: https://github.com/localstack/localstack/issues/98 # TODO we should evaluate whether to replace moto s3 with scality/S3: # https://github.com/scality/S3/issues/237 if headers.get("x-amz-content-sha256") == "STREAMING-AWS4-HMAC-SHA256-PAYLOAD": modified_data = strip_chunk_signatures(data) # POST requests to S3 may include a "${filename}" placeholder in the # key, which should be replaced with an actual file name before storing. if method == "POST": original_data = modified_data or data expanded_data = expand_multipart_filename(original_data, headers) if expanded_data is not original_data: modified_data = expanded_data # persist this API call to disk persistence.record("s3", method, path, data, headers) parsed = urlparse.urlparse(path) query = parsed.query path = parsed.path bucket = path.split("/")[1] query_map = urlparse.parse_qs(query) if query == "notification" or "notification" in query_map: response = Response() response.status_code = 200 if method == "GET": # TODO check if bucket exists result = '<NotificationConfiguration xmlns="%s">' % XMLNS_S3 if bucket in S3_NOTIFICATIONS: notif = S3_NOTIFICATIONS[bucket] events_string = "\n".join( ["<Event>%s</Event>" % e for e in notif["Event"]] ) for dest in ["Queue", "Topic", "CloudFunction"]: if dest in notif: result += ( """<{dest}Configuration> <Id>{uid}</Id> <{dest}>{endpoint}</{dest}> {events} </{dest}Configuration>""" ).format( dest=dest, uid=uuid.uuid4(), endpoint=notif[dest], events=events_string, ) result += "</NotificationConfiguration>" response._content = result if method == "PUT": parsed = xmltodict.parse(data) notif_config = parsed.get("NotificationConfiguration") S3_NOTIFICATIONS.pop(bucket, None) for dest in ["Queue", "Topic", "CloudFunction"]: config = notif_config.get("%sConfiguration" % (dest)) if config: events = config.get("Event") if isinstance(events, six.string_types): events = [events] notification_details = { "Id": config.get("Id"), "Event": events, dest: config.get(dest), "Filter": config.get("Filter"), } # TODO: what if we have multiple destinations - would we overwrite the config? S3_NOTIFICATIONS[bucket] = clone(notification_details) # return response for ?notification request return response if query == "cors" or "cors" in query_map: if method == "GET": return get_cors(bucket) if method == "PUT": return set_cors(bucket, data) if method == "DELETE": return delete_cors(bucket) if modified_data: return Request(data=modified_data, headers=headers, method=method) return True
def forward_request(self, method, path, data, headers): modified_data = None # If this request contains streaming v4 authentication signatures, strip them from the message # Related isse: https://github.com/localstack/localstack/issues/98 # TODO we should evaluate whether to replace moto s3 with scality/S3: # https://github.com/scality/S3/issues/237 if headers.get("x-amz-content-sha256") == "STREAMING-AWS4-HMAC-SHA256-PAYLOAD": modified_data = strip_chunk_signatures(data) # POST requests to S3 may include a "${filename}" placeholder in the # key, which should be replaced with an actual file name before storing. if method == "POST": original_data = modified_data or data expanded_data = expand_multipart_filename(original_data, headers) if expanded_data is not original_data: modified_data = expanded_data # persist this API call to disk persistence.record("s3", method, path, data, headers) parsed = urlparse.urlparse(path) query = parsed.query path = parsed.path bucket = path.split("/")[1] query_map = urlparse.parse_qs(query) if query == "notification" or "notification" in query_map: response = Response() response.status_code = 200 if method == "GET": # TODO check if bucket exists result = '<NotificationConfiguration xmlns="%s">' % XMLNS_S3 if bucket in S3_NOTIFICATIONS: notif = S3_NOTIFICATIONS[bucket] events_string = "\n".join( ["<Event>%s</Event>" % e for e in notif["Event"]] ) for dest in ["Queue", "Topic", "CloudFunction"]: if dest in notif: result += ( """<{dest}Configuration> <Id>{uid}</Id> <{dest}>{endpoint}</{dest}> {events} </{dest}Configuration>""" ).format( dest=dest, uid=uuid.uuid4(), endpoint=notif[dest], events=events_string, ) result += "</NotificationConfiguration>" response._content = result if method == "PUT": parsed = xmltodict.parse(data) notif_config = parsed.get("NotificationConfiguration") for dest in ["Queue", "Topic", "CloudFunction"]: config = notif_config.get("%sConfiguration" % (dest)) if config: # TODO: what if we have multiple destinations - would we overwrite the config? notification_details = { "Id": config.get("Id"), "Event": config.get("Event"), dest: config.get(dest), "Filter": config.get("Filter"), } S3_NOTIFICATIONS[bucket] = json.loads( json.dumps(notification_details) ) # return response for ?notification request return response if query == "cors" or "cors" in query_map: if method == "GET": return get_cors(bucket) if method == "PUT": return set_cors(bucket, data) if method == "DELETE": return delete_cors(bucket) if modified_data: return Request(data=modified_data, headers=headers, method=method) return True
https://github.com/localstack/localstack/issues/396
2017-10-10T10:58:34:ERROR:localstack.services.generic_proxy: Error forwarding request: string indices must be integers Traceback (most recent call last): File "/usr/local/lib/python3.6/site-packages/localstack/services/generic_proxy.py", line 194, in forward path=path, data=data, headers=forward_headers, response=response) File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 436, in return_response send_notifications(method, bucket_name, object_path) File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 122, in send_notifications filter_rules_match(config.get('Filter'), object_path)): File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 50, in filter_rules_match if rule['Name'] == 'prefix': TypeError: string indices must be integers
TypeError
def filter_rules_match(filters, object_path): """check whether the given object path matches all of the given filters""" filters = filters or {} s3_filter = _get_s3_filter(filters) for rule in s3_filter.get("FilterRule", []): if rule["Name"] == "prefix": if not prefix_with_slash(object_path).startswith( prefix_with_slash(rule["Value"]) ): return False elif rule["Name"] == "suffix": if not object_path.endswith(rule["Value"]): return False else: LOGGER.warning('Unknown filter name: "%s"' % rule["Name"]) return True
def filter_rules_match(filters, object_path): """check whether the given object path matches all of the given filters""" filters = filters or {} key_filter = filters.get("S3Key", filters.get("Key", {})) for rule in key_filter.get("FilterRule", []): if rule["Name"] == "prefix": if not prefix_with_slash(object_path).startswith( prefix_with_slash(rule["Value"]) ): return False elif rule["Name"] == "suffix": if not object_path.endswith(rule["Value"]): return False else: LOGGER.warning('Unknown filter name: "%s"' % rule["Name"]) return True
https://github.com/localstack/localstack/issues/396
2017-10-10T10:58:34:ERROR:localstack.services.generic_proxy: Error forwarding request: string indices must be integers Traceback (most recent call last): File "/usr/local/lib/python3.6/site-packages/localstack/services/generic_proxy.py", line 194, in forward path=path, data=data, headers=forward_headers, response=response) File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 436, in return_response send_notifications(method, bucket_name, object_path) File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 122, in send_notifications filter_rules_match(config.get('Filter'), object_path)): File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 50, in filter_rules_match if rule['Name'] == 'prefix': TypeError: string indices must be integers
TypeError
def expand_multipart_filename(data, headers): """Replace instance of '${filename}' in key with given file name. Data is given as multipart form submission bytes, and file name is replace according to Amazon S3 documentation for Post uploads: http://docs.aws.amazon.com/AmazonS3/latest/API/RESTObjectPOST.html """ _, params = cgi.parse_header(headers.get("Content-Type", "")) if "boundary" not in params: return data boundary = params["boundary"].encode("ascii") data_bytes = to_bytes(data) filename = None for disposition, _ in _iter_multipart_parts(data_bytes, boundary): if disposition.get("name") == "file" and "filename" in disposition: filename = disposition["filename"] break if filename is None: # Found nothing, return unaltered return data for disposition, part in _iter_multipart_parts(data_bytes, boundary): if disposition.get("name") == "key" and b"${filename}" in part: search = boundary + part replace = boundary + part.replace(b"${filename}", filename.encode("utf8")) if search in data_bytes: return data_bytes.replace(search, replace) return data
def expand_multipart_filename(data, headers): """Replace instance of '${filename}' in key with given file name. Data is given as multipart form submission bytes, and file name is replace according to Amazon S3 documentation for Post uploads: http://docs.aws.amazon.com/AmazonS3/latest/API/RESTObjectPOST.html """ _, params = cgi.parse_header(headers.get("Content-Type")) if "boundary" not in params: return data boundary = params["boundary"].encode("ascii") data_bytes = to_bytes(data) filename = None for disposition, _ in _iter_multipart_parts(data_bytes, boundary): if disposition.get("name") == "file" and "filename" in disposition: filename = disposition["filename"] break if filename is None: # Found nothing, return unaltered return data for disposition, part in _iter_multipart_parts(data_bytes, boundary): if disposition.get("name") == "key" and b"${filename}" in part: search = boundary + part replace = boundary + part.replace(b"${filename}", filename.encode("utf8")) if search in data_bytes: return data_bytes.replace(search, replace) return data
https://github.com/localstack/localstack/issues/396
2017-10-10T10:58:34:ERROR:localstack.services.generic_proxy: Error forwarding request: string indices must be integers Traceback (most recent call last): File "/usr/local/lib/python3.6/site-packages/localstack/services/generic_proxy.py", line 194, in forward path=path, data=data, headers=forward_headers, response=response) File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 436, in return_response send_notifications(method, bucket_name, object_path) File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 122, in send_notifications filter_rules_match(config.get('Filter'), object_path)): File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 50, in filter_rules_match if rule['Name'] == 'prefix': TypeError: string indices must be integers
TypeError
def find_multipart_redirect_url(data, headers): """Return object key and redirect URL if they can be found. Data is given as multipart form submission bytes, and redirect is found in the success_action_redirect field according to Amazon S3 documentation for Post uploads: http://docs.aws.amazon.com/AmazonS3/latest/API/RESTObjectPOST.html """ _, params = cgi.parse_header(headers.get("Content-Type", "")) key, redirect_url = None, None if "boundary" not in params: return key, redirect_url boundary = params["boundary"].encode("ascii") data_bytes = to_bytes(data) for disposition, part in _iter_multipart_parts(data_bytes, boundary): if disposition.get("name") == "key": _, value = part.split(b"\r\n\r\n", 1) key = value.rstrip(b"\r\n--").decode("utf8") if key: for disposition, part in _iter_multipart_parts(data_bytes, boundary): if disposition.get("name") == "success_action_redirect": _, value = part.split(b"\r\n\r\n", 1) redirect_url = value.rstrip(b"\r\n--").decode("utf8") return key, redirect_url
def find_multipart_redirect_url(data, headers): """Return object key and redirect URL if they can be found. Data is given as multipart form submission bytes, and redirect is found in the success_action_redirect field according to Amazon S3 documentation for Post uploads: http://docs.aws.amazon.com/AmazonS3/latest/API/RESTObjectPOST.html """ _, params = cgi.parse_header(headers.get("Content-Type")) boundary = params["boundary"].encode("ascii") data_bytes = to_bytes(data) key, redirect_url = None, None for disposition, part in _iter_multipart_parts(data_bytes, boundary): if disposition.get("name") == "key": _, value = part.split(b"\r\n\r\n", 1) key = value.rstrip(b"\r\n--").decode("utf8") if key: for disposition, part in _iter_multipart_parts(data_bytes, boundary): if disposition.get("name") == "success_action_redirect": _, value = part.split(b"\r\n\r\n", 1) redirect_url = value.rstrip(b"\r\n--").decode("utf8") return key, redirect_url
https://github.com/localstack/localstack/issues/396
2017-10-10T10:58:34:ERROR:localstack.services.generic_proxy: Error forwarding request: string indices must be integers Traceback (most recent call last): File "/usr/local/lib/python3.6/site-packages/localstack/services/generic_proxy.py", line 194, in forward path=path, data=data, headers=forward_headers, response=response) File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 436, in return_response send_notifications(method, bucket_name, object_path) File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 122, in send_notifications filter_rules_match(config.get('Filter'), object_path)): File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 50, in filter_rules_match if rule['Name'] == 'prefix': TypeError: string indices must be integers
TypeError
def forward_request(self, method, path, data, headers): modified_data = None # If this request contains streaming v4 authentication signatures, strip them from the message # Related isse: https://github.com/localstack/localstack/issues/98 # TODO we should evaluate whether to replace moto s3 with scality/S3: # https://github.com/scality/S3/issues/237 if headers.get("x-amz-content-sha256") == "STREAMING-AWS4-HMAC-SHA256-PAYLOAD": modified_data = strip_chunk_signatures(data) # POST requests to S3 may include a "${filename}" placeholder in the # key, which should be replaced with an actual file name before storing. if method == "POST": original_data = modified_data or data expanded_data = expand_multipart_filename(original_data, headers) if expanded_data is not original_data: modified_data = expanded_data # persist this API call to disk persistence.record("s3", method, path, data, headers) parsed = urlparse.urlparse(path) query = parsed.query path = parsed.path bucket = path.split("/")[1] query_map = urlparse.parse_qs(query) if query == "notification" or "notification" in query_map: response = Response() response.status_code = 200 if method == "GET": # TODO check if bucket exists result = '<NotificationConfiguration xmlns="%s">' % XMLNS_S3 if bucket in S3_NOTIFICATIONS: notif = S3_NOTIFICATIONS[bucket] for dest in ["Queue", "Topic", "CloudFunction"]: if dest in notif: dest_dict = { "%sConfiguration" % dest: { "Id": uuid.uuid4(), dest: notif[dest], "Event": notif["Event"], "Filter": notif["Filter"], } } result += xmltodict.unparse(dest_dict, full_document=False) result += "</NotificationConfiguration>" response._content = result if method == "PUT": parsed = xmltodict.parse(data) notif_config = parsed.get("NotificationConfiguration") S3_NOTIFICATIONS.pop(bucket, None) for dest in ["Queue", "Topic", "CloudFunction"]: config = notif_config.get("%sConfiguration" % (dest)) if config: events = config.get("Event") if isinstance(events, six.string_types): events = [events] event_filter = config.get("Filter", {}) # make sure FilterRule is an array s3_filter = _get_s3_filter(event_filter) if s3_filter and not isinstance( s3_filter.get("FilterRule", []), list ): s3_filter["FilterRule"] = [s3_filter["FilterRule"]] # create final details dict notification_details = { "Id": config.get("Id"), "Event": events, dest: config.get(dest), "Filter": event_filter, } # TODO: what if we have multiple destinations - would we overwrite the config? S3_NOTIFICATIONS[bucket] = clone(notification_details) # return response for ?notification request return response if query == "cors" or "cors" in query_map: if method == "GET": return get_cors(bucket) if method == "PUT": return set_cors(bucket, data) if method == "DELETE": return delete_cors(bucket) if modified_data: return Request(data=modified_data, headers=headers, method=method) return True
def forward_request(self, method, path, data, headers): modified_data = None # If this request contains streaming v4 authentication signatures, strip them from the message # Related isse: https://github.com/localstack/localstack/issues/98 # TODO we should evaluate whether to replace moto s3 with scality/S3: # https://github.com/scality/S3/issues/237 if headers.get("x-amz-content-sha256") == "STREAMING-AWS4-HMAC-SHA256-PAYLOAD": modified_data = strip_chunk_signatures(data) # POST requests to S3 may include a "${filename}" placeholder in the # key, which should be replaced with an actual file name before storing. if method == "POST": original_data = modified_data or data expanded_data = expand_multipart_filename(original_data, headers) if expanded_data is not original_data: modified_data = expanded_data # persist this API call to disk persistence.record("s3", method, path, data, headers) parsed = urlparse.urlparse(path) query = parsed.query path = parsed.path bucket = path.split("/")[1] query_map = urlparse.parse_qs(query) if query == "notification" or "notification" in query_map: response = Response() response.status_code = 200 if method == "GET": # TODO check if bucket exists result = '<NotificationConfiguration xmlns="%s">' % XMLNS_S3 if bucket in S3_NOTIFICATIONS: notif = S3_NOTIFICATIONS[bucket] for dest in ["Queue", "Topic", "CloudFunction"]: if dest in notif: dest_dict = { "%sConfiguration" % dest: { "Id": uuid.uuid4(), dest: notif[dest], "Event": notif["Event"], "Filter": notif["Filter"], } } result += xmltodict.unparse(dest_dict, full_document=False) result += "</NotificationConfiguration>" response._content = result if method == "PUT": parsed = xmltodict.parse(data) notif_config = parsed.get("NotificationConfiguration") S3_NOTIFICATIONS.pop(bucket, None) for dest in ["Queue", "Topic", "CloudFunction"]: config = notif_config.get("%sConfiguration" % (dest)) if config: events = config.get("Event") if isinstance(events, six.string_types): events = [events] notification_details = { "Id": config.get("Id"), "Event": events, dest: config.get(dest), "Filter": config.get("Filter", {}), } # TODO: what if we have multiple destinations - would we overwrite the config? S3_NOTIFICATIONS[bucket] = clone(notification_details) # return response for ?notification request return response if query == "cors" or "cors" in query_map: if method == "GET": return get_cors(bucket) if method == "PUT": return set_cors(bucket, data) if method == "DELETE": return delete_cors(bucket) if modified_data: return Request(data=modified_data, headers=headers, method=method) return True
https://github.com/localstack/localstack/issues/396
2017-10-10T10:58:34:ERROR:localstack.services.generic_proxy: Error forwarding request: string indices must be integers Traceback (most recent call last): File "/usr/local/lib/python3.6/site-packages/localstack/services/generic_proxy.py", line 194, in forward path=path, data=data, headers=forward_headers, response=response) File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 436, in return_response send_notifications(method, bucket_name, object_path) File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 122, in send_notifications filter_rules_match(config.get('Filter'), object_path)): File "/usr/local/lib/python3.6/site-packages/localstack/services/s3/s3_listener.py", line 50, in filter_rules_match if rule['Name'] == 'prefix': TypeError: string indices must be integers
TypeError
def expand_multipart_filename(data, headers): """Replace instance of '${filename}' in key with given file name. Data is given as multipart form submission bytes, and file name is replace according to Amazon S3 documentation for Post uploads: http://docs.aws.amazon.com/AmazonS3/latest/API/RESTObjectPOST.html """ _, params = cgi.parse_header(headers.get("Content-Type")) if "boundary" not in params: return data boundary = params["boundary"].encode("ascii") data_bytes = to_bytes(data) filename = None for disposition, _ in _iter_multipart_parts(data_bytes, boundary): if disposition.get("name") == "file" and "filename" in disposition: filename = disposition["filename"] break if filename is None: # Found nothing, return unaltered return data for disposition, part in _iter_multipart_parts(data_bytes, boundary): if disposition.get("name") == "key" and b"${filename}" in part: search = boundary + part replace = boundary + part.replace(b"${filename}", filename.encode("utf8")) if search in data_bytes: return data_bytes.replace(search, replace) return data
def expand_multipart_filename(data, headers): """Replace instance of '${filename}' in key with given file name. Data is given as multipart form submission bytes, and file name is replace according to Amazon S3 documentation for Post uploads: http://docs.aws.amazon.com/AmazonS3/latest/API/RESTObjectPOST.html """ _, params = cgi.parse_header(headers.get("Content-Type")) boundary = params["boundary"].encode("ascii") data_bytes = to_bytes(data) filename = None for disposition, _ in _iter_multipart_parts(data_bytes, boundary): if disposition.get("name") == "file" and "filename" in disposition: filename = disposition["filename"] break if filename is None: # Found nothing, return unaltered return data for disposition, part in _iter_multipart_parts(data_bytes, boundary): if disposition.get("name") == "key" and b"${filename}" in part: search = boundary + part replace = boundary + part.replace(b"${filename}", filename.encode("utf8")) if search in data_bytes: return data_bytes.replace(search, replace) return data
https://github.com/localstack/localstack/issues/310
2017-09-11T04:24:30:ERROR:localstack.services.generic_proxy: Error forwarding request: 'boundary' Traceback (most recent call last): File "/opt/code/localstack/localstack/services/generic_proxy.py", line 166, in forward path=path, data=data, headers=forward_headers) File "/opt/code/localstack/localstack/services/s3/s3_listener.py", line 345, in forward_request expanded_data = expand_multipart_filename(original_data, headers) File "/opt/code/localstack/localstack/services/s3/s3_listener.py", line 261, in expand_multipart_filename boundary = params['boundary'].encode('ascii') KeyError: 'boundary'
KeyError
def post_request(): action = request.headers.get("x-amz-target") data = json.loads(to_str(request.data)) result = {} kinesis = aws_stack.connect_to_service("kinesis") if action == "%s.ListStreams" % ACTION_HEADER_PREFIX: result = { "Streams": list(DDB_STREAMS.values()), "LastEvaluatedStreamArn": "TODO", } elif action == "%s.DescribeStream" % ACTION_HEADER_PREFIX: for stream in DDB_STREAMS.values(): if stream["StreamArn"] == data["StreamArn"]: result = {"StreamDescription": stream} # get stream details dynamodb = aws_stack.connect_to_service("dynamodb") table_name = table_name_from_stream_arn(stream["StreamArn"]) stream_name = get_kinesis_stream_name(table_name) stream_details = kinesis.describe_stream(StreamName=stream_name) table_details = dynamodb.describe_table(TableName=table_name) stream["KeySchema"] = table_details["Table"]["KeySchema"] stream["Shards"] = stream_details["StreamDescription"]["Shards"] break if not result: return error_response( "Requested resource not found", error_type="ResourceNotFoundException" ) elif action == "%s.GetShardIterator" % ACTION_HEADER_PREFIX: # forward request to Kinesis API stream_name = stream_name_from_stream_arn(data["StreamArn"]) result = kinesis.get_shard_iterator( StreamName=stream_name, ShardId=data["ShardId"], ShardIteratorType=data["ShardIteratorType"], ) elif action == "%s.GetRecords" % ACTION_HEADER_PREFIX: kinesis_records = kinesis.get_records(**data) result = {"Records": []} for record in kinesis_records["Records"]: result["Records"].append(json.loads(to_str(record["Data"]))) else: print('WARNING: Unknown operation "%s"' % action) return jsonify(result)
def post_request(): action = request.headers.get("x-amz-target") data = json.loads(to_str(request.data)) result = None kinesis = aws_stack.connect_to_service("kinesis") if action == "%s.ListStreams" % ACTION_HEADER_PREFIX: result = { "Streams": list(DDB_STREAMS.values()), "LastEvaluatedStreamArn": "TODO", } elif action == "%s.DescribeStream" % ACTION_HEADER_PREFIX: for stream in DDB_STREAMS.values(): if stream["StreamArn"] == data["StreamArn"]: result = {"StreamDescription": stream} # get stream details dynamodb = aws_stack.connect_to_service("dynamodb") table_name = table_name_from_stream_arn(stream["StreamArn"]) stream_name = get_kinesis_stream_name(table_name) stream_details = kinesis.describe_stream(StreamName=stream_name) table_details = dynamodb.describe_table(TableName=table_name) stream["KeySchema"] = table_details["Table"]["KeySchema"] stream["Shards"] = stream_details["StreamDescription"]["Shards"] break elif action == "%s.GetShardIterator" % ACTION_HEADER_PREFIX: # forward request to Kinesis API stream_name = stream_name_from_stream_arn(data["StreamArn"]) result = kinesis.get_shard_iterator( StreamName=stream_name, ShardId=data["ShardId"], ShardIteratorType=data["ShardIteratorType"], ) elif action == "%s.GetRecords" % ACTION_HEADER_PREFIX: kinesis_records = kinesis.get_records(**data) result = {"Records": []} for record in kinesis_records["Records"]: result["Records"].append(json.loads(to_str(record["Data"]))) else: print('WARNING: Unknown operation "%s"' % action) return jsonify(result)
https://github.com/localstack/localstack/issues/219
$ localstack start Starting local dev environment. CTRL-C to quit. Error starting infrastructure: 'zipimport.zipimporter' object has no attribute 'path' Traceback (most recent call last): File ".../bin/localstack", line 86, in <module> infra.start_infra() File ".../lib/python3.6/site-packages/localstack/services/infra.py", line 362, in start_infra raise e File ".../lib/python3.6/site-packages/localstack/services/infra.py", line 306, in start_infra load_plugins() File ".../lib/python3.6/site-packages/localstack/services/infra.py", line 100, in load_plugins file_path = '%s/%s/plugins.py' % (module[0].path, module[1]) AttributeError: 'zipimport.zipimporter' object has no attribute 'path'
AttributeError
def forward(self, method): path = self.path if "://" in path: path = "/" + path.split("://", 1)[1].split("/", 1)[1] proxy_url = "http://%s%s" % (self.proxy.forward_host, path) target_url = self.path if "://" not in target_url: target_url = "http://%s%s" % (self.proxy.forward_host, target_url) data = None if method in ["POST", "PUT", "PATCH"]: data_string = self.data_bytes try: if not isinstance(data_string, string_types): data_string = data_string.decode(DEFAULT_ENCODING) data = json.loads(data_string) except Exception as e: # unable to parse JSON, fallback to verbatim string/bytes data = data_string forward_headers = CaseInsensitiveDict(self.headers) # update original "Host" header forward_headers["host"] = urlparse(target_url).netloc try: response = None modified_request = None # update listener (pre-invocation) if self.proxy.update_listener: listener_result = self.proxy.update_listener( method=method, path=path, data=data, headers=forward_headers, return_forward_info=True, ) if isinstance(listener_result, Response): response = listener_result elif isinstance(listener_result, Request): modified_request = listener_result data = modified_request.data forward_headers = modified_request.headers elif listener_result is not True: # get status code from response, or use Bad Gateway status code code = listener_result if isinstance(listener_result, int) else 503 self.send_response(code) self.end_headers() return if response is None: if modified_request: response = self.method( proxy_url, data=modified_request.data, headers=modified_request.headers, ) else: response = self.method( proxy_url, data=self.data_bytes, headers=forward_headers ) # update listener (post-invocation) if self.proxy.update_listener: updated_response = self.proxy.update_listener( method=method, path=path, data=data, headers=forward_headers, response=response, ) if isinstance(updated_response, Response): response = updated_response # copy headers and return response self.send_response(response.status_code) for header_key, header_value in iteritems(response.headers): self.send_header(header_key, header_value) self.end_headers() self.wfile.write(bytes_(response.content)) except Exception as e: if not self.proxy.quiet: LOGGER.exception("Error forwarding request: %s" % str(e))
def forward(self, method): path = self.path if "://" in path: path = "/" + path.split("://", 1)[1].split("/", 1)[1] proxy_url = "http://%s%s" % (self.proxy.forward_host, path) target_url = self.path if "://" not in target_url: target_url = "http://%s%s" % (self.proxy.forward_host, target_url) data = None if method in ["POST", "PUT", "PATCH"]: data_string = self.data_bytes try: if not isinstance(data_string, string_types): data_string = data_string.decode(DEFAULT_ENCODING) data = json.loads(data_string) except Exception as e: # unable to parse JSON, fallback to verbatim string/bytes data = data_string forward_headers = dict(self.headers) # update original "Host" header forward_headers["host"] = urlparse(target_url).netloc try: response = None modified_request = None # update listener (pre-invocation) if self.proxy.update_listener: listener_result = self.proxy.update_listener( method=method, path=path, data=data, headers=forward_headers, return_forward_info=True, ) if isinstance(listener_result, Response): response = listener_result elif isinstance(listener_result, Request): modified_request = listener_result elif listener_result is not True: # get status code from response, or use Bad Gateway status code code = listener_result if isinstance(listener_result, int) else 503 self.send_response(code) self.end_headers() return if response is None: if modified_request: response = self.method( proxy_url, data=modified_request.data, headers=modified_request.headers, ) else: response = self.method( proxy_url, data=self.data_bytes, headers=forward_headers ) # update listener (post-invocation) if self.proxy.update_listener: updated_response = self.proxy.update_listener( method=method, path=path, data=data, headers=self.headers, response=response, ) if isinstance(updated_response, Response): response = updated_response # copy headers and return response self.send_response(response.status_code) for header_key, header_value in iteritems(response.headers): self.send_header(header_key, header_value) self.end_headers() self.wfile.write(bytes_(response.content)) except Exception as e: if not self.proxy.quiet: LOGGER.exception("Error forwarding request: %s" % str(e))
https://github.com/localstack/localstack/issues/83
ERROR:localstack.mock.generic_proxy:Error forwarding request: Traceback (most recent call last): File "/opt/code/localstack/localstack/mock/generic_proxy.py", line 88, in forward data=data, headers=self.headers, return_forward_info=True) File "/opt/code/localstack/localstack/mock/proxy/sns_listener.py", line 37, in update_sns queue_url = aws_stack.get_sqs_queue_url(queue_name) File "/opt/code/localstack/localstack/utils/aws/aws_stack.py", line 285, in get_sqs_queue_url response = client.get_queue_url(QueueName=queue_name) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 253, in _api_call return self._make_api_call(operation_name, kwargs) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 531, in _make_api_call operation_model, request_dict) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 141, in make_request return self._send_request(request_dict, operation_model) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 168, in _send_request request, operation_model, attempts) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 233, in _get_response response_dict, operation_model.output_shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 210, in parse parsed = self._do_error_parse(response, shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 438, in _do_error_parse root = self._parse_xml_string_to_dom(xml_contents) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 390, in _parse_xml_string_to_dom "invalid XML received:\n%s" % (e, xml_string)) ResponseParserError: Unable to parse response (syntax error: line 1, column 54), invalid XML received: <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2 Final//EN"> <title>500 Internal Server Error</title> <h1>Internal Server Error</h1> <p>The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application.</p>
ResponseParserError
def update_cloudformation( method, path, data, headers, response=None, return_forward_info=False ): req_data = None if method == "POST" and path == "/": req_data = urlparse.parse_qs(data) action = req_data.get("Action")[0] if return_forward_info: if req_data: if action == "CreateChangeSet": return create_change_set(req_data) elif action == "DescribeChangeSet": return describe_change_set(req_data) elif action == "ExecuteChangeSet": return execute_change_set(req_data) elif action == "UpdateStack" and req_data.get("TemplateURL"): # Temporary fix until the moto CF backend can handle TemplateURL (currently fails) url = re.sub( r"https?://s3\.amazonaws\.com", aws_stack.get_local_service_url("s3"), req_data.get("TemplateURL")[0], ) req_data["TemplateBody"] = requests.get(url).content modified_data = urlparse.urlencode(req_data, doseq=True) return Request(data=modified_data, headers=headers, method=method) return True if req_data: if action == "DescribeStackResources": if response.status_code < 300: response_dict = xmltodict.parse(response.content)[ "DescribeStackResourcesResponse" ] resources = response_dict["DescribeStackResourcesResult"][ "StackResources" ] if not resources: # Check if stack exists stack_name = req_data.get("StackName")[0] cloudformation_client = aws_stack.connect_to_service( "cloudformation" ) try: cloudformation_client.describe_stacks(StackName=stack_name) except Exception as e: return error_response( "Stack with id %s does not exist" % stack_name, code=404 ) if action == "DescribeStackResource": if response.status_code >= 500: # fix an error in moto where it fails with 500 if the stack does not exist return error_response("Stack resource does not exist", code=404) elif action == "CreateStack" or action == "UpdateStack": # run the actual deployment template = template_deployer.template_to_json( req_data.get("TemplateBody")[0] ) template_deployer.deploy_template(template, req_data.get("StackName")[0]) if response.status_code >= 400: return make_response(action)
def update_cloudformation( method, path, data, headers, response=None, return_forward_info=False ): req_data = None if method == "POST" and path == "/": req_data = urlparse.parse_qs(data) action = req_data.get("Action")[0] if return_forward_info: if req_data: if action == "CreateChangeSet": return create_change_set(req_data) elif action == "DescribeChangeSet": return describe_change_set(req_data) elif action == "ExecuteChangeSet": return execute_change_set(req_data) return True if req_data: if action == "DescribeStackResources": response_dict = xmltodict.parse(response.content)[ "DescribeStackResourcesResponse" ] resources = response_dict["DescribeStackResourcesResult"]["StackResources"] if not resources: # TODO: check if stack exists return error_response("Stack does not exist", code=404) if action == "DescribeStackResource": if response.status_code >= 500: # fix an error in moto where it fails with 500 if the stack does not exist return error_response("Stack resource does not exist", code=404) elif action == "CreateStack" or action == "UpdateStack": if response.status_code in range(200, 300): # run the actual deployment template = template_deployer.template_to_json( req_data.get("TemplateBody")[0] ) template_deployer.deploy_template(template)
https://github.com/localstack/localstack/issues/83
ERROR:localstack.mock.generic_proxy:Error forwarding request: Traceback (most recent call last): File "/opt/code/localstack/localstack/mock/generic_proxy.py", line 88, in forward data=data, headers=self.headers, return_forward_info=True) File "/opt/code/localstack/localstack/mock/proxy/sns_listener.py", line 37, in update_sns queue_url = aws_stack.get_sqs_queue_url(queue_name) File "/opt/code/localstack/localstack/utils/aws/aws_stack.py", line 285, in get_sqs_queue_url response = client.get_queue_url(QueueName=queue_name) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 253, in _api_call return self._make_api_call(operation_name, kwargs) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 531, in _make_api_call operation_model, request_dict) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 141, in make_request return self._send_request(request_dict, operation_model) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 168, in _send_request request, operation_model, attempts) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 233, in _get_response response_dict, operation_model.output_shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 210, in parse parsed = self._do_error_parse(response, shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 438, in _do_error_parse root = self._parse_xml_string_to_dom(xml_contents) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 390, in _parse_xml_string_to_dom "invalid XML received:\n%s" % (e, xml_string)) ResponseParserError: Unable to parse response (syntax error: line 1, column 54), invalid XML received: <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2 Final//EN"> <title>500 Internal Server Error</title> <h1>Internal Server Error</h1> <p>The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application.</p>
ResponseParserError
def update_dynamodb( method, path, data, headers, response=None, return_forward_info=False ): if return_forward_info: if random.random() < config.DYNAMODB_ERROR_PROBABILITY: return dynamodb_error_response(data) return True # update table definitions if data and "TableName" in data and "KeySchema" in data: TABLE_DEFINITIONS[data["TableName"]] = data action = headers.get("X-Amz-Target") if not action: return response_data = json.loads(to_str(response.content)) record = { "eventID": "1", "eventVersion": "1.0", "dynamodb": { "StreamViewType": "NEW_AND_OLD_IMAGES", "SequenceNumber": "1", "SizeBytes": -1, }, "awsRegion": DEFAULT_REGION, "eventSource": "aws:dynamodb", } event = {"Records": [record]} if action == "DynamoDB_20120810.UpdateItem": req = {"TableName": data["TableName"], "Key": data["Key"]} new_item = aws_stack.dynamodb_get_item_raw(req) if "Item" not in new_item: if "message" in new_item: ddb_client = aws_stack.connect_to_service("dynamodb") table_names = ddb_client.list_tables()["TableNames"] msg = "Unable to get item from DynamoDB (existing tables: %s): %s" % ( table_names, new_item["message"], ) LOGGER.warning(msg) return record["eventName"] = "MODIFY" record["dynamodb"]["Keys"] = data["Key"] record["dynamodb"]["NewImage"] = new_item["Item"] elif action == "DynamoDB_20120810.PutItem": record["eventName"] = "INSERT" keys = dynamodb_extract_keys(item=data["Item"], table_name=data["TableName"]) record["dynamodb"]["Keys"] = keys record["dynamodb"]["NewImage"] = data["Item"] elif action == "DynamoDB_20120810.DeleteItem": record["eventName"] = "REMOVE" record["dynamodb"]["Keys"] = data["Key"] elif action == "DynamoDB_20120810.CreateTable": if "StreamSpecification" in data: stream = data["StreamSpecification"] enabled = stream.get("StreamEnabled") if enabled not in [False, "False"]: table_name = data["TableName"] view_type = stream["StreamViewType"] dynamodbstreams_api.add_dynamodb_stream( table_name=table_name, view_type=view_type, enabled=enabled ) return else: # nothing to do return record["eventSourceARN"] = aws_stack.dynamodb_table_arn(data["TableName"]) sources = lambda_api.get_event_sources(source_arn=record["eventSourceARN"]) if len(sources) > 0: pass for src in sources: func_to_call = lambda_api.lambda_arn_to_function[src["FunctionArn"]] lambda_api.run_lambda( func_to_call, event=event, context={}, func_arn=src["FunctionArn"] )
def update_dynamodb( method, path, data, headers, response=None, return_forward_info=False ): if return_forward_info: if random.random() < config.DYNAMODB_ERROR_PROBABILITY: return dynamodb_error_response(data) return True # update table definitions if data and "TableName" in data and "KeySchema" in data: TABLE_DEFINITIONS[data["TableName"]] = data action = headers.get("X-Amz-Target") if not action: return response_data = json.loads(to_str(response.content)) record = { "eventID": "1", "eventVersion": "1.0", "dynamodb": { "StreamViewType": "NEW_AND_OLD_IMAGES", "SequenceNumber": "1", "SizeBytes": -1, }, "awsRegion": DEFAULT_REGION, "eventSource": "aws:dynamodb", } event = {"Records": [record]} if action == "DynamoDB_20120810.UpdateItem": req = {"TableName": data["TableName"], "Key": data["Key"]} new_item = aws_stack.dynamodb_get_item_raw(req) if "Item" not in new_item: if "message" in new_item: ddb_client = aws_stack.connect_to_service("dynamodb") table_names = ddb_client.list_tables()["TableNames"] msg = "Unable to get item from DynamoDB (existing tables: %s): %s" % ( table_names, new_item["message"], ) LOGGER.warning(msg) return record["eventName"] = "MODIFY" record["dynamodb"]["Keys"] = data["Key"] record["dynamodb"]["NewImage"] = new_item["Item"] elif action == "DynamoDB_20120810.PutItem": record["eventName"] = "INSERT" keys = dynamodb_extract_keys(item=data["Item"], table_name=data["TableName"]) record["dynamodb"]["Keys"] = keys record["dynamodb"]["NewImage"] = data["Item"] elif action == "DynamoDB_20120810.DeleteItem": record["eventName"] = "REMOVE" record["dynamodb"]["Keys"] = data["Key"] elif action == "DynamoDB_20120810.CreateTable": if "StreamSpecification" in data: stream = data["StreamSpecification"] enabled = stream["StreamEnabled"] if enabled: table_name = data["TableName"] view_type = stream["StreamViewType"] dynamodbstreams_api.add_dynamodb_stream( table_name=table_name, view_type=view_type, enabled=enabled ) return else: # nothing to do return record["eventSourceARN"] = aws_stack.dynamodb_table_arn(data["TableName"]) sources = lambda_api.get_event_sources(source_arn=record["eventSourceARN"]) if len(sources) > 0: pass for src in sources: func_to_call = lambda_api.lambda_arn_to_function[src["FunctionArn"]] lambda_api.run_lambda( func_to_call, event=event, context={}, func_arn=src["FunctionArn"] )
https://github.com/localstack/localstack/issues/83
ERROR:localstack.mock.generic_proxy:Error forwarding request: Traceback (most recent call last): File "/opt/code/localstack/localstack/mock/generic_proxy.py", line 88, in forward data=data, headers=self.headers, return_forward_info=True) File "/opt/code/localstack/localstack/mock/proxy/sns_listener.py", line 37, in update_sns queue_url = aws_stack.get_sqs_queue_url(queue_name) File "/opt/code/localstack/localstack/utils/aws/aws_stack.py", line 285, in get_sqs_queue_url response = client.get_queue_url(QueueName=queue_name) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 253, in _api_call return self._make_api_call(operation_name, kwargs) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 531, in _make_api_call operation_model, request_dict) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 141, in make_request return self._send_request(request_dict, operation_model) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 168, in _send_request request, operation_model, attempts) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 233, in _get_response response_dict, operation_model.output_shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 210, in parse parsed = self._do_error_parse(response, shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 438, in _do_error_parse root = self._parse_xml_string_to_dom(xml_contents) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 390, in _parse_xml_string_to_dom "invalid XML received:\n%s" % (e, xml_string)) ResponseParserError: Unable to parse response (syntax error: line 1, column 54), invalid XML received: <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2 Final//EN"> <title>500 Internal Server Error</title> <h1>Internal Server Error</h1> <p>The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application.</p>
ResponseParserError
def update_s3(method, path, data, headers, response=None, return_forward_info=False): if return_forward_info: modified_data = None # If this request contains streaming v4 authentication signatures, strip them from the message # Related isse: https://github.com/atlassian/localstack/issues/98 # TODO we should evaluate whether to replace moto s3 with scality/S3: # https://github.com/scality/S3/issues/237 if headers.get("x-amz-content-sha256") == "STREAMING-AWS4-HMAC-SHA256-PAYLOAD": modified_data = strip_chunk_signatures(data) # persist this API call to disk persistence.record("s3", method, path, data, headers) parsed = urlparse.urlparse(path) query = parsed.query path = parsed.path bucket = path.split("/")[1] query_map = urlparse.parse_qs(query) if method == "PUT" and (query == "notification" or "notification" in query_map): tree = ET.fromstring(data) queue_config = tree.find("{%s}QueueConfiguration" % XMLNS_S3) if len(queue_config): S3_NOTIFICATIONS[bucket] = { "Id": get_xml_text(queue_config, "Id"), "Event": get_xml_text(queue_config, "Event", ns=XMLNS_S3), "Queue": get_xml_text(queue_config, "Queue", ns=XMLNS_S3), "Topic": get_xml_text(queue_config, "Topic", ns=XMLNS_S3), "CloudFunction": get_xml_text( queue_config, "CloudFunction", ns=XMLNS_S3 ), } if query == "cors" or "cors" in query_map: if method == "GET": return get_cors(bucket) if method == "PUT": return set_cors(bucket, data) if method == "DELETE": return delete_cors(bucket) if modified_data: return Request(data=modified_data, headers=headers, method=method) return True # get subscribers and send bucket notifications if method in ("PUT", "DELETE") and "/" in path[1:]: parts = path[1:].split("/", 1) bucket_name = parts[0] object_path = "/%s" % parts[1] send_notifications(method, bucket_name, object_path) # append CORS headers to response if response: parsed = urlparse.urlparse(path) bucket_name = parsed.path.split("/")[0] append_cors_headers( bucket_name, request_method=method, request_headers=headers, response=response, )
def update_s3(method, path, data, headers, response=None, return_forward_info=False): if return_forward_info: modified_data = None # If this request contains streaming v4 authentication signatures, strip them from the message # Related isse: https://github.com/atlassian/localstack/issues/98 # TODO we should evaluate whether to replace moto s3 with scality/S3: # https://github.com/scality/S3/issues/237 if headers.get("x-amz-content-sha256") == "STREAMING-AWS4-HMAC-SHA256-PAYLOAD": modified_data = strip_chunk_signatures(data) # persist this API call to disk persistence.record("s3", method, path, data, headers) parsed = urlparse.urlparse(path) query = parsed.query path = parsed.path bucket = path.split("/")[1] query_map = urlparse.parse_qs(query) if method == "PUT" and (query == "notification" or "notification" in query_map): tree = ET.fromstring(data) queue_config = tree.find("{%s}QueueConfiguration" % XMLNS_S3) if len(queue_config): S3_NOTIFICATIONS[bucket] = { "Id": get_xml_text(queue_config, "Id"), "Event": get_xml_text(queue_config, "Event", ns=XMLNS_S3), "Queue": get_xml_text(queue_config, "Queue", ns=XMLNS_S3), "Topic": get_xml_text(queue_config, "Topic", ns=XMLNS_S3), "CloudFunction": get_xml_text( queue_config, "CloudFunction", ns=XMLNS_S3 ), } if query == "cors" or "cors" in query_map: if method == "GET": return get_cors(bucket) if method == "PUT": return set_cors(bucket, data) if method == "DELETE": return delete_cors(bucket) if modified_data: return Request(data=modified_data, headers=headers) return True # get subscribers and send bucket notifications if method in ("PUT", "DELETE") and "/" in path[1:]: parts = path[1:].split("/", 1) bucket_name = parts[0] object_path = "/%s" % parts[1] send_notifications(method, bucket_name, object_path) # append CORS headers to response if response: parsed = urlparse.urlparse(path) bucket_name = parsed.path.split("/")[0] append_cors_headers( bucket_name, request_method=method, request_headers=headers, response=response, )
https://github.com/localstack/localstack/issues/83
ERROR:localstack.mock.generic_proxy:Error forwarding request: Traceback (most recent call last): File "/opt/code/localstack/localstack/mock/generic_proxy.py", line 88, in forward data=data, headers=self.headers, return_forward_info=True) File "/opt/code/localstack/localstack/mock/proxy/sns_listener.py", line 37, in update_sns queue_url = aws_stack.get_sqs_queue_url(queue_name) File "/opt/code/localstack/localstack/utils/aws/aws_stack.py", line 285, in get_sqs_queue_url response = client.get_queue_url(QueueName=queue_name) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 253, in _api_call return self._make_api_call(operation_name, kwargs) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 531, in _make_api_call operation_model, request_dict) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 141, in make_request return self._send_request(request_dict, operation_model) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 168, in _send_request request, operation_model, attempts) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 233, in _get_response response_dict, operation_model.output_shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 210, in parse parsed = self._do_error_parse(response, shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 438, in _do_error_parse root = self._parse_xml_string_to_dom(xml_contents) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 390, in _parse_xml_string_to_dom "invalid XML received:\n%s" % (e, xml_string)) ResponseParserError: Unable to parse response (syntax error: line 1, column 54), invalid XML received: <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2 Final//EN"> <title>500 Internal Server Error</title> <h1>Internal Server Error</h1> <p>The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application.</p>
ResponseParserError
def get_client(resource): resource_type = get_resource_type(resource) service = get_service_name(resource) resource_config = RESOURCE_TO_FUNCTION.get(resource_type) if resource_config is None: raise Exception( "CloudFormation deployment for resource type %s not yet implemented" % resource_type ) if ACTION_CREATE not in resource_config: # nothing to do for this resource return try: if resource_config[ACTION_CREATE].get("boto_client") == "resource": return aws_stack.connect_to_resource(service) return aws_stack.connect_to_service(service) except Exception as e: LOGGER.warning( 'Unable to get client for "%s" API, skipping deployment.' % service ) return None
def get_client(resource): resource_type = get_resource_type(resource) service = get_service_name(resource) if ( RESOURCE_TO_FUNCTION[resource_type][ACTION_CREATE].get("boto_client") == "resource" ): return aws_stack.connect_to_resource(service) return aws_stack.connect_to_service(service)
https://github.com/localstack/localstack/issues/83
ERROR:localstack.mock.generic_proxy:Error forwarding request: Traceback (most recent call last): File "/opt/code/localstack/localstack/mock/generic_proxy.py", line 88, in forward data=data, headers=self.headers, return_forward_info=True) File "/opt/code/localstack/localstack/mock/proxy/sns_listener.py", line 37, in update_sns queue_url = aws_stack.get_sqs_queue_url(queue_name) File "/opt/code/localstack/localstack/utils/aws/aws_stack.py", line 285, in get_sqs_queue_url response = client.get_queue_url(QueueName=queue_name) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 253, in _api_call return self._make_api_call(operation_name, kwargs) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 531, in _make_api_call operation_model, request_dict) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 141, in make_request return self._send_request(request_dict, operation_model) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 168, in _send_request request, operation_model, attempts) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 233, in _get_response response_dict, operation_model.output_shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 210, in parse parsed = self._do_error_parse(response, shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 438, in _do_error_parse root = self._parse_xml_string_to_dom(xml_contents) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 390, in _parse_xml_string_to_dom "invalid XML received:\n%s" % (e, xml_string)) ResponseParserError: Unable to parse response (syntax error: line 1, column 54), invalid XML received: <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2 Final//EN"> <title>500 Internal Server Error</title> <h1>Internal Server Error</h1> <p>The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application.</p>
ResponseParserError
def deploy_resource(resource_id, resources, stack_name): resource = resources[resource_id] client = get_client(resource) if not client: return False resource_type = get_resource_type(resource) func_details = RESOURCE_TO_FUNCTION.get(resource_type) if not func_details: LOGGER.warning("Resource type not yet implemented: %s" % resource["Type"]) return func_details = func_details[ACTION_CREATE] function = getattr(client, func_details["function"]) params = dict(func_details["parameters"]) defaults = func_details.get("defaults", {}) if "Properties" not in resource: resource["Properties"] = {} # print('deploying', resource_id, resource_type) for param_key, prop_keys in iteritems(dict(params)): params.pop(param_key, None) if not isinstance(prop_keys, list): prop_keys = [prop_keys] for prop_key in prop_keys: if prop_key == PLACEHOLDER_RESOURCE_NAME: # obtain physical resource name from stack resources params[param_key] = resolve_ref( stack_name, resource_id, resources, attribute="PhysicalResourceId" ) else: prop_value = resource["Properties"].get(prop_key) if prop_value is not None: params[param_key] = prop_value tmp_value = params.get(param_key) if tmp_value is not None: params[param_key] = resolve_refs_recursively( stack_name, tmp_value, resources ) break # hack: convert to boolean if params.get(param_key) in ["True", "False"]: params[param_key] = params.get(param_key) == "True" # assign default value if empty params = common.merge_recursive(defaults, params) # invoke function try: result = function(**params) except Exception as e: LOGGER.warning( "Error calling %s with params: %s for resource: %s" % (function, params, resource) ) raise e # update status set_status_deployed(resource_id, resource, stack_name) return result
def deploy_resource(resource): client = get_client(resource) resource_type = get_resource_type(resource) func_details = RESOURCE_TO_FUNCTION.get(resource_type) if not func_details: LOGGER.warning("Resource type not yet implemented: %s" % resource["Type"]) return func_details = func_details[ACTION_CREATE] function = getattr(client, func_details["function"]) params = dict(func_details["parameters"]) if "Properties" not in resource: resource["Properties"] = {} for param_key, prop_key in iteritems(params): params[param_key] = resource["Properties"].get(prop_key) # invoke function return function(**params)
https://github.com/localstack/localstack/issues/83
ERROR:localstack.mock.generic_proxy:Error forwarding request: Traceback (most recent call last): File "/opt/code/localstack/localstack/mock/generic_proxy.py", line 88, in forward data=data, headers=self.headers, return_forward_info=True) File "/opt/code/localstack/localstack/mock/proxy/sns_listener.py", line 37, in update_sns queue_url = aws_stack.get_sqs_queue_url(queue_name) File "/opt/code/localstack/localstack/utils/aws/aws_stack.py", line 285, in get_sqs_queue_url response = client.get_queue_url(QueueName=queue_name) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 253, in _api_call return self._make_api_call(operation_name, kwargs) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 531, in _make_api_call operation_model, request_dict) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 141, in make_request return self._send_request(request_dict, operation_model) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 168, in _send_request request, operation_model, attempts) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 233, in _get_response response_dict, operation_model.output_shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 210, in parse parsed = self._do_error_parse(response, shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 438, in _do_error_parse root = self._parse_xml_string_to_dom(xml_contents) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 390, in _parse_xml_string_to_dom "invalid XML received:\n%s" % (e, xml_string)) ResponseParserError: Unable to parse response (syntax error: line 1, column 54), invalid XML received: <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2 Final//EN"> <title>500 Internal Server Error</title> <h1>Internal Server Error</h1> <p>The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application.</p>
ResponseParserError
def deploy_template(template, stack_name): if isinstance(template, string_types): template = parse_template(template) if MARKER_DONT_REDEPLOY_STACK in template: # If we are currently deploying, then bail. This can occur if # deploy_template(..) method calls boto's update_stack(..) (to update the # state of resources) which itself triggers another call to deploy_template(..). # We don't want to end up in an infinite/recursive deployment loop. return resource_map = template.get("Resources") if not resource_map: LOGGER.warning("CloudFormation template contains no Resources section") return next = resource_map # resource_list = resource_map.values() iters = 3 for i in range(0, iters): # print('deployment iteration', i) # get resource details for resource_id, resource in iteritems(next): resource["__details__"] = describe_stack_resources(stack_name, resource_id)[ 0 ] next = resources_to_deploy_next(resource_map, stack_name) if not next: return for resource_id, resource in iteritems(next): deploy_resource(resource_id, resource_map, stack_name=stack_name) LOGGER.warning( "Unable to resolve all dependencies and deploy all resources " + "after %s iterations. Remaining (%s): %s" % (iters, len(next), next) )
def deploy_template(template): if isinstance(template, string_types): template = parse_template(template) for key, resource in iteritems(template["Resources"]): deploy_resource(resource)
https://github.com/localstack/localstack/issues/83
ERROR:localstack.mock.generic_proxy:Error forwarding request: Traceback (most recent call last): File "/opt/code/localstack/localstack/mock/generic_proxy.py", line 88, in forward data=data, headers=self.headers, return_forward_info=True) File "/opt/code/localstack/localstack/mock/proxy/sns_listener.py", line 37, in update_sns queue_url = aws_stack.get_sqs_queue_url(queue_name) File "/opt/code/localstack/localstack/utils/aws/aws_stack.py", line 285, in get_sqs_queue_url response = client.get_queue_url(QueueName=queue_name) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 253, in _api_call return self._make_api_call(operation_name, kwargs) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/client.py", line 531, in _make_api_call operation_model, request_dict) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 141, in make_request return self._send_request(request_dict, operation_model) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 168, in _send_request request, operation_model, attempts) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/endpoint.py", line 233, in _get_response response_dict, operation_model.output_shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 210, in parse parsed = self._do_error_parse(response, shape) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 438, in _do_error_parse root = self._parse_xml_string_to_dom(xml_contents) File "/opt/code/localstack/.venv/lib/python2.7/site-packages/botocore/parsers.py", line 390, in _parse_xml_string_to_dom "invalid XML received:\n%s" % (e, xml_string)) ResponseParserError: Unable to parse response (syntax error: line 1, column 54), invalid XML received: <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2 Final//EN"> <title>500 Internal Server Error</title> <h1>Internal Server Error</h1> <p>The server encountered an internal error and was unable to complete your request. Either the server is overloaded or there is an error in the application.</p>
ResponseParserError
def send_command(): """ Run a remote command. This is called via py3-cmd utility. We look for any uds sockets with the correct name prefix and send our command to all that we find. This allows us to communicate with multiple py3status instances. """ def verbose(msg): """ print output if verbose is set. """ if options.verbose: print(msg) options = command_parser() msg = json.dumps(vars(options)).encode("utf-8") if len(msg) > MAX_SIZE: verbose(f"Message length too long, max length ({MAX_SIZE})") # find all likely socket addresses uds_list = Path(SERVER_ADDRESS).parent.glob(f"{Path(SERVER_ADDRESS).name}.[0-9]*") verbose(f"message {msg!r}") for uds in uds_list: # Create a UDS socket sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM) # Connect the socket to the port where the server is listening verbose(f"connecting to {uds}") try: sock.connect(uds.as_posix()) except OSError: # this is a stale socket so delete it verbose("stale socket deleting") try: uds.unlink() except OSError: pass continue try: # Send data verbose("sending") sock.sendall(msg) finally: verbose("closing socket") sock.close()
def send_command(): """ Run a remote command. This is called via py3-cmd utility. We look for any uds sockets with the correct name prefix and send our command to all that we find. This allows us to communicate with multiple py3status instances. """ def verbose(msg): """ print output if verbose is set. """ if options.verbose: print(msg) options = command_parser() msg = json.dumps(vars(options)).encode("utf-8") if len(msg) > MAX_SIZE: verbose(f"Message length too long, max length ({MAX_SIZE})") # find all likely socket addresses uds_list = Path(".").glob(f"{SERVER_ADDRESS}.[0-9]*") verbose(f"message {msg!r}") for uds in uds_list: # Create a UDS socket sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM) # Connect the socket to the port where the server is listening verbose(f"connecting to {uds}") try: sock.connect(uds) except OSError: # this is a stale socket so delete it verbose("stale socket deleting") try: uds.unlink() except OSError: pass continue try: # Send data verbose("sending") sock.sendall(msg) finally: verbose("closing socket") sock.close()
https://github.com/ultrabug/py3status/issues/2003
$ uname -a Linux eolas 5.10.12-arch1-1 #1 SMP PREEMPT Sun, 31 Jan 2021 00:41:06 +0000 x86_64 GNU/Linux $ py3-cmd --version py3status 3.32 (python 3.9.1) $ py3-cmd refresh --all Traceback (most recent call last): File "/usr/bin/py3-cmd", line 13, in <module> sys.exit(send_command()) File "/usr/lib/python3.9/site-packages/py3status/command.py", line 534, in send_command for uds in uds_list: File "/usr/lib/python3.9/pathlib.py", line 1164, in glob raise NotImplementedError("Non-relative patterns are unsupported") NotImplementedError: Non-relative patterns are unsupported
NotImplementedError
def _add_player(self, player_id): """ Add player to mpris_players """ if not player_id.startswith(SERVICE_BUS): return False player = self._dbus.get(player_id, SERVICE_BUS_URL) if player.Identity not in self._mpris_names: self._mpris_names[player.Identity] = player_id.split(".")[-1] for p in self._mpris_players.values(): if not p["name"] and p["identity"] in self._mpris_names: p["name"] = self._mpris_names[p["identity"]] p["full_name"] = "{} {}".format(p["name"], p["index"]) identity = player.Identity name = self._mpris_names.get(identity) if ( self.player_priority != [] and name not in self.player_priority and "*" not in self.player_priority ): return False if identity not in self._mpris_name_index: self._mpris_name_index[identity] = 0 status = player.PlaybackStatus state_priority = WORKING_STATES.index(status) index = self._mpris_name_index[identity] self._mpris_name_index[identity] += 1 try: subscription = player.PropertiesChanged.connect(self._player_monitor(player_id)) except AttributeError: subscription = {} self._mpris_players[player_id] = { "_dbus_player": player, "_id": player_id, "_state_priority": state_priority, "index": index, "identity": identity, "name": name, "full_name": "{} {}".format(name, index), "status": status, "subscription": subscription, } return True
def _add_player(self, player_id): """ Add player to mpris_players """ if not player_id.startswith(SERVICE_BUS): return False player = self._dbus.get(player_id, SERVICE_BUS_URL) if player.Identity not in self._mpris_names: self._mpris_names[player.Identity] = player_id.split(".")[-1] for p in self._mpris_players.values(): if not p["name"] and p["identity"] in self._mpris_names: p["name"] = self._mpris_names[p["identity"]] p["full_name"] = "{} {}".format(p["name"], p["index"]) identity = player.Identity name = self._mpris_names.get(identity) if ( self.player_priority != [] and name not in self.player_priority and "*" not in self.player_priority ): return False if identity not in self._mpris_name_index: self._mpris_name_index[identity] = 0 status = player.PlaybackStatus state_priority = WORKING_STATES.index(status) index = self._mpris_name_index[identity] self._mpris_name_index[identity] += 1 subscription = player.PropertiesChanged.connect(self._player_monitor(player_id)) self._mpris_players[player_id] = { "_dbus_player": player, "_id": player_id, "_state_priority": state_priority, "index": index, "identity": identity, "name": name, "full_name": "{} {}".format(name, index), "status": status, "subscription": subscription, } return True
https://github.com/ultrabug/py3status/issues/911
lasers~/src/py3status/py3status/modules git:(master) python3 mpris.py. Traceback (most recent call last): File "mpris.py", line 578, in <module> module_test(Py3status) File "/usr/lib/python3.6/site-packages/py3status-3.6rc1-py3.6.egg/py3status/module_test.py", line 47, in module_test module.post_config_hook() File "mpris.py", line 176, in post_config_hook self._start_listener() File "mpris.py", line 454, in _start_listener self._get_players() File "mpris.py", line 440, in _get_players self._add_player(player) File "mpris.py", line 411, in _add_player subscription = player.PropertiesChanged.connect(self._player_monitor(player_id)) AttributeError: '<CompositeObject>' object has no attribute 'PropertiesChanged'
AttributeError
def backlight(self): full_text = "" if self.device_path is not None: level = self._get_backlight_level() full_text = self.py3.safe_format(self.format, {"level": level}) response = { "cached_until": self.py3.time_in(self.cache_timeout), "full_text": full_text, } return response
def backlight(self): level = self._get_backlight_level() full_text = self.py3.safe_format(self.format, {"level": level}) response = { "cached_until": self.py3.time_in(self.cache_timeout), "full_text": full_text, } return response
https://github.com/ultrabug/py3status/issues/557
Traceback (most recent call last): File "battery_level.py", line 448, in <module> module_test(Py3status) File "/usr/lib/python3.5/site-packages/py3status/module_test.py", line 51, in module_test print(getattr(module, method)(*method_args)) File "battery_level.py", line 174, in battery_level self._refresh_battery_info() File "battery_level.py", line 316, in _refresh_battery_info battery = battery_list[self.battery_id] IndexError: list index out of range
IndexError
def battery_level(self): if not os.listdir(self.sys_battery_path): return {"full_text": "", "cached_until": self.py3.time_in(self.cache_timeout)} self._refresh_battery_info() self._update_icon() self._update_ascii_bar() self._update_full_text() return self._build_response()
def battery_level(self): self._refresh_battery_info() self._update_icon() self._update_ascii_bar() self._update_full_text() return self._build_response()
https://github.com/ultrabug/py3status/issues/557
Traceback (most recent call last): File "battery_level.py", line 448, in <module> module_test(Py3status) File "/usr/lib/python3.5/site-packages/py3status/module_test.py", line 51, in module_test print(getattr(module, method)(*method_args)) File "battery_level.py", line 174, in battery_level self._refresh_battery_info() File "battery_level.py", line 316, in _refresh_battery_info battery = battery_list[self.battery_id] IndexError: list index out of range
IndexError
def _config_from_pyproject(path): if os.path.isfile(path): try: with open(path, "r") as f: pyproject = tomlkit.loads(f.read()) if pyproject: return pyproject.get("tool", {}).get("semantic_release", {}) except TOMLKitError as e: logger.debug(f"Could not decode pyproject.toml: {e}") return {}
def _config_from_pyproject(path): if os.path.isfile(path): try: with open(path, "r") as f: pyproject = tomlkit.loads(f.read()) if pyproject: return dict(pyproject.get("tool").get("semantic_release")) except TOMLKitError as e: logger.debug(f"Could not decode pyproject.toml: {e}") return {}
https://github.com/relekang/python-semantic-release/issues/317
Run relekang/python-semantic-release@master /usr/bin/docker run --name eb9cc679ae0e4f1f83d7f2d23985a34f_6e2f70 --label 442333 --workdir /github/workspace --rm -e INPUT_GITHUB_TOKEN -e INPUT_PYPI_TOKEN -e INPUT_DIRECTORY -e INPUT_PYPI_USERNAME -e INPUT_PYPI_PASSWORD -e HOME -e GITHUB_JOB -e GITHUB_REF -e GITHUB_SHA -e GITHUB_REPOSITORY -e GITHUB_REPOSITORY_OWNER -e GITHUB_RUN_ID -e GITHUB_RUN_NUMBER -e GITHUB_RETENTION_DAYS -e GITHUB_ACTOR -e GITHUB_WORKFLOW -e GITHUB_HEAD_REF -e GITHUB_BASE_REF -e GITHUB_EVENT_NAME -e GITHUB_SERVER_URL -e GITHUB_API_URL -e GITHUB_GRAPHQL_URL -e GITHUB_WORKSPACE -e GITHUB_ACTION -e GITHUB_EVENT_PATH -e GITHUB_ACTION_REPOSITORY -e GITHUB_ACTION_REF -e GITHUB_PATH -e GITHUB_ENV -e RUNNER_OS -e RUNNER_TOOL_CACHE -e RUNNER_TEMP -e RUNNER_WORKSPACE -e ACTIONS_RUNTIME_URL -e ACTIONS_RUNTIME_TOKEN -e ACTIONS_CACHE_URL -e GITHUB_ACTIONS=true -e CI=true -v "/var/run/docker.sock":"/var/run/docker.sock" -v "/home/runner/work/_temp/_github_home":"/github/home" -v "/home/runner/work/_temp/_github_workflow":"/github/workflow" -v "/home/runner/work/_temp/_runner_file_commands":"/github/file_commands" -v "/home/runner/work/arbie/arbie":"/github/workspace" 442333:eb9cc679ae0e4f1f83d7f2d23985a34f Traceback (most recent call last): File "/usr/local/lib/python3.7/runpy.py", line 193, in _run_module_as_main "__main__", mod_spec) File "/usr/local/lib/python3.7/runpy.py", line 85, in _run_code exec(code, run_globals) File "/semantic-release/semantic_release/__main__.py", line 1, in <module> from .cli import entry File "/semantic-release/semantic_release/cli.py", line 13, in <module> from .changelog import markdown_changelog File "/semantic-release/semantic_release/changelog/__init__.py", line 4, in <module> from ..settings import config, current_changelog_components File "/semantic-release/semantic_release/settings.py", line 77, in <module> config = _config() File "/semantic-release/semantic_release/settings.py", line 29, in _config toml_config = _config_from_pyproject(toml_path) File "/semantic-release/semantic_release/settings.py", line 70, in _config_from_pyproject return dict(pyproject.get("tool").get("semantic_release")) TypeError: 'NoneType' object is not iterable
TypeError
def commit_new_version(version: str): """ Commits the file containing the version number variable with the version number as the commit message. :param version: The version number to be used in the commit message. """ check_repo() commit_message = config.get("semantic_release", "commit_message") message = "{0}\n\n{1}".format(version, commit_message) version_file = config.get("semantic_release", "version_variable").split(":")[0] # get actual path to filename, to allow running cmd from subdir of git root version_filepath = PurePath(os.getcwd(), version_file).relative_to(repo.working_dir) repo.git.add(str(version_filepath)) return repo.git.commit(m=message, author="semantic-release <semantic-release>")
def commit_new_version(version: str): """ Commits the file containing the version number variable with the version number as the commit message. :param version: The version number to be used in the commit message. """ check_repo() commit_message = config.get("semantic_release", "commit_message") message = "{0}\n\n{1}".format(version, commit_message) repo.git.add(config.get("semantic_release", "version_variable").split(":")[0]) return repo.git.commit(m=message, author="semantic-release <semantic-release>")
https://github.com/relekang/python-semantic-release/issues/66
venv) C:\workspace\checklive\src>semantic-release --patch publish Traceback (most recent call last): File "c:\python35\lib\runpy.py", line 170, in _run_module_as_main "__main__", mod_spec) File "c:\python35\lib\runpy.py", line 85, in _run_code exec(code, run_globals) File "C:\workspace\checklive\venv\Scripts\semantic-release.exe\__main__.py", line 5, in <module> File "c:\workspace\checklive\venv\lib\site-packages\semantic_release\cli.py", line 9, in <module> from .history import (evaluate_version_bump, get_current_version, get_new_version, File "c:\workspace\checklive\venv\lib\site-packages\semantic_release\history\__init__.py", line 6, in <module> from ..vcs_helpers import get_commit_log, get_last_version File "c:\workspace\checklive\venv\lib\site-packages\semantic_release\vcs_helpers.py", line 8, in <module> repo = Repo('.git', search_parent_directories=True) File "c:\workspace\checklive\venv\lib\site-packages\git\repo\base.py", line 135, in __init__ raise NoSuchPathError(epath) git.exc.NoSuchPathError: C:\workspace\checklive\src\.git (venv) C:\workspace\checklive\src>
git.exc.NoSuchPathError
def __getattr__(self, key): # TODO keep this for a version, in order to not break old code # this entire method (as well as the _dict attribute in __slots__ and the __setattr__ method) # can be removed in 4.0 # this method is only called if the attribute was not found elsewhere, like in __slots_ if key not in self.__slots__: raise AttributeError try: warnings.warn( "Custom attributes of messages are deprecated and will be removed in 4.0", DeprecationWarning, ) return self._dict[key] except KeyError: raise AttributeError("'message' object has no attribute '{}'".format(key))
def __getattr__(self, key): # TODO keep this for a version, in order to not break old code # this entire method (as well as the _dict attribute in __slots__ and the __setattr__ method) # can be removed in 4.0 # this method is only called if the attribute was not found elsewhere, like in __slots__ try: warnings.warn( "Custom attributes of messages are deprecated and will be removed in 4.0", DeprecationWarning, ) return self._dict[key] except KeyError: raise AttributeError("'message' object has no attribute '{}'".format(key))
https://github.com/hardbyte/python-can/issues/804
/usr/bin/python3.7 /XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX/SerializationTest.py 2020-04-02 13:35:59,352:MainThread:INFO: Created a socket 2020-04-02 13:35:59,389:MainThread:INFO: pickled Traceback (most recent call last): File "/XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX/SerializationTest.py", line 39, in <module> canReader.run() File "/XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX/SerializationTest.py", line 29, in run unpick = pickle.loads(pick) File "/home/XXXXXX/.local/lib/python3.7/site-packages/can/message.py", line 59, in __getattr__ return self._dict[key] File "/home/XXXXXX/.local/lib/python3.7/site-packages/can/message.py", line 59, in __getattr__ return self._dict[key] File "/home/XXXXXX/.local/lib/python3.7/site-packages/can/message.py", line 59, in __getattr__ return self._dict[key] [Previous line repeated 494 more times] File "/home/XXXXXX/.local/lib/python3.7/site-packages/can/message.py", line 58, in __getattr__ warnings.warn("Custom attributes of messages are deprecated and will be removed in 4.0", DeprecationWarning) RecursionError: maximum recursion depth exceeded while calling a Python object Process finished with exit code 1
RecursionError
def build_bcm_header( opcode, flags, count, ival1_seconds, ival1_usec, ival2_seconds, ival2_usec, can_id, nframes, ): result = BcmMsgHead( opcode=opcode, flags=flags, count=count, ival1_tv_sec=ival1_seconds, ival1_tv_usec=ival1_usec, ival2_tv_sec=ival2_seconds, ival2_tv_usec=ival2_usec, can_id=can_id, nframes=nframes, ) return ctypes.string_at(ctypes.addressof(result), ctypes.sizeof(result))
def build_bcm_header( opcode, flags, count, ival1_seconds, ival1_usec, ival2_seconds, ival2_usec, can_id, nframes, ): # == Must use native not standard types for packing == # struct bcm_msg_head { # __u32 opcode; -> I # __u32 flags; -> I # __u32 count; -> I # struct timeval ival1, ival2; -> llll ... # canid_t can_id; -> I # __u32 nframes; -> I bcm_cmd_msg_fmt = "@3I4l2I0q" return struct.pack( bcm_cmd_msg_fmt, opcode, flags, count, ival1_seconds, ival1_usec, ival2_seconds, ival2_usec, can_id, nframes, )
https://github.com/hardbyte/python-can/issues/470
Traceback (most recent call last): File "./test.py", line 8, in <module> bus.send_periodic(msg, 0.01, 9) File "/usr/local/lib/python3.5/dist-packages/can/bus.py", line 201, in send_periodic task = self._send_periodic_internal(msg, period, duration) File "/usr/local/lib/python3.5/dist-packages/can/interfaces/socketcan/socketcan.py", line 601, in _send_periodic_internal task = CyclicSendTask(bcm_socket, msg, period, duration) File "/usr/local/lib/python3.5/dist-packages/can/interfaces/socketcan/socketcan.py", line 254, in __init__ self._tx_setup(message) File "/usr/local/lib/python3.5/dist-packages/can/interfaces/socketcan/socketcan.py", line 274, in _tx_setup send_bcm(self.bcm_socket, header + frame) File "/usr/local/lib/python3.5/dist-packages/can/interfaces/socketcan/socketcan.py", line 206, in send_bcm raise can.CanError(base + "You are probably referring to a non-existing frame.") can.CanError: Couldn't send CAN BCM frame. OS Error 22: Invalid argument You are probably referring to a non-existing frame.
can.CanError
def __init__(self, channel, ttyBaudrate=115200, timeout=1, bitrate=None, **kwargs): """ :param str channel: port of underlying serial or usb device (e.g. /dev/ttyUSB0, COM8, ...) Must not be empty. :param int ttyBaudrate: baudrate of underlying serial or usb device :param int bitrate: Bitrate in bit/s :param float poll_interval: Poll interval in seconds when reading messages :param float timeout: timeout in seconds when reading message """ if not channel: # if None or empty raise TypeError("Must specify a serial port.") if "@" in channel: (channel, ttyBaudrate) = channel.split("@") self.serialPortOrig = serial.Serial(channel, baudrate=ttyBaudrate, timeout=timeout) time.sleep(self._SLEEP_AFTER_SERIAL_OPEN) if bitrate is not None: self.close() if bitrate in self._BITRATES: self.write(self._BITRATES[bitrate]) else: raise ValueError( "Invalid bitrate, choose one of " + (", ".join(self._BITRATES)) + "." ) self.open() super(slcanBus, self).__init__( channel, ttyBaudrate=115200, timeout=1, bitrate=None, **kwargs )
def __init__(self, channel, ttyBaudrate=115200, timeout=1, bitrate=None, **kwargs): """ :param str channel: port of underlying serial or usb device (e.g. /dev/ttyUSB0, COM8, ...) Must not be empty. :param int ttyBaudrate: baudrate of underlying serial or usb device :param int bitrate: Bitrate in bit/s :param float poll_interval: Poll interval in seconds when reading messages :param float timeout: timeout in seconds when reading message """ if not channel: # if None or empty raise TypeError("Must specify a serial port.") if "@" in channel: (channel, ttyBaudrate) = channel.split("@") self.serialPortOrig = serial.Serial(channel, baudrate=ttyBaudrate, timeout=timeout) self.serialPort = io.TextIOWrapper( io.BufferedRWPair(self.serialPortOrig, self.serialPortOrig, 1), newline="\r", line_buffering=True, ) time.sleep(self._SLEEP_AFTER_SERIAL_OPEN) if bitrate is not None: self.close() if bitrate in self._BITRATES: self.write(self._BITRATES[bitrate]) else: raise ValueError( "Invalid bitrate, choose one of " + (", ".join(self._BITRATES)) + "." ) self.open() super(slcanBus, self).__init__( channel, ttyBaudrate=115200, timeout=1, bitrate=None, **kwargs )
https://github.com/hardbyte/python-can/issues/382
DEBUG:can:loaded can config: {'interface': 'slcan', 'channel': '/dev/ttyUSB0@115200'} Traceback (most recent call last): File "encoder-test.py", line 19, in <module> network.connect(channel='/dev/ttyUSB0@115200', bustype='slcan') File "/usr/local/lib/python3.5/dist-packages/canopen/network.py", line 100, in connect self.bus = can.interface.Bus(*args, **kwargs) File "/usr/local/lib/python3.5/dist-packages/can/interface.py", line 120, in __new__ return cls(channel, *args, **config) File "/usr/local/lib/python3.5/dist-packages/can/interfaces/slcan.py", line 81, in __init__ self.open() File "/usr/local/lib/python3.5/dist-packages/can/interfaces/slcan.py", line 93, in open self.write('O') File "/usr/local/lib/python3.5/dist-packages/can/interfaces/slcan.py", line 89, in write self.serialPort.write(string.decode()) AttributeError: 'str' object has no attribute 'decode'
AttributeError
def write(self, string): if not string.endswith("\r"): string += "\r" self.serialPortOrig.write(string.encode()) self.serialPortOrig.flush()
def write(self, string): if not string.endswith("\r"): string += "\r" self.serialPort.write(string.decode()) self.serialPort.flush()
https://github.com/hardbyte/python-can/issues/382
DEBUG:can:loaded can config: {'interface': 'slcan', 'channel': '/dev/ttyUSB0@115200'} Traceback (most recent call last): File "encoder-test.py", line 19, in <module> network.connect(channel='/dev/ttyUSB0@115200', bustype='slcan') File "/usr/local/lib/python3.5/dist-packages/canopen/network.py", line 100, in connect self.bus = can.interface.Bus(*args, **kwargs) File "/usr/local/lib/python3.5/dist-packages/can/interface.py", line 120, in __new__ return cls(channel, *args, **config) File "/usr/local/lib/python3.5/dist-packages/can/interfaces/slcan.py", line 81, in __init__ self.open() File "/usr/local/lib/python3.5/dist-packages/can/interfaces/slcan.py", line 93, in open self.write('O') File "/usr/local/lib/python3.5/dist-packages/can/interfaces/slcan.py", line 89, in write self.serialPort.write(string.decode()) AttributeError: 'str' object has no attribute 'decode'
AttributeError
def _recv_internal(self, timeout): if timeout is not None: self.serialPortOrig.timeout = timeout canId = None remote = False extended = False frame = [] readStr = self.serialPortOrig.read_until(b"\r") if not readStr: return None, False else: readStr = readStr.decode() if readStr[0] == "T": # extended frame canId = int(readStr[1:9], 16) dlc = int(readStr[9]) extended = True for i in range(0, dlc): frame.append(int(readStr[10 + i * 2 : 12 + i * 2], 16)) elif readStr[0] == "t": # normal frame canId = int(readStr[1:4], 16) dlc = int(readStr[4]) for i in range(0, dlc): frame.append(int(readStr[5 + i * 2 : 7 + i * 2], 16)) elif readStr[0] == "r": # remote frame canId = int(readStr[1:4], 16) remote = True elif readStr[0] == "R": # remote extended frame canId = int(readStr[1:9], 16) extended = True remote = True if canId is not None: msg = Message( arbitration_id=canId, extended_id=extended, timestamp=time.time(), # Better than nothing... is_remote_frame=remote, dlc=dlc, data=frame, ) return msg, False else: return None, False
def _recv_internal(self, timeout): if timeout is not None: self.serialPortOrig.timeout = timeout canId = None remote = False extended = False frame = [] readStr = self.serialPort.readline() if not readStr: return None, False else: if readStr[0] == "T": # extended frame canId = int(readStr[1:9], 16) dlc = int(readStr[9]) extended = True for i in range(0, dlc): frame.append(int(readStr[10 + i * 2 : 12 + i * 2], 16)) elif readStr[0] == "t": # normal frame canId = int(readStr[1:4], 16) dlc = int(readStr[4]) for i in range(0, dlc): frame.append(int(readStr[5 + i * 2 : 7 + i * 2], 16)) elif readStr[0] == "r": # remote frame canId = int(readStr[1:4], 16) remote = True elif readStr[0] == "R": # remote extended frame canId = int(readStr[1:9], 16) extended = True remote = True if canId is not None: msg = Message( arbitration_id=canId, extended_id=extended, timestamp=time.time(), # Better than nothing... is_remote_frame=remote, dlc=dlc, data=frame, ) return msg, False else: return None, False
https://github.com/hardbyte/python-can/issues/382
DEBUG:can:loaded can config: {'interface': 'slcan', 'channel': '/dev/ttyUSB0@115200'} Traceback (most recent call last): File "encoder-test.py", line 19, in <module> network.connect(channel='/dev/ttyUSB0@115200', bustype='slcan') File "/usr/local/lib/python3.5/dist-packages/canopen/network.py", line 100, in connect self.bus = can.interface.Bus(*args, **kwargs) File "/usr/local/lib/python3.5/dist-packages/can/interface.py", line 120, in __new__ return cls(channel, *args, **config) File "/usr/local/lib/python3.5/dist-packages/can/interfaces/slcan.py", line 81, in __init__ self.open() File "/usr/local/lib/python3.5/dist-packages/can/interfaces/slcan.py", line 93, in open self.write('O') File "/usr/local/lib/python3.5/dist-packages/can/interfaces/slcan.py", line 89, in write self.serialPort.write(string.decode()) AttributeError: 'str' object has no attribute 'decode'
AttributeError
def __init__(self, filename): self.fp = open(filename, "rb") data = self.fp.read(FILE_HEADER_STRUCT.size) header = FILE_HEADER_STRUCT.unpack(data) # print(header) if header[0] != b"LOGG": raise BLFParseError("Unexpected file format") self.file_size = header[10] self.uncompressed_size = header[11] self.object_count = header[12] self.start_timestamp = systemtime_to_timestamp(header[14:22]) self.stop_timestamp = systemtime_to_timestamp(header[22:30]) # Read rest of header self.fp.read(header[1] - FILE_HEADER_STRUCT.size)
def __init__(self, filename): self.fp = open(filename, "rb") data = self.fp.read(FILE_HEADER_STRUCT.size) header = FILE_HEADER_STRUCT.unpack(data) # print(header) assert header[0] == b"LOGG", "Unknown file format" self.file_size = header[10] self.uncompressed_size = header[11] self.object_count = header[12] self.start_timestamp = systemtime_to_timestamp(header[14:22]) self.stop_timestamp = systemtime_to_timestamp(header[22:30])
https://github.com/hardbyte/python-can/issues/314
Traceback (most recent call last): File "D:\eclipse-workspace\blf2csv\pythoncan_blf2csv.py", line 7, in <module> logging = list(logging) File "C:\Users\my_user_name\AppData\Local\Python\Python36\lib\site-packages\can\io\blf.py", line 129, in __iter__ assert header[0] == b"LOBJ", "Parse error" AssertionError: Parse error
AssertionError
def __iter__(self): tail = b"" while True: data = self.fp.read(OBJ_HEADER_BASE_STRUCT.size) if not data: # EOF break header = OBJ_HEADER_BASE_STRUCT.unpack(data) # print(header) if header[0] != b"LOBJ": raise BLFParseError() obj_type = header[4] obj_data_size = header[3] - OBJ_HEADER_BASE_STRUCT.size obj_data = self.fp.read(obj_data_size) # Read padding bytes self.fp.read(obj_data_size % 4) if obj_type == LOG_CONTAINER: method, uncompressed_size = LOG_CONTAINER_STRUCT.unpack_from(obj_data) container_data = obj_data[LOG_CONTAINER_STRUCT.size :] if method == NO_COMPRESSION: data = container_data elif method == ZLIB_DEFLATE: data = zlib.decompress(container_data, 15, uncompressed_size) else: # Unknown compression method LOG.warning("Unknown compression method (%d)", method) continue if tail: data = tail + data pos = 0 while pos + OBJ_HEADER_BASE_STRUCT.size < len(data): header = OBJ_HEADER_BASE_STRUCT.unpack_from(data, pos) # print(header) if header[0] != b"LOBJ": raise BLFParseError() obj_size = header[3] # Calculate position of next object next_pos = pos + obj_size + (obj_size % 4) if next_pos > len(data): # Object continues in next log container break pos += OBJ_HEADER_BASE_STRUCT.size # Read rest of header header_version = header[2] if header_version == 1: flags, _, _, timestamp = OBJ_HEADER_V1_STRUCT.unpack_from(data, pos) pos += OBJ_HEADER_V1_STRUCT.size elif header_version == 2: flags, _, _, timestamp, _ = OBJ_HEADER_V2_STRUCT.unpack_from( data, pos ) pos += OBJ_HEADER_V2_STRUCT.size else: # Unknown header version LOG.warning("Unknown object header version (%d)", header_version) pos = next_pos continue if flags == TIME_TEN_MICS: factor = 10 * 1e-6 else: factor = 1e-9 timestamp = timestamp * factor + self.start_timestamp obj_type = header[4] # Both CAN message types have the same starting content if obj_type in (CAN_MESSAGE, CAN_MESSAGE2): (channel, flags, dlc, can_id, can_data) = ( CAN_MSG_STRUCT.unpack_from(data, pos) ) msg = Message( timestamp=timestamp, arbitration_id=can_id & 0x1FFFFFFF, extended_id=bool(can_id & CAN_MSG_EXT), is_remote_frame=bool(flags & REMOTE_FLAG), dlc=dlc, data=can_data[:dlc], channel=channel - 1, ) yield msg elif obj_type == CAN_FD_MESSAGE: (channel, flags, dlc, can_id, _, _, fd_flags, _, can_data) = ( CAN_FD_MSG_STRUCT.unpack_from(data, pos) ) length = dlc2len(dlc) msg = Message( timestamp=timestamp, arbitration_id=can_id & 0x1FFFFFFF, extended_id=bool(can_id & CAN_MSG_EXT), is_remote_frame=bool(flags & REMOTE_FLAG), is_fd=bool(fd_flags & EDL), bitrate_switch=bool(fd_flags & BRS), error_state_indicator=bool(fd_flags & ESI), dlc=length, data=can_data[:length], channel=channel - 1, ) yield msg elif obj_type == CAN_ERROR_EXT: (channel, _, _, _, _, dlc, _, can_id, _, can_data) = ( CAN_ERROR_EXT_STRUCT.unpack_from(data, pos) ) msg = Message( timestamp=timestamp, is_error_frame=True, extended_id=bool(can_id & CAN_MSG_EXT), arbitration_id=can_id & 0x1FFFFFFF, dlc=dlc, data=can_data[:dlc], channel=channel - 1, ) yield msg pos = next_pos # Save remaing data that could not be processed tail = data[pos:] self.fp.close()
def __iter__(self): tail = b"" while True: data = self.fp.read(OBJ_HEADER_BASE_STRUCT.size) if not data: # EOF break header = OBJ_HEADER_BASE_STRUCT.unpack(data) # print(header) assert header[0] == b"LOBJ", "Parse error" obj_type = header[4] obj_data_size = header[3] - OBJ_HEADER_BASE_STRUCT.size obj_data = self.fp.read(obj_data_size) # Read padding bytes self.fp.read(obj_data_size % 4) if obj_type == LOG_CONTAINER: method, uncompressed_size = LOG_CONTAINER_STRUCT.unpack_from(obj_data) container_data = obj_data[LOG_CONTAINER_STRUCT.size :] if method == NO_COMPRESSION: data = container_data elif method == ZLIB_DEFLATE: data = zlib.decompress(container_data, 15, uncompressed_size) else: # Unknown compression method continue if tail: data = tail + data pos = 0 while pos + OBJ_HEADER_BASE_STRUCT.size < len(data): header = OBJ_HEADER_BASE_STRUCT.unpack_from(data, pos) # print(header) assert header[0] == b"LOBJ", "Parse error" obj_size = header[3] if pos + obj_size > len(data): # Object continues in next log container break pos += OBJ_HEADER_BASE_STRUCT.size # Read rest of header header += OBJ_HEADER_STRUCT.unpack_from(data, pos) pos += OBJ_HEADER_STRUCT.size obj_type = header[4] timestamp = header[8] * 1e-9 + self.start_timestamp if obj_type == CAN_MESSAGE: (channel, flags, dlc, can_id, can_data) = ( CAN_MSG_STRUCT.unpack_from(data, pos) ) msg = Message( timestamp=timestamp, arbitration_id=can_id & 0x1FFFFFFF, extended_id=bool(can_id & CAN_MSG_EXT), is_remote_frame=bool(flags & REMOTE_FLAG), dlc=dlc, data=can_data[:dlc], channel=channel - 1, ) yield msg elif obj_type == CAN_FD_MESSAGE: (channel, flags, dlc, can_id, _, _, fd_flags, _, can_data) = ( CAN_FD_MSG_STRUCT.unpack_from(data, pos) ) length = dlc2len(dlc) msg = Message( timestamp=timestamp, arbitration_id=can_id & 0x1FFFFFFF, extended_id=bool(can_id & CAN_MSG_EXT), is_remote_frame=bool(flags & REMOTE_FLAG), is_fd=bool(fd_flags & EDL), bitrate_switch=bool(fd_flags & BRS), error_state_indicator=bool(fd_flags & ESI), dlc=length, data=can_data[:length], channel=channel - 1, ) yield msg elif obj_type == CAN_ERROR_EXT: (channel, _, _, _, _, dlc, _, can_id, _, can_data) = ( CAN_ERROR_EXT_STRUCT.unpack_from(data, pos) ) msg = Message( timestamp=timestamp, is_error_frame=True, extended_id=bool(can_id & CAN_MSG_EXT), arbitration_id=can_id & 0x1FFFFFFF, dlc=dlc, data=can_data[:dlc], channel=channel - 1, ) yield msg pos += obj_size - HEADER_SIZE # Add padding bytes pos += obj_size % 4 # Save remaing data that could not be processed tail = data[pos:] self.fp.close()
https://github.com/hardbyte/python-can/issues/314
Traceback (most recent call last): File "D:\eclipse-workspace\blf2csv\pythoncan_blf2csv.py", line 7, in <module> logging = list(logging) File "C:\Users\my_user_name\AppData\Local\Python\Python36\lib\site-packages\can\io\blf.py", line 129, in __iter__ assert header[0] == b"LOBJ", "Parse error" AssertionError: Parse error
AssertionError
def __init__(self, filename, channel=1): self.fp = open(filename, "wb") self.channel = channel # Header will be written after log is done self.fp.write(b"\x00" * FILE_HEADER_SIZE) self.cache = [] self.cache_size = 0 self.count_of_objects = 0 self.uncompressed_size = FILE_HEADER_SIZE self.start_timestamp = None self.stop_timestamp = None
def __init__(self, filename, channel=1): self.fp = open(filename, "wb") self.channel = channel # Header will be written after log is done self.fp.write(b"\x00" * FILE_HEADER_STRUCT.size) self.cache = [] self.cache_size = 0 self.count_of_objects = 0 self.uncompressed_size = FILE_HEADER_STRUCT.size self.start_timestamp = None self.stop_timestamp = None
https://github.com/hardbyte/python-can/issues/314
Traceback (most recent call last): File "D:\eclipse-workspace\blf2csv\pythoncan_blf2csv.py", line 7, in <module> logging = list(logging) File "C:\Users\my_user_name\AppData\Local\Python\Python36\lib\site-packages\can\io\blf.py", line 129, in __iter__ assert header[0] == b"LOBJ", "Parse error" AssertionError: Parse error
AssertionError
def _add_object(self, obj_type, data, timestamp=None): if timestamp is None: timestamp = self.stop_timestamp or time.time() if self.start_timestamp is None: self.start_timestamp = timestamp self.stop_timestamp = timestamp timestamp = int((timestamp - self.start_timestamp) * 1e9) header_size = OBJ_HEADER_BASE_STRUCT.size + OBJ_HEADER_V1_STRUCT.size obj_size = header_size + len(data) base_header = OBJ_HEADER_BASE_STRUCT.pack( b"LOBJ", header_size, 1, obj_size, obj_type ) obj_header = OBJ_HEADER_V1_STRUCT.pack(TIME_ONE_NANS, 0, 0, max(timestamp, 0)) self.cache.append(base_header) self.cache.append(obj_header) self.cache.append(data) padding_size = len(data) % 4 if padding_size: self.cache.append(b"\x00" * padding_size) self.cache_size += obj_size + padding_size self.count_of_objects += 1 if self.cache_size >= self.MAX_CACHE_SIZE: self._flush()
def _add_object(self, obj_type, data, timestamp=None): if timestamp is None: timestamp = self.stop_timestamp or time.time() if self.start_timestamp is None: self.start_timestamp = timestamp self.stop_timestamp = timestamp timestamp = int((timestamp - self.start_timestamp) * 1e9) obj_size = HEADER_SIZE + len(data) base_header = OBJ_HEADER_BASE_STRUCT.pack( b"LOBJ", HEADER_SIZE, 1, obj_size, obj_type ) obj_header = OBJ_HEADER_STRUCT.pack(2, 0, 0, max(timestamp, 0)) self.cache.append(base_header) self.cache.append(obj_header) self.cache.append(data) padding_size = len(data) % 4 if padding_size: self.cache.append(b"\x00" * padding_size) self.cache_size += obj_size + padding_size self.count_of_objects += 1 if self.cache_size >= self.MAX_CACHE_SIZE: self._flush()
https://github.com/hardbyte/python-can/issues/314
Traceback (most recent call last): File "D:\eclipse-workspace\blf2csv\pythoncan_blf2csv.py", line 7, in <module> logging = list(logging) File "C:\Users\my_user_name\AppData\Local\Python\Python36\lib\site-packages\can\io\blf.py", line 129, in __iter__ assert header[0] == b"LOBJ", "Parse error" AssertionError: Parse error
AssertionError
def _flush(self): """Compresses and writes data in the cache to file.""" if self.fp.closed: return cache = b"".join(self.cache) if not cache: # Nothing to write return uncompressed_data = cache[: self.MAX_CACHE_SIZE] # Save data that comes after max size to next round tail = cache[self.MAX_CACHE_SIZE :] self.cache = [tail] self.cache_size = len(tail) compressed_data = zlib.compress(uncompressed_data, self.COMPRESSION_LEVEL) obj_size = ( OBJ_HEADER_V1_STRUCT.size + LOG_CONTAINER_STRUCT.size + len(compressed_data) ) base_header = OBJ_HEADER_BASE_STRUCT.pack( b"LOBJ", OBJ_HEADER_BASE_STRUCT.size, 1, obj_size, LOG_CONTAINER ) container_header = LOG_CONTAINER_STRUCT.pack(ZLIB_DEFLATE, len(uncompressed_data)) self.fp.write(base_header) self.fp.write(container_header) self.fp.write(compressed_data) # Write padding bytes self.fp.write(b"\x00" * (obj_size % 4)) self.uncompressed_size += OBJ_HEADER_V1_STRUCT.size + LOG_CONTAINER_STRUCT.size self.uncompressed_size += len(uncompressed_data)
def _flush(self): """Compresses and writes data in the cache to file.""" if self.fp.closed: return cache = b"".join(self.cache) if not cache: # Nothing to write return uncompressed_data = cache[: self.MAX_CACHE_SIZE] # Save data that comes after max size to next round tail = cache[self.MAX_CACHE_SIZE :] self.cache = [tail] self.cache_size = len(tail) compressed_data = zlib.compress(uncompressed_data, self.COMPRESSION_LEVEL) obj_size = OBJ_HEADER_STRUCT.size + LOG_CONTAINER_STRUCT.size + len(compressed_data) base_header = OBJ_HEADER_BASE_STRUCT.pack( b"LOBJ", OBJ_HEADER_BASE_STRUCT.size, 1, obj_size, LOG_CONTAINER ) container_header = LOG_CONTAINER_STRUCT.pack(ZLIB_DEFLATE, len(uncompressed_data)) self.fp.write(base_header) self.fp.write(container_header) self.fp.write(compressed_data) # Write padding bytes self.fp.write(b"\x00" * (obj_size % 4)) self.uncompressed_size += OBJ_HEADER_STRUCT.size + LOG_CONTAINER_STRUCT.size self.uncompressed_size += len(uncompressed_data)
https://github.com/hardbyte/python-can/issues/314
Traceback (most recent call last): File "D:\eclipse-workspace\blf2csv\pythoncan_blf2csv.py", line 7, in <module> logging = list(logging) File "C:\Users\my_user_name\AppData\Local\Python\Python36\lib\site-packages\can\io\blf.py", line 129, in __iter__ assert header[0] == b"LOBJ", "Parse error" AssertionError: Parse error
AssertionError
def stop(self): """Stops logging and closes the file.""" if self.fp.closed: return self._flush() filesize = self.fp.tell() self.fp.close() # Write header in the beginning of the file header = [b"LOGG", FILE_HEADER_SIZE, APPLICATION_ID, 0, 0, 0, 2, 6, 8, 1] # The meaning of "count of objects read" is unknown header.extend([filesize, self.uncompressed_size, self.count_of_objects, 0]) header.extend(timestamp_to_systemtime(self.start_timestamp)) header.extend(timestamp_to_systemtime(self.stop_timestamp)) with open(self.fp.name, "r+b") as f: f.write(FILE_HEADER_STRUCT.pack(*header))
def stop(self): """Stops logging and closes the file.""" if self.fp.closed: return self._flush() filesize = self.fp.tell() self.fp.close() # Write header in the beginning of the file header = [b"LOGG", FILE_HEADER_STRUCT.size, APPLICATION_ID, 0, 0, 0, 2, 6, 8, 1] # The meaning of "count of objects read" is unknown header.extend([filesize, self.uncompressed_size, self.count_of_objects, 0]) header.extend(timestamp_to_systemtime(self.start_timestamp)) header.extend(timestamp_to_systemtime(self.stop_timestamp)) with open(self.fp.name, "r+b") as f: f.write(FILE_HEADER_STRUCT.pack(*header))
https://github.com/hardbyte/python-can/issues/314
Traceback (most recent call last): File "D:\eclipse-workspace\blf2csv\pythoncan_blf2csv.py", line 7, in <module> logging = list(logging) File "C:\Users\my_user_name\AppData\Local\Python\Python36\lib\site-packages\can\io\blf.py", line 129, in __iter__ assert header[0] == b"LOBJ", "Parse error" AssertionError: Parse error
AssertionError
def set_filters(self, can_filters=None): """Apply filtering to all messages received by this Bus. Calling without passing any filters will reset the applied filters. Since Kvaser only supports setting one filter per handle, the filtering will be disabled if more than one filter is requested. :param list can_filters: A list of dictionaries each containing a "can_id", "can_mask" and "extended". >>> [{"can_id": 0x11, "can_mask": 0x21, "extended": False}] A filter matches, when ``<received_can_id> & can_mask == can_id & can_mask`` """ if can_filters and len(can_filters) == 1: can_id = can_filters[0]["can_id"] can_mask = can_filters[0]["can_mask"] extended = 1 if can_filters[0].get("extended") else 0 try: for handle in (self._read_handle, self._write_handle): canSetAcceptanceFilter(handle, can_id, can_mask, extended) except NotImplementedError: log.warning("Filtering is not supported") else: log.info("canlib is filtering on ID 0x%X, mask 0x%X", can_id, can_mask) else: log.info("Hardware filtering has been disabled") try: for handle in (self._read_handle, self._write_handle): for extended in (0, 1): canSetAcceptanceFilter(handle, 0, 0, extended) except NotImplementedError: pass
def set_filters(self, can_filters=None): """Apply filtering to all messages received by this Bus. Calling without passing any filters will reset the applied filters. Since Kvaser only supports setting one filter per handle, the filtering will be done in the :meth:`recv` if more than one filter is requested. :param list can_filters: A list of dictionaries each containing a "can_id" and a "can_mask". >>> [{"can_id": 0x11, "can_mask": 0x21}] A filter matches, when ``<received_can_id> & can_mask == can_id & can_mask`` """ if can_filters and len(can_filters) == 1: can_id = can_filters[0]["can_id"] can_mask = can_filters[0]["can_mask"] extended = 1 if can_filters[0].get("extended") else 0 log.info("canlib is filtering on ID 0x%X, mask 0x%X", can_id, can_mask) for handle in (self._read_handle, self._write_handle): canSetAcceptanceFilter(handle, can_id, can_mask, extended) else: log.info("Hardware filtering has been disabled") for handle in (self._read_handle, self._write_handle): for extended in (0, 1): canSetAcceptanceFilter(handle, 0, 0, extended)
https://github.com/hardbyte/python-can/issues/154
Traceback (most recent call last): File "pycan-test.py", line 3, in <module> interface = KvaserBus(0) File "/usr/local/lib/python2.7/dist-packages/can/interfaces/kvaser/canlib.py", line 361, in __init__ self.set_filters(can_filters) File "/usr/local/lib/python2.7/dist-packages/can/interfaces/kvaser/canlib.py", line 413, in set_filters canSetAcceptanceFilter(handle, can_id, can_mask, ext) File "/usr/local/lib/python2.7/dist-packages/can/interfaces/kvaser/canlib.py", line 39, in _unimplemented_function raise NotImplementedError('This function is not implemented in canlib') NotImplementedError: This function is not implemented in canlib
NotImplementedError
def set_filters(self, can_filters=None): """Apply filtering to all messages received by this Bus. Calling without passing any filters will reset the applied filters. Since Kvaser only supports setting one filter per handle, the filtering will be disabled if more than one filter is requested. :param list can_filters: A list of dictionaries each containing a "can_id", "can_mask" and "extended". >>> [{"can_id": 0x11, "can_mask": 0x21, "extended": False}] A filter matches, when ``<received_can_id> & can_mask == can_id & can_mask`` """ if can_filters and len(can_filters) == 1: can_id = can_filters[0]["can_id"] can_mask = can_filters[0]["can_mask"] extended = 1 if can_filters[0].get("extended") else 0 try: for handle in (self._read_handle, self._write_handle): canSetAcceptanceFilter(handle, can_id, can_mask, extended) except (NotImplementedError, CANLIBError) as e: log.error("Filtering is not supported - %s", e) else: log.info("canlib is filtering on ID 0x%X, mask 0x%X", can_id, can_mask) else: log.info("Hardware filtering has been disabled") try: for handle in (self._read_handle, self._write_handle): for extended in (0, 1): canSetAcceptanceFilter(handle, 0, 0, extended) except (NotImplementedError, CANLIBError): pass
def set_filters(self, can_filters=None): """Apply filtering to all messages received by this Bus. Calling without passing any filters will reset the applied filters. Since Kvaser only supports setting one filter per handle, the filtering will be disabled if more than one filter is requested. :param list can_filters: A list of dictionaries each containing a "can_id", "can_mask" and "extended". >>> [{"can_id": 0x11, "can_mask": 0x21, "extended": False}] A filter matches, when ``<received_can_id> & can_mask == can_id & can_mask`` """ if can_filters and len(can_filters) == 1: can_id = can_filters[0]["can_id"] can_mask = can_filters[0]["can_mask"] extended = 1 if can_filters[0].get("extended") else 0 try: for handle in (self._read_handle, self._write_handle): canSetAcceptanceFilter(handle, can_id, can_mask, extended) except NotImplementedError: log.warning("Filtering is not supported") else: log.info("canlib is filtering on ID 0x%X, mask 0x%X", can_id, can_mask) else: log.info("Hardware filtering has been disabled") try: for handle in (self._read_handle, self._write_handle): for extended in (0, 1): canSetAcceptanceFilter(handle, 0, 0, extended) except NotImplementedError: pass
https://github.com/hardbyte/python-can/issues/154
Traceback (most recent call last): File "pycan-test.py", line 3, in <module> interface = KvaserBus(0) File "/usr/local/lib/python2.7/dist-packages/can/interfaces/kvaser/canlib.py", line 361, in __init__ self.set_filters(can_filters) File "/usr/local/lib/python2.7/dist-packages/can/interfaces/kvaser/canlib.py", line 413, in set_filters canSetAcceptanceFilter(handle, can_id, can_mask, ext) File "/usr/local/lib/python2.7/dist-packages/can/interfaces/kvaser/canlib.py", line 39, in _unimplemented_function raise NotImplementedError('This function is not implemented in canlib') NotImplementedError: This function is not implemented in canlib
NotImplementedError
def db_writer_thread(self): num_frames = 0 last_write = time.time() self._create_db() while not self.stop_running_event.is_set(): messages = [] m = self.get_message(self.GET_MESSAGE_TIMEOUT) while m is not None: log.debug("sqlitewriter buffering message") messages.append( ( m.timestamp, m.arbitration_id, m.id_type, m.is_remote_frame, m.is_error_frame, m.dlc, buffer(m.data), ) ) if time.time() - last_write > self.MAX_TIME_BETWEEN_WRITES: log.debug("Max timeout between writes reached") break m = self.get_message(self.GET_MESSAGE_TIMEOUT) if len(messages) > 0: with self.conn: log.debug("Writing %s frames to db", len(messages)) self.conn.executemany(SqliteWriter.insert_msg_template, messages) num_frames += len(messages) last_write = time.time() self.conn.close() log.info("Stopped sqlite writer after writing %s messages", num_frames)
def db_writer_thread(self): num_frames = 0 last_write = time.time() self._create_db() while not self.stop_running_event.is_set(): messages = [] m = self.get_message(self.GET_MESSAGE_TIMEOUT) while m is not None: log.debug("sqlitewriter buffering message") messages.append( ( m.timestamp, m.arbitration_id, m.id_type, m.is_remote_frame, m.is_error_frame, m.dlc, buffer(m.data), ) ) m = self.get_message(self.GET_MESSAGE_TIMEOUT) if time.time() - last_write > self.MAX_TIME_BETWEEN_WRITES: log.debug("Max timeout between writes reached") break if len(messages) > 0: with self.conn: log.debug("Writing %s frames to db", len(messages)) self.conn.executemany(SqliteWriter.insert_msg_template, messages) num_frames += len(messages) last_write = time.time() self.conn.close() log.info("Stopped sqlite writer after writing %s messages", num_frames)
https://github.com/hardbyte/python-can/issues/139
====================================================================== FAIL: test_sql_reader (listener_test.FileReaderTest) ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/travis/build/hardbyte/python-can/test/listener_test.py", line 179, in test_sql_reader self.assertEqual(len(ms), 1) AssertionError: 0 != 1 -------------------- >> begin captured logging << -------------------- can: DEBUG: can config: {'channel': None, 'interface': 'virtual'} can.io.sql: INFO: Creating sqlite db can.io.sql: DEBUG: Stopping sqlite writer can.io.sql: INFO: Stopped sqlite writer after writing 0 messages can.io.sql: DEBUG: Starting sqlreader with /tmp/tmpcqqrl_m3 can.io.sql: DEBUG: Iterating through messages from sql db --------------------- >> end captured logging << ---------------------
AssertionError
def __init__(self, filename): self.csv_file = open(filename, "wt") # Write a header row self.csv_file.write( "timestamp, arbitration id, extended, remote, error, dlc, data\n" )
def __init__(self, filename): self.csv_file = open(filename, "wt") # Write a header row self.csv_file.write("timestamp, arbitrationid, flags, dlc, data")
https://github.com/hardbyte/python-can/issues/72
#!shell (py35_python_can) e:\bitbucket_hg\python-can\bin>python can_logger.py -f ./temp.txt Can Logger (Started on 2016-07-19 09:49:10.052735) enter.. Shutdown Bus and Exit. exit.. close exit .. Exception in thread Thread-1: Traceback (most recent call last): File "C:\Python35\lib\threading.py", line 914, in _bootstrap_inner self.run() File "C:\Python35\lib\threading.py", line 862, in run self._target(*self._args, **self._kwargs) File "e:\bitbucket_hg\python-can\can\notifier.py", line 32, in rx_thread msg = self.bus.recv(self.timeout) File "e:\bitbucket_hg\python-can\can\interfaces\pcan.py", line 169, in recv raise Exception(self._get_formatted_error(result[0])) Exception: Der PCAN Kanal ist nicht initialisiert oder der Initialisierungsvorgang ist fehlgeschlagen Exception ignored in: <bound method Printer.__del__ of <can.CAN.Printer object at 0x00000000015C3550>> Traceback (most recent call last): File "e:\bitbucket_hg\python-can\can\CAN.py", line 97, in __del__ ValueError: I/O operation on closed file. (py35_python_can) e:\bitbucket_hg\python-can\bin>
ValueError
def on_message_received(self, msg): row = ",".join( [ str(msg.timestamp), hex(msg.arbitration_id), "1" if msg.id_type else "0", "1" if msg.is_remote_frame else "0", "1" if msg.is_error_frame else "0", str(msg.dlc), base64.b64encode(msg.data).decode("utf8"), ] ) self.csv_file.write(row + "\n")
def on_message_received(self, msg): row = ",".join([msg.timestamp, msg.arbitration_id, msg.flags, msg.dlc, msg.data]) self.csv_file.write(row + "\n")
https://github.com/hardbyte/python-can/issues/72
#!shell (py35_python_can) e:\bitbucket_hg\python-can\bin>python can_logger.py -f ./temp.txt Can Logger (Started on 2016-07-19 09:49:10.052735) enter.. Shutdown Bus and Exit. exit.. close exit .. Exception in thread Thread-1: Traceback (most recent call last): File "C:\Python35\lib\threading.py", line 914, in _bootstrap_inner self.run() File "C:\Python35\lib\threading.py", line 862, in run self._target(*self._args, **self._kwargs) File "e:\bitbucket_hg\python-can\can\notifier.py", line 32, in rx_thread msg = self.bus.recv(self.timeout) File "e:\bitbucket_hg\python-can\can\interfaces\pcan.py", line 169, in recv raise Exception(self._get_formatted_error(result[0])) Exception: Der PCAN Kanal ist nicht initialisiert oder der Initialisierungsvorgang ist fehlgeschlagen Exception ignored in: <bound method Printer.__del__ of <can.CAN.Printer object at 0x00000000015C3550>> Traceback (most recent call last): File "e:\bitbucket_hg\python-can\can\CAN.py", line 97, in __del__ ValueError: I/O operation on closed file. (py35_python_can) e:\bitbucket_hg\python-can\bin>
ValueError
def __init__(self, bus, listeners, timeout=None): """Manages the distribution of **Messages** from a given bus to a list of listeners. :param bus: The :ref:`bus` to listen too. :param listeners: An iterable of :class:`~can.Listeners` :param timeout: An optional maximum number of seconds to wait for any message. """ self.listeners = listeners self.bus = bus self.timeout = timeout self.running = threading.Event() self.running.set() self._reader = threading.Thread(target=self.rx_thread) self._reader.daemon = True self._reader.start()
def __init__(self, bus, listeners, timeout=None): """Manages the distribution of **Messages** from a given bus to a list of listeners. :param bus: The :class:`~can.Bus` to listen too. :param listeners: An iterable of :class:`~can.Listeners` :param timeout: An optional maximum number of seconds to wait for any message. """ self.listeners = listeners self.bus = bus self.timeout = timeout self.running = threading.Event() self.running.set() self._reader = threading.Thread(target=self.rx_thread) self._reader.daemon = True self._reader.start()
https://github.com/hardbyte/python-can/issues/72
#!shell (py35_python_can) e:\bitbucket_hg\python-can\bin>python can_logger.py -f ./temp.txt Can Logger (Started on 2016-07-19 09:49:10.052735) enter.. Shutdown Bus and Exit. exit.. close exit .. Exception in thread Thread-1: Traceback (most recent call last): File "C:\Python35\lib\threading.py", line 914, in _bootstrap_inner self.run() File "C:\Python35\lib\threading.py", line 862, in run self._target(*self._args, **self._kwargs) File "e:\bitbucket_hg\python-can\can\notifier.py", line 32, in rx_thread msg = self.bus.recv(self.timeout) File "e:\bitbucket_hg\python-can\can\interfaces\pcan.py", line 169, in recv raise Exception(self._get_formatted_error(result[0])) Exception: Der PCAN Kanal ist nicht initialisiert oder der Initialisierungsvorgang ist fehlgeschlagen Exception ignored in: <bound method Printer.__del__ of <can.CAN.Printer object at 0x00000000015C3550>> Traceback (most recent call last): File "e:\bitbucket_hg\python-can\can\CAN.py", line 97, in __del__ ValueError: I/O operation on closed file. (py35_python_can) e:\bitbucket_hg\python-can\bin>
ValueError
def stop(self): """Stop notifying Listeners when new :class:`~can.Message` objects arrive and call :meth:`~can.Listener.stop` on each Listener.""" self.running.clear() if self.timeout is not None: self._reader.join(self.timeout + 0.1)
def stop(self): self.running.clear() if self.timeout is not None: self._reader.join(self.timeout + 0.1)
https://github.com/hardbyte/python-can/issues/72
#!shell (py35_python_can) e:\bitbucket_hg\python-can\bin>python can_logger.py -f ./temp.txt Can Logger (Started on 2016-07-19 09:49:10.052735) enter.. Shutdown Bus and Exit. exit.. close exit .. Exception in thread Thread-1: Traceback (most recent call last): File "C:\Python35\lib\threading.py", line 914, in _bootstrap_inner self.run() File "C:\Python35\lib\threading.py", line 862, in run self._target(*self._args, **self._kwargs) File "e:\bitbucket_hg\python-can\can\notifier.py", line 32, in rx_thread msg = self.bus.recv(self.timeout) File "e:\bitbucket_hg\python-can\can\interfaces\pcan.py", line 169, in recv raise Exception(self._get_formatted_error(result[0])) Exception: Der PCAN Kanal ist nicht initialisiert oder der Initialisierungsvorgang ist fehlgeschlagen Exception ignored in: <bound method Printer.__del__ of <can.CAN.Printer object at 0x00000000015C3550>> Traceback (most recent call last): File "e:\bitbucket_hg\python-can\can\CAN.py", line 97, in __del__ ValueError: I/O operation on closed file. (py35_python_can) e:\bitbucket_hg\python-can\bin>
ValueError
def rx_thread(self): while self.running.is_set(): msg = self.bus.recv(self.timeout) if msg is not None: for callback in self.listeners: callback(msg) for listener in self.listeners: listener.stop()
def rx_thread(self): while self.running.is_set(): msg = self.bus.recv(self.timeout) if msg is not None: for callback in self.listeners: callback(msg)
https://github.com/hardbyte/python-can/issues/72
#!shell (py35_python_can) e:\bitbucket_hg\python-can\bin>python can_logger.py -f ./temp.txt Can Logger (Started on 2016-07-19 09:49:10.052735) enter.. Shutdown Bus and Exit. exit.. close exit .. Exception in thread Thread-1: Traceback (most recent call last): File "C:\Python35\lib\threading.py", line 914, in _bootstrap_inner self.run() File "C:\Python35\lib\threading.py", line 862, in run self._target(*self._args, **self._kwargs) File "e:\bitbucket_hg\python-can\can\notifier.py", line 32, in rx_thread msg = self.bus.recv(self.timeout) File "e:\bitbucket_hg\python-can\can\interfaces\pcan.py", line 169, in recv raise Exception(self._get_formatted_error(result[0])) Exception: Der PCAN Kanal ist nicht initialisiert oder der Initialisierungsvorgang ist fehlgeschlagen Exception ignored in: <bound method Printer.__del__ of <can.CAN.Printer object at 0x00000000015C3550>> Traceback (most recent call last): File "e:\bitbucket_hg\python-can\can\CAN.py", line 97, in __del__ ValueError: I/O operation on closed file. (py35_python_can) e:\bitbucket_hg\python-can\bin>
ValueError
async def get(self): user = self.current_user if user is None: # whoami can be accessed via oauth token user = self.get_current_user_oauth_token() if user is None: raise web.HTTPError(403) if isinstance(user, orm.Service): model = self.service_model(user) else: model = self.user_model(user) self.write(json.dumps(model))
async def get(self): user = self.current_user if user is None: # whoami can be accessed via oauth token user = self.get_current_user_oauth_token() if user is None: raise web.HTTPError(403) self.write(json.dumps(self.user_model(user)))
https://github.com/jupyterhub/jupyterhub/issues/3217
Uncaught exception GET /hub/api/user (172.17.0.2) HTTPServerRequest(protocol='http', host='172.17.0.2:8081', method='GET', uri='/hub/api/user', version='HTTP/1.1', remote_ip='172.17.0.2') Traceback (most recent call last): File "/usr/local/lib/python3.6/dist-packages/tornado/web.py", line 1703, in _execute result = await result File "/usr/local/lib/python3.6/dist-packages/jupyterhub/apihandlers/users.py", line 38, in get self.write(json.dumps(self.user_model(user))) File "/usr/local/lib/python3.6/dist-packages/jupyterhub/apihandlers/base.py", line 193, in user_model 'groups': [g.name for g in user.groups], AttributeError: 'Service' object has no attribute 'groups'
AttributeError
async def shutdown_cancel_tasks(self, sig): """Cancel all other tasks of the event loop and initiate cleanup""" self.log.critical("Received signal %s, initiating shutdown...", sig.name) tasks = [t for t in asyncio_all_tasks() if t is not asyncio_current_task()] if tasks: self.log.debug("Cancelling pending tasks") [t.cancel() for t in tasks] try: await asyncio.wait(tasks) except asyncio.CancelledError as e: self.log.debug("Caught Task CancelledError. Ignoring") except StopAsyncIteration as e: self.log.error("Caught StopAsyncIteration Exception", exc_info=True) tasks = [t for t in asyncio_all_tasks()] for t in tasks: self.log.debug("Task status: %s", t) await self.cleanup() asyncio.get_event_loop().stop()
async def shutdown_cancel_tasks(self, sig): """Cancel all other tasks of the event loop and initiate cleanup""" self.log.critical("Received signal %s, initiating shutdown...", sig.name) tasks = [ t for t in asyncio.Task.all_tasks() if t is not asyncio.Task.current_task() ] if tasks: self.log.debug("Cancelling pending tasks") [t.cancel() for t in tasks] try: await asyncio.wait(tasks) except asyncio.CancelledError as e: self.log.debug("Caught Task CancelledError. Ignoring") except StopAsyncIteration as e: self.log.error("Caught StopAsyncIteration Exception", exc_info=True) tasks = [t for t in asyncio.Task.all_tasks()] for t in tasks: self.log.debug("Task status: %s", t) await self.cleanup() asyncio.get_event_loop().stop()
https://github.com/jupyterhub/jupyterhub/issues/3297
^C[C 2020-12-02 16:16:45.801 JupyterHub app:2810] Received signal SIGINT, initiating shutdown... ERROR:asyncio:Task exception was never retrieved future: <Task finished name='Task-8' coro=<JupyterHub.shutdown_cancel_tasks() done, defined at /opt/miniconda3/envs/jupyterhub/lib/python3.9/site-packages/jupyterhub/app.py:2808> exception=AttributeError("type object '_asyncio.Task' has no attribute 'all_tasks'")> Traceback (most recent call last): File "/opt/miniconda3/envs/jupyterhub/lib/python3.9/site-packages/jupyterhub/app.py", line 2812, in shutdown_cancel_tasks t for t in asyncio.Task.all_tasks() if t is not asyncio.Task.current_task() AttributeError: type object '_asyncio.Task' has no attribute 'all_tasks'
AttributeError
def print_stacks(file=sys.stderr): """Print current status of the process For debugging purposes. Used as part of SIGINFO handler. - Shows active thread count - Shows current stack for all threads Parameters: file: file to write output to (default: stderr) """ # local imports because these will not be used often, # no need to add them to startup import asyncio import traceback from .log import coroutine_frames print("Active threads: %i" % threading.active_count(), file=file) for thread in threading.enumerate(): print("Thread %s:" % thread.name, end="", file=file) frame = sys._current_frames()[thread.ident] stack = traceback.extract_stack(frame) if thread is threading.current_thread(): # truncate last two frames of the current thread # which are this function and its caller stack = stack[:-2] stack = coroutine_frames(stack) if stack: last_frame = stack[-1] if ( last_frame[0].endswith("threading.py") and last_frame[-1] == "waiter.acquire()" ) or ( last_frame[0].endswith("thread.py") and last_frame[-1].endswith("work_queue.get(block=True)") ): # thread is waiting on a condition # call it idle rather than showing the uninteresting stack # most threadpools will be in this state print(" idle", file=file) continue print("".join(["\n"] + traceback.format_list(stack)), file=file) # also show asyncio tasks, if any # this will increase over time as we transition from tornado # coroutines to native `async def` tasks = asyncio_all_tasks() if tasks: print("AsyncIO tasks: %i" % len(tasks)) for task in tasks: task.print_stack(file=file)
def print_stacks(file=sys.stderr): """Print current status of the process For debugging purposes. Used as part of SIGINFO handler. - Shows active thread count - Shows current stack for all threads Parameters: file: file to write output to (default: stderr) """ # local imports because these will not be used often, # no need to add them to startup import asyncio import traceback from .log import coroutine_frames print("Active threads: %i" % threading.active_count(), file=file) for thread in threading.enumerate(): print("Thread %s:" % thread.name, end="", file=file) frame = sys._current_frames()[thread.ident] stack = traceback.extract_stack(frame) if thread is threading.current_thread(): # truncate last two frames of the current thread # which are this function and its caller stack = stack[:-2] stack = coroutine_frames(stack) if stack: last_frame = stack[-1] if ( last_frame[0].endswith("threading.py") and last_frame[-1] == "waiter.acquire()" ) or ( last_frame[0].endswith("thread.py") and last_frame[-1].endswith("work_queue.get(block=True)") ): # thread is waiting on a condition # call it idle rather than showing the uninteresting stack # most threadpools will be in this state print(" idle", file=file) continue print("".join(["\n"] + traceback.format_list(stack)), file=file) # also show asyncio tasks, if any # this will increase over time as we transition from tornado # coroutines to native `async def` tasks = asyncio.Task.all_tasks() if tasks: print("AsyncIO tasks: %i" % len(tasks)) for task in tasks: task.print_stack(file=file)
https://github.com/jupyterhub/jupyterhub/issues/3297
^C[C 2020-12-02 16:16:45.801 JupyterHub app:2810] Received signal SIGINT, initiating shutdown... ERROR:asyncio:Task exception was never retrieved future: <Task finished name='Task-8' coro=<JupyterHub.shutdown_cancel_tasks() done, defined at /opt/miniconda3/envs/jupyterhub/lib/python3.9/site-packages/jupyterhub/app.py:2808> exception=AttributeError("type object '_asyncio.Task' has no attribute 'all_tasks'")> Traceback (most recent call last): File "/opt/miniconda3/envs/jupyterhub/lib/python3.9/site-packages/jupyterhub/app.py", line 2812, in shutdown_cancel_tasks t for t in asyncio.Task.all_tasks() if t is not asyncio.Task.current_task() AttributeError: type object '_asyncio.Task' has no attribute 'all_tasks'
AttributeError
async def api_request(self, path, method="GET", body=None, client=None): """Make an authenticated API request of the proxy.""" client = client or AsyncHTTPClient() url = url_path_join(self.api_url, "api/routes", path) if isinstance(body, dict): body = json.dumps(body) self.log.debug("Proxy: Fetching %s %s", method, url) req = HTTPRequest( url, method=method, headers={"Authorization": "token {}".format(self.auth_token)}, body=body, connect_timeout=3, # default: 20s request_timeout=10, # default: 20s ) async def _wait_for_api_request(): try: async with self.semaphore: return await client.fetch(req) except HTTPError as e: # Retry on potentially transient errors in CHP, typically # numbered 500 and up. Note that CHP isn't able to emit 429 # errors. if e.code >= 500: self.log.warning( "api_request to the proxy failed with status code {}, retrying...".format( e.code ) ) return False # a falsy return value make exponential_backoff retry else: self.log.error("api_request to proxy failed: {0}".format(e)) # An unhandled error here will help the hub invoke cleanup logic raise result = await exponential_backoff( _wait_for_api_request, 'Repeated api_request to proxy path "{}" failed.'.format(path), timeout=30, ) return result
async def api_request(self, path, method="GET", body=None, client=None): """Make an authenticated API request of the proxy.""" client = client or AsyncHTTPClient() url = url_path_join(self.api_url, "api/routes", path) if isinstance(body, dict): body = json.dumps(body) self.log.debug("Proxy: Fetching %s %s", method, url) req = HTTPRequest( url, method=method, headers={"Authorization": "token {}".format(self.auth_token)}, body=body, ) async with self.semaphore: result = await client.fetch(req) return result
https://github.com/jupyterhub/jupyterhub/issues/3222
[I 2020-10-20 16:48:25.540 JupyterHub base:893] User testuser-aa6aa5ea-64bb-4719-93c7-04557f25c3d5 took 2.179 seconds to start [I 2020-10-20 16:48:25.540 JupyterHub proxy:257] Adding user testuser-aa6aa5ea-64bb-4719-93c7-04557f25c3d5 to proxy /user/testuser-aa6aa5ea-64bb-4719-93c7-04557f25c3d5/ => http://192.168.79.75:8888 [D 2020-10-20 16:48:25.540 JupyterHub proxy:765] Proxy: Fetching POST http://proxy-api:8001/api/routes/user/testuser-aa6aa5ea-64bb-4719-93c7-04557f25c3d5 [I 2020-10-20 16:48:25.541 JupyterHub log:181] 200 GET /hub/api (@10.20.0.120) 1.70ms [E 2020-10-20 16:48:25.542 JupyterHub base:915] Failed to add testuser-aa6aa5ea-64bb-4719-93c7-04557f25c3d5 to proxy! Traceback (most recent call last): File "/usr/local/lib/python3.8/dist-packages/jupyterhub/handlers/base.py", line 908, in finish_user_spawn await self.proxy.add_user(user, server_name) File "/usr/local/lib/python3.8/dist-packages/jupyterhub/proxy.py", line 270, in add_user await self.add_route( File "/usr/local/lib/python3.8/dist-packages/jupyterhub/proxy.py", line 781, in add_route await self.api_request(path, method='POST', body=body) File "/usr/local/lib/python3.8/dist-packages/jupyterhub/proxy.py", line 773, in api_request result = await client.fetch(req) tornado.curl_httpclient.CurlError: HTTP 599: Send failure: Broken pipe
tornado.curl_httpclient.CurlError
async def spawn_single_user(self, user, server_name="", options=None): # in case of error, include 'try again from /hub/home' message if self.authenticator.refresh_pre_spawn: auth_user = await self.refresh_auth(user, force=True) if auth_user is None: raise web.HTTPError(403, "auth has expired for %s, login again", user.name) spawn_start_time = time.perf_counter() self.extra_error_html = self.spawn_home_error user_server_name = user.name if server_name: user_server_name = "%s:%s" % (user.name, server_name) if server_name in user.spawners and user.spawners[server_name].pending: pending = user.spawners[server_name].pending SERVER_SPAWN_DURATION_SECONDS.labels( status=ServerSpawnStatus.already_pending ).observe(time.perf_counter() - spawn_start_time) raise RuntimeError("%s pending %s" % (user_server_name, pending)) # count active servers and pending spawns # we could do careful bookkeeping to avoid # but for 10k users this takes ~5ms # and saves us from bookkeeping errors active_counts = self.users.count_active_users() spawn_pending_count = ( active_counts["spawn_pending"] + active_counts["proxy_pending"] ) active_count = active_counts["active"] RUNNING_SERVERS.set(active_count) concurrent_spawn_limit = self.concurrent_spawn_limit active_server_limit = self.active_server_limit if concurrent_spawn_limit and spawn_pending_count >= concurrent_spawn_limit: SERVER_SPAWN_DURATION_SECONDS.labels( status=ServerSpawnStatus.throttled ).observe(time.perf_counter() - spawn_start_time) # Suggest number of seconds client should wait before retrying # This helps prevent thundering herd problems, where users simply # immediately retry when we are overloaded. retry_range = self.settings["spawn_throttle_retry_range"] retry_time = int(random.uniform(*retry_range)) # round suggestion to nicer human value (nearest 10 seconds or minute) if retry_time <= 90: # round human seconds up to nearest 10 human_retry_time = "%i0 seconds" % math.ceil(retry_time / 10.0) else: # round number of minutes human_retry_time = "%i minutes" % math.round(retry_time / 60.0) self.log.warning( "%s pending spawns, throttling. Suggested retry in %s seconds.", spawn_pending_count, retry_time, ) err = web.HTTPError( 429, "Too many users trying to log in right now. Try again in {}.".format( human_retry_time ), ) # can't call set_header directly here because it gets ignored # when errors are raised # we handle err.headers ourselves in Handler.write_error err.headers = {"Retry-After": retry_time} raise err if active_server_limit and active_count >= active_server_limit: self.log.info("%s servers active, no space available", active_count) SERVER_SPAWN_DURATION_SECONDS.labels( status=ServerSpawnStatus.too_many_users ).observe(time.perf_counter() - spawn_start_time) raise web.HTTPError( 429, "Active user limit exceeded. Try again in a few minutes." ) tic = IOLoop.current().time() self.log.debug("Initiating spawn for %s", user_server_name) spawn_future = user.spawn(server_name, options, handler=self) self.log.debug( "%i%s concurrent spawns", spawn_pending_count, "/%i" % concurrent_spawn_limit if concurrent_spawn_limit else "", ) self.log.debug( "%i%s active servers", active_count, "/%i" % active_server_limit if active_server_limit else "", ) spawner = user.spawners[server_name] # set spawn_pending now, so there's no gap where _spawn_pending is False # while we are waiting for _proxy_pending to be set spawner._spawn_pending = True async def finish_user_spawn(): """Finish the user spawn by registering listeners and notifying the proxy. If the spawner is slow to start, this is passed as an async callback, otherwise it is called immediately. """ # wait for spawn Future await spawn_future toc = IOLoop.current().time() self.log.info("User %s took %.3f seconds to start", user_server_name, toc - tic) self.statsd.timing("spawner.success", (toc - tic) * 1000) SERVER_SPAWN_DURATION_SECONDS.labels(status=ServerSpawnStatus.success).observe( time.perf_counter() - spawn_start_time ) self.eventlog.record_event( "hub.jupyter.org/server-action", 1, {"action": "start", "username": user.name, "servername": server_name}, ) proxy_add_start_time = time.perf_counter() spawner._proxy_pending = True try: await self.proxy.add_user(user, server_name) PROXY_ADD_DURATION_SECONDS.labels(status="success").observe( time.perf_counter() - proxy_add_start_time ) RUNNING_SERVERS.inc() except Exception: self.log.exception("Failed to add %s to proxy!", user_server_name) self.log.error("Stopping %s to avoid inconsistent state", user_server_name) await user.stop(server_name) PROXY_ADD_DURATION_SECONDS.labels(status="failure").observe( time.perf_counter() - proxy_add_start_time ) else: spawner.add_poll_callback(self.user_stopped, user, server_name) finally: spawner._proxy_pending = False # hook up spawner._spawn_future so that other requests can await # this result finish_spawn_future = spawner._spawn_future = maybe_future(finish_user_spawn()) def _clear_spawn_future(f): # clear spawner._spawn_future when it's done # keep an exception around, though, to prevent repeated implicit spawns # if spawn is failing if f.cancelled() or f.exception() is None: spawner._spawn_future = None # Now we're all done. clear _spawn_pending flag spawner._spawn_pending = False finish_spawn_future.add_done_callback(_clear_spawn_future) # when spawn finishes (success or failure) # update failure count and abort if consecutive failure limit # is reached def _track_failure_count(f): if f.cancelled() or f.exception() is None: # spawn succeeded, reset failure count self.settings["failure_count"] = 0 return # spawn failed, increment count and abort if limit reached self.settings.setdefault("failure_count", 0) self.settings["failure_count"] += 1 failure_count = self.settings["failure_count"] failure_limit = spawner.consecutive_failure_limit if failure_limit and 1 < failure_count < failure_limit: self.log.warning( "%i consecutive spawns failed. " "Hub will exit if failure count reaches %i before succeeding", failure_count, failure_limit, ) if failure_limit and failure_count >= failure_limit: self.log.critical( "Aborting due to %i consecutive spawn failures", failure_count ) # abort in 2 seconds to allow pending handlers to resolve # mostly propagating errors for the current failures def abort(): raise SystemExit(1) IOLoop.current().call_later(2, abort) finish_spawn_future.add_done_callback(_track_failure_count) try: await gen.with_timeout( timedelta(seconds=self.slow_spawn_timeout), finish_spawn_future ) except gen.TimeoutError: # waiting_for_response indicates server process has started, # but is yet to become responsive. if spawner._spawn_pending and not spawner._waiting_for_response: # still in Spawner.start, which is taking a long time # we shouldn't poll while spawn is incomplete. self.log.warning( "User %s is slow to start (timeout=%s)", user_server_name, self.slow_spawn_timeout, ) return # start has finished, but the server hasn't come up # check if the server died while we were waiting poll_start_time = time.perf_counter() status = await spawner.poll() SERVER_POLL_DURATION_SECONDS.labels( status=ServerPollStatus.from_status(status) ).observe(time.perf_counter() - poll_start_time) if status is not None: toc = IOLoop.current().time() self.statsd.timing("spawner.failure", (toc - tic) * 1000) SERVER_SPAWN_DURATION_SECONDS.labels( status=ServerSpawnStatus.failure ).observe(time.perf_counter() - spawn_start_time) raise web.HTTPError( 500, "Spawner failed to start [status=%s]. The logs for %s may contain details." % (status, spawner._log_name), ) if spawner._waiting_for_response: # hit timeout waiting for response, but server's running. # Hope that it'll show up soon enough, # though it's possible that it started at the wrong URL self.log.warning( "User %s is slow to become responsive (timeout=%s)", user_server_name, self.slow_spawn_timeout, ) self.log.debug( "Expecting server for %s at: %s", user_server_name, spawner.server.url, ) if spawner._proxy_pending: # User.spawn finished, but it hasn't been added to the proxy # Could be due to load or a slow proxy self.log.warning( "User %s is slow to be added to the proxy (timeout=%s)", user_server_name, self.slow_spawn_timeout, )
async def spawn_single_user(self, user, server_name="", options=None): # in case of error, include 'try again from /hub/home' message if self.authenticator.refresh_pre_spawn: auth_user = await self.refresh_auth(user, force=True) if auth_user is None: raise web.HTTPError(403, "auth has expired for %s, login again", user.name) spawn_start_time = time.perf_counter() self.extra_error_html = self.spawn_home_error user_server_name = user.name if server_name: user_server_name = "%s:%s" % (user.name, server_name) if server_name in user.spawners and user.spawners[server_name].pending: pending = user.spawners[server_name].pending SERVER_SPAWN_DURATION_SECONDS.labels( status=ServerSpawnStatus.already_pending ).observe(time.perf_counter() - spawn_start_time) raise RuntimeError("%s pending %s" % (user_server_name, pending)) # count active servers and pending spawns # we could do careful bookkeeping to avoid # but for 10k users this takes ~5ms # and saves us from bookkeeping errors active_counts = self.users.count_active_users() spawn_pending_count = ( active_counts["spawn_pending"] + active_counts["proxy_pending"] ) active_count = active_counts["active"] RUNNING_SERVERS.set(active_count) concurrent_spawn_limit = self.concurrent_spawn_limit active_server_limit = self.active_server_limit if concurrent_spawn_limit and spawn_pending_count >= concurrent_spawn_limit: SERVER_SPAWN_DURATION_SECONDS.labels( status=ServerSpawnStatus.throttled ).observe(time.perf_counter() - spawn_start_time) # Suggest number of seconds client should wait before retrying # This helps prevent thundering herd problems, where users simply # immediately retry when we are overloaded. retry_range = self.settings["spawn_throttle_retry_range"] retry_time = int(random.uniform(*retry_range)) # round suggestion to nicer human value (nearest 10 seconds or minute) if retry_time <= 90: # round human seconds up to nearest 10 human_retry_time = "%i0 seconds" % math.ceil(retry_time / 10.0) else: # round number of minutes human_retry_time = "%i minutes" % math.round(retry_time / 60.0) self.log.warning( "%s pending spawns, throttling. Suggested retry in %s seconds.", spawn_pending_count, retry_time, ) err = web.HTTPError( 429, "Too many users trying to log in right now. Try again in {}.".format( human_retry_time ), ) # can't call set_header directly here because it gets ignored # when errors are raised # we handle err.headers ourselves in Handler.write_error err.headers = {"Retry-After": retry_time} raise err if active_server_limit and active_count >= active_server_limit: self.log.info("%s servers active, no space available", active_count) SERVER_SPAWN_DURATION_SECONDS.labels( status=ServerSpawnStatus.too_many_users ).observe(time.perf_counter() - spawn_start_time) raise web.HTTPError( 429, "Active user limit exceeded. Try again in a few minutes." ) tic = IOLoop.current().time() self.log.debug("Initiating spawn for %s", user_server_name) spawn_future = user.spawn(server_name, options, handler=self) self.log.debug( "%i%s concurrent spawns", spawn_pending_count, "/%i" % concurrent_spawn_limit if concurrent_spawn_limit else "", ) self.log.debug( "%i%s active servers", active_count, "/%i" % active_server_limit if active_server_limit else "", ) spawner = user.spawners[server_name] # set spawn_pending now, so there's no gap where _spawn_pending is False # while we are waiting for _proxy_pending to be set spawner._spawn_pending = True async def finish_user_spawn(): """Finish the user spawn by registering listeners and notifying the proxy. If the spawner is slow to start, this is passed as an async callback, otherwise it is called immediately. """ # wait for spawn Future await spawn_future toc = IOLoop.current().time() self.log.info("User %s took %.3f seconds to start", user_server_name, toc - tic) self.statsd.timing("spawner.success", (toc - tic) * 1000) SERVER_SPAWN_DURATION_SECONDS.labels(status=ServerSpawnStatus.success).observe( time.perf_counter() - spawn_start_time ) self.eventlog.record_event( "hub.jupyter.org/server-action", 1, {"action": "start", "username": user.name, "servername": server_name}, ) proxy_add_start_time = time.perf_counter() spawner._proxy_pending = True try: await self.proxy.add_user(user, server_name) PROXY_ADD_DURATION_SECONDS.labels(status="success").observe( time.perf_counter() - proxy_add_start_time ) RUNNING_SERVERS.inc() except Exception: self.log.exception("Failed to add %s to proxy!", user_server_name) self.log.error("Stopping %s to avoid inconsistent state", user_server_name) await user.stop() PROXY_ADD_DURATION_SECONDS.labels(status="failure").observe( time.perf_counter() - proxy_add_start_time ) else: spawner.add_poll_callback(self.user_stopped, user, server_name) finally: spawner._proxy_pending = False # hook up spawner._spawn_future so that other requests can await # this result finish_spawn_future = spawner._spawn_future = maybe_future(finish_user_spawn()) def _clear_spawn_future(f): # clear spawner._spawn_future when it's done # keep an exception around, though, to prevent repeated implicit spawns # if spawn is failing if f.cancelled() or f.exception() is None: spawner._spawn_future = None # Now we're all done. clear _spawn_pending flag spawner._spawn_pending = False finish_spawn_future.add_done_callback(_clear_spawn_future) # when spawn finishes (success or failure) # update failure count and abort if consecutive failure limit # is reached def _track_failure_count(f): if f.cancelled() or f.exception() is None: # spawn succeeded, reset failure count self.settings["failure_count"] = 0 return # spawn failed, increment count and abort if limit reached self.settings.setdefault("failure_count", 0) self.settings["failure_count"] += 1 failure_count = self.settings["failure_count"] failure_limit = spawner.consecutive_failure_limit if failure_limit and 1 < failure_count < failure_limit: self.log.warning( "%i consecutive spawns failed. " "Hub will exit if failure count reaches %i before succeeding", failure_count, failure_limit, ) if failure_limit and failure_count >= failure_limit: self.log.critical( "Aborting due to %i consecutive spawn failures", failure_count ) # abort in 2 seconds to allow pending handlers to resolve # mostly propagating errors for the current failures def abort(): raise SystemExit(1) IOLoop.current().call_later(2, abort) finish_spawn_future.add_done_callback(_track_failure_count) try: await gen.with_timeout( timedelta(seconds=self.slow_spawn_timeout), finish_spawn_future ) except gen.TimeoutError: # waiting_for_response indicates server process has started, # but is yet to become responsive. if spawner._spawn_pending and not spawner._waiting_for_response: # still in Spawner.start, which is taking a long time # we shouldn't poll while spawn is incomplete. self.log.warning( "User %s is slow to start (timeout=%s)", user_server_name, self.slow_spawn_timeout, ) return # start has finished, but the server hasn't come up # check if the server died while we were waiting poll_start_time = time.perf_counter() status = await spawner.poll() SERVER_POLL_DURATION_SECONDS.labels( status=ServerPollStatus.from_status(status) ).observe(time.perf_counter() - poll_start_time) if status is not None: toc = IOLoop.current().time() self.statsd.timing("spawner.failure", (toc - tic) * 1000) SERVER_SPAWN_DURATION_SECONDS.labels( status=ServerSpawnStatus.failure ).observe(time.perf_counter() - spawn_start_time) raise web.HTTPError( 500, "Spawner failed to start [status=%s]. The logs for %s may contain details." % (status, spawner._log_name), ) if spawner._waiting_for_response: # hit timeout waiting for response, but server's running. # Hope that it'll show up soon enough, # though it's possible that it started at the wrong URL self.log.warning( "User %s is slow to become responsive (timeout=%s)", user_server_name, self.slow_spawn_timeout, ) self.log.debug( "Expecting server for %s at: %s", user_server_name, spawner.server.url, ) if spawner._proxy_pending: # User.spawn finished, but it hasn't been added to the proxy # Could be due to load or a slow proxy self.log.warning( "User %s is slow to be added to the proxy (timeout=%s)", user_server_name, self.slow_spawn_timeout, )
https://github.com/jupyterhub/jupyterhub/issues/3060
[E 2020-05-28 22:02:11.206 JupyterHub base:876] Failed to add michaeldzamba:doublegpu7 to proxy! Traceback (most recent call last): File "/fn/lib/python3.7/site-packages/jupyterhub/handlers/base.py", line 869, in finish_user_spawn await self.proxy.add_user(user, server_name) File "/fn/lib/python3.7/site-packages/jupyterhub/proxy.py", line 274, in add_user {'user': user.name, 'server_name': server_name}, File "/fn/lib/python3.7/site-packages/jupyterhub_traefik_proxy/kv_proxy.py", line 289, in add_route await self._wait_for_route(routespec, provider=self.kv_name) File "/fn/lib/python3.7/site-packages/jupyterhub_traefik_proxy/proxy.py", line 147, in _wait_for_route timeout=self.check_route_timeout, File "/fn/lib/python3.7/site-packages/jupyterhub/utils.py", line 177, in exponential_backoff raise TimeoutError(fail_message) TimeoutError: Traefik route for /user/michaeldzamba/doublegpu7/ configuration not available [E 2020-05-28 22:02:11.207 JupyterHub base:878] Stopping michaeldzamba:doublegpu7 to avoid inconsistent state [I 2020-05-28 22:02:11.208 JupyterHub spawner:1866] Deleting pod jupyter-michaeldzamba
TimeoutError
async def finish_user_spawn(): """Finish the user spawn by registering listeners and notifying the proxy. If the spawner is slow to start, this is passed as an async callback, otherwise it is called immediately. """ # wait for spawn Future await spawn_future toc = IOLoop.current().time() self.log.info("User %s took %.3f seconds to start", user_server_name, toc - tic) self.statsd.timing("spawner.success", (toc - tic) * 1000) SERVER_SPAWN_DURATION_SECONDS.labels(status=ServerSpawnStatus.success).observe( time.perf_counter() - spawn_start_time ) self.eventlog.record_event( "hub.jupyter.org/server-action", 1, {"action": "start", "username": user.name, "servername": server_name}, ) proxy_add_start_time = time.perf_counter() spawner._proxy_pending = True try: await self.proxy.add_user(user, server_name) PROXY_ADD_DURATION_SECONDS.labels(status="success").observe( time.perf_counter() - proxy_add_start_time ) RUNNING_SERVERS.inc() except Exception: self.log.exception("Failed to add %s to proxy!", user_server_name) self.log.error("Stopping %s to avoid inconsistent state", user_server_name) await user.stop(server_name) PROXY_ADD_DURATION_SECONDS.labels(status="failure").observe( time.perf_counter() - proxy_add_start_time ) else: spawner.add_poll_callback(self.user_stopped, user, server_name) finally: spawner._proxy_pending = False
async def finish_user_spawn(): """Finish the user spawn by registering listeners and notifying the proxy. If the spawner is slow to start, this is passed as an async callback, otherwise it is called immediately. """ # wait for spawn Future await spawn_future toc = IOLoop.current().time() self.log.info("User %s took %.3f seconds to start", user_server_name, toc - tic) self.statsd.timing("spawner.success", (toc - tic) * 1000) SERVER_SPAWN_DURATION_SECONDS.labels(status=ServerSpawnStatus.success).observe( time.perf_counter() - spawn_start_time ) self.eventlog.record_event( "hub.jupyter.org/server-action", 1, {"action": "start", "username": user.name, "servername": server_name}, ) proxy_add_start_time = time.perf_counter() spawner._proxy_pending = True try: await self.proxy.add_user(user, server_name) PROXY_ADD_DURATION_SECONDS.labels(status="success").observe( time.perf_counter() - proxy_add_start_time ) RUNNING_SERVERS.inc() except Exception: self.log.exception("Failed to add %s to proxy!", user_server_name) self.log.error("Stopping %s to avoid inconsistent state", user_server_name) await user.stop() PROXY_ADD_DURATION_SECONDS.labels(status="failure").observe( time.perf_counter() - proxy_add_start_time ) else: spawner.add_poll_callback(self.user_stopped, user, server_name) finally: spawner._proxy_pending = False
https://github.com/jupyterhub/jupyterhub/issues/3060
[E 2020-05-28 22:02:11.206 JupyterHub base:876] Failed to add michaeldzamba:doublegpu7 to proxy! Traceback (most recent call last): File "/fn/lib/python3.7/site-packages/jupyterhub/handlers/base.py", line 869, in finish_user_spawn await self.proxy.add_user(user, server_name) File "/fn/lib/python3.7/site-packages/jupyterhub/proxy.py", line 274, in add_user {'user': user.name, 'server_name': server_name}, File "/fn/lib/python3.7/site-packages/jupyterhub_traefik_proxy/kv_proxy.py", line 289, in add_route await self._wait_for_route(routespec, provider=self.kv_name) File "/fn/lib/python3.7/site-packages/jupyterhub_traefik_proxy/proxy.py", line 147, in _wait_for_route timeout=self.check_route_timeout, File "/fn/lib/python3.7/site-packages/jupyterhub/utils.py", line 177, in exponential_backoff raise TimeoutError(fail_message) TimeoutError: Traefik route for /user/michaeldzamba/doublegpu7/ configuration not available [E 2020-05-28 22:02:11.207 JupyterHub base:878] Stopping michaeldzamba:doublegpu7 to avoid inconsistent state [I 2020-05-28 22:02:11.208 JupyterHub spawner:1866] Deleting pod jupyter-michaeldzamba
TimeoutError
def write_error(self, status_code, **kwargs): """Write JSON errors instead of HTML""" exc_info = kwargs.get("exc_info") message = "" exception = None status_message = responses.get(status_code, "Unknown Error") if exc_info: exception = exc_info[1] # get the custom message, if defined try: message = exception.log_message % exception.args except Exception: pass # construct the custom reason, if defined reason = getattr(exception, "reason", "") if reason: status_message = reason if exception and isinstance(exception, SQLAlchemyError): self.log.warning("Rolling back session due to database error %s", exception) self.db.rollback() self.set_header("Content-Type", "application/json") # allow setting headers from exceptions # since exception handler clears headers headers = getattr(exception, "headers", None) if headers: for key, value in headers.items(): self.set_header(key, value) self.write( json.dumps( { "status": status_code, "message": message or status_message, } ) )
def write_error(self, status_code, **kwargs): """Write JSON errors instead of HTML""" exc_info = kwargs.get("exc_info") message = "" exception = None status_message = responses.get(status_code, "Unknown Error") if exc_info: exception = exc_info[1] # get the custom message, if defined try: message = exception.log_message % exception.args except Exception: pass # construct the custom reason, if defined reason = getattr(exception, "reason", "") if reason: status_message = reason self.set_header("Content-Type", "application/json") # allow setting headers from exceptions # since exception handler clears headers headers = getattr(exception, "headers", None) if headers: for key, value in headers.items(): self.set_header(key, value) self.write( json.dumps( { "status": status_code, "message": message or status_message, } ) )
https://github.com/jupyterhub/jupyterhub/issues/1626
[E 2018-01-19 04:14:19.920 JupyterHub web:1518] Exception in exception handler Traceback (most recent call last): File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1516, in _execute self._handle_request_exception(e) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1570, in _handle_request_exception self.send_error(500, exc_info=sys.exc_info()) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1040, in send_error self.finish() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 105, in finish super().finish(*args, **kwargs) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 993, in finish self._log() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1540, in _log self.application.log_request(self) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 2053, in log_request self.settings["log_function"](handler) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/log.py", line 90, in log_request user = handler.get_current_user() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 229, in get_current_user return self.get_current_user_cookie() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 222, in get_current_user_cookie return self._user_for_cookie(self.hub.cookie_name) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 206, in _user_for_cookie u = self.db.query(orm.User).filter(orm.User.cookie_id==cookie_id).first() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2755, in first ret = list(self[0:1]) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2547, in __getitem__ return list(res) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2855, in __iter__ return self._execute_and_instances(context) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2878, in _execute_and_instances result = conn.execute(querycontext.statement, self._params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/sql/elements.py", line 263, in _execute_on_connection return connection._execute_clauseelement(self, multiparams, params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1053, in _execute_clauseelement compiled_sql, distilled_params File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1121, in _execute_context None, None) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1114, in _execute_context conn = self._revalidate_connection() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 424, in _revalidate_connection "Can't reconnect until invalid " sqlalchemy.exc.StatementError: (sqlalchemy.exc.InvalidRequestError) Can't reconnect until invalid transaction is rolled back [SQL: 'SELECT users.id AS users_id, users.name AS users_name, users.`admin` AS users_admin, users.last_activity AS users_last_activity, users.cookie_id AS users_cookie_id, users.state AS users_state, users.encrypted_auth_state AS users_encrypted_auth_state \nFROM users \nWHERE users.cookie_id = %(cookie_id_1)s \n LIMIT %(param_1)s'] [parameters: [{}]]
sqlalchemy.exc.StatementError
async def update_last_activity(self): """Update User.last_activity timestamps from the proxy""" routes = await self.proxy.get_all_routes() users_count = 0 active_users_count = 0 now = datetime.utcnow() for prefix, route in routes.items(): route_data = route["data"] if "user" not in route_data: # not a user route, ignore it continue if "server_name" not in route_data: continue users_count += 1 if "last_activity" not in route_data: # no last activity data (possibly proxy other than CHP) continue user = orm.User.find(self.db, route_data["user"]) if user is None: self.log.warning("Found no user for route: %s", route) continue spawner = user.orm_spawners.get(route_data["server_name"]) if spawner is None: self.log.warning("Found no spawner for route: %s", route) continue dt = parse_date(route_data["last_activity"]) if dt.tzinfo: # strip timezone info to naïve UTC datetime dt = dt.astimezone(timezone.utc).replace(tzinfo=None) if user.last_activity: user.last_activity = max(user.last_activity, dt) else: user.last_activity = dt if spawner.last_activity: spawner.last_activity = max(spawner.last_activity, dt) else: spawner.last_activity = dt # FIXME: Make this configurable duration. 30 minutes for now! if (now - user.last_activity).total_seconds() < 30 * 60: active_users_count += 1 self.statsd.gauge("users.running", users_count) self.statsd.gauge("users.active", active_users_count) try: self.db.commit() except SQLAlchemyError: self.log.exception("Rolling back session due to database error") self.db.rollback() return await self.proxy.check_routes(self.users, self._service_map, routes)
async def update_last_activity(self): """Update User.last_activity timestamps from the proxy""" routes = await self.proxy.get_all_routes() users_count = 0 active_users_count = 0 now = datetime.utcnow() for prefix, route in routes.items(): route_data = route["data"] if "user" not in route_data: # not a user route, ignore it continue if "server_name" not in route_data: continue users_count += 1 if "last_activity" not in route_data: # no last activity data (possibly proxy other than CHP) continue user = orm.User.find(self.db, route_data["user"]) if user is None: self.log.warning("Found no user for route: %s", route) continue spawner = user.orm_spawners.get(route_data["server_name"]) if spawner is None: self.log.warning("Found no spawner for route: %s", route) continue dt = parse_date(route_data["last_activity"]) if dt.tzinfo: # strip timezone info to naïve UTC datetime dt = dt.astimezone(timezone.utc).replace(tzinfo=None) if user.last_activity: user.last_activity = max(user.last_activity, dt) else: user.last_activity = dt if spawner.last_activity: spawner.last_activity = max(spawner.last_activity, dt) else: spawner.last_activity = dt # FIXME: Make this configurable duration. 30 minutes for now! if (now - user.last_activity).total_seconds() < 30 * 60: active_users_count += 1 self.statsd.gauge("users.running", users_count) self.statsd.gauge("users.active", active_users_count) self.db.commit() await self.proxy.check_routes(self.users, self._service_map, routes)
https://github.com/jupyterhub/jupyterhub/issues/1626
[E 2018-01-19 04:14:19.920 JupyterHub web:1518] Exception in exception handler Traceback (most recent call last): File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1516, in _execute self._handle_request_exception(e) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1570, in _handle_request_exception self.send_error(500, exc_info=sys.exc_info()) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1040, in send_error self.finish() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 105, in finish super().finish(*args, **kwargs) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 993, in finish self._log() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1540, in _log self.application.log_request(self) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 2053, in log_request self.settings["log_function"](handler) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/log.py", line 90, in log_request user = handler.get_current_user() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 229, in get_current_user return self.get_current_user_cookie() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 222, in get_current_user_cookie return self._user_for_cookie(self.hub.cookie_name) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 206, in _user_for_cookie u = self.db.query(orm.User).filter(orm.User.cookie_id==cookie_id).first() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2755, in first ret = list(self[0:1]) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2547, in __getitem__ return list(res) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2855, in __iter__ return self._execute_and_instances(context) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2878, in _execute_and_instances result = conn.execute(querycontext.statement, self._params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/sql/elements.py", line 263, in _execute_on_connection return connection._execute_clauseelement(self, multiparams, params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1053, in _execute_clauseelement compiled_sql, distilled_params File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1121, in _execute_context None, None) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1114, in _execute_context conn = self._revalidate_connection() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 424, in _revalidate_connection "Can't reconnect until invalid " sqlalchemy.exc.StatementError: (sqlalchemy.exc.InvalidRequestError) Can't reconnect until invalid transaction is rolled back [SQL: 'SELECT users.id AS users_id, users.name AS users_name, users.`admin` AS users_admin, users.last_activity AS users_last_activity, users.cookie_id AS users_cookie_id, users.state AS users_state, users.encrypted_auth_state AS users_encrypted_auth_state \nFROM users \nWHERE users.cookie_id = %(cookie_id_1)s \n LIMIT %(param_1)s'] [parameters: [{}]]
sqlalchemy.exc.StatementError
def get_current_user(self): """get current username""" if not hasattr(self, "_jupyterhub_user"): try: user = self.get_current_user_token() if user is None: user = self.get_current_user_cookie() self._jupyterhub_user = user except Exception: # don't let errors here raise more than once self._jupyterhub_user = None raise return self._jupyterhub_user
def get_current_user(self): """get current username""" user = self.get_current_user_token() if user is not None: return user return self.get_current_user_cookie()
https://github.com/jupyterhub/jupyterhub/issues/1626
[E 2018-01-19 04:14:19.920 JupyterHub web:1518] Exception in exception handler Traceback (most recent call last): File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1516, in _execute self._handle_request_exception(e) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1570, in _handle_request_exception self.send_error(500, exc_info=sys.exc_info()) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1040, in send_error self.finish() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 105, in finish super().finish(*args, **kwargs) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 993, in finish self._log() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1540, in _log self.application.log_request(self) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 2053, in log_request self.settings["log_function"](handler) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/log.py", line 90, in log_request user = handler.get_current_user() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 229, in get_current_user return self.get_current_user_cookie() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 222, in get_current_user_cookie return self._user_for_cookie(self.hub.cookie_name) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 206, in _user_for_cookie u = self.db.query(orm.User).filter(orm.User.cookie_id==cookie_id).first() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2755, in first ret = list(self[0:1]) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2547, in __getitem__ return list(res) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2855, in __iter__ return self._execute_and_instances(context) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2878, in _execute_and_instances result = conn.execute(querycontext.statement, self._params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/sql/elements.py", line 263, in _execute_on_connection return connection._execute_clauseelement(self, multiparams, params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1053, in _execute_clauseelement compiled_sql, distilled_params File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1121, in _execute_context None, None) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1114, in _execute_context conn = self._revalidate_connection() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 424, in _revalidate_connection "Can't reconnect until invalid " sqlalchemy.exc.StatementError: (sqlalchemy.exc.InvalidRequestError) Can't reconnect until invalid transaction is rolled back [SQL: 'SELECT users.id AS users_id, users.name AS users_name, users.`admin` AS users_admin, users.last_activity AS users_last_activity, users.cookie_id AS users_cookie_id, users.state AS users_state, users.encrypted_auth_state AS users_encrypted_auth_state \nFROM users \nWHERE users.cookie_id = %(cookie_id_1)s \n LIMIT %(param_1)s'] [parameters: [{}]]
sqlalchemy.exc.StatementError
def write_error(self, status_code, **kwargs): """render custom error pages""" exc_info = kwargs.get("exc_info") message = "" exception = None status_message = responses.get(status_code, "Unknown HTTP Error") if exc_info: exception = exc_info[1] # get the custom message, if defined try: message = exception.log_message % exception.args except Exception: pass # construct the custom reason, if defined reason = getattr(exception, "reason", "") if reason: message = reasons.get(reason, reason) if exception and isinstance(exception, SQLAlchemyError): self.log.warning("Rolling back session due to database error %s", exception) self.db.rollback() # build template namespace ns = dict( status_code=status_code, status_message=status_message, message=message, extra_error_html=getattr(self, "extra_error_html", ""), exception=exception, ) self.set_header("Content-Type", "text/html") # allow setting headers from exceptions # since exception handler clears headers headers = getattr(exception, "headers", None) if headers: for key, value in headers.items(): self.set_header(key, value) # render the template try: html = self.render_template("%s.html" % status_code, **ns) except TemplateNotFound: self.log.debug("No template for %d", status_code) html = self.render_template("error.html", **ns) self.write(html)
def write_error(self, status_code, **kwargs): """render custom error pages""" exc_info = kwargs.get("exc_info") message = "" exception = None status_message = responses.get(status_code, "Unknown HTTP Error") if exc_info: exception = exc_info[1] # get the custom message, if defined try: message = exception.log_message % exception.args except Exception: pass # construct the custom reason, if defined reason = getattr(exception, "reason", "") if reason: message = reasons.get(reason, reason) # build template namespace ns = dict( status_code=status_code, status_message=status_message, message=message, extra_error_html=getattr(self, "extra_error_html", ""), exception=exception, ) self.set_header("Content-Type", "text/html") # allow setting headers from exceptions # since exception handler clears headers headers = getattr(exception, "headers", None) if headers: for key, value in headers.items(): self.set_header(key, value) # render the template try: html = self.render_template("%s.html" % status_code, **ns) except TemplateNotFound: self.log.debug("No template for %d", status_code) html = self.render_template("error.html", **ns) self.write(html)
https://github.com/jupyterhub/jupyterhub/issues/1626
[E 2018-01-19 04:14:19.920 JupyterHub web:1518] Exception in exception handler Traceback (most recent call last): File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1516, in _execute self._handle_request_exception(e) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1570, in _handle_request_exception self.send_error(500, exc_info=sys.exc_info()) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1040, in send_error self.finish() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 105, in finish super().finish(*args, **kwargs) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 993, in finish self._log() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1540, in _log self.application.log_request(self) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 2053, in log_request self.settings["log_function"](handler) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/log.py", line 90, in log_request user = handler.get_current_user() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 229, in get_current_user return self.get_current_user_cookie() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 222, in get_current_user_cookie return self._user_for_cookie(self.hub.cookie_name) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 206, in _user_for_cookie u = self.db.query(orm.User).filter(orm.User.cookie_id==cookie_id).first() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2755, in first ret = list(self[0:1]) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2547, in __getitem__ return list(res) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2855, in __iter__ return self._execute_and_instances(context) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2878, in _execute_and_instances result = conn.execute(querycontext.statement, self._params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/sql/elements.py", line 263, in _execute_on_connection return connection._execute_clauseelement(self, multiparams, params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1053, in _execute_clauseelement compiled_sql, distilled_params File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1121, in _execute_context None, None) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1114, in _execute_context conn = self._revalidate_connection() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 424, in _revalidate_connection "Can't reconnect until invalid " sqlalchemy.exc.StatementError: (sqlalchemy.exc.InvalidRequestError) Can't reconnect until invalid transaction is rolled back [SQL: 'SELECT users.id AS users_id, users.name AS users_name, users.`admin` AS users_admin, users.last_activity AS users_last_activity, users.cookie_id AS users_cookie_id, users.state AS users_state, users.encrypted_auth_state AS users_encrypted_auth_state \nFROM users \nWHERE users.cookie_id = %(cookie_id_1)s \n LIMIT %(param_1)s'] [parameters: [{}]]
sqlalchemy.exc.StatementError
def _notify_deleted_relationships(session, obj): """Expire relationships when an object becomes deleted Needed to keep relationships up to date. """ mapper = inspect(obj).mapper for prop in mapper.relationships: if prop.back_populates: _expire_relationship(obj, prop)
def _notify_deleted_relationships(session, obj): """Expire relationships when an object becomes deleted Needed for """ mapper = inspect(obj).mapper for prop in mapper.relationships: if prop.back_populates: _expire_relationship(obj, prop)
https://github.com/jupyterhub/jupyterhub/issues/1626
[E 2018-01-19 04:14:19.920 JupyterHub web:1518] Exception in exception handler Traceback (most recent call last): File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1516, in _execute self._handle_request_exception(e) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1570, in _handle_request_exception self.send_error(500, exc_info=sys.exc_info()) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1040, in send_error self.finish() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 105, in finish super().finish(*args, **kwargs) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 993, in finish self._log() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1540, in _log self.application.log_request(self) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 2053, in log_request self.settings["log_function"](handler) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/log.py", line 90, in log_request user = handler.get_current_user() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 229, in get_current_user return self.get_current_user_cookie() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 222, in get_current_user_cookie return self._user_for_cookie(self.hub.cookie_name) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 206, in _user_for_cookie u = self.db.query(orm.User).filter(orm.User.cookie_id==cookie_id).first() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2755, in first ret = list(self[0:1]) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2547, in __getitem__ return list(res) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2855, in __iter__ return self._execute_and_instances(context) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2878, in _execute_and_instances result = conn.execute(querycontext.statement, self._params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/sql/elements.py", line 263, in _execute_on_connection return connection._execute_clauseelement(self, multiparams, params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1053, in _execute_clauseelement compiled_sql, distilled_params File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1121, in _execute_context None, None) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1114, in _execute_context conn = self._revalidate_connection() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 424, in _revalidate_connection "Can't reconnect until invalid " sqlalchemy.exc.StatementError: (sqlalchemy.exc.InvalidRequestError) Can't reconnect until invalid transaction is rolled back [SQL: 'SELECT users.id AS users_id, users.name AS users_name, users.`admin` AS users_admin, users.last_activity AS users_last_activity, users.cookie_id AS users_cookie_id, users.state AS users_state, users.encrypted_auth_state AS users_encrypted_auth_state \nFROM users \nWHERE users.cookie_id = %(cookie_id_1)s \n LIMIT %(param_1)s'] [parameters: [{}]]
sqlalchemy.exc.StatementError
def new_session_factory( url="sqlite:///:memory:", reset=False, expire_on_commit=False, **kwargs ): """Create a new session at url""" if url.startswith("sqlite"): kwargs.setdefault("connect_args", {"check_same_thread": False}) listeners = kwargs.setdefault("listeners", []) listeners.append(ForeignKeysListener()) elif url.startswith("mysql"): kwargs.setdefault("pool_recycle", 60) if url.endswith(":memory:"): # If we're using an in-memory database, ensure that only one connection # is ever created. kwargs.setdefault("poolclass", StaticPool) engine = create_engine(url, **kwargs) # enable pessimistic disconnect handling register_ping_connection(engine) if reset: Base.metadata.drop_all(engine) if mysql_large_prefix_check(engine): # if mysql is allows large indexes add_row_format(Base) # set format on the tables # check the db revision (will raise, pointing to `upgrade-db` if version doesn't match) check_db_revision(engine) Base.metadata.create_all(engine) # We set expire_on_commit=False, since we don't actually need # SQLAlchemy to expire objects after commiting - we don't expect # concurrent runs of the hub talking to the same db. Turning # this off gives us a major performance boost session_factory = sessionmaker( bind=engine, expire_on_commit=expire_on_commit, ) return session_factory
def new_session_factory( url="sqlite:///:memory:", reset=False, expire_on_commit=False, **kwargs ): """Create a new session at url""" if url.startswith("sqlite"): kwargs.setdefault("connect_args", {"check_same_thread": False}) listeners = kwargs.setdefault("listeners", []) listeners.append(ForeignKeysListener()) elif url.startswith("mysql"): kwargs.setdefault("pool_recycle", 60) if url.endswith(":memory:"): # If we're using an in-memory database, ensure that only one connection # is ever created. kwargs.setdefault("poolclass", StaticPool) engine = create_engine(url, **kwargs) if reset: Base.metadata.drop_all(engine) if mysql_large_prefix_check(engine): # if mysql is allows large indexes add_row_format(Base) # set format on the tables # check the db revision (will raise, pointing to `upgrade-db` if version doesn't match) check_db_revision(engine) Base.metadata.create_all(engine) # We set expire_on_commit=False, since we don't actually need # SQLAlchemy to expire objects after commiting - we don't expect # concurrent runs of the hub talking to the same db. Turning # this off gives us a major performance boost session_factory = sessionmaker( bind=engine, expire_on_commit=expire_on_commit, ) return session_factory
https://github.com/jupyterhub/jupyterhub/issues/1626
[E 2018-01-19 04:14:19.920 JupyterHub web:1518] Exception in exception handler Traceback (most recent call last): File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1516, in _execute self._handle_request_exception(e) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1570, in _handle_request_exception self.send_error(500, exc_info=sys.exc_info()) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1040, in send_error self.finish() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 105, in finish super().finish(*args, **kwargs) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 993, in finish self._log() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 1540, in _log self.application.log_request(self) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/tornado/web.py", line 2053, in log_request self.settings["log_function"](handler) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/log.py", line 90, in log_request user = handler.get_current_user() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 229, in get_current_user return self.get_current_user_cookie() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 222, in get_current_user_cookie return self._user_for_cookie(self.hub.cookie_name) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/jupyterhub/handlers/base.py", line 206, in _user_for_cookie u = self.db.query(orm.User).filter(orm.User.cookie_id==cookie_id).first() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2755, in first ret = list(self[0:1]) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2547, in __getitem__ return list(res) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2855, in __iter__ return self._execute_and_instances(context) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/orm/query.py", line 2878, in _execute_and_instances result = conn.execute(querycontext.statement, self._params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/sql/elements.py", line 263, in _execute_on_connection return connection._execute_clauseelement(self, multiparams, params) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1053, in _execute_clauseelement compiled_sql, distilled_params File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1121, in _execute_context None, None) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 1114, in _execute_context conn = self._revalidate_connection() File "/Users/bhatt/anaconda3/lib/python3.6/site-packages/sqlalchemy/engine/base.py", line 424, in _revalidate_connection "Can't reconnect until invalid " sqlalchemy.exc.StatementError: (sqlalchemy.exc.InvalidRequestError) Can't reconnect until invalid transaction is rolled back [SQL: 'SELECT users.id AS users_id, users.name AS users_name, users.`admin` AS users_admin, users.last_activity AS users_last_activity, users.cookie_id AS users_cookie_id, users.state AS users_state, users.encrypted_auth_state AS users_encrypted_auth_state \nFROM users \nWHERE users.cookie_id = %(cookie_id_1)s \n LIMIT %(param_1)s'] [parameters: [{}]]
sqlalchemy.exc.StatementError
def validate(self, obj, value): """ Validate that the passed in value is a valid memory specification It could either be a pure int, when it is taken as a byte value. If it has one of the suffixes, it is converted into the appropriate pure byte value. """ if isinstance(value, (int, float)): return int(value) try: num = float(value[:-1]) except ValueError: raise TraitError( "{val} is not a valid memory specification. Must be an int or a string with suffix K, M, G, T".format( val=value ) ) suffix = value[-1] if suffix not in self.UNIT_SUFFIXES: raise TraitError( "{val} is not a valid memory specification. Must be an int or a string with suffix K, M, G, T".format( val=value ) ) else: return int(float(num) * self.UNIT_SUFFIXES[suffix])
def validate(self, obj, value): """ Validate that the passed in value is a valid memory specification It could either be a pure int, when it is taken as a byte value. If it has one of the suffixes, it is converted into the appropriate pure byte value. """ if isinstance(value, int): return value num = value[:-1] suffix = value[-1] if not num.isdigit() and suffix not in ByteSpecification.UNIT_SUFFIXES: raise TraitError( "{val} is not a valid memory specification. Must be an int or a string with suffix K, M, G, T".format( val=value ) ) else: return int(num) * ByteSpecification.UNIT_SUFFIXES[suffix]
https://github.com/jupyterhub/jupyterhub/issues/1089
[E 2017-04-18 05:39:02.270 JupyterHub app:1527] Traceback (most recent call last): File "/usr/local/lib/python3.4/dist-packages/jupyterhub/app.py", line 1524, in launch_instance_async yield self.initialize(argv) File "/usr/local/lib/python3.4/dist-packages/jupyterhub/app.py", line 1315, in initialize yield self.init_spawners() File "/usr/local/lib/python3.4/dist-packages/jupyterhub/app.py", line 1084, in init_spawners self.users[orm_user.id] = user = User(orm_user, self.tornado_settings) File "/usr/local/lib/python3.4/dist-packages/jupyterhub/user.py", line 128, in __init__ config=self.settings.get('config'), File "/usr/local/lib/python3.4/dist-packages/kubespawner/spawner.py", line 29, in __init__ super().__init__(*args, **kwargs) File "/usr/local/lib/python3.4/dist-packages/jupyterhub/spawner.py", line 345, in __init__ super(Spawner, self).__init__(**kwargs) File "/usr/local/lib/python3.4/dist-packages/traitlets/config/configurable.py", line 84, in __init__ self.config = config File "/usr/local/lib/python3.4/dist-packages/traitlets/traitlets.py", line 585, in __set__ self.set(obj, value) File "/usr/local/lib/python3.4/dist-packages/traitlets/traitlets.py", line 574, in set obj._notify_trait(self.name, old_value, new_value) File "/usr/local/lib/python3.4/dist-packages/traitlets/traitlets.py", line 1139, in _notify_trait type='change', File "/usr/local/lib/python3.4/dist-packages/traitlets/traitlets.py", line 1176, in notify_change c(change) File "/usr/local/lib/python3.4/dist-packages/traitlets/traitlets.py", line 819, in compatible_observer return func(self, change) File "/usr/local/lib/python3.4/dist-packages/traitlets/config/configurable.py", line 186, in _config_changed self._load_config(change.new, traits=traits, section_names=section_names) File "/usr/local/lib/python3.4/dist-packages/traitlets/config/configurable.py", line 153, in _load_config setattr(self, name, deepcopy(config_value)) File "/usr/local/lib/python3.4/dist-packages/traitlets/traitlets.py", line 585, in __set__ self.set(obj, value) File "/usr/local/lib/python3.4/dist-packages/traitlets/traitlets.py", line 559, in set new_value = self._validate(obj, value) File "/usr/local/lib/python3.4/dist-packages/traitlets/traitlets.py", line 591, in _validate value = self.validate(obj, value) File "/usr/local/lib/python3.4/dist-packages/jupyterhub/traitlets.py", line 71, in validate return int(num) * ByteSpecification.UNIT_SUFFIXES[suffix] ValueError: invalid literal for int() with base 10: '1.5'
ValueError
def init_spawners(self): db = self.db user_summaries = [""] def _user_summary(user): parts = ["{0: >8}".format(user.name)] if user.admin: parts.append("admin") for name, spawner in sorted(user.spawners.items(), key=itemgetter(0)): if spawner.server: parts.append("%s:%s running at %s" % (user.name, name, spawner.server)) return " ".join(parts) @gen.coroutine def user_stopped(user, server_name): spawner = user.spawners[server_name] status = yield spawner.poll() self.log.warning( "User %s server stopped with exit code: %s", user.name, status, ) yield self.proxy.delete_user(user, server_name) yield user.stop(server_name) for orm_user in db.query(orm.User): self.users[orm_user.id] = user = User(orm_user, self.tornado_settings) self.log.debug("Loading state for %s from db", user.name) for name, spawner in user.spawners.items(): status = 0 if spawner.server: try: status = yield spawner.poll() except Exception: self.log.exception( "Failed to poll spawner for %s, assuming the spawner is not running.", spawner._log_name, ) status = -1 if status is None: self.log.info("%s still running", user.name) spawner.add_poll_callback(user_stopped, user, name) spawner.start_polling() else: # user not running. This is expected if server is None, # but indicates the user's server died while the Hub wasn't running # if spawner.server is defined. if spawner.server: self.log.warning( "%s appears to have stopped while the Hub was down", spawner._log_name, ) # remove server entry from db db.delete(spawner.orm_spawner.server) spawner.server = None else: self.log.debug("%s not running", spawner._log_name) db.commit() user_summaries.append(_user_summary(user)) self.log.debug("Loaded users: %s", "\n".join(user_summaries)) db.commit()
def init_spawners(self): db = self.db user_summaries = [""] def _user_summary(user): parts = ["{0: >8}".format(user.name)] if user.admin: parts.append("admin") for name, spawner in sorted(user.spawners.items(), key=itemgetter(0)): if spawner.server: parts.append("%s:%s running at %s" % (user.name, name, spawner.server)) return " ".join(parts) @gen.coroutine def user_stopped(user, server_name): spawner = user.spawners[server_name] status = yield spawner.poll() self.log.warning( "User %s server stopped with exit code: %s", user.name, status, ) yield self.proxy.delete_user(user, server_name) yield user.stop(server_name) for orm_user in db.query(orm.User): self.users[orm_user.id] = user = User(orm_user, self.tornado_settings) self.log.debug("Loading state for %s from db", user.name) for name, spawner in user.spawners.items(): status = 0 if spawner.server: try: status = yield spawner.poll() except Exception: self.log.exception( "Failed to poll spawner for %s, assuming the spawner is not running.", user.name if name else "%s|%s" % (user.name, name), ) status = -1 if status is None: self.log.info("%s still running", user.name) spawner.add_poll_callback(user_stopped, user, name) spawner.start_polling() else: # user not running. This is expected if server is None, # but indicates the user's server died while the Hub wasn't running # if spawner.server is defined. log = self.log.warning if spawner.server else self.log.debug log("%s not running.", user.name) # remove all server or servers entry from db related to the user if spawner.server: db.delete(spawner.orm_spawner.server) db.commit() user_summaries.append(_user_summary(user)) self.log.debug("Loaded users: %s", "\n".join(user_summaries)) db.commit()
https://github.com/jupyterhub/jupyterhub/issues/1414
singleuser.cmd jupyterhub-singleuser Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1623, in launch_instance_async yield self.initialize(argv) File "/usr/lib/python3.5/types.py", line 179, in throw return self.__wrapped.throw(tp, *rest) File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1385, in initialize yield self.init_spawners() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1240, in init_spawners db.commit() File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/session.py", line 906, in commit self.transaction.commit() File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/session.py", line 461, in commit self._prepare_impl() File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/session.py", line 441, in _prepare_impl self.session.flush() File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/session.py", line 2171, in flush self._flush(objects) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/session.py", line 2291, in _flush transaction.rollback(_capture_exception=True) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/langhelpers.py", line 66, in __exit__ compat.reraise(exc_type, exc_value, exc_tb) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 187, in reraise raise value File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/session.py", line 2255, in _flush flush_context.execute() File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/unitofwork.py", line 389, in execute rec.execute(self) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/unitofwork.py", line 577, in execute uow File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/persistence.py", line 258, in delete_obj cached_connections, mapper, table, delete) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/persistence.py", line 931, in _emit_delete_statements c = connection.execute(statement, del_objects) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/sql/elements.py", line 263, in _execute_on_connection return connection._execute_clauseelement(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1053, in _execute_clauseelement compiled_sql, distilled_params File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1189, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1182, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/default.py", line 470, in do_execute cursor.execute(statement, parameters) sqlalchemy.exc.IntegrityError: (psycopg2.IntegrityError) update or delete on table "servers" violates foreign key constraint "spawners_server_id_fkey" on table "spawners" DETAIL: Key (id)=(24433) is still referenced from table "spawners". [SQL: 'DELETE FROM servers WHERE servers.id = %(id)s'] [parameters: {'id': 24433}]
sqlalchemy.exc.IntegrityError
def stop(self): """Stop a managed service""" if not self.managed: raise RuntimeError("Cannot stop unmanaged service %s" % self) if self.spawner: if self.orm.server: self.db.delete(self.orm.server) self.db.commit() self.spawner.stop_polling() return self.spawner.stop()
def stop(self): """Stop a managed service""" if not self.managed: raise RuntimeError("Cannot stop unmanaged service %s" % self) if self.spawner: self.spawner.stop_polling() return self.spawner.stop()
https://github.com/jupyterhub/jupyterhub/issues/1414
singleuser.cmd jupyterhub-singleuser Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1623, in launch_instance_async yield self.initialize(argv) File "/usr/lib/python3.5/types.py", line 179, in throw return self.__wrapped.throw(tp, *rest) File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1385, in initialize yield self.init_spawners() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1240, in init_spawners db.commit() File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/session.py", line 906, in commit self.transaction.commit() File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/session.py", line 461, in commit self._prepare_impl() File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/session.py", line 441, in _prepare_impl self.session.flush() File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/session.py", line 2171, in flush self._flush(objects) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/session.py", line 2291, in _flush transaction.rollback(_capture_exception=True) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/langhelpers.py", line 66, in __exit__ compat.reraise(exc_type, exc_value, exc_tb) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 187, in reraise raise value File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/session.py", line 2255, in _flush flush_context.execute() File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/unitofwork.py", line 389, in execute rec.execute(self) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/unitofwork.py", line 577, in execute uow File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/persistence.py", line 258, in delete_obj cached_connections, mapper, table, delete) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/orm/persistence.py", line 931, in _emit_delete_statements c = connection.execute(statement, del_objects) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/sql/elements.py", line 263, in _execute_on_connection return connection._execute_clauseelement(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1053, in _execute_clauseelement compiled_sql, distilled_params File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1189, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1182, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/default.py", line 470, in do_execute cursor.execute(statement, parameters) sqlalchemy.exc.IntegrityError: (psycopg2.IntegrityError) update or delete on table "servers" violates foreign key constraint "spawners_server_id_fkey" on table "spawners" DETAIL: Key (id)=(24433) is still referenced from table "spawners". [SQL: 'DELETE FROM servers WHERE servers.id = %(id)s'] [parameters: {'id': 24433}]
sqlalchemy.exc.IntegrityError
def get(self, token): orm_token = orm.APIToken.find(self.db, token) if orm_token is None: orm_token = orm.OAuthAccessToken.find(self.db, token) if orm_token is None: raise web.HTTPError(404) if orm_token.user: model = self.user_model(self.users[orm_token.user]) elif orm_token.service: model = self.service_model(orm_token.service) else: self.log.warning("%s has no user or service. Deleting..." % orm_token) self.db.delete(orm_token) self.db.commit() raise web.HTTPError(404) self.write(json.dumps(model))
def get(self, token): orm_token = orm.APIToken.find(self.db, token) if orm_token is None: orm_token = orm.OAuthAccessToken.find(self.db, token) if orm_token is None: raise web.HTTPError(404) if orm_token.user: model = self.user_model(self.users[orm_token.user]) elif orm_token.service: model = self.service_model(orm_token.service) self.write(json.dumps(model))
https://github.com/jupyterhub/jupyterhub/issues/1309
Traceback (most recent call last): File "/usr/lib64/python3.4/site-packages/tornado/web.py", line 1509, in _execute result = method(*self.path_args, **self.path_kwargs) File "/usr/lib/python3.4/site-packages/jupyterhub/utils.py", line 193, in decorated return method(self, *args, **kwargs) File "/usr/lib/python3.4/site-packages/jupyterhub/apihandlers/auth.py", line 27, in get elif orm_token.service: AttributeError: 'OAuthAccessToken' object has no attribute 'service'
AttributeError
def save_token(self, access_token): """ Stores an access token in the database. :param access_token: An instance of :class:`oauth2.datatype.AccessToken`. """ user = self.db.query(orm.User).filter(orm.User.id == access_token.user_id).first() if user is None: raise ValueError("No user for access token: %s" % access_token.user_id) orm_access_token = orm.OAuthAccessToken( generated=True, client_id=access_token.client_id, grant_type=access_token.grant_type, expires_at=access_token.expires_at, refresh_token=access_token.refresh_token, refresh_expires_at=access_token.refresh_expires_at, token=access_token.token, user=user, ) self.db.add(orm_access_token) self.db.commit()
def save_token(self, access_token): """ Stores an access token in the database. :param access_token: An instance of :class:`oauth2.datatype.AccessToken`. """ user = self.db.query(orm.User).filter(orm.User.id == access_token.user_id).first() orm_access_token = orm.OAuthAccessToken( client_id=access_token.client_id, grant_type=access_token.grant_type, expires_at=access_token.expires_at, refresh_token=access_token.refresh_token, refresh_expires_at=access_token.refresh_expires_at, token=access_token.token, user=user, ) self.db.add(orm_access_token) self.db.commit()
https://github.com/jupyterhub/jupyterhub/issues/1309
Traceback (most recent call last): File "/usr/lib64/python3.4/site-packages/tornado/web.py", line 1509, in _execute result = method(*self.path_args, **self.path_kwargs) File "/usr/lib/python3.4/site-packages/jupyterhub/utils.py", line 193, in decorated return method(self, *args, **kwargs) File "/usr/lib/python3.4/site-packages/jupyterhub/apihandlers/auth.py", line 27, in get elif orm_token.service: AttributeError: 'OAuthAccessToken' object has no attribute 'service'
AttributeError
def upgrade(): # proxy/table info is no longer in the database op.drop_table("proxies") op.drop_table("hubs") # drop some columns no longer in use try: op.drop_column("users", "auth_state") op.drop_column("users", "_server_id") except sa.exc.OperationalError: # this won't be a problem moving forward, but downgrade will fail if op.get_context().dialect.name == "sqlite": logger.warning( "sqlite cannot drop columns. Leaving unused old columns in place." ) else: raise op.add_column("users", sa.Column("encrypted_auth_state", sa.types.LargeBinary))
def upgrade(): try: op.drop_column("users", "auth_state") except sa.exc.OperationalError as e: # sqlite3 can't drop columns warnings.warn("Failed to drop column: %s" % e) op.add_column("users", sa.Column("encrypted_auth_state", sa.types.LargeBinary))
https://github.com/jupyterhub/jupyterhub/issues/1162
$ jupyterhub ... $ jupyterhub upgrade-db INFO [alembic.runtime.migration] Context impl SQLiteImpl. INFO [alembic.runtime.migration] Will assume non-transactional DDL. INFO [alembic.runtime.migration] Running upgrade -> 19c0846f6344, base revision for 0.5 INFO [alembic.runtime.migration] Running upgrade 19c0846f6344 -> eeb276e51423, auth_state Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1182, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/default.py", line 470, in do_execute cursor.execute(statement, parameters) sqlite3.OperationalError: duplicate column name: auth_state The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/usr/local/bin/alembic", line 11, in <module> sys.exit(main()) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 479, in main CommandLine(prog=prog).main(argv=argv) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 473, in main self.run_cmd(cfg, options) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 456, in run_cmd **dict((k, getattr(options, k, None)) for k in kwarg) File "/usr/local/lib/python3.5/dist-packages/alembic/command.py", line 254, in upgrade script.run_env() File "/usr/local/lib/python3.5/dist-packages/alembic/script/base.py", line 416, in run_env util.load_python_file(self.dir, 'env.py') File "/usr/local/lib/python3.5/dist-packages/alembic/util/pyfiles.py", line 93, in load_python_file module = load_module_py(module_id, path) File "/usr/local/lib/python3.5/dist-packages/alembic/util/compat.py", line 64, in load_module_py module_id, path).load_module(module_id) File "<frozen importlib._bootstrap_external>", line 388, in _check_name_wrapper File "<frozen importlib._bootstrap_external>", line 809, in load_module File "<frozen importlib._bootstrap_external>", line 668, in load_module File "<frozen importlib._bootstrap>", line 268, in _load_module_shim File "<frozen importlib._bootstrap>", line 693, in _load File "<frozen importlib._bootstrap>", line 673, in _load_unlocked File "<frozen importlib._bootstrap_external>", line 665, in exec_module File "<frozen importlib._bootstrap>", line 222, in _call_with_frames_removed File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/env.py", line 70, in <module> run_migrations_online() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/env.py", line 65, in run_migrations_online context.run_migrations() File "<string>", line 8, in run_migrations File "/usr/local/lib/python3.5/dist-packages/alembic/runtime/environment.py", line 817, in run_migrations self.get_context().run_migrations(**kw) File "/usr/local/lib/python3.5/dist-packages/alembic/runtime/migration.py", line 323, in run_migrations step.migration_fn(**kw) File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/versions/eeb276e51423_auth_state.py", line 21, in upgrade op.add_column('users', sa.Column('auth_state', JSONDict)) File "<string>", line 8, in add_column File "<string>", line 3, in add_column File "/usr/local/lib/python3.5/dist-packages/alembic/operations/ops.py", line 1551, in add_column return operations.invoke(op) File "/usr/local/lib/python3.5/dist-packages/alembic/operations/base.py", line 318, in invoke return fn(self, operation) File "/usr/local/lib/python3.5/dist-packages/alembic/operations/toimpl.py", line 123, in add_column schema=schema File "/usr/local/lib/python3.5/dist-packages/alembic/ddl/impl.py", line 172, in add_column self._exec(base.AddColumn(table_name, column, schema=schema)) File "/usr/local/lib/python3.5/dist-packages/alembic/ddl/impl.py", line 118, in _exec return conn.execute(construct, *multiparams, **params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/sql/ddl.py", line 68, in _execute_on_connection return connection._execute_ddl(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1002, in _execute_ddl compiled File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1189, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1182, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/default.py", line 470, in do_execute cursor.execute(statement, parameters) sqlalchemy.exc.OperationalError: (sqlite3.OperationalError) duplicate column name: auth_state [SQL: 'ALTER TABLE users ADD COLUMN auth_state TEXT'] [E 2017-06-02 19:55:16.017 JupyterHub app:1527] Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1525, in launch_instance_async yield self.start() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1436, in start self.subapp.start() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 185, in start dbutil.upgrade(hub.db_url) File "/usr/local/lib/python3.5/dist-packages/jupyterhub/dbutil.py", line 80, in upgrade ['alembic', '-c', alembic_ini, 'upgrade', revision] File "/usr/lib/python3.5/subprocess.py", line 581, in check_call raise CalledProcessError(retcode, cmd) subprocess.CalledProcessError: Command '['alembic', '-c', '/tmp/tmpkqvnuq0a/alembic.ini', 'upgrade', 'head']' returned non-zero exit status 1
sqlite3.OperationalError
def downgrade(): # drop all the new tables engine = op.get_bind().engine for table in ("oauth_clients", "oauth_codes", "oauth_access_tokens", "spawners"): if engine.has_table(table): op.drop_table(table) op.drop_column("users", "encrypted_auth_state") op.add_column("users", sa.Column("auth_state", JSONDict)) op.add_column( "users", sa.Column("_server_id", sa.Integer, sa.ForeignKey("servers.id")) )
def downgrade(): op.drop_column("users", "encrypted_auth_state") op.add_column("users", sa.Column("auth_state", JSONDict))
https://github.com/jupyterhub/jupyterhub/issues/1162
$ jupyterhub ... $ jupyterhub upgrade-db INFO [alembic.runtime.migration] Context impl SQLiteImpl. INFO [alembic.runtime.migration] Will assume non-transactional DDL. INFO [alembic.runtime.migration] Running upgrade -> 19c0846f6344, base revision for 0.5 INFO [alembic.runtime.migration] Running upgrade 19c0846f6344 -> eeb276e51423, auth_state Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1182, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/default.py", line 470, in do_execute cursor.execute(statement, parameters) sqlite3.OperationalError: duplicate column name: auth_state The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/usr/local/bin/alembic", line 11, in <module> sys.exit(main()) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 479, in main CommandLine(prog=prog).main(argv=argv) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 473, in main self.run_cmd(cfg, options) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 456, in run_cmd **dict((k, getattr(options, k, None)) for k in kwarg) File "/usr/local/lib/python3.5/dist-packages/alembic/command.py", line 254, in upgrade script.run_env() File "/usr/local/lib/python3.5/dist-packages/alembic/script/base.py", line 416, in run_env util.load_python_file(self.dir, 'env.py') File "/usr/local/lib/python3.5/dist-packages/alembic/util/pyfiles.py", line 93, in load_python_file module = load_module_py(module_id, path) File "/usr/local/lib/python3.5/dist-packages/alembic/util/compat.py", line 64, in load_module_py module_id, path).load_module(module_id) File "<frozen importlib._bootstrap_external>", line 388, in _check_name_wrapper File "<frozen importlib._bootstrap_external>", line 809, in load_module File "<frozen importlib._bootstrap_external>", line 668, in load_module File "<frozen importlib._bootstrap>", line 268, in _load_module_shim File "<frozen importlib._bootstrap>", line 693, in _load File "<frozen importlib._bootstrap>", line 673, in _load_unlocked File "<frozen importlib._bootstrap_external>", line 665, in exec_module File "<frozen importlib._bootstrap>", line 222, in _call_with_frames_removed File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/env.py", line 70, in <module> run_migrations_online() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/env.py", line 65, in run_migrations_online context.run_migrations() File "<string>", line 8, in run_migrations File "/usr/local/lib/python3.5/dist-packages/alembic/runtime/environment.py", line 817, in run_migrations self.get_context().run_migrations(**kw) File "/usr/local/lib/python3.5/dist-packages/alembic/runtime/migration.py", line 323, in run_migrations step.migration_fn(**kw) File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/versions/eeb276e51423_auth_state.py", line 21, in upgrade op.add_column('users', sa.Column('auth_state', JSONDict)) File "<string>", line 8, in add_column File "<string>", line 3, in add_column File "/usr/local/lib/python3.5/dist-packages/alembic/operations/ops.py", line 1551, in add_column return operations.invoke(op) File "/usr/local/lib/python3.5/dist-packages/alembic/operations/base.py", line 318, in invoke return fn(self, operation) File "/usr/local/lib/python3.5/dist-packages/alembic/operations/toimpl.py", line 123, in add_column schema=schema File "/usr/local/lib/python3.5/dist-packages/alembic/ddl/impl.py", line 172, in add_column self._exec(base.AddColumn(table_name, column, schema=schema)) File "/usr/local/lib/python3.5/dist-packages/alembic/ddl/impl.py", line 118, in _exec return conn.execute(construct, *multiparams, **params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/sql/ddl.py", line 68, in _execute_on_connection return connection._execute_ddl(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1002, in _execute_ddl compiled File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1189, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1182, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/default.py", line 470, in do_execute cursor.execute(statement, parameters) sqlalchemy.exc.OperationalError: (sqlite3.OperationalError) duplicate column name: auth_state [SQL: 'ALTER TABLE users ADD COLUMN auth_state TEXT'] [E 2017-06-02 19:55:16.017 JupyterHub app:1527] Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1525, in launch_instance_async yield self.start() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1436, in start self.subapp.start() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 185, in start dbutil.upgrade(hub.db_url) File "/usr/local/lib/python3.5/dist-packages/jupyterhub/dbutil.py", line 80, in upgrade ['alembic', '-c', alembic_ini, 'upgrade', revision] File "/usr/lib/python3.5/subprocess.py", line 581, in check_call raise CalledProcessError(retcode, cmd) subprocess.CalledProcessError: Command '['alembic', '-c', '/tmp/tmpkqvnuq0a/alembic.ini', 'upgrade', 'head']' returned non-zero exit status 1
sqlite3.OperationalError
def start(self): hub = JupyterHub(parent=self) hub.load_config_file(hub.config_file) self.log = hub.log if hub.db_url.startswith("sqlite:///"): db_file = hub.db_url.split(":///", 1)[1] self._backup_db_file(db_file) self.log.info("Upgrading %s", hub.db_url) dbutil.upgrade(hub.db_url)
def start(self): hub = JupyterHub(parent=self) hub.load_config_file(hub.config_file) if hub.db_url.startswith("sqlite:///"): db_file = hub.db_url.split(":///", 1)[1] self._backup_db_file(db_file) self.log.info("Upgrading %s", hub.db_url) dbutil.upgrade(hub.db_url)
https://github.com/jupyterhub/jupyterhub/issues/1162
$ jupyterhub ... $ jupyterhub upgrade-db INFO [alembic.runtime.migration] Context impl SQLiteImpl. INFO [alembic.runtime.migration] Will assume non-transactional DDL. INFO [alembic.runtime.migration] Running upgrade -> 19c0846f6344, base revision for 0.5 INFO [alembic.runtime.migration] Running upgrade 19c0846f6344 -> eeb276e51423, auth_state Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1182, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/default.py", line 470, in do_execute cursor.execute(statement, parameters) sqlite3.OperationalError: duplicate column name: auth_state The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/usr/local/bin/alembic", line 11, in <module> sys.exit(main()) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 479, in main CommandLine(prog=prog).main(argv=argv) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 473, in main self.run_cmd(cfg, options) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 456, in run_cmd **dict((k, getattr(options, k, None)) for k in kwarg) File "/usr/local/lib/python3.5/dist-packages/alembic/command.py", line 254, in upgrade script.run_env() File "/usr/local/lib/python3.5/dist-packages/alembic/script/base.py", line 416, in run_env util.load_python_file(self.dir, 'env.py') File "/usr/local/lib/python3.5/dist-packages/alembic/util/pyfiles.py", line 93, in load_python_file module = load_module_py(module_id, path) File "/usr/local/lib/python3.5/dist-packages/alembic/util/compat.py", line 64, in load_module_py module_id, path).load_module(module_id) File "<frozen importlib._bootstrap_external>", line 388, in _check_name_wrapper File "<frozen importlib._bootstrap_external>", line 809, in load_module File "<frozen importlib._bootstrap_external>", line 668, in load_module File "<frozen importlib._bootstrap>", line 268, in _load_module_shim File "<frozen importlib._bootstrap>", line 693, in _load File "<frozen importlib._bootstrap>", line 673, in _load_unlocked File "<frozen importlib._bootstrap_external>", line 665, in exec_module File "<frozen importlib._bootstrap>", line 222, in _call_with_frames_removed File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/env.py", line 70, in <module> run_migrations_online() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/env.py", line 65, in run_migrations_online context.run_migrations() File "<string>", line 8, in run_migrations File "/usr/local/lib/python3.5/dist-packages/alembic/runtime/environment.py", line 817, in run_migrations self.get_context().run_migrations(**kw) File "/usr/local/lib/python3.5/dist-packages/alembic/runtime/migration.py", line 323, in run_migrations step.migration_fn(**kw) File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/versions/eeb276e51423_auth_state.py", line 21, in upgrade op.add_column('users', sa.Column('auth_state', JSONDict)) File "<string>", line 8, in add_column File "<string>", line 3, in add_column File "/usr/local/lib/python3.5/dist-packages/alembic/operations/ops.py", line 1551, in add_column return operations.invoke(op) File "/usr/local/lib/python3.5/dist-packages/alembic/operations/base.py", line 318, in invoke return fn(self, operation) File "/usr/local/lib/python3.5/dist-packages/alembic/operations/toimpl.py", line 123, in add_column schema=schema File "/usr/local/lib/python3.5/dist-packages/alembic/ddl/impl.py", line 172, in add_column self._exec(base.AddColumn(table_name, column, schema=schema)) File "/usr/local/lib/python3.5/dist-packages/alembic/ddl/impl.py", line 118, in _exec return conn.execute(construct, *multiparams, **params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/sql/ddl.py", line 68, in _execute_on_connection return connection._execute_ddl(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1002, in _execute_ddl compiled File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1189, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1182, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/default.py", line 470, in do_execute cursor.execute(statement, parameters) sqlalchemy.exc.OperationalError: (sqlite3.OperationalError) duplicate column name: auth_state [SQL: 'ALTER TABLE users ADD COLUMN auth_state TEXT'] [E 2017-06-02 19:55:16.017 JupyterHub app:1527] Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1525, in launch_instance_async yield self.start() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1436, in start self.subapp.start() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 185, in start dbutil.upgrade(hub.db_url) File "/usr/local/lib/python3.5/dist-packages/jupyterhub/dbutil.py", line 80, in upgrade ['alembic', '-c', alembic_ini, 'upgrade', revision] File "/usr/lib/python3.5/subprocess.py", line 581, in check_call raise CalledProcessError(retcode, cmd) subprocess.CalledProcessError: Command '['alembic', '-c', '/tmp/tmpkqvnuq0a/alembic.ini', 'upgrade', 'head']' returned non-zero exit status 1
sqlite3.OperationalError
def init_db(self): """Create the database connection""" self.log.debug("Connecting to db: %s", self.db_url) try: self.session_factory = orm.new_session_factory( self.db_url, reset=self.reset_db, echo=self.debug_db, **self.db_kwargs ) # trigger constructing thread local db property self.db = scoped_session(self.session_factory)() except OperationalError as e: self.log.error("Failed to connect to db: %s", self.db_url) self.log.debug("Database error was:", exc_info=True) if self.db_url.startswith("sqlite:///"): self._check_db_path(self.db_url.split(":///", 1)[1]) self.log.critical( "\n".join( [ "If you recently upgraded JupyterHub, try running", " jupyterhub upgrade-db", "to upgrade your JupyterHub database schema", ] ) ) self.exit(1) except orm.DatabaseSchemaMismatch as e: self.exit(e)
def init_db(self): """Create the database connection""" self.log.debug("Connecting to db: %s", self.db_url) try: self.session_factory = orm.new_session_factory( self.db_url, reset=self.reset_db, echo=self.debug_db, **self.db_kwargs ) # trigger constructing thread local db property self.db = scoped_session(self.session_factory)() except OperationalError as e: self.log.error("Failed to connect to db: %s", self.db_url) self.log.debug("Database error was:", exc_info=True) if self.db_url.startswith("sqlite:///"): self._check_db_path(self.db_url.split(":///", 1)[1]) self.log.critical( "\n".join( [ "If you recently upgraded JupyterHub, try running", " jupyterhub upgrade-db", "to upgrade your JupyterHub database schema", ] ) ) self.exit(1)
https://github.com/jupyterhub/jupyterhub/issues/1162
$ jupyterhub ... $ jupyterhub upgrade-db INFO [alembic.runtime.migration] Context impl SQLiteImpl. INFO [alembic.runtime.migration] Will assume non-transactional DDL. INFO [alembic.runtime.migration] Running upgrade -> 19c0846f6344, base revision for 0.5 INFO [alembic.runtime.migration] Running upgrade 19c0846f6344 -> eeb276e51423, auth_state Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1182, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/default.py", line 470, in do_execute cursor.execute(statement, parameters) sqlite3.OperationalError: duplicate column name: auth_state The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/usr/local/bin/alembic", line 11, in <module> sys.exit(main()) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 479, in main CommandLine(prog=prog).main(argv=argv) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 473, in main self.run_cmd(cfg, options) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 456, in run_cmd **dict((k, getattr(options, k, None)) for k in kwarg) File "/usr/local/lib/python3.5/dist-packages/alembic/command.py", line 254, in upgrade script.run_env() File "/usr/local/lib/python3.5/dist-packages/alembic/script/base.py", line 416, in run_env util.load_python_file(self.dir, 'env.py') File "/usr/local/lib/python3.5/dist-packages/alembic/util/pyfiles.py", line 93, in load_python_file module = load_module_py(module_id, path) File "/usr/local/lib/python3.5/dist-packages/alembic/util/compat.py", line 64, in load_module_py module_id, path).load_module(module_id) File "<frozen importlib._bootstrap_external>", line 388, in _check_name_wrapper File "<frozen importlib._bootstrap_external>", line 809, in load_module File "<frozen importlib._bootstrap_external>", line 668, in load_module File "<frozen importlib._bootstrap>", line 268, in _load_module_shim File "<frozen importlib._bootstrap>", line 693, in _load File "<frozen importlib._bootstrap>", line 673, in _load_unlocked File "<frozen importlib._bootstrap_external>", line 665, in exec_module File "<frozen importlib._bootstrap>", line 222, in _call_with_frames_removed File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/env.py", line 70, in <module> run_migrations_online() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/env.py", line 65, in run_migrations_online context.run_migrations() File "<string>", line 8, in run_migrations File "/usr/local/lib/python3.5/dist-packages/alembic/runtime/environment.py", line 817, in run_migrations self.get_context().run_migrations(**kw) File "/usr/local/lib/python3.5/dist-packages/alembic/runtime/migration.py", line 323, in run_migrations step.migration_fn(**kw) File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/versions/eeb276e51423_auth_state.py", line 21, in upgrade op.add_column('users', sa.Column('auth_state', JSONDict)) File "<string>", line 8, in add_column File "<string>", line 3, in add_column File "/usr/local/lib/python3.5/dist-packages/alembic/operations/ops.py", line 1551, in add_column return operations.invoke(op) File "/usr/local/lib/python3.5/dist-packages/alembic/operations/base.py", line 318, in invoke return fn(self, operation) File "/usr/local/lib/python3.5/dist-packages/alembic/operations/toimpl.py", line 123, in add_column schema=schema File "/usr/local/lib/python3.5/dist-packages/alembic/ddl/impl.py", line 172, in add_column self._exec(base.AddColumn(table_name, column, schema=schema)) File "/usr/local/lib/python3.5/dist-packages/alembic/ddl/impl.py", line 118, in _exec return conn.execute(construct, *multiparams, **params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/sql/ddl.py", line 68, in _execute_on_connection return connection._execute_ddl(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1002, in _execute_ddl compiled File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1189, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1182, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/default.py", line 470, in do_execute cursor.execute(statement, parameters) sqlalchemy.exc.OperationalError: (sqlite3.OperationalError) duplicate column name: auth_state [SQL: 'ALTER TABLE users ADD COLUMN auth_state TEXT'] [E 2017-06-02 19:55:16.017 JupyterHub app:1527] Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1525, in launch_instance_async yield self.start() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1436, in start self.subapp.start() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 185, in start dbutil.upgrade(hub.db_url) File "/usr/local/lib/python3.5/dist-packages/jupyterhub/dbutil.py", line 80, in upgrade ['alembic', '-c', alembic_ini, 'upgrade', revision] File "/usr/lib/python3.5/subprocess.py", line 581, in check_call raise CalledProcessError(retcode, cmd) subprocess.CalledProcessError: Command '['alembic', '-c', '/tmp/tmpkqvnuq0a/alembic.ini', 'upgrade', 'head']' returned non-zero exit status 1
sqlite3.OperationalError
def new_session_factory(url="sqlite:///:memory:", reset=False, **kwargs): """Create a new session at url""" if url.startswith("sqlite"): kwargs.setdefault("connect_args", {"check_same_thread": False}) elif url.startswith("mysql"): kwargs.setdefault("pool_recycle", 60) if url.endswith(":memory:"): # If we're using an in-memory database, ensure that only one connection # is ever created. kwargs.setdefault("poolclass", StaticPool) engine = create_engine(url, **kwargs) if reset: Base.metadata.drop_all(engine) # check the db revision (will raise, pointing to `upgrade-db` if version doesn't match) check_db_revision(engine) Base.metadata.create_all(engine) session_factory = sessionmaker(bind=engine) return session_factory
def new_session_factory(url="sqlite:///:memory:", reset=False, **kwargs): """Create a new session at url""" if url.startswith("sqlite"): kwargs.setdefault("connect_args", {"check_same_thread": False}) elif url.startswith("mysql"): kwargs.setdefault("pool_recycle", 60) if url.endswith(":memory:"): # If we're using an in-memory database, ensure that only one connection # is ever created. kwargs.setdefault("poolclass", StaticPool) engine = create_engine(url, **kwargs) if reset: Base.metadata.drop_all(engine) Base.metadata.create_all(engine) session_factory = sessionmaker(bind=engine) return session_factory
https://github.com/jupyterhub/jupyterhub/issues/1162
$ jupyterhub ... $ jupyterhub upgrade-db INFO [alembic.runtime.migration] Context impl SQLiteImpl. INFO [alembic.runtime.migration] Will assume non-transactional DDL. INFO [alembic.runtime.migration] Running upgrade -> 19c0846f6344, base revision for 0.5 INFO [alembic.runtime.migration] Running upgrade 19c0846f6344 -> eeb276e51423, auth_state Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1182, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/default.py", line 470, in do_execute cursor.execute(statement, parameters) sqlite3.OperationalError: duplicate column name: auth_state The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/usr/local/bin/alembic", line 11, in <module> sys.exit(main()) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 479, in main CommandLine(prog=prog).main(argv=argv) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 473, in main self.run_cmd(cfg, options) File "/usr/local/lib/python3.5/dist-packages/alembic/config.py", line 456, in run_cmd **dict((k, getattr(options, k, None)) for k in kwarg) File "/usr/local/lib/python3.5/dist-packages/alembic/command.py", line 254, in upgrade script.run_env() File "/usr/local/lib/python3.5/dist-packages/alembic/script/base.py", line 416, in run_env util.load_python_file(self.dir, 'env.py') File "/usr/local/lib/python3.5/dist-packages/alembic/util/pyfiles.py", line 93, in load_python_file module = load_module_py(module_id, path) File "/usr/local/lib/python3.5/dist-packages/alembic/util/compat.py", line 64, in load_module_py module_id, path).load_module(module_id) File "<frozen importlib._bootstrap_external>", line 388, in _check_name_wrapper File "<frozen importlib._bootstrap_external>", line 809, in load_module File "<frozen importlib._bootstrap_external>", line 668, in load_module File "<frozen importlib._bootstrap>", line 268, in _load_module_shim File "<frozen importlib._bootstrap>", line 693, in _load File "<frozen importlib._bootstrap>", line 673, in _load_unlocked File "<frozen importlib._bootstrap_external>", line 665, in exec_module File "<frozen importlib._bootstrap>", line 222, in _call_with_frames_removed File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/env.py", line 70, in <module> run_migrations_online() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/env.py", line 65, in run_migrations_online context.run_migrations() File "<string>", line 8, in run_migrations File "/usr/local/lib/python3.5/dist-packages/alembic/runtime/environment.py", line 817, in run_migrations self.get_context().run_migrations(**kw) File "/usr/local/lib/python3.5/dist-packages/alembic/runtime/migration.py", line 323, in run_migrations step.migration_fn(**kw) File "/usr/local/lib/python3.5/dist-packages/jupyterhub/alembic/versions/eeb276e51423_auth_state.py", line 21, in upgrade op.add_column('users', sa.Column('auth_state', JSONDict)) File "<string>", line 8, in add_column File "<string>", line 3, in add_column File "/usr/local/lib/python3.5/dist-packages/alembic/operations/ops.py", line 1551, in add_column return operations.invoke(op) File "/usr/local/lib/python3.5/dist-packages/alembic/operations/base.py", line 318, in invoke return fn(self, operation) File "/usr/local/lib/python3.5/dist-packages/alembic/operations/toimpl.py", line 123, in add_column schema=schema File "/usr/local/lib/python3.5/dist-packages/alembic/ddl/impl.py", line 172, in add_column self._exec(base.AddColumn(table_name, column, schema=schema)) File "/usr/local/lib/python3.5/dist-packages/alembic/ddl/impl.py", line 118, in _exec return conn.execute(construct, *multiparams, **params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 945, in execute return meth(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/sql/ddl.py", line 68, in _execute_on_connection return connection._execute_ddl(self, multiparams, params) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1002, in _execute_ddl compiled File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1189, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1402, in _handle_dbapi_exception exc_info File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 203, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/util/compat.py", line 186, in reraise raise value.with_traceback(tb) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/base.py", line 1182, in _execute_context context) File "/usr/local/lib/python3.5/dist-packages/sqlalchemy/engine/default.py", line 470, in do_execute cursor.execute(statement, parameters) sqlalchemy.exc.OperationalError: (sqlite3.OperationalError) duplicate column name: auth_state [SQL: 'ALTER TABLE users ADD COLUMN auth_state TEXT'] [E 2017-06-02 19:55:16.017 JupyterHub app:1527] Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1525, in launch_instance_async yield self.start() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1436, in start self.subapp.start() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 185, in start dbutil.upgrade(hub.db_url) File "/usr/local/lib/python3.5/dist-packages/jupyterhub/dbutil.py", line 80, in upgrade ['alembic', '-c', alembic_ini, 'upgrade', revision] File "/usr/lib/python3.5/subprocess.py", line 581, in check_call raise CalledProcessError(retcode, cmd) subprocess.CalledProcessError: Command '['alembic', '-c', '/tmp/tmpkqvnuq0a/alembic.ini', 'upgrade', 'head']' returned non-zero exit status 1
sqlite3.OperationalError
def start(self): """Start a managed service""" if not self.managed: raise RuntimeError("Cannot start unmanaged service %s" % self) self.log.info("Starting service %r: %r", self.name, self.command) env = {} env.update(self.environment) env["JUPYTERHUB_SERVICE_NAME"] = self.name env["JUPYTERHUB_API_TOKEN"] = self.api_token env["JUPYTERHUB_API_URL"] = self.hub_api_url env["JUPYTERHUB_BASE_URL"] = self.base_url if self.url: env["JUPYTERHUB_SERVICE_URL"] = self.url env["JUPYTERHUB_SERVICE_PREFIX"] = self.server.base_url self.spawner = _ServiceSpawner( cmd=self.command, environment=env, api_token=self.api_token, cwd=self.cwd, user=_MockUser( name=self.user, service=self, server=self.orm.server, ), ) self.spawner.start() self.proc = self.spawner.proc self.spawner.add_poll_callback(self._proc_stopped) self.spawner.start_polling()
def start(self): """Start a managed service""" if not self.managed: raise RuntimeError("Cannot start unmanaged service %s" % self) self.log.info("Starting service %r: %r", self.name, self.command) env = {} env.update(self.environment) env["JUPYTERHUB_SERVICE_NAME"] = self.name env["JUPYTERHUB_API_TOKEN"] = self.api_token env["JUPYTERHUB_API_URL"] = self.hub_api_url env["JUPYTERHUB_BASE_URL"] = self.base_url env["JUPYTERHUB_SERVICE_PREFIX"] = self.server.base_url env["JUPYTERHUB_SERVICE_URL"] = self.url self.spawner = _ServiceSpawner( cmd=self.command, environment=env, api_token=self.api_token, cwd=self.cwd, user=_MockUser( name=self.user, service=self, server=self.orm.server, ), ) self.spawner.start() self.proc = self.spawner.proc self.spawner.add_poll_callback(self._proc_stopped) self.spawner.start_polling()
https://github.com/jupyterhub/jupyterhub/issues/765
[C 2016-09-20 02:28:37.026 JupyterHub app:1444] Failed to start service cull-idle Traceback (most recent call last): File "/usr/local/lib/python3.5/dist-packages/jupyterhub/app.py", line 1442, in start yield service.start() File "/usr/local/lib/python3.5/dist-packages/jupyterhub/services/service.py", line 228, in start env['JUPYTERHUB_SERVICE_PREFIX'] = self.server.base_url AttributeError: 'NoneType' object has no attribute 'base_url'
AttributeError
def get_init_detail(self, params=None, user=None): """ At the end of the initialization we return the certificate and the PKCS12 file, if the private key exists. """ response_detail = TokenClass.get_init_detail(self, params, user) params = params or {} certificate = self.get_tokeninfo("certificate") response_detail["certificate"] = certificate privatekey = self.get_tokeninfo("privatekey") # If there is a private key, we dump a PKCS12 if privatekey: response_detail["pkcs12"] = b64encode_and_unicode(self._create_pkcs12_bin()) return response_detail
def get_init_detail(self, params=None, user=None): """ At the end of the initialization we return the certificate and the PKCS12 file, if the private key exists. """ response_detail = TokenClass.get_init_detail(self, params, user) params = params or {} certificate = self.get_tokeninfo("certificate") response_detail["certificate"] = certificate privatekey = self.get_tokeninfo("privatekey") # If there is a private key, we dump a PKCS12 if privatekey: response_detail["pkcs12"] = base64.b64encode(self._create_pkcs12_bin()) return response_detail
https://github.com/privacyidea/privacyidea/issues/1799
[2019-08-19 16:06:52,849] ERROR in app: Exception on /token/init [POST] Traceback (most recent call last): File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/app.py", line 2292, in wsgi_app response = self.full_dispatch_request() File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/app.py", line 1815, in full_dispatch_request rv = self.handle_user_exception(e) File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/app.py", line 1718, in handle_user_exception reraise(exc_type, exc_value, tb) File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/_compat.py", line 35, in reraise raise value File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/app.py", line 1813, in full_dispatch_request rv = self.dispatch_request() File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/app.py", line 1799, in dispatch_request return self.view_functions[rule.endpoint](**req.view_args) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/prepolicy.py", line 129, in policy_wrapper return wrapped_function(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/prepolicy.py", line 129, in policy_wrapper return wrapped_function(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/prepolicy.py", line 129, in policy_wrapper return wrapped_function(*args, **kwds) [Previous line repeated 15 more times] File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/postpolicy.py", line 102, in policy_wrapper response = wrapped_function(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/lib/subscriptions.py", line 333, in check_subscription_wrapper f_result = func(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/lib/event.py", line 99, in event_wrapper f_result = func(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/lib/log.py", line 154, in log_wrapper return func(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/api/token.py", line 291, in init return send_result(True, details=response_details) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/utils.py", line 104, in send_result return jsonify(prepare_result(obj, rid, details)) File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/json/__init__.py", line 321, in jsonify dumps(data, indent=indent, separators=separators) + '\n', File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/json/__init__.py", line 179, in dumps rv = _json.dumps(obj, **kwargs) File "/usr/lib64/python3.7/json/__init__.py", line 238, in dumps **kw).encode(obj) File "/usr/lib64/python3.7/json/encoder.py", line 199, in encode chunks = self.iterencode(o, _one_shot=True) File "/usr/lib64/python3.7/json/encoder.py", line 257, in iterencode return _iterencode(o, 0) File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/json/__init__.py", line 81, in default return _json.JSONEncoder.default(self, o) File "/usr/lib64/python3.7/json/encoder.py", line 179, in default raise TypeError(f'Object of type {o.__class__.__name__} ' TypeError: Object of type bytes is not JSON serializable
TypeError
def get_as_dict(self): """ This returns the token data as a dictionary. It is used to display the token list at /token/list. The certificate token can add the PKCS12 file if it exists :return: The token data as dict :rtype: dict """ # first get the database values as dict token_dict = self.token.get() if "privatekey" in token_dict.get("info"): token_dict["info"]["pkcs12"] = b64encode_and_unicode(self._create_pkcs12_bin()) return token_dict
def get_as_dict(self): """ This returns the token data as a dictionary. It is used to display the token list at /token/list. The certificate token can add the PKCS12 file if it exists :return: The token data as dict :rtype: dict """ # first get the database values as dict token_dict = self.token.get() if "privatekey" in token_dict.get("info"): token_dict["info"]["pkcs12"] = base64.b64encode(self._create_pkcs12_bin()) # del(token_dict["privatekey"]) return token_dict
https://github.com/privacyidea/privacyidea/issues/1799
[2019-08-19 16:06:52,849] ERROR in app: Exception on /token/init [POST] Traceback (most recent call last): File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/app.py", line 2292, in wsgi_app response = self.full_dispatch_request() File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/app.py", line 1815, in full_dispatch_request rv = self.handle_user_exception(e) File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/app.py", line 1718, in handle_user_exception reraise(exc_type, exc_value, tb) File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/_compat.py", line 35, in reraise raise value File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/app.py", line 1813, in full_dispatch_request rv = self.dispatch_request() File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/app.py", line 1799, in dispatch_request return self.view_functions[rule.endpoint](**req.view_args) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/prepolicy.py", line 129, in policy_wrapper return wrapped_function(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/prepolicy.py", line 129, in policy_wrapper return wrapped_function(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/prepolicy.py", line 129, in policy_wrapper return wrapped_function(*args, **kwds) [Previous line repeated 15 more times] File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/postpolicy.py", line 102, in policy_wrapper response = wrapped_function(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/lib/subscriptions.py", line 333, in check_subscription_wrapper f_result = func(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/lib/event.py", line 99, in event_wrapper f_result = func(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/lib/log.py", line 154, in log_wrapper return func(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/api/token.py", line 291, in init return send_result(True, details=response_details) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/utils.py", line 104, in send_result return jsonify(prepare_result(obj, rid, details)) File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/json/__init__.py", line 321, in jsonify dumps(data, indent=indent, separators=separators) + '\n', File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/json/__init__.py", line 179, in dumps rv = _json.dumps(obj, **kwargs) File "/usr/lib64/python3.7/json/__init__.py", line 238, in dumps **kw).encode(obj) File "/usr/lib64/python3.7/json/encoder.py", line 199, in encode chunks = self.iterencode(o, _one_shot=True) File "/usr/lib64/python3.7/json/encoder.py", line 257, in iterencode return _iterencode(o, 0) File "/home/fred/privacyidea/privacyidea/venv3/lib/python3.7/site-packages/flask/json/__init__.py", line 81, in default return _json.JSONEncoder.default(self, o) File "/usr/lib64/python3.7/json/encoder.py", line 179, in default raise TypeError(f'Object of type {o.__class__.__name__} ' TypeError: Object of type bytes is not JSON serializable
TypeError
def upgrade(): try: op.create_table( "tokenowner", sa.Column("id", sa.Integer()), sa.Column("token_id", sa.Integer(), nullable=True), sa.Column("resolver", sa.Unicode(length=120), nullable=True), sa.Column("user_id", sa.Unicode(length=320), nullable=True), sa.Column("realm_id", sa.Integer(), nullable=True), sa.ForeignKeyConstraint( ["realm_id"], ["realm.id"], ), sa.ForeignKeyConstraint( ["token_id"], ["token.id"], ), sa.PrimaryKeyConstraint("id"), ) op.create_index( op.f("ix_tokenowner_resolver"), "tokenowner", ["resolver"], unique=False ) op.create_index( op.f("ix_tokenowner_user_id"), "tokenowner", ["user_id"], unique=False ) except Exception as exx: print("Can not create table 'tokenowner'. It probably already exists") print(exx) try: bind = op.get_bind() session = orm.Session(bind=bind) # For each token, that has an owner, create a tokenowner entry for token in session.query(Token).filter(Token.user_id): token_realms = ( session.query(TokenRealm).filter(TokenRealm.token_id == token.id).all() ) realm_id = None if not token_realms: sys.stderr.write( "{serial!s}, {userid!s}, {resolver!s}, " "Error while migrating token assignment. " "This token has no realm assignments!".format( serial=token.serial, userid=token.user_id, resolver=token.resolver, ) ) elif len(token_realms) == 1: realm_id = token_realms[0].realm_id elif len(token_realms) > 1: # If the resolver is only contained in one realm, we fetch the realms: reso_realms = ( session.query(ResolverRealm) .filter(ResolverRealm.resolver == token.resolver) .all() ) if not reso_realms: sys.stderr.write( "{serial!s}, {userid!s}, {resolver!s}, " "The token is assigned, but the assigned resolver is not " "contained in any realm!".format( serial=token.serial, userid=token.user_id, resolver=token.resolver, ) ) elif len(reso_realms) == 1: # The resolver is only in one realm, so this is the new realm of the token! realm_id = reso_realms[0].realm_id elif len(reso_realms) > 1: # The resolver is contained in two realms, we have to apply more logic between the realms in which # the resolver is contained and the realms, to which the token is assigend. found_realm_ids = [] for token_realm in token_realms: if token_realm.realm_id in [r.realm_id for r in reso_realms]: # The token realm, that also fits the resolver_realm is used as owner realm found_realm_ids.append(realm_id) if len(found_realm_ids) > 1: sys.stderr.write( "{serial!s}, {userid!s}, {resolver!s}, " "Your realm configuration for the token is not distinct!. " "The tokenowner could be in multiple realms! " "The token is assigned to the following realms and the resolver is also " "contained in these realm IDs: {realms!s}.".format( serial=token.serial, userid=token.user_id, resolver=token.resolver, realms=found_realm_ids, ) ) elif len(found_realm_ids) == 1: realm_id = found_realm_ids[0] else: sys.stderr.write( "{serial!s}, {userid!s}, {resolver!s}, " "Can not assign token. The resolver is not contained in any " "realms, to which the token is assigned!" ) to = TokenOwner( token_id=token.id, user_id=token.user_id, resolver=token.resolver, realm_id=realm_id, ) session.add(to) session.commit() # Now we drop the columns op.drop_column("token", "user_id") op.drop_column("token", "resolver") op.drop_column("token", "resolver_type") except Exception as exx: session.rollback() print("Failed to migrate token assignment data!") print(exx)
def upgrade(): try: op.create_table( "tokenowner", sa.Column("id", sa.Integer()), sa.Column("token_id", sa.Integer(), nullable=True), sa.Column("resolver", sa.Unicode(length=120), nullable=True), sa.Column("user_id", sa.Unicode(length=320), nullable=True), sa.Column("realm_id", sa.Integer(), nullable=True), sa.ForeignKeyConstraint( ["realm_id"], ["realm.id"], ), sa.ForeignKeyConstraint( ["token_id"], ["token.id"], ), sa.PrimaryKeyConstraint("id"), ) op.create_index( op.f("ix_tokenowner_resolver"), "tokenowner", ["resolver"], unique=False ) op.create_index( op.f("ix_tokenowner_user_id"), "tokenowner", ["user_id"], unique=False ) except Exception as exx: print("Can not create table 'tokenowner'. It probably already exists") print(exx) try: bind = op.get_bind() session = orm.Session(bind=bind) # For each token, that has an owner, create a tokenowner entry for token in session.query(Token).filter(Token.user_id): token_realms = TokenRealm.query.filter( TokenRealm.token_id == token.id ).all() realm_id = None if not token_realms: sys.stderr.write( "{serial!s}, {userid!s}, {resolver!s}, " "Error while migrating token assignment. " "This token has no realm assignments!".format( serial=token.serial, userid=token.user_id, resolver=token.resolver, ) ) elif len(token_realms) == 1: realm_id = token_realms[0].realm_id elif len(token_realms) > 1: # If the resolver is only contained in one realm, we fetch the realms: reso_realms = ResolverRealm.query.filter( ResolverRealm.resolver == token.resolver ).all() if not reso_realms: sys.stderr.write( "{serial!s}, {userid!s}, {resolver!s}, " "The token is assigned, but the assigned resolver is not " "contained in any realm!".format( serial=token.serial, userid=token.user_id, resolver=token.resolver, ) ) elif len(reso_realms) == 1: # The resolver is only in one realm, so this is the new realm of the token! realm_id = reso_realms[0].realm_id elif len(reso_realms) > 1: # The resolver is contained in two realms, we have to apply more logic between the realms in which # the resolver is contained and the realms, to which the token is assigend. found_realm_ids = [] for token_realm in token_realms: if token_realm.realm_id in [r.realm_id for r in reso_realms]: # The token realm, that also fits the resolver_realm is used as owner realm found_realm_ids.append(realm_id) if len(found_realm_ids) > 1: sys.stderr.write( "{serial!s}, {userid!s}, {resolver!s}, " "Your realm configuration for the token is not distinct!. " "The tokenowner could be in multiple realms! " "The token is assigned to the following realms and the resolver is also " "contained in these realm IDs: {realms!s}.".format( serial=token.serial, userid=token.user_id, resolver=token.resolver, realms=found_realm_ids, ) ) elif len(found_realm_ids) == 1: realm_id = found_realm_ids[0] else: sys.stderr.write( "{serial!s}, {userid!s}, {resolver!s}, " "Can not assign token. The resolver is not contained in any " "realms, to which the token is assigned!" ) to = TokenOwner( token_id=token.id, user_id=token.user_id, resolver=token.resolver, realm_id=realm_id, ) session.add(to) session.commit() # Now we drop the columns op.drop_column("token", "user_id") op.drop_column("token", "resolver") op.drop_column("token", "resolver_type") except Exception as exx: session.rollback() print("Failed to migrate token assignment data!") print(exx)
https://github.com/privacyidea/privacyidea/issues/1461
ERROR [sqlalchemy.pool.QueuePool] Exception during reset or similar Traceback (most recent call last): File "/opt/venv/lib/python2.7/site-packages/sqlalchemy/pool.py", line 742, in _finalize_fairy fairy._reset(pool) File "/opt/venv/lib/python2.7/site-packages/sqlalchemy/pool.py", line 927, in _reset self._reset_agent.rollback() File "/opt/venv/lib/python2.7/site-packages/sqlalchemy/engine/base.py", line 1697, in rollback self._do_rollback() File "/opt/venv/lib/python2.7/site-packages/sqlalchemy/engine/base.py", line 1735, in _do_rollback self.connection._rollback_impl() File "/opt/venv/lib/python2.7/site-packages/sqlalchemy/engine/base.py", line 733, in _rollback_impl self._handle_dbapi_exception(e, None, None, None, None) File "/opt/venv/lib/python2.7/site-packages/sqlalchemy/engine/base.py", line 1458, in _handle_dbapi_exception util.raise_from_cause(sqlalchemy_exception, exc_info) File "/opt/venv/lib/python2.7/site-packages/sqlalchemy/util/compat.py", line 296, in raise_from_cause reraise(type(exception), exception, tb=exc_tb, cause=cause) File "/opt/venv/lib/python2.7/site-packages/sqlalchemy/engine/base.py", line 731, in _rollback_impl self.engine.dialect.do_rollback(self.connection) File "/opt/venv/lib/python2.7/site-packages/sqlalchemy/dialects/mysql/base.py", line 2148, in do_rollback dbapi_connection.rollback() File "/opt/venv/lib/python2.7/site-packages/pymysql/connections.py", line 809, in rollback self._read_ok_packet() File "/opt/venv/lib/python2.7/site-packages/pymysql/connections.py", line 773, in _read_ok_packet pkt = self._read_packet() File "/opt/venv/lib/python2.7/site-packages/pymysql/connections.py", line 1032, in _read_packet packet_header = self._read_bytes(4) File "/opt/venv/lib/python2.7/site-packages/pymysql/connections.py", line 1078, in _read_bytes CR.CR_SERVER_LOST, "Lost connection to MySQL server during query") OperationalError: (pymysql.err.OperationalError) (2013, 'Lost connection to MySQL server during query') (Background on this error at: http://sqlalche.me/e/e3q8)
OperationalError
def reload_from_db(self): """ Read the timestamp from the database. If the timestamp is newer than the internal timestamp, then read the complete data :return: """ if ( not self.timestamp or self.timestamp + datetime.timedelta( seconds=current_app.config.get("PI_CHECK_RELOAD_CONFIG", 0) ) < datetime.datetime.now() ): db_ts = Config.query.filter_by(Key=PRIVACYIDEA_TIMESTAMP).first() if reload_db(self.timestamp, db_ts): self.config = {} self.resolver = {} self.realm = {} self.default_realm = None for sysconf in Config.query.all(): self.config[sysconf.Key] = { "Value": sysconf.Value, "Type": sysconf.Type, "Description": sysconf.Description, } for resolver in Resolver.query.all(): resolverdef = {"type": resolver.rtype, "resolvername": resolver.name} data = {} for rconf in resolver.config_list: if rconf.Type == "password": value = decryptPassword(rconf.Value, convert_unicode=True) else: value = rconf.Value data[rconf.Key] = value resolverdef["data"] = data self.resolver[resolver.name] = resolverdef for realm in Realm.query.all(): if realm.default: self.default_realm = realm.name realmdef = { "option": realm.option, "default": realm.default, "resolver": [], } for x in realm.resolver_list: realmdef["resolver"].append( { "priority": x.priority, "name": x.resolver.name, "type": x.resolver.rtype, } ) self.realm[realm.name] = realmdef self.timestamp = datetime.datetime.now()
def reload_from_db(self): """ Read the timestamp from the database. If the timestamp is newer than the internal timestamp, then read the complete data :return: """ if ( not self.timestamp or self.timestamp + datetime.timedelta( seconds=current_app.config.get("PI_CHECK_RELOAD_CONFIG", 0) ) < datetime.datetime.now() ): db_ts = Config.query.filter_by(Key=PRIVACYIDEA_TIMESTAMP).first() if reload_db(self.timestamp, db_ts): self.config = {} self.resolver = {} self.realm = {} self.default_realm = None for sysconf in Config.query.all(): self.config[sysconf.Key] = { "Value": sysconf.Value, "Type": sysconf.Type, "Description": sysconf.Description, } for resolver in Resolver.query.all(): resolverdef = {"type": resolver.rtype, "resolvername": resolver.name} data = {} for rconf in resolver.config_list: if rconf.Type == "password": value = decryptPassword(rconf.Value) else: value = rconf.Value data[rconf.Key] = value resolverdef["data"] = data self.resolver[resolver.name] = resolverdef for realm in Realm.query.all(): if realm.default: self.default_realm = realm.name realmdef = { "option": realm.option, "default": realm.default, "resolver": [], } for x in realm.resolver_list: realmdef["resolver"].append( { "priority": x.priority, "name": x.resolver.name, "type": x.resolver.rtype, } ) self.realm[realm.name] = realmdef self.timestamp = datetime.datetime.now()
https://github.com/privacyidea/privacyidea/issues/1181
[2018-08-14 14:49:53,123] ERROR in app: Exception on /system/documentation [GET] Traceback (most recent call last): File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 2292, in wsgi_app response = self.full_dispatch_request() File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1815, in full_dispatch_request rv = self.handle_user_exception(e) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1718, in handle_user_exception reraise(exc_type, exc_value, tb) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1813, in full_dispatch_request rv = self.dispatch_request() File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1799, in dispatch_request return self.view_functions[rule.endpoint](**req.view_args) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/prepolicy.py", line 120, in policy_wrapper return wrapped_function(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/api/auth.py", line 316, in decorated_function return f(*args, **kwargs) File "/home/fred/privacyidea/privacyidea/privacyidea/api/system.py", line 113, in get_config_documentation context=context)) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/templating.py", line 135, in render_template context, ctx.app) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/templating.py", line 117, in _render rv = template.render(context) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/jinja2/environment.py", line 1008, in render return self.environment.handle_exception(exc_info, True) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/jinja2/environment.py", line 780, in handle_exception reraise(exc_type, exc_value, tb) File "/home/fred/privacyidea/privacyidea/privacyidea/static/templates/documentation.rst", line 56, in top-level template code {{k}}: **{{v}}** UnicodeDecodeError: 'ascii' codec can't decode byte 0xc3 in position 8: ordinal not in range(128)
UnicodeDecodeError
def get_config(self, key=None, default=None, role="admin", return_bool=False): """ :param key: A key to retrieve :type key: string :param default: The default value, if it does not exist in the database :param role: The role which wants to retrieve the system config. Can be "admin" or "public". If "public", only values with type="public" are returned. :type role: string :param return_bool: If the a boolean value should be returned. Returns True if value is "True", "true", 1, "1", True... :return: If key is None, then a dictionary is returned. If a certain key is given a string/bool is returned. """ default_true_keys = [ SYSCONF.PREPENDPIN, SYSCONF.SPLITATSIGN, SYSCONF.INCFAILCOUNTER, SYSCONF.RETURNSAML, ] r_config = {} # reduce the dictionary to only public keys! reduced_config = {} for ckey, cvalue in self.config.iteritems(): if role == "admin" or cvalue.get("Type") == "public": reduced_config[ckey] = self.config[ckey] if not reduced_config and role == "admin": reduced_config = self.config for ckey, cvalue in reduced_config.iteritems(): if cvalue.get("Type") == "password": # decrypt the password r_config[ckey] = decryptPassword(cvalue.get("Value"), convert_unicode=True) else: r_config[ckey] = cvalue.get("Value") for t_key in default_true_keys: if t_key not in r_config: r_config[t_key] = "True" if key: # We only return a single key r_config = r_config.get(key, default) if return_bool: if isinstance(r_config, bool): pass if isinstance(r_config, int): r_config = r_config > 0 if isinstance(r_config, basestring): r_config = is_true(r_config.lower()) return r_config
def get_config(self, key=None, default=None, role="admin", return_bool=False): """ :param key: A key to retrieve :type key: string :param default: The default value, if it does not exist in the database :param role: The role which wants to retrieve the system config. Can be "admin" or "public". If "public", only values with type="public" are returned. :type role: string :param return_bool: If the a boolean value should be returned. Returns True if value is "True", "true", 1, "1", True... :return: If key is None, then a dictionary is returned. If a certain key is given a string/bool is returned. """ default_true_keys = [ SYSCONF.PREPENDPIN, SYSCONF.SPLITATSIGN, SYSCONF.INCFAILCOUNTER, SYSCONF.RETURNSAML, ] r_config = {} # reduce the dictionary to only public keys! reduced_config = {} for ckey, cvalue in self.config.iteritems(): if role == "admin" or cvalue.get("Type") == "public": reduced_config[ckey] = self.config[ckey] if not reduced_config and role == "admin": reduced_config = self.config for ckey, cvalue in reduced_config.iteritems(): if cvalue.get("Type") == "password": # decrypt the password r_config[ckey] = decryptPassword(cvalue.get("Value")) else: r_config[ckey] = cvalue.get("Value") for t_key in default_true_keys: if t_key not in r_config: r_config[t_key] = "True" if key: # We only return a single key r_config = r_config.get(key, default) if return_bool: if isinstance(r_config, bool): pass if isinstance(r_config, int): r_config = r_config > 0 if isinstance(r_config, basestring): r_config = is_true(r_config.lower()) return r_config
https://github.com/privacyidea/privacyidea/issues/1181
[2018-08-14 14:49:53,123] ERROR in app: Exception on /system/documentation [GET] Traceback (most recent call last): File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 2292, in wsgi_app response = self.full_dispatch_request() File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1815, in full_dispatch_request rv = self.handle_user_exception(e) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1718, in handle_user_exception reraise(exc_type, exc_value, tb) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1813, in full_dispatch_request rv = self.dispatch_request() File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1799, in dispatch_request return self.view_functions[rule.endpoint](**req.view_args) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/prepolicy.py", line 120, in policy_wrapper return wrapped_function(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/api/auth.py", line 316, in decorated_function return f(*args, **kwargs) File "/home/fred/privacyidea/privacyidea/privacyidea/api/system.py", line 113, in get_config_documentation context=context)) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/templating.py", line 135, in render_template context, ctx.app) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/templating.py", line 117, in _render rv = template.render(context) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/jinja2/environment.py", line 1008, in render return self.environment.handle_exception(exc_info, True) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/jinja2/environment.py", line 780, in handle_exception reraise(exc_type, exc_value, tb) File "/home/fred/privacyidea/privacyidea/privacyidea/static/templates/documentation.rst", line 56, in top-level template code {{k}}: **{{v}}** UnicodeDecodeError: 'ascii' codec can't decode byte 0xc3 in position 8: ordinal not in range(128)
UnicodeDecodeError
def decryptPassword(cryptPass, convert_unicode=False): """ Decrypt the encrypted password ``cryptPass`` and return it. If an error occurs during decryption, return FAILED_TO_DECRYPT_PASSWORD. :param cryptPass: bytestring :param convert_unicode: If true, interpret the decrypted password as an UTF-8 string and convert it to unicode. If an error occurs here, the original bytestring is returned. """ # NOTE: Why do we have the ``convert_unicode`` parameter? # Up until now, this always returned bytestrings. However, this breaks # LDAP and SQL resolvers, which expect this to return an unicode string # (and this makes more sense, because ``encryptPassword`` also # takes unicode strings!). But always returning unicode might break # other call sites of ``decryptPassword``. So we add the # keyword argument to avoid breaking compatibility. from privacyidea.lib.utils import to_unicode hsm = _get_hsm() try: ret = hsm.decrypt_password(cryptPass) except Exception as exx: # pragma: no cover log.warning(exx) ret = FAILED_TO_DECRYPT_PASSWORD try: if convert_unicode: ret = to_unicode(ret) except Exception as exx: # pragma: no cover log.warning(exx) # just keep ``ret`` as a bytestring in that case return ret
def decryptPassword(cryptPass): hsm = _get_hsm() try: ret = hsm.decrypt_password(cryptPass) except Exception as exx: # pragma: no cover log.warning(exx) ret = FAILED_TO_DECRYPT_PASSWORD return ret
https://github.com/privacyidea/privacyidea/issues/1181
[2018-08-14 14:49:53,123] ERROR in app: Exception on /system/documentation [GET] Traceback (most recent call last): File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 2292, in wsgi_app response = self.full_dispatch_request() File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1815, in full_dispatch_request rv = self.handle_user_exception(e) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1718, in handle_user_exception reraise(exc_type, exc_value, tb) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1813, in full_dispatch_request rv = self.dispatch_request() File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1799, in dispatch_request return self.view_functions[rule.endpoint](**req.view_args) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/prepolicy.py", line 120, in policy_wrapper return wrapped_function(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/api/auth.py", line 316, in decorated_function return f(*args, **kwargs) File "/home/fred/privacyidea/privacyidea/privacyidea/api/system.py", line 113, in get_config_documentation context=context)) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/templating.py", line 135, in render_template context, ctx.app) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/templating.py", line 117, in _render rv = template.render(context) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/jinja2/environment.py", line 1008, in render return self.environment.handle_exception(exc_info, True) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/jinja2/environment.py", line 780, in handle_exception reraise(exc_type, exc_value, tb) File "/home/fred/privacyidea/privacyidea/privacyidea/static/templates/documentation.rst", line 56, in top-level template code {{k}}: **{{v}}** UnicodeDecodeError: 'ascii' codec can't decode byte 0xc3 in position 8: ordinal not in range(128)
UnicodeDecodeError
def _create_engine(self): log.info( "using the connect string {0!s}".format( censor_connect_string(self.connect_string) ) ) try: log.debug( "using pool_size={0!s}, pool_timeout={1!s}, pool_recycle={2!s}".format( self.pool_size, self.pool_timeout, self.pool_recycle ) ) engine = create_engine( self.connect_string, encoding=self.encoding, convert_unicode=False, pool_size=self.pool_size, pool_recycle=self.pool_recycle, pool_timeout=self.pool_timeout, ) except TypeError: # The DB Engine/Poolclass might not support the pool_size. log.debug("connecting without pool_size.") engine = create_engine( self.connect_string, encoding=self.encoding, convert_unicode=False ) return engine
def _create_engine(self): log.info( "using the connect string {0!s}".format( censor_connect_string(self.connect_string) ) ) try: log.debug( "using pool_size={0!s}, pool_timeout={1!s}, pool_recycle={2!s}".format( self.pool_size, self.pool_timeout, self.pool_recycle ) ) engine = create_engine( self.connect_string, encoding=self.encoding, convert_unicode=False, pool_size=self.pool_size, pool_recycle=self.pool_recycle, pool_timeout=self.pool_timeout, ) except TypeError: # The DB Engine/Poolclass might not support the pool_size. log.debug("connecting without pool_size.") engine = create_engine( self.connect_string, encoding=self.encoding, convert_unicode=False ) return engine
https://github.com/privacyidea/privacyidea/issues/1181
[2018-08-14 14:49:53,123] ERROR in app: Exception on /system/documentation [GET] Traceback (most recent call last): File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 2292, in wsgi_app response = self.full_dispatch_request() File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1815, in full_dispatch_request rv = self.handle_user_exception(e) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1718, in handle_user_exception reraise(exc_type, exc_value, tb) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1813, in full_dispatch_request rv = self.dispatch_request() File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1799, in dispatch_request return self.view_functions[rule.endpoint](**req.view_args) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/prepolicy.py", line 120, in policy_wrapper return wrapped_function(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/api/auth.py", line 316, in decorated_function return f(*args, **kwargs) File "/home/fred/privacyidea/privacyidea/privacyidea/api/system.py", line 113, in get_config_documentation context=context)) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/templating.py", line 135, in render_template context, ctx.app) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/templating.py", line 117, in _render rv = template.render(context) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/jinja2/environment.py", line 1008, in render return self.environment.handle_exception(exc_info, True) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/jinja2/environment.py", line 780, in handle_exception reraise(exc_type, exc_value, tb) File "/home/fred/privacyidea/privacyidea/privacyidea/static/templates/documentation.rst", line 56, in top-level template code {{k}}: **{{v}}** UnicodeDecodeError: 'ascii' codec can't decode byte 0xc3 in position 8: ordinal not in range(128)
UnicodeDecodeError
def _create_connect_string(param): """ create the connectstring Port, Password, conParams, Driver, User, Server, Database """ port = "" password = "" conParams = "" if param.get("Port"): port = ":{0!s}".format(param.get("Port")) if param.get("Password"): password = ":{0!s}".format(param.get("Password")) if param.get("conParams"): conParams = "?{0!s}".format(param.get("conParams")) connect_string = "{0!s}://{1!s}{2!s}{3!s}{4!s}{5!s}/{6!s}{7!s}".format( param.get("Driver", ""), param.get("User", ""), password, "@" if (param.get("User") or password) else "", param.get("Server", ""), port, param.get("Database", ""), conParams, ) # SQLAlchemy does not like a unicode connect string! if param.get("Driver").lower() == "sqlite": connect_string = str(connect_string) return connect_string
def _create_connect_string(param): """ create the connectstring Port, Password, conParams, Driver, User, Server, Database """ port = "" password = "" conParams = "" if param.get("Port"): port = ":{0!s}".format(param.get("Port")) if param.get("Password"): password = ":{0!s}".format(param.get("Password")) if param.get("conParams"): conParams = "?{0!s}".format(param.get("conParams")) connect_string = "{0!s}://{1!s}{2!s}{3!s}{4!s}{5!s}/{6!s}{7!s}".format( param.get("Driver", ""), param.get("User", ""), password, "@" if (param.get("User") or password) else "", param.get("Server", ""), port, param.get("Database", ""), conParams, ) # SQLAlchemy does not like a unicode connect string! if param.get("Driver").lower() == "sqlite": connect_string = str(connect_string) return connect_string
https://github.com/privacyidea/privacyidea/issues/1181
[2018-08-14 14:49:53,123] ERROR in app: Exception on /system/documentation [GET] Traceback (most recent call last): File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 2292, in wsgi_app response = self.full_dispatch_request() File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1815, in full_dispatch_request rv = self.handle_user_exception(e) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1718, in handle_user_exception reraise(exc_type, exc_value, tb) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1813, in full_dispatch_request rv = self.dispatch_request() File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/app.py", line 1799, in dispatch_request return self.view_functions[rule.endpoint](**req.view_args) File "/home/fred/privacyidea/privacyidea/privacyidea/api/lib/prepolicy.py", line 120, in policy_wrapper return wrapped_function(*args, **kwds) File "/home/fred/privacyidea/privacyidea/privacyidea/api/auth.py", line 316, in decorated_function return f(*args, **kwargs) File "/home/fred/privacyidea/privacyidea/privacyidea/api/system.py", line 113, in get_config_documentation context=context)) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/templating.py", line 135, in render_template context, ctx.app) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/flask/templating.py", line 117, in _render rv = template.render(context) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/jinja2/environment.py", line 1008, in render return self.environment.handle_exception(exc_info, True) File "/home/fred/privacyidea/privacyidea/venv/lib/python2.7/site-packages/jinja2/environment.py", line 780, in handle_exception reraise(exc_type, exc_value, tb) File "/home/fred/privacyidea/privacyidea/privacyidea/static/templates/documentation.rst", line 56, in top-level template code {{k}}: **{{v}}** UnicodeDecodeError: 'ascii' codec can't decode byte 0xc3 in position 8: ordinal not in range(128)
UnicodeDecodeError
def getUserInfo(self, userId): """ This function returns all user info for a given userid/object. :param userId: The userid of the object :type userId: string :return: A dictionary with the keys defined in self.userinfo :rtype: dict """ ret = {} self._bind() if self.uidtype.lower() == "dn": # encode utf8, so that also german ulauts work in the DN self.l.search( search_base=to_utf8(userId), search_scope=self.scope, search_filter="(&" + self.searchfilter + ")", attributes=self.userinfo.values(), ) else: if self.uidtype == "objectGUID": userId = uuid.UUID("{%s}" % userId).bytes_le userId = escape_bytes(userId) filter = "(&%s(%s=%s))" % (self.searchfilter, self.uidtype, userId) self.l.search( search_base=self.basedn, search_scope=self.scope, search_filter=filter, attributes=self.userinfo.values(), ) r = self.l.response r = self._trim_result(r) if len(r) > 1: # pragma: no cover raise Exception("Found more than one object for uid %r" % userId) for entry in r: attributes = entry.get("attributes") ret = self._ldap_attributes_to_user_object(attributes) return ret
def getUserInfo(self, userId): """ This function returns all user info for a given userid/object. :param userId: The userid of the object :type userId: string :return: A dictionary with the keys defined in self.userinfo :rtype: dict """ ret = {} self._bind() if self.uidtype.lower() == "dn": # encode utf8, so that also german ulauts work in the DN self.l.search( search_base=to_utf8(userId), search_scope=self.scope, search_filter="(&" + self.searchfilter + ")", attributes=self.userinfo.values(), ) else: filter = "(&%s(%s=%s))" % (self.searchfilter, self.uidtype, userId) self.l.search( search_base=self.basedn, search_scope=self.scope, search_filter=filter, attributes=self.userinfo.values(), ) r = self.l.response r = self._trim_result(r) if len(r) > 1: # pragma: no cover raise Exception("Found more than one object for uid %r" % userId) for entry in r: attributes = entry.get("attributes") ret = self._ldap_attributes_to_user_object(attributes) return ret
https://github.com/privacyidea/privacyidea/issues/385
Found this userlist: [...list of users...] Found this userlist: [...list of users...] Exiting get_user_list with result [...list of users...] Exiting get_user_list with result [...list of users...] Exception on /user/ [GET] Traceback (most recent call last): File "/usr/lib/python2.7/dist-packages/flask/app.py", line 1817, in wsgi_app response = self.full_dispatch_request() File "/usr/lib/python2.7/dist-packages/flask/app.py", line 1477, in full_dispatch_request rv = self.handle_user_exception(e) File "/usr/lib/python2.7/dist-packages/flask/app.py", line 1381, in handle_user_exception reraise(exc_type, exc_value, tb) File "/usr/lib/python2.7/dist-packages/flask/app.py", line 1475, in full_dispatch_request rv = self.dispatch_request() File "/usr/lib/python2.7/dist-packages/flask/app.py", line 1461, in dispatch_request return self.view_functions[rule.endpoint](**req.view_args) File "/usr/lib/python2.7/dist-packages/privacyidea/api/lib/prepolicy.py", line 96, in policy_wrapper return wrapped_function(*args, **kwds) File "/usr/lib/python2.7/dist-packages/privacyidea/api/auth.py", line 302, in decorated_function return f(*args, **kwargs) File "/usr/lib/python2.7/dist-packages/privacyidea/api/user.py", line 104, in get_users return send_result(users) File "/usr/lib/python2.7/dist-packages/privacyidea/api/lib/utils.py", line 122, in send_result return jsonify(res) File "/usr/lib/python2.7/dist-packages/flask/json.py", line 238, in jsonify indent=indent), File "/usr/lib/python2.7/dist-packages/flask/json.py", line 126, in dumps rv = _json.dumps(obj, **kwargs) File "/usr/lib/python2.7/dist-packages/simplejson/__init__.py", line 369, in dumps **kw).encode(obj) File "/usr/lib/python2.7/dist-packages/simplejson/encoder.py", line 264, in encode chunks = list(chunks) File "/usr/lib/python2.7/dist-packages/simplejson/encoder.py", line 612, in _iterencode for chunk in _iterencode_dict(o, _current_indent_level): File "/usr/lib/python2.7/dist-packages/simplejson/encoder.py", line 568, in _iterencode_dict for chunk in chunks: File "/usr/lib/python2.7/dist-packages/simplejson/encoder.py", line 568, in _iterencode_dict for chunk in chunks: File "/usr/lib/python2.7/dist-packages/simplejson/encoder.py", line 455, in _iterencode_list for chunk in chunks: File "/usr/lib/python2.7/dist-packages/simplejson/encoder.py", line 535, in _iterencode_dict yield _encoder(value) UnicodeDecodeError: 'utf8' codec can't decode byte 0xd6 in position 0: invalid continuation byte Exception on /user/ [GET] Traceback (most recent call last): File "/usr/lib/python2.7/dist-packages/flask/app.py", line 1817, in wsgi_app response = self.full_dispatch_request() File "/usr/lib/python2.7/dist-packages/flask/app.py", line 1477, in full_dispatch_request rv = self.handle_user_exception(e) File "/usr/lib/python2.7/dist-packages/flask/app.py", line 1381, in handle_user_exception reraise(exc_type, exc_value, tb) File "/usr/lib/python2.7/dist-packages/flask/app.py", line 1475, in full_dispatch_request rv = self.dispatch_request() File "/usr/lib/python2.7/dist-packages/flask/app.py", line 1461, in dispatch_request return self.view_functions[rule.endpoint](**req.view_args) File "/usr/lib/python2.7/dist-packages/privacyidea/api/lib/prepolicy.py", line 96, in policy_wrapper return wrapped_function(*args, **kwds) File "/usr/lib/python2.7/dist-packages/privacyidea/api/auth.py", line 302, in decorated_function return f(*args, **kwargs) File "/usr/lib/python2.7/dist-packages/privacyidea/api/user.py", line 104, in get_users return send_result(users) File "/usr/lib/python2.7/dist-packages/privacyidea/api/lib/utils.py", line 122, in send_result return jsonify(res) File "/usr/lib/python2.7/dist-packages/flask/json.py", line 238, in jsonify indent=indent), File "/usr/lib/python2.7/dist-packages/flask/json.py", line 126, in dumps rv = _json.dumps(obj, **kwargs) File "/usr/lib/python2.7/dist-packages/simplejson/__init__.py", line 369, in dumps **kw).encode(obj) File "/usr/lib/python2.7/dist-packages/simplejson/encoder.py", line 264, in encode chunks = list(chunks) File "/usr/lib/python2.7/dist-packages/simplejson/encoder.py", line 612, in _iterencode for chunk in _iterencode_dict(o, _current_indent_level): File "/usr/lib/python2.7/dist-packages/simplejson/encoder.py", line 568, in _iterencode_dict for chunk in chunks: File "/usr/lib/python2.7/dist-packages/simplejson/encoder.py", line 568, in _iterencode_dict for chunk in chunks: File "/usr/lib/python2.7/dist-packages/simplejson/encoder.py", line 455, in _iterencode_list for chunk in chunks: File "/usr/lib/python2.7/dist-packages/simplejson/encoder.py", line 535, in _iterencode_dict yield _encoder(value) UnicodeDecodeError: 'utf8' codec can't decode byte 0xd6 in position 0: invalid continuation byte Can not get param: No JSON object could be decoded Can not get param: No JSON object could be decoded
UnicodeDecodeError
def decryptPassword(cryptPass): hsm = _get_hsm() try: ret = hsm.decrypt_password(cryptPass) except Exception as exx: # pragma: no cover log.warning(exx) ret = FAILED_TO_DECRYPT_PASSWORD return ret
def decryptPassword(cryptPass): hsm = _get_hsm() try: ret = hsm.decrypt_password(cryptPass) except Exception as exx: # pragma: no cover log.warning(exx) ret = "FAILED TO DECRYPT PASSWORD!" return ret
https://github.com/privacyidea/privacyidea/issues/350
SMTPAuthenticationError: (535, '5.7.8 Error: authentication failed:') [2016-03-28 19:55:39,479][30338][140453494273792][WARNING][privacyidea.lib.crypto:326] 'NoneType' object has no attribute 'find' [2016-03-28 19:55:41,528][30338][140453494273792][ERROR][privacyidea.app:1423] Exception on /smtpserver/send_test_email [POST] Traceback (most recent call last): File "/opt/privacyidea/venv/local/lib/python2.7/site-packages/flask/app.py", line 1817, in wsgi_app response = self.full_dispatch_request() File "/opt/privacyidea/venv/local/lib/python2.7/site-packages/flask/app.py", line 1477, in full_dispatch_request rv = self.handle_user_exception(e) File "/opt/privacyidea/venv/local/lib/python2.7/site-packages/flask/app.py", line 1381, in handle_user_exception reraise(exc_type, exc_value, tb) File "/opt/privacyidea/venv/local/lib/python2.7/site-packages/flask/app.py", line 1475, in full_dispatch_request rv = self.dispatch_request() File "/opt/privacyidea/venv/local/lib/python2.7/site-packages/flask/app.py", line 1461, in dispatch_request return self.view_functions[rule.endpoint](**req.view_args) File "/opt/privacyidea/privacyidea/api/lib/prepolicy.py", line 96, in policy_wrapper return wrapped_function(*args, **kwds) File "/opt/privacyidea/privacyidea/lib/log.py", line 125, in log_wrapper f_result = func(*args, **kwds) File "/opt/privacyidea/privacyidea/api/smtpserver.py", line 146, in test "The configuration %s is working." % identifier) File "/opt/privacyidea/privacyidea/lib/smtpserver.py", line 93, in test_email mail.login(config.username, password) File "/usr/lib/python2.7/smtplib.py", line 613, in login raise SMTPAuthenticationError(code, resp)
SMTPAuthenticationError
def _display_as_base(cls): """ A decorator that makes an exception class look like its base. We use this to hide subclasses that are implementation details - the user should catch the base type, which is what the traceback will show them. Classes decorated with this decorator are subject to removal without a deprecation warning. """ assert issubclass(cls, Exception) cls.__name__ = cls.__base__.__name__ return cls
def _display_as_base(cls): """ A decorator that makes an exception class look like its base. We use this to hide subclasses that are implementation details - the user should catch the base type, which is what the traceback will show them. Classes decorated with this decorator are subject to removal without a deprecation warning. """ assert issubclass(cls, Exception) cls.__name__ = cls.__base__.__name__ cls.__qualname__ = cls.__base__.__qualname__ set_module(cls.__base__.__module__)(cls) return cls
https://github.com/numpy/numpy/issues/16490
Traceback (most recent call last): File "ufunctypeerror.py", line 6, in <module> numpy.ones(1) * "foo" numpy.core._exceptions.UFuncTypeError: ufunc 'multiply' did not contain a loop with signature matching types (dtype('<U32'), dtype('<U32')) -> dtype('<U32') During handling of the above exception, another exception occurred: Traceback (most recent call last): File "ufunctypeerror.py", line 8, in <module> pickle.dumps(e) _pickle.PicklingError: Can't pickle <class 'numpy.core._exceptions.UFuncTypeError'>: it's not the same object as numpy.core._exceptions.UFuncTypeError
numpy.core._exceptions.UFuncTypeError
def _raw_fft(a, n, axis, is_real, is_forward, inv_norm): axis = normalize_axis_index(axis, a.ndim) if n is None: n = a.shape[axis] if n < 1: raise ValueError("Invalid number of FFT data points (%d) specified." % n) fct = 1 / inv_norm if a.shape[axis] != n: s = list(a.shape) if s[axis] > n: index = [slice(None)] * len(s) index[axis] = slice(0, n) a = a[tuple(index)] else: index = [slice(None)] * len(s) index[axis] = slice(0, s[axis]) s[axis] = n z = zeros(s, a.dtype.char) z[tuple(index)] = a a = z if axis == a.ndim - 1: r = pfi.execute(a, is_real, is_forward, fct) else: a = swapaxes(a, axis, -1) r = pfi.execute(a, is_real, is_forward, fct) r = swapaxes(r, axis, -1) return r
def _raw_fft(a, n, axis, is_real, is_forward, fct): axis = normalize_axis_index(axis, a.ndim) if n is None: n = a.shape[axis] if n < 1: raise ValueError("Invalid number of FFT data points (%d) specified." % n) if a.shape[axis] != n: s = list(a.shape) if s[axis] > n: index = [slice(None)] * len(s) index[axis] = slice(0, n) a = a[tuple(index)] else: index = [slice(None)] * len(s) index[axis] = slice(0, s[axis]) s[axis] = n z = zeros(s, a.dtype.char) z[tuple(index)] = a a = z if axis == a.ndim - 1: r = pfi.execute(a, is_real, is_forward, fct) else: a = swapaxes(a, axis, -1) r = pfi.execute(a, is_real, is_forward, fct) r = swapaxes(r, axis, -1) return r
https://github.com/numpy/numpy/issues/14176
Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<__array_function__ internals>", line 6, in ifft File "/home/peter/.local/lib/python3.7/site-packages/numpy/fft/pocketfft.py", line 274, in ifft fct = 1/n ZeroDivisionError: division by zero
ZeroDivisionError
def fft(a, n=None, axis=-1, norm=None): """ Compute the one-dimensional discrete Fourier Transform. This function computes the one-dimensional *n*-point discrete Fourier Transform (DFT) with the efficient Fast Fourier Transform (FFT) algorithm [CT]. Parameters ---------- a : array_like Input array, can be complex. n : int, optional Length of the transformed axis of the output. If `n` is smaller than the length of the input, the input is cropped. If it is larger, the input is padded with zeros. If `n` is not given, the length of the input along the axis specified by `axis` is used. axis : int, optional Axis over which to compute the FFT. If not given, the last axis is used. norm : {None, "ortho"}, optional .. versionadded:: 1.10.0 Normalization mode (see `numpy.fft`). Default is None. Returns ------- out : complex ndarray The truncated or zero-padded input, transformed along the axis indicated by `axis`, or the last one if `axis` is not specified. Raises ------ IndexError if `axes` is larger than the last axis of `a`. See Also -------- numpy.fft : for definition of the DFT and conventions used. ifft : The inverse of `fft`. fft2 : The two-dimensional FFT. fftn : The *n*-dimensional FFT. rfftn : The *n*-dimensional FFT of real input. fftfreq : Frequency bins for given FFT parameters. Notes ----- FFT (Fast Fourier Transform) refers to a way the discrete Fourier Transform (DFT) can be calculated efficiently, by using symmetries in the calculated terms. The symmetry is highest when `n` is a power of 2, and the transform is therefore most efficient for these sizes. The DFT is defined, with the conventions used in this implementation, in the documentation for the `numpy.fft` module. References ---------- .. [CT] Cooley, James W., and John W. Tukey, 1965, "An algorithm for the machine calculation of complex Fourier series," *Math. Comput.* 19: 297-301. Examples -------- >>> np.fft.fft(np.exp(2j * np.pi * np.arange(8) / 8)) array([-2.33486982e-16+1.14423775e-17j, 8.00000000e+00-1.25557246e-15j, 2.33486982e-16+2.33486982e-16j, 0.00000000e+00+1.22464680e-16j, -1.14423775e-17+2.33486982e-16j, 0.00000000e+00+5.20784380e-16j, 1.14423775e-17+1.14423775e-17j, 0.00000000e+00+1.22464680e-16j]) In this example, real input has an FFT which is Hermitian, i.e., symmetric in the real part and anti-symmetric in the imaginary part, as described in the `numpy.fft` documentation: >>> import matplotlib.pyplot as plt >>> t = np.arange(256) >>> sp = np.fft.fft(np.sin(t)) >>> freq = np.fft.fftfreq(t.shape[-1]) >>> plt.plot(freq, sp.real, freq, sp.imag) [<matplotlib.lines.Line2D object at 0x...>, <matplotlib.lines.Line2D object at 0x...>] >>> plt.show() """ a = asarray(a) if n is None: n = a.shape[axis] inv_norm = 1 if norm is not None and _unitary(norm): inv_norm = sqrt(n) output = _raw_fft(a, n, axis, False, True, inv_norm) return output
def fft(a, n=None, axis=-1, norm=None): """ Compute the one-dimensional discrete Fourier Transform. This function computes the one-dimensional *n*-point discrete Fourier Transform (DFT) with the efficient Fast Fourier Transform (FFT) algorithm [CT]. Parameters ---------- a : array_like Input array, can be complex. n : int, optional Length of the transformed axis of the output. If `n` is smaller than the length of the input, the input is cropped. If it is larger, the input is padded with zeros. If `n` is not given, the length of the input along the axis specified by `axis` is used. axis : int, optional Axis over which to compute the FFT. If not given, the last axis is used. norm : {None, "ortho"}, optional .. versionadded:: 1.10.0 Normalization mode (see `numpy.fft`). Default is None. Returns ------- out : complex ndarray The truncated or zero-padded input, transformed along the axis indicated by `axis`, or the last one if `axis` is not specified. Raises ------ IndexError if `axes` is larger than the last axis of `a`. See Also -------- numpy.fft : for definition of the DFT and conventions used. ifft : The inverse of `fft`. fft2 : The two-dimensional FFT. fftn : The *n*-dimensional FFT. rfftn : The *n*-dimensional FFT of real input. fftfreq : Frequency bins for given FFT parameters. Notes ----- FFT (Fast Fourier Transform) refers to a way the discrete Fourier Transform (DFT) can be calculated efficiently, by using symmetries in the calculated terms. The symmetry is highest when `n` is a power of 2, and the transform is therefore most efficient for these sizes. The DFT is defined, with the conventions used in this implementation, in the documentation for the `numpy.fft` module. References ---------- .. [CT] Cooley, James W., and John W. Tukey, 1965, "An algorithm for the machine calculation of complex Fourier series," *Math. Comput.* 19: 297-301. Examples -------- >>> np.fft.fft(np.exp(2j * np.pi * np.arange(8) / 8)) array([-2.33486982e-16+1.14423775e-17j, 8.00000000e+00-1.25557246e-15j, 2.33486982e-16+2.33486982e-16j, 0.00000000e+00+1.22464680e-16j, -1.14423775e-17+2.33486982e-16j, 0.00000000e+00+5.20784380e-16j, 1.14423775e-17+1.14423775e-17j, 0.00000000e+00+1.22464680e-16j]) In this example, real input has an FFT which is Hermitian, i.e., symmetric in the real part and anti-symmetric in the imaginary part, as described in the `numpy.fft` documentation: >>> import matplotlib.pyplot as plt >>> t = np.arange(256) >>> sp = np.fft.fft(np.sin(t)) >>> freq = np.fft.fftfreq(t.shape[-1]) >>> plt.plot(freq, sp.real, freq, sp.imag) [<matplotlib.lines.Line2D object at 0x...>, <matplotlib.lines.Line2D object at 0x...>] >>> plt.show() """ a = asarray(a) if n is None: n = a.shape[axis] fct = 1 if norm is not None and _unitary(norm): fct = 1 / sqrt(n) output = _raw_fft(a, n, axis, False, True, fct) return output
https://github.com/numpy/numpy/issues/14176
Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<__array_function__ internals>", line 6, in ifft File "/home/peter/.local/lib/python3.7/site-packages/numpy/fft/pocketfft.py", line 274, in ifft fct = 1/n ZeroDivisionError: division by zero
ZeroDivisionError
def ifft(a, n=None, axis=-1, norm=None): """ Compute the one-dimensional inverse discrete Fourier Transform. This function computes the inverse of the one-dimensional *n*-point discrete Fourier transform computed by `fft`. In other words, ``ifft(fft(a)) == a`` to within numerical accuracy. For a general description of the algorithm and definitions, see `numpy.fft`. The input should be ordered in the same way as is returned by `fft`, i.e., * ``a[0]`` should contain the zero frequency term, * ``a[1:n//2]`` should contain the positive-frequency terms, * ``a[n//2 + 1:]`` should contain the negative-frequency terms, in increasing order starting from the most negative frequency. For an even number of input points, ``A[n//2]`` represents the sum of the values at the positive and negative Nyquist frequencies, as the two are aliased together. See `numpy.fft` for details. Parameters ---------- a : array_like Input array, can be complex. n : int, optional Length of the transformed axis of the output. If `n` is smaller than the length of the input, the input is cropped. If it is larger, the input is padded with zeros. If `n` is not given, the length of the input along the axis specified by `axis` is used. See notes about padding issues. axis : int, optional Axis over which to compute the inverse DFT. If not given, the last axis is used. norm : {None, "ortho"}, optional .. versionadded:: 1.10.0 Normalization mode (see `numpy.fft`). Default is None. Returns ------- out : complex ndarray The truncated or zero-padded input, transformed along the axis indicated by `axis`, or the last one if `axis` is not specified. Raises ------ IndexError If `axes` is larger than the last axis of `a`. See Also -------- numpy.fft : An introduction, with definitions and general explanations. fft : The one-dimensional (forward) FFT, of which `ifft` is the inverse ifft2 : The two-dimensional inverse FFT. ifftn : The n-dimensional inverse FFT. Notes ----- If the input parameter `n` is larger than the size of the input, the input is padded by appending zeros at the end. Even though this is the common approach, it might lead to surprising results. If a different padding is desired, it must be performed before calling `ifft`. Examples -------- >>> np.fft.ifft([0, 4, 0, 0]) array([ 1.+0.j, 0.+1.j, -1.+0.j, 0.-1.j]) # may vary Create and plot a band-limited signal with random phases: >>> import matplotlib.pyplot as plt >>> t = np.arange(400) >>> n = np.zeros((400,), dtype=complex) >>> n[40:60] = np.exp(1j*np.random.uniform(0, 2*np.pi, (20,))) >>> s = np.fft.ifft(n) >>> plt.plot(t, s.real, 'b-', t, s.imag, 'r--') [<matplotlib.lines.Line2D object at ...>, <matplotlib.lines.Line2D object at ...>] >>> plt.legend(('real', 'imaginary')) <matplotlib.legend.Legend object at ...> >>> plt.show() """ a = asarray(a) if n is None: n = a.shape[axis] if norm is not None and _unitary(norm): inv_norm = sqrt(max(n, 1)) else: inv_norm = n output = _raw_fft(a, n, axis, False, False, inv_norm) return output
def ifft(a, n=None, axis=-1, norm=None): """ Compute the one-dimensional inverse discrete Fourier Transform. This function computes the inverse of the one-dimensional *n*-point discrete Fourier transform computed by `fft`. In other words, ``ifft(fft(a)) == a`` to within numerical accuracy. For a general description of the algorithm and definitions, see `numpy.fft`. The input should be ordered in the same way as is returned by `fft`, i.e., * ``a[0]`` should contain the zero frequency term, * ``a[1:n//2]`` should contain the positive-frequency terms, * ``a[n//2 + 1:]`` should contain the negative-frequency terms, in increasing order starting from the most negative frequency. For an even number of input points, ``A[n//2]`` represents the sum of the values at the positive and negative Nyquist frequencies, as the two are aliased together. See `numpy.fft` for details. Parameters ---------- a : array_like Input array, can be complex. n : int, optional Length of the transformed axis of the output. If `n` is smaller than the length of the input, the input is cropped. If it is larger, the input is padded with zeros. If `n` is not given, the length of the input along the axis specified by `axis` is used. See notes about padding issues. axis : int, optional Axis over which to compute the inverse DFT. If not given, the last axis is used. norm : {None, "ortho"}, optional .. versionadded:: 1.10.0 Normalization mode (see `numpy.fft`). Default is None. Returns ------- out : complex ndarray The truncated or zero-padded input, transformed along the axis indicated by `axis`, or the last one if `axis` is not specified. Raises ------ IndexError If `axes` is larger than the last axis of `a`. See Also -------- numpy.fft : An introduction, with definitions and general explanations. fft : The one-dimensional (forward) FFT, of which `ifft` is the inverse ifft2 : The two-dimensional inverse FFT. ifftn : The n-dimensional inverse FFT. Notes ----- If the input parameter `n` is larger than the size of the input, the input is padded by appending zeros at the end. Even though this is the common approach, it might lead to surprising results. If a different padding is desired, it must be performed before calling `ifft`. Examples -------- >>> np.fft.ifft([0, 4, 0, 0]) array([ 1.+0.j, 0.+1.j, -1.+0.j, 0.-1.j]) # may vary Create and plot a band-limited signal with random phases: >>> import matplotlib.pyplot as plt >>> t = np.arange(400) >>> n = np.zeros((400,), dtype=complex) >>> n[40:60] = np.exp(1j*np.random.uniform(0, 2*np.pi, (20,))) >>> s = np.fft.ifft(n) >>> plt.plot(t, s.real, 'b-', t, s.imag, 'r--') [<matplotlib.lines.Line2D object at ...>, <matplotlib.lines.Line2D object at ...>] >>> plt.legend(('real', 'imaginary')) <matplotlib.legend.Legend object at ...> >>> plt.show() """ a = asarray(a) if n is None: n = a.shape[axis] if norm is not None and _unitary(norm): fct = 1 / sqrt(max(n, 1)) else: fct = 1 / max(n, 1) output = _raw_fft(a, n, axis, False, False, fct) return output
https://github.com/numpy/numpy/issues/14176
Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<__array_function__ internals>", line 6, in ifft File "/home/peter/.local/lib/python3.7/site-packages/numpy/fft/pocketfft.py", line 274, in ifft fct = 1/n ZeroDivisionError: division by zero
ZeroDivisionError
def rfft(a, n=None, axis=-1, norm=None): """ Compute the one-dimensional discrete Fourier Transform for real input. This function computes the one-dimensional *n*-point discrete Fourier Transform (DFT) of a real-valued array by means of an efficient algorithm called the Fast Fourier Transform (FFT). Parameters ---------- a : array_like Input array n : int, optional Number of points along transformation axis in the input to use. If `n` is smaller than the length of the input, the input is cropped. If it is larger, the input is padded with zeros. If `n` is not given, the length of the input along the axis specified by `axis` is used. axis : int, optional Axis over which to compute the FFT. If not given, the last axis is used. norm : {None, "ortho"}, optional .. versionadded:: 1.10.0 Normalization mode (see `numpy.fft`). Default is None. Returns ------- out : complex ndarray The truncated or zero-padded input, transformed along the axis indicated by `axis`, or the last one if `axis` is not specified. If `n` is even, the length of the transformed axis is ``(n/2)+1``. If `n` is odd, the length is ``(n+1)/2``. Raises ------ IndexError If `axis` is larger than the last axis of `a`. See Also -------- numpy.fft : For definition of the DFT and conventions used. irfft : The inverse of `rfft`. fft : The one-dimensional FFT of general (complex) input. fftn : The *n*-dimensional FFT. rfftn : The *n*-dimensional FFT of real input. Notes ----- When the DFT is computed for purely real input, the output is Hermitian-symmetric, i.e. the negative frequency terms are just the complex conjugates of the corresponding positive-frequency terms, and the negative-frequency terms are therefore redundant. This function does not compute the negative frequency terms, and the length of the transformed axis of the output is therefore ``n//2 + 1``. When ``A = rfft(a)`` and fs is the sampling frequency, ``A[0]`` contains the zero-frequency term 0*fs, which is real due to Hermitian symmetry. If `n` is even, ``A[-1]`` contains the term representing both positive and negative Nyquist frequency (+fs/2 and -fs/2), and must also be purely real. If `n` is odd, there is no term at fs/2; ``A[-1]`` contains the largest positive frequency (fs/2*(n-1)/n), and is complex in the general case. If the input `a` contains an imaginary part, it is silently discarded. Examples -------- >>> np.fft.fft([0, 1, 0, 0]) array([ 1.+0.j, 0.-1.j, -1.+0.j, 0.+1.j]) # may vary >>> np.fft.rfft([0, 1, 0, 0]) array([ 1.+0.j, 0.-1.j, -1.+0.j]) # may vary Notice how the final element of the `fft` output is the complex conjugate of the second element, for real input. For `rfft`, this symmetry is exploited to compute only the non-negative frequency terms. """ a = asarray(a) inv_norm = 1 if norm is not None and _unitary(norm): if n is None: n = a.shape[axis] inv_norm = sqrt(n) output = _raw_fft(a, n, axis, True, True, inv_norm) return output
def rfft(a, n=None, axis=-1, norm=None): """ Compute the one-dimensional discrete Fourier Transform for real input. This function computes the one-dimensional *n*-point discrete Fourier Transform (DFT) of a real-valued array by means of an efficient algorithm called the Fast Fourier Transform (FFT). Parameters ---------- a : array_like Input array n : int, optional Number of points along transformation axis in the input to use. If `n` is smaller than the length of the input, the input is cropped. If it is larger, the input is padded with zeros. If `n` is not given, the length of the input along the axis specified by `axis` is used. axis : int, optional Axis over which to compute the FFT. If not given, the last axis is used. norm : {None, "ortho"}, optional .. versionadded:: 1.10.0 Normalization mode (see `numpy.fft`). Default is None. Returns ------- out : complex ndarray The truncated or zero-padded input, transformed along the axis indicated by `axis`, or the last one if `axis` is not specified. If `n` is even, the length of the transformed axis is ``(n/2)+1``. If `n` is odd, the length is ``(n+1)/2``. Raises ------ IndexError If `axis` is larger than the last axis of `a`. See Also -------- numpy.fft : For definition of the DFT and conventions used. irfft : The inverse of `rfft`. fft : The one-dimensional FFT of general (complex) input. fftn : The *n*-dimensional FFT. rfftn : The *n*-dimensional FFT of real input. Notes ----- When the DFT is computed for purely real input, the output is Hermitian-symmetric, i.e. the negative frequency terms are just the complex conjugates of the corresponding positive-frequency terms, and the negative-frequency terms are therefore redundant. This function does not compute the negative frequency terms, and the length of the transformed axis of the output is therefore ``n//2 + 1``. When ``A = rfft(a)`` and fs is the sampling frequency, ``A[0]`` contains the zero-frequency term 0*fs, which is real due to Hermitian symmetry. If `n` is even, ``A[-1]`` contains the term representing both positive and negative Nyquist frequency (+fs/2 and -fs/2), and must also be purely real. If `n` is odd, there is no term at fs/2; ``A[-1]`` contains the largest positive frequency (fs/2*(n-1)/n), and is complex in the general case. If the input `a` contains an imaginary part, it is silently discarded. Examples -------- >>> np.fft.fft([0, 1, 0, 0]) array([ 1.+0.j, 0.-1.j, -1.+0.j, 0.+1.j]) # may vary >>> np.fft.rfft([0, 1, 0, 0]) array([ 1.+0.j, 0.-1.j, -1.+0.j]) # may vary Notice how the final element of the `fft` output is the complex conjugate of the second element, for real input. For `rfft`, this symmetry is exploited to compute only the non-negative frequency terms. """ a = asarray(a) fct = 1 if norm is not None and _unitary(norm): if n is None: n = a.shape[axis] fct = 1 / sqrt(n) output = _raw_fft(a, n, axis, True, True, fct) return output
https://github.com/numpy/numpy/issues/14176
Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<__array_function__ internals>", line 6, in ifft File "/home/peter/.local/lib/python3.7/site-packages/numpy/fft/pocketfft.py", line 274, in ifft fct = 1/n ZeroDivisionError: division by zero
ZeroDivisionError
def irfft(a, n=None, axis=-1, norm=None): """ Compute the inverse of the n-point DFT for real input. This function computes the inverse of the one-dimensional *n*-point discrete Fourier Transform of real input computed by `rfft`. In other words, ``irfft(rfft(a), len(a)) == a`` to within numerical accuracy. (See Notes below for why ``len(a)`` is necessary here.) The input is expected to be in the form returned by `rfft`, i.e. the real zero-frequency term followed by the complex positive frequency terms in order of increasing frequency. Since the discrete Fourier Transform of real input is Hermitian-symmetric, the negative frequency terms are taken to be the complex conjugates of the corresponding positive frequency terms. Parameters ---------- a : array_like The input array. n : int, optional Length of the transformed axis of the output. For `n` output points, ``n//2+1`` input points are necessary. If the input is longer than this, it is cropped. If it is shorter than this, it is padded with zeros. If `n` is not given, it is taken to be ``2*(m-1)`` where ``m`` is the length of the input along the axis specified by `axis`. axis : int, optional Axis over which to compute the inverse FFT. If not given, the last axis is used. norm : {None, "ortho"}, optional .. versionadded:: 1.10.0 Normalization mode (see `numpy.fft`). Default is None. Returns ------- out : ndarray The truncated or zero-padded input, transformed along the axis indicated by `axis`, or the last one if `axis` is not specified. The length of the transformed axis is `n`, or, if `n` is not given, ``2*(m-1)`` where ``m`` is the length of the transformed axis of the input. To get an odd number of output points, `n` must be specified. Raises ------ IndexError If `axis` is larger than the last axis of `a`. See Also -------- numpy.fft : For definition of the DFT and conventions used. rfft : The one-dimensional FFT of real input, of which `irfft` is inverse. fft : The one-dimensional FFT. irfft2 : The inverse of the two-dimensional FFT of real input. irfftn : The inverse of the *n*-dimensional FFT of real input. Notes ----- Returns the real valued `n`-point inverse discrete Fourier transform of `a`, where `a` contains the non-negative frequency terms of a Hermitian-symmetric sequence. `n` is the length of the result, not the input. If you specify an `n` such that `a` must be zero-padded or truncated, the extra/removed values will be added/removed at high frequencies. One can thus resample a series to `m` points via Fourier interpolation by: ``a_resamp = irfft(rfft(a), m)``. The correct interpretation of the hermitian input depends on the length of the original data, as given by `n`. This is because each input shape could correspond to either an odd or even length signal. By default, `irfft` assumes an even output length which puts the last entry at the Nyquist frequency; aliasing with its symmetric counterpart. By Hermitian symmetry, the value is thus treated as purely real. To avoid losing information, the correct length of the real input **must** be given. Examples -------- >>> np.fft.ifft([1, -1j, -1, 1j]) array([0.+0.j, 1.+0.j, 0.+0.j, 0.+0.j]) # may vary >>> np.fft.irfft([1, -1j, -1]) array([0., 1., 0., 0.]) Notice how the last term in the input to the ordinary `ifft` is the complex conjugate of the second term, and the output has zero imaginary part everywhere. When calling `irfft`, the negative frequencies are not specified, and the output array is purely real. """ a = asarray(a) if n is None: n = (a.shape[axis] - 1) * 2 inv_norm = n if norm is not None and _unitary(norm): inv_norm = sqrt(n) output = _raw_fft(a, n, axis, True, False, inv_norm) return output
def irfft(a, n=None, axis=-1, norm=None): """ Compute the inverse of the n-point DFT for real input. This function computes the inverse of the one-dimensional *n*-point discrete Fourier Transform of real input computed by `rfft`. In other words, ``irfft(rfft(a), len(a)) == a`` to within numerical accuracy. (See Notes below for why ``len(a)`` is necessary here.) The input is expected to be in the form returned by `rfft`, i.e. the real zero-frequency term followed by the complex positive frequency terms in order of increasing frequency. Since the discrete Fourier Transform of real input is Hermitian-symmetric, the negative frequency terms are taken to be the complex conjugates of the corresponding positive frequency terms. Parameters ---------- a : array_like The input array. n : int, optional Length of the transformed axis of the output. For `n` output points, ``n//2+1`` input points are necessary. If the input is longer than this, it is cropped. If it is shorter than this, it is padded with zeros. If `n` is not given, it is taken to be ``2*(m-1)`` where ``m`` is the length of the input along the axis specified by `axis`. axis : int, optional Axis over which to compute the inverse FFT. If not given, the last axis is used. norm : {None, "ortho"}, optional .. versionadded:: 1.10.0 Normalization mode (see `numpy.fft`). Default is None. Returns ------- out : ndarray The truncated or zero-padded input, transformed along the axis indicated by `axis`, or the last one if `axis` is not specified. The length of the transformed axis is `n`, or, if `n` is not given, ``2*(m-1)`` where ``m`` is the length of the transformed axis of the input. To get an odd number of output points, `n` must be specified. Raises ------ IndexError If `axis` is larger than the last axis of `a`. See Also -------- numpy.fft : For definition of the DFT and conventions used. rfft : The one-dimensional FFT of real input, of which `irfft` is inverse. fft : The one-dimensional FFT. irfft2 : The inverse of the two-dimensional FFT of real input. irfftn : The inverse of the *n*-dimensional FFT of real input. Notes ----- Returns the real valued `n`-point inverse discrete Fourier transform of `a`, where `a` contains the non-negative frequency terms of a Hermitian-symmetric sequence. `n` is the length of the result, not the input. If you specify an `n` such that `a` must be zero-padded or truncated, the extra/removed values will be added/removed at high frequencies. One can thus resample a series to `m` points via Fourier interpolation by: ``a_resamp = irfft(rfft(a), m)``. The correct interpretation of the hermitian input depends on the length of the original data, as given by `n`. This is because each input shape could correspond to either an odd or even length signal. By default, `irfft` assumes an even output length which puts the last entry at the Nyquist frequency; aliasing with its symmetric counterpart. By Hermitian symmetry, the value is thus treated as purely real. To avoid losing information, the correct length of the real input **must** be given. Examples -------- >>> np.fft.ifft([1, -1j, -1, 1j]) array([0.+0.j, 1.+0.j, 0.+0.j, 0.+0.j]) # may vary >>> np.fft.irfft([1, -1j, -1]) array([0., 1., 0., 0.]) Notice how the last term in the input to the ordinary `ifft` is the complex conjugate of the second term, and the output has zero imaginary part everywhere. When calling `irfft`, the negative frequencies are not specified, and the output array is purely real. """ a = asarray(a) if n is None: n = (a.shape[axis] - 1) * 2 fct = 1 / n if norm is not None and _unitary(norm): fct = 1 / sqrt(n) output = _raw_fft(a, n, axis, True, False, fct) return output
https://github.com/numpy/numpy/issues/14176
Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<__array_function__ internals>", line 6, in ifft File "/home/peter/.local/lib/python3.7/site-packages/numpy/fft/pocketfft.py", line 274, in ifft fct = 1/n ZeroDivisionError: division by zero
ZeroDivisionError
def __init__( self, pyfunc, otypes=None, doc=None, excluded=None, cache=False, signature=None ): self.pyfunc = pyfunc self.cache = cache self.signature = signature self._ufunc = {} # Caching to improve default performance if doc is None: self.__doc__ = pyfunc.__doc__ else: self.__doc__ = doc if isinstance(otypes, str): for char in otypes: if char not in typecodes["All"]: raise ValueError("Invalid otype specified: %s" % (char,)) elif iterable(otypes): otypes = "".join([_nx.dtype(x).char for x in otypes]) elif otypes is not None: raise ValueError("Invalid otype specification") self.otypes = otypes # Excluded variable support if excluded is None: excluded = set() self.excluded = set(excluded) if signature is not None: self._in_and_out_core_dims = _parse_gufunc_signature(signature) else: self._in_and_out_core_dims = None
def __init__( self, pyfunc, otypes=None, doc=None, excluded=None, cache=False, signature=None ): self.pyfunc = pyfunc self.cache = cache self.signature = signature self._ufunc = None # Caching to improve default performance if doc is None: self.__doc__ = pyfunc.__doc__ else: self.__doc__ = doc if isinstance(otypes, str): for char in otypes: if char not in typecodes["All"]: raise ValueError("Invalid otype specified: %s" % (char,)) elif iterable(otypes): otypes = "".join([_nx.dtype(x).char for x in otypes]) elif otypes is not None: raise ValueError("Invalid otype specification") self.otypes = otypes # Excluded variable support if excluded is None: excluded = set() self.excluded = set(excluded) if signature is not None: self._in_and_out_core_dims = _parse_gufunc_signature(signature) else: self._in_and_out_core_dims = None
https://github.com/numpy/numpy/issues/16120
Traceback (most recent call last): File "function.py", line 17, in <module> g(np.arange(3.0)) # Crash! File "/home/hylke/.local/lib/python3.8/site-packages/numpy/lib/function_base.py", line 2091, in __call__ return self._vectorize_call(func=func, args=vargs) File "/home/hylke/.local/lib/python3.8/site-packages/numpy/lib/function_base.py", line 2167, in _vectorize_call outputs = ufunc(*inputs) ValueError: invalid number of arguments
ValueError
def _get_ufunc_and_otypes(self, func, args): """Return (ufunc, otypes).""" # frompyfunc will fail if args is empty if not args: raise ValueError("args can not be empty") if self.otypes is not None: otypes = self.otypes # self._ufunc is a dictionary whose keys are the number of # arguments (i.e. len(args)) and whose values are ufuncs created # by frompyfunc. len(args) can be different for different calls if # self.pyfunc has parameters with default values. We only use the # cache when func is self.pyfunc, which occurs when the call uses # only positional arguments and no arguments are excluded. nin = len(args) nout = len(self.otypes) if func is not self.pyfunc or nin not in self._ufunc: ufunc = frompyfunc(func, nin, nout) else: ufunc = None # We'll get it from self._ufunc if func is self.pyfunc: ufunc = self._ufunc.setdefault(nin, ufunc) else: # Get number of outputs and output types by calling the function on # the first entries of args. We also cache the result to prevent # the subsequent call when the ufunc is evaluated. # Assumes that ufunc first evaluates the 0th elements in the input # arrays (the input values are not checked to ensure this) args = [asarray(arg) for arg in args] if builtins.any(arg.size == 0 for arg in args): raise ValueError( "cannot call `vectorize` on size 0 inputs unless `otypes` is set" ) inputs = [arg.flat[0] for arg in args] outputs = func(*inputs) # Performance note: profiling indicates that -- for simple # functions at least -- this wrapping can almost double the # execution time. # Hence we make it optional. if self.cache: _cache = [outputs] def _func(*vargs): if _cache: return _cache.pop() else: return func(*vargs) else: _func = func if isinstance(outputs, tuple): nout = len(outputs) else: nout = 1 outputs = (outputs,) otypes = "".join([asarray(outputs[_k]).dtype.char for _k in range(nout)]) # Performance note: profiling indicates that creating the ufunc is # not a significant cost compared with wrapping so it seems not # worth trying to cache this. ufunc = frompyfunc(_func, len(args), nout) return ufunc, otypes
def _get_ufunc_and_otypes(self, func, args): """Return (ufunc, otypes).""" # frompyfunc will fail if args is empty if not args: raise ValueError("args can not be empty") if self.otypes is not None: otypes = self.otypes nout = len(otypes) # Note logic here: We only *use* self._ufunc if func is self.pyfunc # even though we set self._ufunc regardless. if func is self.pyfunc and self._ufunc is not None: ufunc = self._ufunc else: ufunc = self._ufunc = frompyfunc(func, len(args), nout) else: # Get number of outputs and output types by calling the function on # the first entries of args. We also cache the result to prevent # the subsequent call when the ufunc is evaluated. # Assumes that ufunc first evaluates the 0th elements in the input # arrays (the input values are not checked to ensure this) args = [asarray(arg) for arg in args] if builtins.any(arg.size == 0 for arg in args): raise ValueError( "cannot call `vectorize` on size 0 inputs unless `otypes` is set" ) inputs = [arg.flat[0] for arg in args] outputs = func(*inputs) # Performance note: profiling indicates that -- for simple # functions at least -- this wrapping can almost double the # execution time. # Hence we make it optional. if self.cache: _cache = [outputs] def _func(*vargs): if _cache: return _cache.pop() else: return func(*vargs) else: _func = func if isinstance(outputs, tuple): nout = len(outputs) else: nout = 1 outputs = (outputs,) otypes = "".join([asarray(outputs[_k]).dtype.char for _k in range(nout)]) # Performance note: profiling indicates that creating the ufunc is # not a significant cost compared with wrapping so it seems not # worth trying to cache this. ufunc = frompyfunc(_func, len(args), nout) return ufunc, otypes
https://github.com/numpy/numpy/issues/16120
Traceback (most recent call last): File "function.py", line 17, in <module> g(np.arange(3.0)) # Crash! File "/home/hylke/.local/lib/python3.8/site-packages/numpy/lib/function_base.py", line 2091, in __call__ return self._vectorize_call(func=func, args=vargs) File "/home/hylke/.local/lib/python3.8/site-packages/numpy/lib/function_base.py", line 2167, in _vectorize_call outputs = ufunc(*inputs) ValueError: invalid number of arguments
ValueError
def __getitem__(self, indx): """ x.__getitem__(y) <==> x[y] Return the item described by i, as a masked array. """ # We could directly use ndarray.__getitem__ on self. # But then we would have to modify __array_finalize__ to prevent the # mask of being reshaped if it hasn't been set up properly yet # So it's easier to stick to the current version dout = self.data[indx] _mask = self._mask def _is_scalar(m): return not isinstance(m, np.ndarray) def _scalar_heuristic(arr, elem): """ Return whether `elem` is a scalar result of indexing `arr`, or None if undecidable without promoting nomask to a full mask """ # obviously a scalar if not isinstance(elem, np.ndarray): return True # object array scalar indexing can return anything elif arr.dtype.type is np.object_: if arr.dtype is not elem.dtype: # elem is an array, but dtypes do not match, so must be # an element return True # well-behaved subclass that only returns 0d arrays when # expected - this is not a scalar elif type(arr).__getitem__ == ndarray.__getitem__: return False return None if _mask is not nomask: # _mask cannot be a subclass, so it tells us whether we should # expect a scalar. It also cannot be of dtype object. mout = _mask[indx] scalar_expected = _is_scalar(mout) else: # attempt to apply the heuristic to avoid constructing a full mask mout = nomask scalar_expected = _scalar_heuristic(self.data, dout) if scalar_expected is None: # heuristics have failed # construct a full array, so we can be certain. This is costly. # we could also fall back on ndarray.__getitem__(self.data, indx) scalar_expected = _is_scalar(getmaskarray(self)[indx]) # Did we extract a single item? if scalar_expected: # A record if isinstance(dout, np.void): # We should always re-cast to mvoid, otherwise users can # change masks on rows that already have masked values, but not # on rows that have no masked values, which is inconsistent. return mvoid(dout, mask=mout, hardmask=self._hardmask) # special case introduced in gh-5962 elif ( self.dtype.type is np.object_ and isinstance(dout, np.ndarray) and dout is not masked ): # If masked, turn into a MaskedArray, with everything masked. if mout: return MaskedArray(dout, mask=True) else: return dout # Just a scalar else: if mout: return masked else: return dout else: # Force dout to MA dout = dout.view(type(self)) # Inherit attributes from self dout._update_from(self) # Check the fill_value if is_string_or_list_of_strings(indx): if self._fill_value is not None: dout._fill_value = self._fill_value[indx] # Something like gh-15895 has happened if this check fails. # _fill_value should always be an ndarray. if not isinstance(dout._fill_value, np.ndarray): raise RuntimeError("Internal NumPy error.") # If we're indexing a multidimensional field in a # structured array (such as dtype("(2,)i2,(2,)i1")), # dimensionality goes up (M[field].ndim == M.ndim + # M.dtype[field].ndim). That's fine for # M[field] but problematic for M[field].fill_value # which should have shape () to avoid breaking several # methods. There is no great way out, so set to # first element. See issue #6723. if dout._fill_value.ndim > 0: if not (dout._fill_value == dout._fill_value.flat[0]).all(): warnings.warn( "Upon accessing multidimensional field " f"{indx!s}, need to keep dimensionality " "of fill_value at 0. Discarding " "heterogeneous fill_value and setting " f"all to {dout._fill_value[0]!s}.", stacklevel=2, ) # Need to use `.flat[0:1].squeeze(...)` instead of just # `.flat[0]` to ensure the result is a 0d array and not # a scalar. dout._fill_value = dout._fill_value.flat[0:1].squeeze(axis=0) dout._isfield = True # Update the mask if needed if mout is not nomask: # set shape to match that of data; this is needed for matrices dout._mask = reshape(mout, dout.shape) dout._sharedmask = True # Note: Don't try to check for m.any(), that'll take too long return dout
def __getitem__(self, indx): """ x.__getitem__(y) <==> x[y] Return the item described by i, as a masked array. """ # We could directly use ndarray.__getitem__ on self. # But then we would have to modify __array_finalize__ to prevent the # mask of being reshaped if it hasn't been set up properly yet # So it's easier to stick to the current version dout = self.data[indx] _mask = self._mask def _is_scalar(m): return not isinstance(m, np.ndarray) def _scalar_heuristic(arr, elem): """ Return whether `elem` is a scalar result of indexing `arr`, or None if undecidable without promoting nomask to a full mask """ # obviously a scalar if not isinstance(elem, np.ndarray): return True # object array scalar indexing can return anything elif arr.dtype.type is np.object_: if arr.dtype is not elem.dtype: # elem is an array, but dtypes do not match, so must be # an element return True # well-behaved subclass that only returns 0d arrays when # expected - this is not a scalar elif type(arr).__getitem__ == ndarray.__getitem__: return False return None if _mask is not nomask: # _mask cannot be a subclass, so it tells us whether we should # expect a scalar. It also cannot be of dtype object. mout = _mask[indx] scalar_expected = _is_scalar(mout) else: # attempt to apply the heuristic to avoid constructing a full mask mout = nomask scalar_expected = _scalar_heuristic(self.data, dout) if scalar_expected is None: # heuristics have failed # construct a full array, so we can be certain. This is costly. # we could also fall back on ndarray.__getitem__(self.data, indx) scalar_expected = _is_scalar(getmaskarray(self)[indx]) # Did we extract a single item? if scalar_expected: # A record if isinstance(dout, np.void): # We should always re-cast to mvoid, otherwise users can # change masks on rows that already have masked values, but not # on rows that have no masked values, which is inconsistent. return mvoid(dout, mask=mout, hardmask=self._hardmask) # special case introduced in gh-5962 elif ( self.dtype.type is np.object_ and isinstance(dout, np.ndarray) and dout is not masked ): # If masked, turn into a MaskedArray, with everything masked. if mout: return MaskedArray(dout, mask=True) else: return dout # Just a scalar else: if mout: return masked else: return dout else: # Force dout to MA dout = dout.view(type(self)) # Inherit attributes from self dout._update_from(self) # Check the fill_value if is_string_or_list_of_strings(indx): if self._fill_value is not None: dout._fill_value = self._fill_value[indx] # If we're indexing a multidimensional field in a # structured array (such as dtype("(2,)i2,(2,)i1")), # dimensionality goes up (M[field].ndim == M.ndim + # M.dtype[field].ndim). That's fine for # M[field] but problematic for M[field].fill_value # which should have shape () to avoid breaking several # methods. There is no great way out, so set to # first element. See issue #6723. if dout._fill_value.ndim > 0: if not (dout._fill_value == dout._fill_value.flat[0]).all(): warnings.warn( "Upon accessing multidimensional field " f"{indx!s}, need to keep dimensionality " "of fill_value at 0. Discarding " "heterogeneous fill_value and setting " f"all to {dout._fill_value[0]!s}.", stacklevel=2, ) dout._fill_value = dout._fill_value.flat[0] dout._isfield = True # Update the mask if needed if mout is not nomask: # set shape to match that of data; this is needed for matrices dout._mask = reshape(mout, dout.shape) dout._sharedmask = True # Note: Don't try to check for m.any(), that'll take too long return dout
https://github.com/numpy/numpy/issues/15895
Traceback (most recent call last): File "<stdin>", line 1, in <module> File "C:\Python37\lib\site-packages\numpy\ma\core.py", line 3276, in __getitem__ if dout._fill_value.ndim > 0: AttributeError: 'str' object has no attribute 'ndim'
AttributeError
def _replace_nan(a, val): """ If `a` is of inexact type, make a copy of `a`, replace NaNs with the `val` value, and return the copy together with a boolean mask marking the locations where NaNs were present. If `a` is not of inexact type, do nothing and return `a` together with a mask of None. Note that scalars will end up as array scalars, which is important for using the result as the value of the out argument in some operations. Parameters ---------- a : array-like Input array. val : float NaN values are set to val before doing the operation. Returns ------- y : ndarray If `a` is of inexact type, return a copy of `a` with the NaNs replaced by the fill value, otherwise return `a`. mask: {bool, None} If `a` is of inexact type, return a boolean mask marking locations of NaNs, otherwise return None. """ a = np.array(a, subok=True, copy=True) if a.dtype == np.object_: # object arrays do not support `isnan` (gh-9009), so make a guess mask = a != a elif issubclass(a.dtype.type, np.inexact): mask = np.isnan(a) else: mask = None if mask is not None: np.copyto(a, val, where=mask) return a, mask
def _replace_nan(a, val): """ If `a` is of inexact type, make a copy of `a`, replace NaNs with the `val` value, and return the copy together with a boolean mask marking the locations where NaNs were present. If `a` is not of inexact type, do nothing and return `a` together with a mask of None. Note that scalars will end up as array scalars, which is important for using the result as the value of the out argument in some operations. Parameters ---------- a : array-like Input array. val : float NaN values are set to val before doing the operation. Returns ------- y : ndarray If `a` is of inexact type, return a copy of `a` with the NaNs replaced by the fill value, otherwise return `a`. mask: {bool, None} If `a` is of inexact type, return a boolean mask marking locations of NaNs, otherwise return None. """ a = np.array(a, subok=True, copy=True) if not issubclass(a.dtype.type, np.inexact): return a, None mask = np.isnan(a) np.copyto(a, val, where=mask) return a, mask
https://github.com/numpy/numpy/issues/9008
In [2]: import numpy as np In [3]: np.__version__ Out[3]: '1.13.0.dev0+bca7922' In [4]: a = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=object) In [5]: np.nanmax(a, axis=0) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-5-a020f98a2536> in <module>() ----> 1 np.nanmax(a, axis=0) /Users/warren/miniconda3numpy/lib/python3.5/site-packages/numpy-1.13.0.dev0+bca7922-py3.5-macosx-10.6-x86_64.egg/numpy/lib/nanfunctions.py in nanmax(a, axis, out, keepdims) 343 # Fast, but not safe for subclasses of ndarray 344 res = np.fmax.reduce(a, axis=axis, out=out, **kwargs) --> 345 if np.isnan(res).any(): 346 warnings.warn("All-NaN slice encountered", RuntimeWarning, stacklevel=2) 347 else: TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
TypeError
def nanmin(a, axis=None, out=None, keepdims=np._NoValue): """ Return minimum of an array or minimum along an axis, ignoring any NaNs. When all-NaN slices are encountered a ``RuntimeWarning`` is raised and Nan is returned for that slice. Parameters ---------- a : array_like Array containing numbers whose minimum is desired. If `a` is not an array, a conversion is attempted. axis : int, optional Axis along which the minimum is computed. The default is to compute the minimum of the flattened array. out : ndarray, optional Alternate output array in which to place the result. The default is ``None``; if provided, it must have the same shape as the expected output, but the type will be cast if necessary. See `doc.ufuncs` for details. .. versionadded:: 1.8.0 keepdims : bool, optional If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the original `a`. If the value is anything but the default, then `keepdims` will be passed through to the `min` method of sub-classes of `ndarray`. If the sub-classes methods does not implement `keepdims` any exceptions will be raised. .. versionadded:: 1.8.0 Returns ------- nanmin : ndarray An array with the same shape as `a`, with the specified axis removed. If `a` is a 0-d array, or if axis is None, an ndarray scalar is returned. The same dtype as `a` is returned. See Also -------- nanmax : The maximum value of an array along a given axis, ignoring any NaNs. amin : The minimum value of an array along a given axis, propagating any NaNs. fmin : Element-wise minimum of two arrays, ignoring any NaNs. minimum : Element-wise minimum of two arrays, propagating any NaNs. isnan : Shows which elements are Not a Number (NaN). isfinite: Shows which elements are neither NaN nor infinity. amax, fmax, maximum Notes ----- NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Positive infinity is treated as a very large number and negative infinity is treated as a very small (i.e. negative) number. If the input has a integer type the function is equivalent to np.min. Examples -------- >>> a = np.array([[1, 2], [3, np.nan]]) >>> np.nanmin(a) 1.0 >>> np.nanmin(a, axis=0) array([ 1., 2.]) >>> np.nanmin(a, axis=1) array([ 1., 3.]) When positive infinity and negative infinity are present: >>> np.nanmin([1, 2, np.nan, np.inf]) 1.0 >>> np.nanmin([1, 2, np.nan, np.NINF]) -inf """ kwargs = {} if keepdims is not np._NoValue: kwargs["keepdims"] = keepdims if type(a) is np.ndarray and a.dtype != np.object_: # Fast, but not safe for subclasses of ndarray, or object arrays, # which do not implement isnan (gh-9009), or fmin correctly (gh-8975) res = np.fmin.reduce(a, axis=axis, out=out, **kwargs) if np.isnan(res).any(): warnings.warn("All-NaN axis encountered", RuntimeWarning, stacklevel=2) else: # Slow, but safe for subclasses of ndarray a, mask = _replace_nan(a, +np.inf) res = np.amin(a, axis=axis, out=out, **kwargs) if mask is None: return res # Check for all-NaN axis mask = np.all(mask, axis=axis, **kwargs) if np.any(mask): res = _copyto(res, np.nan, mask) warnings.warn("All-NaN axis encountered", RuntimeWarning, stacklevel=2) return res
def nanmin(a, axis=None, out=None, keepdims=np._NoValue): """ Return minimum of an array or minimum along an axis, ignoring any NaNs. When all-NaN slices are encountered a ``RuntimeWarning`` is raised and Nan is returned for that slice. Parameters ---------- a : array_like Array containing numbers whose minimum is desired. If `a` is not an array, a conversion is attempted. axis : int, optional Axis along which the minimum is computed. The default is to compute the minimum of the flattened array. out : ndarray, optional Alternate output array in which to place the result. The default is ``None``; if provided, it must have the same shape as the expected output, but the type will be cast if necessary. See `doc.ufuncs` for details. .. versionadded:: 1.8.0 keepdims : bool, optional If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the original `a`. If the value is anything but the default, then `keepdims` will be passed through to the `min` method of sub-classes of `ndarray`. If the sub-classes methods does not implement `keepdims` any exceptions will be raised. .. versionadded:: 1.8.0 Returns ------- nanmin : ndarray An array with the same shape as `a`, with the specified axis removed. If `a` is a 0-d array, or if axis is None, an ndarray scalar is returned. The same dtype as `a` is returned. See Also -------- nanmax : The maximum value of an array along a given axis, ignoring any NaNs. amin : The minimum value of an array along a given axis, propagating any NaNs. fmin : Element-wise minimum of two arrays, ignoring any NaNs. minimum : Element-wise minimum of two arrays, propagating any NaNs. isnan : Shows which elements are Not a Number (NaN). isfinite: Shows which elements are neither NaN nor infinity. amax, fmax, maximum Notes ----- NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Positive infinity is treated as a very large number and negative infinity is treated as a very small (i.e. negative) number. If the input has a integer type the function is equivalent to np.min. Examples -------- >>> a = np.array([[1, 2], [3, np.nan]]) >>> np.nanmin(a) 1.0 >>> np.nanmin(a, axis=0) array([ 1., 2.]) >>> np.nanmin(a, axis=1) array([ 1., 3.]) When positive infinity and negative infinity are present: >>> np.nanmin([1, 2, np.nan, np.inf]) 1.0 >>> np.nanmin([1, 2, np.nan, np.NINF]) -inf """ kwargs = {} if keepdims is not np._NoValue: kwargs["keepdims"] = keepdims if not isinstance(a, np.ndarray) or type(a) is np.ndarray: # Fast, but not safe for subclasses of ndarray res = np.fmin.reduce(a, axis=axis, out=out, **kwargs) if np.isnan(res).any(): warnings.warn("All-NaN axis encountered", RuntimeWarning, stacklevel=2) else: # Slow, but safe for subclasses of ndarray a, mask = _replace_nan(a, +np.inf) res = np.amin(a, axis=axis, out=out, **kwargs) if mask is None: return res # Check for all-NaN axis mask = np.all(mask, axis=axis, **kwargs) if np.any(mask): res = _copyto(res, np.nan, mask) warnings.warn("All-NaN axis encountered", RuntimeWarning, stacklevel=2) return res
https://github.com/numpy/numpy/issues/9008
In [2]: import numpy as np In [3]: np.__version__ Out[3]: '1.13.0.dev0+bca7922' In [4]: a = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=object) In [5]: np.nanmax(a, axis=0) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-5-a020f98a2536> in <module>() ----> 1 np.nanmax(a, axis=0) /Users/warren/miniconda3numpy/lib/python3.5/site-packages/numpy-1.13.0.dev0+bca7922-py3.5-macosx-10.6-x86_64.egg/numpy/lib/nanfunctions.py in nanmax(a, axis, out, keepdims) 343 # Fast, but not safe for subclasses of ndarray 344 res = np.fmax.reduce(a, axis=axis, out=out, **kwargs) --> 345 if np.isnan(res).any(): 346 warnings.warn("All-NaN slice encountered", RuntimeWarning, stacklevel=2) 347 else: TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
TypeError
def nanmax(a, axis=None, out=None, keepdims=np._NoValue): """ Return the maximum of an array or maximum along an axis, ignoring any NaNs. When all-NaN slices are encountered a ``RuntimeWarning`` is raised and NaN is returned for that slice. Parameters ---------- a : array_like Array containing numbers whose maximum is desired. If `a` is not an array, a conversion is attempted. axis : int, optional Axis along which the maximum is computed. The default is to compute the maximum of the flattened array. out : ndarray, optional Alternate output array in which to place the result. The default is ``None``; if provided, it must have the same shape as the expected output, but the type will be cast if necessary. See `doc.ufuncs` for details. .. versionadded:: 1.8.0 keepdims : bool, optional If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the original `a`. If the value is anything but the default, then `keepdims` will be passed through to the `max` method of sub-classes of `ndarray`. If the sub-classes methods does not implement `keepdims` any exceptions will be raised. .. versionadded:: 1.8.0 Returns ------- nanmax : ndarray An array with the same shape as `a`, with the specified axis removed. If `a` is a 0-d array, or if axis is None, an ndarray scalar is returned. The same dtype as `a` is returned. See Also -------- nanmin : The minimum value of an array along a given axis, ignoring any NaNs. amax : The maximum value of an array along a given axis, propagating any NaNs. fmax : Element-wise maximum of two arrays, ignoring any NaNs. maximum : Element-wise maximum of two arrays, propagating any NaNs. isnan : Shows which elements are Not a Number (NaN). isfinite: Shows which elements are neither NaN nor infinity. amin, fmin, minimum Notes ----- NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Positive infinity is treated as a very large number and negative infinity is treated as a very small (i.e. negative) number. If the input has a integer type the function is equivalent to np.max. Examples -------- >>> a = np.array([[1, 2], [3, np.nan]]) >>> np.nanmax(a) 3.0 >>> np.nanmax(a, axis=0) array([ 3., 2.]) >>> np.nanmax(a, axis=1) array([ 2., 3.]) When positive infinity and negative infinity are present: >>> np.nanmax([1, 2, np.nan, np.NINF]) 2.0 >>> np.nanmax([1, 2, np.nan, np.inf]) inf """ kwargs = {} if keepdims is not np._NoValue: kwargs["keepdims"] = keepdims if type(a) is np.ndarray and a.dtype != np.object_: # Fast, but not safe for subclasses of ndarray, or object arrays, # which do not implement isnan (gh-9009), or fmax correctly (gh-8975) res = np.fmax.reduce(a, axis=axis, out=out, **kwargs) if np.isnan(res).any(): warnings.warn("All-NaN slice encountered", RuntimeWarning, stacklevel=2) else: # Slow, but safe for subclasses of ndarray a, mask = _replace_nan(a, -np.inf) res = np.amax(a, axis=axis, out=out, **kwargs) if mask is None: return res # Check for all-NaN axis mask = np.all(mask, axis=axis, **kwargs) if np.any(mask): res = _copyto(res, np.nan, mask) warnings.warn("All-NaN axis encountered", RuntimeWarning, stacklevel=2) return res
def nanmax(a, axis=None, out=None, keepdims=np._NoValue): """ Return the maximum of an array or maximum along an axis, ignoring any NaNs. When all-NaN slices are encountered a ``RuntimeWarning`` is raised and NaN is returned for that slice. Parameters ---------- a : array_like Array containing numbers whose maximum is desired. If `a` is not an array, a conversion is attempted. axis : int, optional Axis along which the maximum is computed. The default is to compute the maximum of the flattened array. out : ndarray, optional Alternate output array in which to place the result. The default is ``None``; if provided, it must have the same shape as the expected output, but the type will be cast if necessary. See `doc.ufuncs` for details. .. versionadded:: 1.8.0 keepdims : bool, optional If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the original `a`. If the value is anything but the default, then `keepdims` will be passed through to the `max` method of sub-classes of `ndarray`. If the sub-classes methods does not implement `keepdims` any exceptions will be raised. .. versionadded:: 1.8.0 Returns ------- nanmax : ndarray An array with the same shape as `a`, with the specified axis removed. If `a` is a 0-d array, or if axis is None, an ndarray scalar is returned. The same dtype as `a` is returned. See Also -------- nanmin : The minimum value of an array along a given axis, ignoring any NaNs. amax : The maximum value of an array along a given axis, propagating any NaNs. fmax : Element-wise maximum of two arrays, ignoring any NaNs. maximum : Element-wise maximum of two arrays, propagating any NaNs. isnan : Shows which elements are Not a Number (NaN). isfinite: Shows which elements are neither NaN nor infinity. amin, fmin, minimum Notes ----- NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Positive infinity is treated as a very large number and negative infinity is treated as a very small (i.e. negative) number. If the input has a integer type the function is equivalent to np.max. Examples -------- >>> a = np.array([[1, 2], [3, np.nan]]) >>> np.nanmax(a) 3.0 >>> np.nanmax(a, axis=0) array([ 3., 2.]) >>> np.nanmax(a, axis=1) array([ 2., 3.]) When positive infinity and negative infinity are present: >>> np.nanmax([1, 2, np.nan, np.NINF]) 2.0 >>> np.nanmax([1, 2, np.nan, np.inf]) inf """ kwargs = {} if keepdims is not np._NoValue: kwargs["keepdims"] = keepdims if not isinstance(a, np.ndarray) or type(a) is np.ndarray: # Fast, but not safe for subclasses of ndarray res = np.fmax.reduce(a, axis=axis, out=out, **kwargs) if np.isnan(res).any(): warnings.warn("All-NaN slice encountered", RuntimeWarning, stacklevel=2) else: # Slow, but safe for subclasses of ndarray a, mask = _replace_nan(a, -np.inf) res = np.amax(a, axis=axis, out=out, **kwargs) if mask is None: return res # Check for all-NaN axis mask = np.all(mask, axis=axis, **kwargs) if np.any(mask): res = _copyto(res, np.nan, mask) warnings.warn("All-NaN axis encountered", RuntimeWarning, stacklevel=2) return res
https://github.com/numpy/numpy/issues/9008
In [2]: import numpy as np In [3]: np.__version__ Out[3]: '1.13.0.dev0+bca7922' In [4]: a = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=object) In [5]: np.nanmax(a, axis=0) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-5-a020f98a2536> in <module>() ----> 1 np.nanmax(a, axis=0) /Users/warren/miniconda3numpy/lib/python3.5/site-packages/numpy-1.13.0.dev0+bca7922-py3.5-macosx-10.6-x86_64.egg/numpy/lib/nanfunctions.py in nanmax(a, axis, out, keepdims) 343 # Fast, but not safe for subclasses of ndarray 344 res = np.fmax.reduce(a, axis=axis, out=out, **kwargs) --> 345 if np.isnan(res).any(): 346 warnings.warn("All-NaN slice encountered", RuntimeWarning, stacklevel=2) 347 else: TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
TypeError
def norm(x, ord=None, axis=None, keepdims=False): """ Matrix or vector norm. This function is able to return one of eight different matrix norms, or one of an infinite number of vector norms (described below), depending on the value of the ``ord`` parameter. Parameters ---------- x : array_like Input array. If `axis` is None, `x` must be 1-D or 2-D, unless `ord` is None. If both `axis` and `ord` are None, the 2-norm of ``x.ravel`` will be returned. ord : {non-zero int, inf, -inf, 'fro', 'nuc'}, optional Order of the norm (see table under ``Notes``). inf means numpy's `inf` object. The default is None. axis : {None, int, 2-tuple of ints}, optional. If `axis` is an integer, it specifies the axis of `x` along which to compute the vector norms. If `axis` is a 2-tuple, it specifies the axes that hold 2-D matrices, and the matrix norms of these matrices are computed. If `axis` is None then either a vector norm (when `x` is 1-D) or a matrix norm (when `x` is 2-D) is returned. The default is None. .. versionadded:: 1.8.0 keepdims : bool, optional If this is set to True, the axes which are normed over are left in the result as dimensions with size one. With this option the result will broadcast correctly against the original `x`. .. versionadded:: 1.10.0 Returns ------- n : float or ndarray Norm of the matrix or vector(s). See Also -------- scipy.linalg.norm : Similar function in SciPy. Notes ----- For values of ``ord < 1``, the result is, strictly speaking, not a mathematical 'norm', but it may still be useful for various numerical purposes. The following norms can be calculated: ===== ============================ ========================== ord norm for matrices norm for vectors ===== ============================ ========================== None Frobenius norm 2-norm 'fro' Frobenius norm -- 'nuc' nuclear norm -- inf max(sum(abs(x), axis=1)) max(abs(x)) -inf min(sum(abs(x), axis=1)) min(abs(x)) 0 -- sum(x != 0) 1 max(sum(abs(x), axis=0)) as below -1 min(sum(abs(x), axis=0)) as below 2 2-norm (largest sing. value) as below -2 smallest singular value as below other -- sum(abs(x)**ord)**(1./ord) ===== ============================ ========================== The Frobenius norm is given by [1]_: :math:`||A||_F = [\\sum_{i,j} abs(a_{i,j})^2]^{1/2}` The nuclear norm is the sum of the singular values. Both the Frobenius and nuclear norm orders are only defined for matrices and raise a ValueError when ``x.ndim != 2``. References ---------- .. [1] G. H. Golub and C. F. Van Loan, *Matrix Computations*, Baltimore, MD, Johns Hopkins University Press, 1985, pg. 15 Examples -------- >>> from numpy import linalg as LA >>> a = np.arange(9) - 4 >>> a array([-4, -3, -2, ..., 2, 3, 4]) >>> b = a.reshape((3, 3)) >>> b array([[-4, -3, -2], [-1, 0, 1], [ 2, 3, 4]]) >>> LA.norm(a) 7.745966692414834 >>> LA.norm(b) 7.745966692414834 >>> LA.norm(b, 'fro') 7.745966692414834 >>> LA.norm(a, np.inf) 4.0 >>> LA.norm(b, np.inf) 9.0 >>> LA.norm(a, -np.inf) 0.0 >>> LA.norm(b, -np.inf) 2.0 >>> LA.norm(a, 1) 20.0 >>> LA.norm(b, 1) 7.0 >>> LA.norm(a, -1) -4.6566128774142013e-010 >>> LA.norm(b, -1) 6.0 >>> LA.norm(a, 2) 7.745966692414834 >>> LA.norm(b, 2) 7.3484692283495345 >>> LA.norm(a, -2) 0.0 >>> LA.norm(b, -2) 1.8570331885190563e-016 # may vary >>> LA.norm(a, 3) 5.8480354764257312 # may vary >>> LA.norm(a, -3) 0.0 Using the `axis` argument to compute vector norms: >>> c = np.array([[ 1, 2, 3], ... [-1, 1, 4]]) >>> LA.norm(c, axis=0) array([ 1.41421356, 2.23606798, 5. ]) >>> LA.norm(c, axis=1) array([ 3.74165739, 4.24264069]) >>> LA.norm(c, ord=1, axis=1) array([ 6., 6.]) Using the `axis` argument to compute matrix norms: >>> m = np.arange(8).reshape(2,2,2) >>> LA.norm(m, axis=(1,2)) array([ 3.74165739, 11.22497216]) >>> LA.norm(m[0, :, :]), LA.norm(m[1, :, :]) (3.7416573867739413, 11.224972160321824) """ x = asarray(x) if not issubclass(x.dtype.type, (inexact, object_)): x = x.astype(float) # Immediately handle some default, simple, fast, and common cases. if axis is None: ndim = x.ndim if ( (ord is None) or (ord in ("f", "fro") and ndim == 2) or (ord == 2 and ndim == 1) ): x = x.ravel(order="K") if isComplexType(x.dtype.type): sqnorm = dot(x.real, x.real) + dot(x.imag, x.imag) else: sqnorm = dot(x, x) ret = sqrt(sqnorm) if keepdims: ret = ret.reshape(ndim * [1]) return ret # Normalize the `axis` argument to a tuple. nd = x.ndim if axis is None: axis = tuple(range(nd)) elif not isinstance(axis, tuple): try: axis = int(axis) except Exception: raise TypeError("'axis' must be None, an integer or a tuple of integers") axis = (axis,) if len(axis) == 1: if ord == Inf: return abs(x).max(axis=axis, keepdims=keepdims) elif ord == -Inf: return abs(x).min(axis=axis, keepdims=keepdims) elif ord == 0: # Zero norm return (x != 0).astype(x.real.dtype).sum(axis=axis, keepdims=keepdims) elif ord == 1: # special case for speedup return add.reduce(abs(x), axis=axis, keepdims=keepdims) elif ord is None or ord == 2: # special case for speedup s = (x.conj() * x).real return sqrt(add.reduce(s, axis=axis, keepdims=keepdims)) # None of the str-type keywords for ord ('fro', 'nuc') # are valid for vectors elif isinstance(ord, str): raise ValueError(f"Invalid norm order '{ord}' for vectors") else: absx = abs(x) absx **= ord ret = add.reduce(absx, axis=axis, keepdims=keepdims) ret **= 1 / ord return ret elif len(axis) == 2: row_axis, col_axis = axis row_axis = normalize_axis_index(row_axis, nd) col_axis = normalize_axis_index(col_axis, nd) if row_axis == col_axis: raise ValueError("Duplicate axes given.") if ord == 2: ret = _multi_svd_norm(x, row_axis, col_axis, amax) elif ord == -2: ret = _multi_svd_norm(x, row_axis, col_axis, amin) elif ord == 1: if col_axis > row_axis: col_axis -= 1 ret = add.reduce(abs(x), axis=row_axis).max(axis=col_axis) elif ord == Inf: if row_axis > col_axis: row_axis -= 1 ret = add.reduce(abs(x), axis=col_axis).max(axis=row_axis) elif ord == -1: if col_axis > row_axis: col_axis -= 1 ret = add.reduce(abs(x), axis=row_axis).min(axis=col_axis) elif ord == -Inf: if row_axis > col_axis: row_axis -= 1 ret = add.reduce(abs(x), axis=col_axis).min(axis=row_axis) elif ord in [None, "fro", "f"]: ret = sqrt(add.reduce((x.conj() * x).real, axis=axis)) elif ord == "nuc": ret = _multi_svd_norm(x, row_axis, col_axis, sum) else: raise ValueError("Invalid norm order for matrices.") if keepdims: ret_shape = list(x.shape) ret_shape[axis[0]] = 1 ret_shape[axis[1]] = 1 ret = ret.reshape(ret_shape) return ret else: raise ValueError("Improper number of dimensions to norm.")
def norm(x, ord=None, axis=None, keepdims=False): """ Matrix or vector norm. This function is able to return one of eight different matrix norms, or one of an infinite number of vector norms (described below), depending on the value of the ``ord`` parameter. Parameters ---------- x : array_like Input array. If `axis` is None, `x` must be 1-D or 2-D, unless `ord` is None. If both `axis` and `ord` are None, the 2-norm of ``x.ravel`` will be returned. ord : {non-zero int, inf, -inf, 'fro', 'nuc'}, optional Order of the norm (see table under ``Notes``). inf means numpy's `inf` object. The default is None. axis : {None, int, 2-tuple of ints}, optional. If `axis` is an integer, it specifies the axis of `x` along which to compute the vector norms. If `axis` is a 2-tuple, it specifies the axes that hold 2-D matrices, and the matrix norms of these matrices are computed. If `axis` is None then either a vector norm (when `x` is 1-D) or a matrix norm (when `x` is 2-D) is returned. The default is None. .. versionadded:: 1.8.0 keepdims : bool, optional If this is set to True, the axes which are normed over are left in the result as dimensions with size one. With this option the result will broadcast correctly against the original `x`. .. versionadded:: 1.10.0 Returns ------- n : float or ndarray Norm of the matrix or vector(s). See Also -------- scipy.linalg.norm : Similar function in SciPy. Notes ----- For values of ``ord < 1``, the result is, strictly speaking, not a mathematical 'norm', but it may still be useful for various numerical purposes. The following norms can be calculated: ===== ============================ ========================== ord norm for matrices norm for vectors ===== ============================ ========================== None Frobenius norm 2-norm 'fro' Frobenius norm -- 'nuc' nuclear norm -- inf max(sum(abs(x), axis=1)) max(abs(x)) -inf min(sum(abs(x), axis=1)) min(abs(x)) 0 -- sum(x != 0) 1 max(sum(abs(x), axis=0)) as below -1 min(sum(abs(x), axis=0)) as below 2 2-norm (largest sing. value) as below -2 smallest singular value as below other -- sum(abs(x)**ord)**(1./ord) ===== ============================ ========================== The Frobenius norm is given by [1]_: :math:`||A||_F = [\\sum_{i,j} abs(a_{i,j})^2]^{1/2}` The nuclear norm is the sum of the singular values. References ---------- .. [1] G. H. Golub and C. F. Van Loan, *Matrix Computations*, Baltimore, MD, Johns Hopkins University Press, 1985, pg. 15 Examples -------- >>> from numpy import linalg as LA >>> a = np.arange(9) - 4 >>> a array([-4, -3, -2, ..., 2, 3, 4]) >>> b = a.reshape((3, 3)) >>> b array([[-4, -3, -2], [-1, 0, 1], [ 2, 3, 4]]) >>> LA.norm(a) 7.745966692414834 >>> LA.norm(b) 7.745966692414834 >>> LA.norm(b, 'fro') 7.745966692414834 >>> LA.norm(a, np.inf) 4.0 >>> LA.norm(b, np.inf) 9.0 >>> LA.norm(a, -np.inf) 0.0 >>> LA.norm(b, -np.inf) 2.0 >>> LA.norm(a, 1) 20.0 >>> LA.norm(b, 1) 7.0 >>> LA.norm(a, -1) -4.6566128774142013e-010 >>> LA.norm(b, -1) 6.0 >>> LA.norm(a, 2) 7.745966692414834 >>> LA.norm(b, 2) 7.3484692283495345 >>> LA.norm(a, -2) 0.0 >>> LA.norm(b, -2) 1.8570331885190563e-016 # may vary >>> LA.norm(a, 3) 5.8480354764257312 # may vary >>> LA.norm(a, -3) 0.0 Using the `axis` argument to compute vector norms: >>> c = np.array([[ 1, 2, 3], ... [-1, 1, 4]]) >>> LA.norm(c, axis=0) array([ 1.41421356, 2.23606798, 5. ]) >>> LA.norm(c, axis=1) array([ 3.74165739, 4.24264069]) >>> LA.norm(c, ord=1, axis=1) array([ 6., 6.]) Using the `axis` argument to compute matrix norms: >>> m = np.arange(8).reshape(2,2,2) >>> LA.norm(m, axis=(1,2)) array([ 3.74165739, 11.22497216]) >>> LA.norm(m[0, :, :]), LA.norm(m[1, :, :]) (3.7416573867739413, 11.224972160321824) """ x = asarray(x) if not issubclass(x.dtype.type, (inexact, object_)): x = x.astype(float) # Immediately handle some default, simple, fast, and common cases. if axis is None: ndim = x.ndim if ( (ord is None) or (ord in ("f", "fro") and ndim == 2) or (ord == 2 and ndim == 1) ): x = x.ravel(order="K") if isComplexType(x.dtype.type): sqnorm = dot(x.real, x.real) + dot(x.imag, x.imag) else: sqnorm = dot(x, x) ret = sqrt(sqnorm) if keepdims: ret = ret.reshape(ndim * [1]) return ret # Normalize the `axis` argument to a tuple. nd = x.ndim if axis is None: axis = tuple(range(nd)) elif not isinstance(axis, tuple): try: axis = int(axis) except Exception: raise TypeError("'axis' must be None, an integer or a tuple of integers") axis = (axis,) if len(axis) == 1: if ord == Inf: return abs(x).max(axis=axis, keepdims=keepdims) elif ord == -Inf: return abs(x).min(axis=axis, keepdims=keepdims) elif ord == 0: # Zero norm return (x != 0).astype(x.real.dtype).sum(axis=axis, keepdims=keepdims) elif ord == 1: # special case for speedup return add.reduce(abs(x), axis=axis, keepdims=keepdims) elif ord is None or ord == 2: # special case for speedup s = (x.conj() * x).real return sqrt(add.reduce(s, axis=axis, keepdims=keepdims)) else: try: ord + 1 except TypeError: raise ValueError("Invalid norm order for vectors.") absx = abs(x) absx **= ord ret = add.reduce(absx, axis=axis, keepdims=keepdims) ret **= 1 / ord return ret elif len(axis) == 2: row_axis, col_axis = axis row_axis = normalize_axis_index(row_axis, nd) col_axis = normalize_axis_index(col_axis, nd) if row_axis == col_axis: raise ValueError("Duplicate axes given.") if ord == 2: ret = _multi_svd_norm(x, row_axis, col_axis, amax) elif ord == -2: ret = _multi_svd_norm(x, row_axis, col_axis, amin) elif ord == 1: if col_axis > row_axis: col_axis -= 1 ret = add.reduce(abs(x), axis=row_axis).max(axis=col_axis) elif ord == Inf: if row_axis > col_axis: row_axis -= 1 ret = add.reduce(abs(x), axis=col_axis).max(axis=row_axis) elif ord == -1: if col_axis > row_axis: col_axis -= 1 ret = add.reduce(abs(x), axis=row_axis).min(axis=col_axis) elif ord == -Inf: if row_axis > col_axis: row_axis -= 1 ret = add.reduce(abs(x), axis=col_axis).min(axis=row_axis) elif ord in [None, "fro", "f"]: ret = sqrt(add.reduce((x.conj() * x).real, axis=axis)) elif ord == "nuc": ret = _multi_svd_norm(x, row_axis, col_axis, sum) else: raise ValueError("Invalid norm order for matrices.") if keepdims: ret_shape = list(x.shape) ret_shape[axis[0]] = 1 ret_shape[axis[1]] = 1 ret = ret.reshape(ret_shape) return ret else: raise ValueError("Improper number of dimensions to norm.")
https://github.com/numpy/numpy/issues/15533
1.7594677278427366 --------------------------------------------------------------------------- TypeError Traceback (most recent call last) //anaconda3/lib/python3.7/site-packages/numpy/linalg/linalg.py in norm(x, ord, axis, keepdims) 2515 try: -> 2516 ord + 1 2517 except TypeError: TypeError: can only concatenate str (not "int") to str During handling of the above exception, another exception occurred: ValueError Traceback (most recent call last) <ipython-input-18-2ace847024a5> in <module> 3 b = np.squeeze(a) 4 print(np.linalg.norm(a, 'fro')) ----> 5 print(np.linalg.norm(b, 'fro')) <__array_function__ internals> in norm(*args, **kwargs) //anaconda3/lib/python3.7/site-packages/numpy/linalg/linalg.py in norm(x, ord, axis, keepdims) 2516 ord + 1 2517 except TypeError: -> 2518 raise ValueError("Invalid norm order for vectors.") 2519 absx = abs(x) 2520 absx **= ord ValueError: Invalid norm order for vectors.
TypeError
def binary_repr(num, width=None): """ Return the binary representation of the input number as a string. For negative numbers, if width is not given, a minus sign is added to the front. If width is given, the two's complement of the number is returned, with respect to that width. In a two's-complement system negative numbers are represented by the two's complement of the absolute value. This is the most common method of representing signed integers on computers [1]_. A N-bit two's-complement system can represent every integer in the range :math:`-2^{N-1}` to :math:`+2^{N-1}-1`. Parameters ---------- num : int Only an integer decimal number can be used. width : int, optional The length of the returned string if `num` is positive, or the length of the two's complement if `num` is negative, provided that `width` is at least a sufficient number of bits for `num` to be represented in the designated form. If the `width` value is insufficient, it will be ignored, and `num` will be returned in binary (`num` > 0) or two's complement (`num` < 0) form with its width equal to the minimum number of bits needed to represent the number in the designated form. This behavior is deprecated and will later raise an error. .. deprecated:: 1.12.0 Returns ------- bin : str Binary representation of `num` or two's complement of `num`. See Also -------- base_repr: Return a string representation of a number in the given base system. bin: Python's built-in binary representation generator of an integer. Notes ----- `binary_repr` is equivalent to using `base_repr` with base 2, but about 25x faster. References ---------- .. [1] Wikipedia, "Two's complement", https://en.wikipedia.org/wiki/Two's_complement Examples -------- >>> np.binary_repr(3) '11' >>> np.binary_repr(-3) '-11' >>> np.binary_repr(3, width=4) '0011' The two's complement is returned when the input number is negative and width is specified: >>> np.binary_repr(-3, width=3) '101' >>> np.binary_repr(-3, width=5) '11101' """ def warn_if_insufficient(width, binwidth): if width is not None and width < binwidth: warnings.warn( "Insufficient bit width provided. This behavior " "will raise an error in the future.", DeprecationWarning, stacklevel=3, ) # Ensure that num is a Python integer to avoid overflow or unwanted # casts to floating point. num = operator.index(num) if num == 0: return "0" * (width or 1) elif num > 0: binary = bin(num)[2:] binwidth = len(binary) outwidth = binwidth if width is None else max(binwidth, width) warn_if_insufficient(width, binwidth) return binary.zfill(outwidth) else: if width is None: return "-" + bin(-num)[2:] else: poswidth = len(bin(-num)[2:]) # See gh-8679: remove extra digit # for numbers at boundaries. if 2 ** (poswidth - 1) == -num: poswidth -= 1 twocomp = 2 ** (poswidth + 1) + num binary = bin(twocomp)[2:] binwidth = len(binary) outwidth = max(binwidth, width) warn_if_insufficient(width, binwidth) return "1" * (outwidth - binwidth) + binary
def binary_repr(num, width=None): """ Return the binary representation of the input number as a string. For negative numbers, if width is not given, a minus sign is added to the front. If width is given, the two's complement of the number is returned, with respect to that width. In a two's-complement system negative numbers are represented by the two's complement of the absolute value. This is the most common method of representing signed integers on computers [1]_. A N-bit two's-complement system can represent every integer in the range :math:`-2^{N-1}` to :math:`+2^{N-1}-1`. Parameters ---------- num : int Only an integer decimal number can be used. width : int, optional The length of the returned string if `num` is positive, or the length of the two's complement if `num` is negative, provided that `width` is at least a sufficient number of bits for `num` to be represented in the designated form. If the `width` value is insufficient, it will be ignored, and `num` will be returned in binary (`num` > 0) or two's complement (`num` < 0) form with its width equal to the minimum number of bits needed to represent the number in the designated form. This behavior is deprecated and will later raise an error. .. deprecated:: 1.12.0 Returns ------- bin : str Binary representation of `num` or two's complement of `num`. See Also -------- base_repr: Return a string representation of a number in the given base system. bin: Python's built-in binary representation generator of an integer. Notes ----- `binary_repr` is equivalent to using `base_repr` with base 2, but about 25x faster. References ---------- .. [1] Wikipedia, "Two's complement", https://en.wikipedia.org/wiki/Two's_complement Examples -------- >>> np.binary_repr(3) '11' >>> np.binary_repr(-3) '-11' >>> np.binary_repr(3, width=4) '0011' The two's complement is returned when the input number is negative and width is specified: >>> np.binary_repr(-3, width=3) '101' >>> np.binary_repr(-3, width=5) '11101' """ def warn_if_insufficient(width, binwidth): if width is not None and width < binwidth: warnings.warn( "Insufficient bit width provided. This behavior " "will raise an error in the future.", DeprecationWarning, stacklevel=3, ) if num == 0: return "0" * (width or 1) elif num > 0: binary = bin(num)[2:] binwidth = len(binary) outwidth = binwidth if width is None else max(binwidth, width) warn_if_insufficient(width, binwidth) return binary.zfill(outwidth) else: if width is None: return "-" + bin(-num)[2:] else: poswidth = len(bin(-num)[2:]) # See gh-8679: remove extra digit # for numbers at boundaries. if 2 ** (poswidth - 1) == -num: poswidth -= 1 twocomp = 2 ** (poswidth + 1) + num binary = bin(twocomp)[2:] binwidth = len(binary) outwidth = max(binwidth, width) warn_if_insufficient(width, binwidth) return "1" * (outwidth - binwidth) + binary
https://github.com/numpy/numpy/issues/14289
System info: 3.6.8rc1 (v3.6.8rc1:cc3e73212a, Dec 11 2018, 17:37:34) [GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)] NumPy version: 1.17.0 val = -2305843009213693952 Python int: 1110000000000000000000000000000000000000000000000000000000000000 NumPy int64: 1110000000000000000000000000000000000000000000000000000000000000 val = -4611686018427387905 Python int: 1011111111111111111111111111111111111111111111111111111111111111 NumPy int64: 1011111111111111111111111111111111111111111111111111111111111111 val = -4611686018427387904 Python int: 1100000000000000000000000000000000000000000000000000000000000000 --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-29-c41b585b0ed8> in <module> 8 print("val = {}".format(val)) 9 print("Python int: {}".format(np.binary_repr(val, 64))) ---> 10 print("NumPy int64: {}\n".format(np.binary_repr(np.int64(val), 64))) ~/.local/share/virtualenvs/ai_tools-DEcp7MjW/lib/python3.6/site-packages/numpy/core/numeric.py in binary_repr(num, width) 1960 1961 twocomp = 2**(poswidth + 1) + num -> 1962 binary = bin(twocomp)[2:] 1963 binwidth = len(binary) 1964 TypeError: 'numpy.float64' object cannot be interpreted as an integer
TypeError
def __new__(subtype, filename, dtype=uint8, mode="r+", offset=0, shape=None, order="C"): # Import here to minimize 'import numpy' overhead import mmap import os.path try: mode = mode_equivalents[mode] except KeyError: if mode not in valid_filemodes: raise ValueError( "mode must be one of %s" % (valid_filemodes + list(mode_equivalents.keys())) ) if mode == "w+" and shape is None: raise ValueError("shape must be given") if hasattr(filename, "read"): f_ctx = contextlib_nullcontext(filename) else: f_ctx = open(os_fspath(filename), ("r" if mode == "c" else mode) + "b") with f_ctx as fid: fid.seek(0, 2) flen = fid.tell() descr = dtypedescr(dtype) _dbytes = descr.itemsize if shape is None: bytes = flen - offset if bytes % _dbytes: raise ValueError( "Size of available data is not a multiple of the data-type size." ) size = bytes // _dbytes shape = (size,) else: if not isinstance(shape, tuple): shape = (shape,) size = np.intp(1) # avoid default choice of np.int_, which might overflow for k in shape: size *= k bytes = long(offset + size * _dbytes) if mode in ("w+", "r+") and flen < bytes: fid.seek(bytes - 1, 0) fid.write(b"\0") fid.flush() if mode == "c": acc = mmap.ACCESS_COPY elif mode == "r": acc = mmap.ACCESS_READ else: acc = mmap.ACCESS_WRITE start = offset - offset % mmap.ALLOCATIONGRANULARITY bytes -= start array_offset = offset - start mm = mmap.mmap(fid.fileno(), bytes, access=acc, offset=start) self = ndarray.__new__( subtype, shape, dtype=descr, buffer=mm, offset=array_offset, order=order ) self._mmap = mm self.offset = offset self.mode = mode if is_pathlib_path(filename): # special case - if we were constructed with a pathlib.path, # then filename is a path object, not a string self.filename = filename.resolve() elif hasattr(fid, "name") and isinstance(fid.name, basestring): # py3 returns int for TemporaryFile().name self.filename = os.path.abspath(fid.name) # same as memmap copies (e.g. memmap + 1) else: self.filename = None return self
def __new__(subtype, filename, dtype=uint8, mode="r+", offset=0, shape=None, order="C"): # Import here to minimize 'import numpy' overhead import mmap import os.path try: mode = mode_equivalents[mode] except KeyError: if mode not in valid_filemodes: raise ValueError( "mode must be one of %s" % (valid_filemodes + list(mode_equivalents.keys())) ) if mode == "w+" and shape is None: raise ValueError("shape must be given") if hasattr(filename, "read"): f_ctx = contextlib_nullcontext(filename) else: f_ctx = open(os_fspath(filename), ("r" if mode == "c" else mode) + "b") with f_ctx as fid: fid.seek(0, 2) flen = fid.tell() descr = dtypedescr(dtype) _dbytes = descr.itemsize if shape is None: bytes = flen - offset if bytes % _dbytes: raise ValueError( "Size of available data is not a multiple of the data-type size." ) size = bytes // _dbytes shape = (size,) else: if not isinstance(shape, tuple): shape = (shape,) size = np.intp(1) # avoid default choice of np.int_, which might overflow for k in shape: size *= k bytes = long(offset + size * _dbytes) if mode == "w+" or (mode == "r+" and flen < bytes): fid.seek(bytes - 1, 0) fid.write(b"\0") fid.flush() if mode == "c": acc = mmap.ACCESS_COPY elif mode == "r": acc = mmap.ACCESS_READ else: acc = mmap.ACCESS_WRITE start = offset - offset % mmap.ALLOCATIONGRANULARITY bytes -= start array_offset = offset - start mm = mmap.mmap(fid.fileno(), bytes, access=acc, offset=start) self = ndarray.__new__( subtype, shape, dtype=descr, buffer=mm, offset=array_offset, order=order ) self._mmap = mm self.offset = offset self.mode = mode if is_pathlib_path(filename): # special case - if we were constructed with a pathlib.path, # then filename is a path object, not a string self.filename = filename.resolve() elif hasattr(fid, "name") and isinstance(fid.name, basestring): # py3 returns int for TemporaryFile().name self.filename = os.path.abspath(fid.name) # same as memmap copies (e.g. memmap + 1) else: self.filename = None return self
https://github.com/numpy/numpy/issues/12653
Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python3.5/dist-packages/numpy/core/memmap.py", line 250, in __new__ fid.seek(bytes - 1, 0) OSError: [Errno 22] Invalid argument
OSError
def _exec_command(command, use_shell=None, use_tee=None, **env): log.debug("_exec_command(...)") if use_shell is None: use_shell = os.name == "posix" if use_tee is None: use_tee = os.name == "posix" using_command = 0 if use_shell: # We use shell (unless use_shell==0) so that wildcards can be # used. sh = os.environ.get("SHELL", "/bin/sh") if is_sequence(command): argv = [sh, "-c", " ".join(list(command))] else: argv = [sh, "-c", command] else: # On NT, DOS we avoid using command.com as it's exit status is # not related to the exit status of a command. if is_sequence(command): argv = command[:] else: argv = shlex.split(command) # `spawn*p` family with path (vp, vpe, ...) are not available on windows. # Also prefer spawn{v,vp} in favor of spawn{ve,vpe} if no env # modification is actually requested as the *e* functions are not thread # safe on windows (https://bugs.python.org/issue6476) if hasattr(os, "spawnvpe"): spawn_command = os.spawnvpe if env else os.spawnvp else: spawn_command = os.spawnve if env else os.spawnv argv[0] = find_executable(argv[0]) or argv[0] if not os.path.isfile(argv[0]): log.warn("Executable %s does not exist" % (argv[0])) if os.name in ["nt", "dos"]: # argv[0] might be internal command argv = [os.environ["COMSPEC"], "/C"] + argv using_command = 1 _so_has_fileno = _supports_fileno(sys.stdout) _se_has_fileno = _supports_fileno(sys.stderr) so_flush = sys.stdout.flush se_flush = sys.stderr.flush if _so_has_fileno: so_fileno = sys.stdout.fileno() so_dup = os.dup(so_fileno) if _se_has_fileno: se_fileno = sys.stderr.fileno() se_dup = os.dup(se_fileno) outfile = temp_file_name() fout = open(outfile, "w") if using_command: errfile = temp_file_name() ferr = open(errfile, "w") log.debug( "Running %s(%s,%r,%r,os.environ)" % (spawn_command.__name__, os.P_WAIT, argv[0], argv) ) if env and sys.version_info[0] >= 3 and os.name == "nt": # Pre-encode os.environ, discarding un-encodable entries, # to avoid it failing during encoding as part of spawn. Failure # is possible if the environment contains entries that are not # encoded using the system codepage as windows expects. # # This is not necessary on unix, where os.environ is encoded # using the surrogateescape error handler and decoded using # it as part of spawn. encoded_environ = {} for k, v in os.environ.items(): try: encoded_environ[k.encode(sys.getfilesystemencoding())] = v.encode( sys.getfilesystemencoding() ) except UnicodeEncodeError: log.debug("ignoring un-encodable env entry %s", k) else: encoded_environ = os.environ argv0 = argv[0] if not using_command: argv[0] = quote_arg(argv0) so_flush() se_flush() if _so_has_fileno: os.dup2(fout.fileno(), so_fileno) if _se_has_fileno: if using_command: # XXX: disabled for now as it does not work from cmd under win32. # Tests fail on msys os.dup2(ferr.fileno(), se_fileno) else: os.dup2(fout.fileno(), se_fileno) try: # Use spawnv in favor of spawnve, unless necessary if env: status = spawn_command(os.P_WAIT, argv0, argv, encoded_environ) else: status = spawn_command(os.P_WAIT, argv0, argv) except Exception: errmess = str(get_exception()) status = 999 sys.stderr.write("%s: %s" % (errmess, argv[0])) so_flush() se_flush() if _so_has_fileno: os.dup2(so_dup, so_fileno) os.close(so_dup) if _se_has_fileno: os.dup2(se_dup, se_fileno) os.close(se_dup) fout.close() fout = open_latin1(outfile, "r") text = fout.read() fout.close() os.remove(outfile) if using_command: ferr.close() ferr = open_latin1(errfile, "r") errmess = ferr.read() ferr.close() os.remove(errfile) if errmess and not status: # Not sure how to handle the case where errmess # contains only warning messages and that should # not be treated as errors. # status = 998 if text: text = text + "\n" # text = '%sCOMMAND %r FAILED: %s' %(text,command,errmess) text = text + errmess print(errmess) if text[-1:] == "\n": text = text[:-1] if status is None: status = 0 if use_tee: print(text) return status, text
def _exec_command(command, use_shell=None, use_tee=None, **env): log.debug("_exec_command(...)") if use_shell is None: use_shell = os.name == "posix" if use_tee is None: use_tee = os.name == "posix" using_command = 0 if use_shell: # We use shell (unless use_shell==0) so that wildcards can be # used. sh = os.environ.get("SHELL", "/bin/sh") if is_sequence(command): argv = [sh, "-c", " ".join(list(command))] else: argv = [sh, "-c", command] else: # On NT, DOS we avoid using command.com as it's exit status is # not related to the exit status of a command. if is_sequence(command): argv = command[:] else: argv = shlex.split(command) if hasattr(os, "spawnvpe"): spawn_command = os.spawnvpe else: spawn_command = os.spawnve argv[0] = find_executable(argv[0]) or argv[0] if not os.path.isfile(argv[0]): log.warn("Executable %s does not exist" % (argv[0])) if os.name in ["nt", "dos"]: # argv[0] might be internal command argv = [os.environ["COMSPEC"], "/C"] + argv using_command = 1 _so_has_fileno = _supports_fileno(sys.stdout) _se_has_fileno = _supports_fileno(sys.stderr) so_flush = sys.stdout.flush se_flush = sys.stderr.flush if _so_has_fileno: so_fileno = sys.stdout.fileno() so_dup = os.dup(so_fileno) if _se_has_fileno: se_fileno = sys.stderr.fileno() se_dup = os.dup(se_fileno) outfile = temp_file_name() fout = open(outfile, "w") if using_command: errfile = temp_file_name() ferr = open(errfile, "w") log.debug( "Running %s(%s,%r,%r,os.environ)" % (spawn_command.__name__, os.P_WAIT, argv[0], argv) ) if sys.version_info[0] >= 3 and os.name == "nt": # Pre-encode os.environ, discarding un-encodable entries, # to avoid it failing during encoding as part of spawn. Failure # is possible if the environment contains entries that are not # encoded using the system codepage as windows expects. # # This is not necessary on unix, where os.environ is encoded # using the surrogateescape error handler and decoded using # it as part of spawn. encoded_environ = {} for k, v in os.environ.items(): try: encoded_environ[k.encode(sys.getfilesystemencoding())] = v.encode( sys.getfilesystemencoding() ) except UnicodeEncodeError: log.debug("ignoring un-encodable env entry %s", k) else: encoded_environ = os.environ argv0 = argv[0] if not using_command: argv[0] = quote_arg(argv0) so_flush() se_flush() if _so_has_fileno: os.dup2(fout.fileno(), so_fileno) if _se_has_fileno: if using_command: # XXX: disabled for now as it does not work from cmd under win32. # Tests fail on msys os.dup2(ferr.fileno(), se_fileno) else: os.dup2(fout.fileno(), se_fileno) try: status = spawn_command(os.P_WAIT, argv0, argv, encoded_environ) except Exception: errmess = str(get_exception()) status = 999 sys.stderr.write("%s: %s" % (errmess, argv[0])) so_flush() se_flush() if _so_has_fileno: os.dup2(so_dup, so_fileno) os.close(so_dup) if _se_has_fileno: os.dup2(se_dup, se_fileno) os.close(se_dup) fout.close() fout = open_latin1(outfile, "r") text = fout.read() fout.close() os.remove(outfile) if using_command: ferr.close() ferr = open_latin1(errfile, "r") errmess = ferr.read() ferr.close() os.remove(errfile) if errmess and not status: # Not sure how to handle the case where errmess # contains only warning messages and that should # not be treated as errors. # status = 998 if text: text = text + "\n" # text = '%sCOMMAND %r FAILED: %s' %(text,command,errmess) text = text + errmess print(errmess) if text[-1:] == "\n": text = text[:-1] if status is None: status = 0 if use_tee: print(text) return status, text
https://github.com/numpy/numpy/issues/7607
Traceback (most recent call last): File "\cygwin64\home\biolab\spawnve.py", line 46, in run print(exec_command([self.executable] + self.args + [str(i)])) File "C:\Python35-32\lib\site-packages\numpy\distutils\exec_command.py", line 235, in exec_command use_tee=use_tee,**env) File "C:\Python35-32\lib\site-packages\numpy\distutils\exec_command.py", line 453, in _exec_command os.remove(outfile) PermissionError: [WinError 32] The process cannot access the file because it is being used by another process: 'C:\\Users\\biolab\\AppData\\Local\\Temp\\tmpx50_ dmz1\\9sq2lgq8'
PermissionError
def _ctype_ndarray(element_type, shape): """Create an ndarray of the given element type and shape""" for dim in shape[::-1]: element_type = dim * element_type # prevent the type name include np.ctypeslib element_type.__module__ = None return element_type
def _ctype_ndarray(element_type, shape): """Create an ndarray of the given element type and shape""" for dim in shape[::-1]: element_type = element_type * dim return element_type
https://github.com/numpy/numpy/issues/6176
KeyError Traceback (most recent call last) <ipython-input-3-e5712fdde6f3> in <module>() ----> 1 b = np.ctypeslib.as_ctypes(a) /home/chug/.local/lib/python2.7/site-packages/numpy/ctypeslib.py in as_ctypes(obj) 419 if readonly: 420 raise TypeError("readonly arrays unsupported") --> 421 tp = _typecodes[ai["typestr"]] 422 for dim in ai["shape"][::-1]: 423 tp = tp * dim KeyError: '|b1'
KeyError
def as_ctypes(obj): """Create and return a ctypes object from a numpy array. Actually anything that exposes the __array_interface__ is accepted.""" ai = obj.__array_interface__ if ai["strides"]: raise TypeError("strided arrays not supported") if ai["version"] != 3: raise TypeError("only __array_interface__ version 3 supported") addr, readonly = ai["data"] if readonly: raise TypeError("readonly arrays unsupported") dtype = _dtype((ai["typestr"], ai["shape"])) result = as_ctypes_type(dtype).from_address(addr) result.__keep = obj return result
def as_ctypes(obj): """Create and return a ctypes object from a numpy array. Actually anything that exposes the __array_interface__ is accepted.""" ai = obj.__array_interface__ if ai["strides"]: raise TypeError("strided arrays not supported") if ai["version"] != 3: raise TypeError("only __array_interface__ version 3 supported") addr, readonly = ai["data"] if readonly: raise TypeError("readonly arrays unsupported") tp = _ctype_ndarray(_typecodes[ai["typestr"]], ai["shape"]) result = tp.from_address(addr) result.__keep = obj return result
https://github.com/numpy/numpy/issues/6176
KeyError Traceback (most recent call last) <ipython-input-3-e5712fdde6f3> in <module>() ----> 1 b = np.ctypeslib.as_ctypes(a) /home/chug/.local/lib/python2.7/site-packages/numpy/ctypeslib.py in as_ctypes(obj) 419 if readonly: 420 raise TypeError("readonly arrays unsupported") --> 421 tp = _typecodes[ai["typestr"]] 422 for dim in ai["shape"][::-1]: 423 tp = tp * dim KeyError: '|b1'
KeyError
def _read_array_header(fp, version): """ see read_array_header_1_0 """ # Read an unsigned, little-endian short int which has the length of the # header. import struct if version == (1, 0): hlength_type = "<H" elif version == (2, 0): hlength_type = "<I" else: raise ValueError("Invalid version %r" % version) hlength_str = _read_bytes(fp, struct.calcsize(hlength_type), "array header length") header_length = struct.unpack(hlength_type, hlength_str)[0] header = _read_bytes(fp, header_length, "array header") # The header is a pretty-printed string representation of a literal # Python dictionary with trailing newlines padded to a ARRAY_ALIGN byte # boundary. The keys are strings. # "shape" : tuple of int # "fortran_order" : bool # "descr" : dtype.descr header = _filter_header(header) try: d = safe_eval(header) except SyntaxError as e: msg = "Cannot parse header: %r\nException: %r" raise ValueError(msg % (header, e)) if not isinstance(d, dict): msg = "Header is not a dictionary: %r" raise ValueError(msg % d) keys = sorted(d.keys()) if keys != ["descr", "fortran_order", "shape"]: msg = "Header does not contain the correct keys: %r" raise ValueError(msg % (keys,)) # Sanity-check the values. if not isinstance(d["shape"], tuple) or not numpy.all( [isinstance(x, (int, long)) for x in d["shape"]] ): msg = "shape is not valid: %r" raise ValueError(msg % (d["shape"],)) if not isinstance(d["fortran_order"], bool): msg = "fortran_order is not a valid bool: %r" raise ValueError(msg % (d["fortran_order"],)) try: dtype = descr_to_dtype(d["descr"]) except TypeError as e: msg = "descr is not a valid dtype descriptor: %r" raise ValueError(msg % (d["descr"],)) return d["shape"], d["fortran_order"], dtype
def _read_array_header(fp, version): """ see read_array_header_1_0 """ # Read an unsigned, little-endian short int which has the length of the # header. import struct if version == (1, 0): hlength_type = "<H" elif version == (2, 0): hlength_type = "<I" else: raise ValueError("Invalid version %r" % version) hlength_str = _read_bytes(fp, struct.calcsize(hlength_type), "array header length") header_length = struct.unpack(hlength_type, hlength_str)[0] header = _read_bytes(fp, header_length, "array header") # The header is a pretty-printed string representation of a literal # Python dictionary with trailing newlines padded to a ARRAY_ALIGN byte # boundary. The keys are strings. # "shape" : tuple of int # "fortran_order" : bool # "descr" : dtype.descr header = _filter_header(header) try: d = safe_eval(header) except SyntaxError as e: msg = "Cannot parse header: %r\nException: %r" raise ValueError(msg % (header, e)) if not isinstance(d, dict): msg = "Header is not a dictionary: %r" raise ValueError(msg % d) keys = sorted(d.keys()) if keys != ["descr", "fortran_order", "shape"]: msg = "Header does not contain the correct keys: %r" raise ValueError(msg % (keys,)) # Sanity-check the values. if not isinstance(d["shape"], tuple) or not numpy.all( [isinstance(x, (int, long)) for x in d["shape"]] ): msg = "shape is not valid: %r" raise ValueError(msg % (d["shape"],)) if not isinstance(d["fortran_order"], bool): msg = "fortran_order is not a valid bool: %r" raise ValueError(msg % (d["fortran_order"],)) try: dtype = numpy.dtype(d["descr"]) except TypeError as e: msg = "descr is not a valid dtype descriptor: %r" raise ValueError(msg % (d["descr"],)) return d["shape"], d["fortran_order"], dtype
https://github.com/numpy/numpy/issues/2215
import numpy as np t = np.dtype('i1, i4, i1', align=True) d = np.zeros(1, t) np.save("test.npy", d) data = np.load("test.npy") Traceback (most recent call last): File "D:\Projects\Cuda\Cuda_Git\pathwise\liinc\model\feeds\numpy_bug.py", line 8, in <module> data = np.load("test.npy") File "D:\Projects\Cuda\Cuda_Git\pathwise\pathwise\vendors\lib64\x64\python\numpy\lib\npyio.py", line 314, in load return format.read_array(fid) File "D:\Projects\Cuda\Cuda_Git\pathwise\pathwise\vendors\lib64\x64\python\numpy\lib\format.py", line 440, in read_array shape, fortran_order, dtype = read_array_header_1_0(fp) File "D:\Projects\Cuda\Cuda_Git\pathwise\pathwise\vendors\lib64\x64\python\numpy\lib\format.py", line 358, in read_array_header_1_0 dtype = numpy.dtype(d['descr']) ValueError: two fields with the same name
ValueError
def array_repr(arr, max_line_width=None, precision=None, suppress_small=None): """ Return the string representation of an array. Parameters ---------- arr : ndarray Input array. max_line_width : int, optional The maximum number of columns the string should span. Newline characters split the string appropriately after array elements. precision : int, optional Floating point precision. Default is the current printing precision (usually 8), which can be altered using `set_printoptions`. suppress_small : bool, optional Represent very small numbers as zero, default is False. Very small is defined by `precision`, if the precision is 8 then numbers smaller than 5e-9 are represented as zero. Returns ------- string : str The string representation of an array. See Also -------- array_str, array2string, set_printoptions Examples -------- >>> np.array_repr(np.array([1,2])) 'array([1, 2])' >>> np.array_repr(np.ma.array([0.])) 'MaskedArray([ 0.])' >>> np.array_repr(np.array([], np.int32)) 'array([], dtype=int32)' >>> x = np.array([1e-6, 4e-7, 2, 3]) >>> np.array_repr(x, precision=6, suppress_small=True) 'array([ 0.000001, 0. , 2. , 3. ])' """ return _array_repr_implementation(arr, max_line_width, precision, suppress_small)
def array_repr(arr, max_line_width=None, precision=None, suppress_small=None): """ Return the string representation of an array. Parameters ---------- arr : ndarray Input array. max_line_width : int, optional The maximum number of columns the string should span. Newline characters split the string appropriately after array elements. precision : int, optional Floating point precision. Default is the current printing precision (usually 8), which can be altered using `set_printoptions`. suppress_small : bool, optional Represent very small numbers as zero, default is False. Very small is defined by `precision`, if the precision is 8 then numbers smaller than 5e-9 are represented as zero. Returns ------- string : str The string representation of an array. See Also -------- array_str, array2string, set_printoptions Examples -------- >>> np.array_repr(np.array([1,2])) 'array([1, 2])' >>> np.array_repr(np.ma.array([0.])) 'MaskedArray([ 0.])' >>> np.array_repr(np.array([], np.int32)) 'array([], dtype=int32)' >>> x = np.array([1e-6, 4e-7, 2, 3]) >>> np.array_repr(x, precision=6, suppress_small=True) 'array([ 0.000001, 0. , 2. , 3. ])' """ if max_line_width is None: max_line_width = _format_options["linewidth"] if type(arr) is not ndarray: class_name = type(arr).__name__ else: class_name = "array" skipdtype = dtype_is_implied(arr.dtype) and arr.size > 0 prefix = class_name + "(" suffix = ")" if skipdtype else "," if _format_options["legacy"] == "1.13" and arr.shape == () and not arr.dtype.names: lst = repr(arr.item()) elif arr.size > 0 or arr.shape == (0,): lst = array2string( arr, max_line_width, precision, suppress_small, ", ", prefix, suffix=suffix ) else: # show zero-length shape unless it is (0,) lst = "[], shape=%s" % (repr(arr.shape),) arr_str = prefix + lst + suffix if skipdtype: return arr_str dtype_str = "dtype={})".format(dtype_short_repr(arr.dtype)) # compute whether we should put dtype on a new line: Do so if adding the # dtype would extend the last line past max_line_width. # Note: This line gives the correct result even when rfind returns -1. last_line_len = len(arr_str) - (arr_str.rfind("\n") + 1) spacer = " " if _format_options["legacy"] == "1.13": if issubclass(arr.dtype.type, flexible): spacer = "\n" + " " * len(class_name + "(") elif last_line_len + len(dtype_str) + 1 > max_line_width: spacer = "\n" + " " * len(class_name + "(") return arr_str + spacer + dtype_str
https://github.com/numpy/numpy/issues/12162
In [1]: import numpy as np In [2]: class Sub(np.ndarray): ...: def __array_function__(*args, **kwargs): ...: return NotImplemented ...: In [3]: repr(np.array(1).view(Sub)) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-6-d6ff958f4fcf> in <module>() ----> 1 repr(np.array(1).view(Sub)) ~/dev/numpy/numpy/core/overrides.py in public_api(*args, **kwargs) 149 relevant_args = dispatcher(*args, **kwargs) 150 return array_function_implementation_or_override( --> 151 implementation, public_api, relevant_args, args, kwargs) 152 return public_api 153 ~/dev/numpy/numpy/core/overrides.py in array_function_implementation_or_override(implementation, public_api, relevant_args, args, kwargs) 108 raise TypeError('no implementation found for {} on types that implement ' 109 '__array_function__: {}' --> 110 .format(public_api, list(map(type, overloaded_args)))) 111 112 TypeError: no implementation found for <function array_repr at 0x105692e18> on types that implement __array_function__: [<class '__main__.Sub'>]
TypeError
def array_str(a, max_line_width=None, precision=None, suppress_small=None): """ Return a string representation of the data in an array. The data in the array is returned as a single string. This function is similar to `array_repr`, the difference being that `array_repr` also returns information on the kind of array and its data type. Parameters ---------- a : ndarray Input array. max_line_width : int, optional Inserts newlines if text is longer than `max_line_width`. The default is, indirectly, 75. precision : int, optional Floating point precision. Default is the current printing precision (usually 8), which can be altered using `set_printoptions`. suppress_small : bool, optional Represent numbers "very close" to zero as zero; default is False. Very close is defined by precision: if the precision is 8, e.g., numbers smaller (in absolute value) than 5e-9 are represented as zero. See Also -------- array2string, array_repr, set_printoptions Examples -------- >>> np.array_str(np.arange(3)) '[0 1 2]' """ return _array_str_implementation(a, max_line_width, precision, suppress_small)
def array_str(a, max_line_width=None, precision=None, suppress_small=None): """ Return a string representation of the data in an array. The data in the array is returned as a single string. This function is similar to `array_repr`, the difference being that `array_repr` also returns information on the kind of array and its data type. Parameters ---------- a : ndarray Input array. max_line_width : int, optional Inserts newlines if text is longer than `max_line_width`. The default is, indirectly, 75. precision : int, optional Floating point precision. Default is the current printing precision (usually 8), which can be altered using `set_printoptions`. suppress_small : bool, optional Represent numbers "very close" to zero as zero; default is False. Very close is defined by precision: if the precision is 8, e.g., numbers smaller (in absolute value) than 5e-9 are represented as zero. See Also -------- array2string, array_repr, set_printoptions Examples -------- >>> np.array_str(np.arange(3)) '[0 1 2]' """ if _format_options["legacy"] == "1.13" and a.shape == () and not a.dtype.names: return str(a.item()) # the str of 0d arrays is a special case: It should appear like a scalar, # so floats are not truncated by `precision`, and strings are not wrapped # in quotes. So we return the str of the scalar value. if a.shape == (): # obtain a scalar and call str on it, avoiding problems for subclasses # for which indexing with () returns a 0d instead of a scalar by using # ndarray's getindex. Also guard against recursive 0d object arrays. return _guarded_str(np.ndarray.__getitem__(a, ())) return array2string(a, max_line_width, precision, suppress_small, " ", "")
https://github.com/numpy/numpy/issues/12162
In [1]: import numpy as np In [2]: class Sub(np.ndarray): ...: def __array_function__(*args, **kwargs): ...: return NotImplemented ...: In [3]: repr(np.array(1).view(Sub)) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-6-d6ff958f4fcf> in <module>() ----> 1 repr(np.array(1).view(Sub)) ~/dev/numpy/numpy/core/overrides.py in public_api(*args, **kwargs) 149 relevant_args = dispatcher(*args, **kwargs) 150 return array_function_implementation_or_override( --> 151 implementation, public_api, relevant_args, args, kwargs) 152 return public_api 153 ~/dev/numpy/numpy/core/overrides.py in array_function_implementation_or_override(implementation, public_api, relevant_args, args, kwargs) 108 raise TypeError('no implementation found for {} on types that implement ' 109 '__array_function__: {}' --> 110 .format(public_api, list(map(type, overloaded_args)))) 111 112 TypeError: no implementation found for <function array_repr at 0x105692e18> on types that implement __array_function__: [<class '__main__.Sub'>]
TypeError
def set_string_function(f, repr=True): """ Set a Python function to be used when pretty printing arrays. Parameters ---------- f : function or None Function to be used to pretty print arrays. The function should expect a single array argument and return a string of the representation of the array. If None, the function is reset to the default NumPy function to print arrays. repr : bool, optional If True (default), the function for pretty printing (``__repr__``) is set, if False the function that returns the default string representation (``__str__``) is set. See Also -------- set_printoptions, get_printoptions Examples -------- >>> def pprint(arr): ... return 'HA! - What are you going to do now?' ... >>> np.set_string_function(pprint) >>> a = np.arange(10) >>> a HA! - What are you going to do now? >>> print(a) [0 1 2 3 4 5 6 7 8 9] We can reset the function to the default: >>> np.set_string_function(None) >>> a array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) `repr` affects either pretty printing or normal string representation. Note that ``__repr__`` is still affected by setting ``__str__`` because the width of each array element in the returned string becomes equal to the length of the result of ``__str__()``. >>> x = np.arange(4) >>> np.set_string_function(lambda x:'random', repr=False) >>> x.__str__() 'random' >>> x.__repr__() 'array([ 0, 1, 2, 3])' """ if f is None: if repr: return multiarray.set_string_function(_default_array_repr, 1) else: return multiarray.set_string_function(_default_array_str, 0) else: return multiarray.set_string_function(f, repr)
def set_string_function(f, repr=True): """ Set a Python function to be used when pretty printing arrays. Parameters ---------- f : function or None Function to be used to pretty print arrays. The function should expect a single array argument and return a string of the representation of the array. If None, the function is reset to the default NumPy function to print arrays. repr : bool, optional If True (default), the function for pretty printing (``__repr__``) is set, if False the function that returns the default string representation (``__str__``) is set. See Also -------- set_printoptions, get_printoptions Examples -------- >>> def pprint(arr): ... return 'HA! - What are you going to do now?' ... >>> np.set_string_function(pprint) >>> a = np.arange(10) >>> a HA! - What are you going to do now? >>> print(a) [0 1 2 3 4 5 6 7 8 9] We can reset the function to the default: >>> np.set_string_function(None) >>> a array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) `repr` affects either pretty printing or normal string representation. Note that ``__repr__`` is still affected by setting ``__str__`` because the width of each array element in the returned string becomes equal to the length of the result of ``__str__()``. >>> x = np.arange(4) >>> np.set_string_function(lambda x:'random', repr=False) >>> x.__str__() 'random' >>> x.__repr__() 'array([ 0, 1, 2, 3])' """ if f is None: if repr: return multiarray.set_string_function(array_repr, 1) else: return multiarray.set_string_function(array_str, 0) else: return multiarray.set_string_function(f, repr)
https://github.com/numpy/numpy/issues/12162
In [1]: import numpy as np In [2]: class Sub(np.ndarray): ...: def __array_function__(*args, **kwargs): ...: return NotImplemented ...: In [3]: repr(np.array(1).view(Sub)) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-6-d6ff958f4fcf> in <module>() ----> 1 repr(np.array(1).view(Sub)) ~/dev/numpy/numpy/core/overrides.py in public_api(*args, **kwargs) 149 relevant_args = dispatcher(*args, **kwargs) 150 return array_function_implementation_or_override( --> 151 implementation, public_api, relevant_args, args, kwargs) 152 return public_api 153 ~/dev/numpy/numpy/core/overrides.py in array_function_implementation_or_override(implementation, public_api, relevant_args, args, kwargs) 108 raise TypeError('no implementation found for {} on types that implement ' 109 '__array_function__: {}' --> 110 .format(public_api, list(map(type, overloaded_args)))) 111 112 TypeError: no implementation found for <function array_repr at 0x105692e18> on types that implement __array_function__: [<class '__main__.Sub'>]
TypeError
def array_function_dispatch(dispatcher, module=None, verify=True): """Decorator for adding dispatch with the __array_function__ protocol.""" def decorator(implementation): # TODO: only do this check when the appropriate flag is enabled or for # a dev install. We want this check for testing but don't want to # slow down all numpy imports. if verify: verify_matching_signatures(implementation, dispatcher) @functools.wraps(implementation) def public_api(*args, **kwargs): relevant_args = dispatcher(*args, **kwargs) return array_function_implementation_or_override( implementation, public_api, relevant_args, args, kwargs ) if module is not None: public_api.__module__ = module # TODO: remove this when we drop Python 2 support (functools.wraps # adds __wrapped__ automatically in later versions) public_api.__wrapped__ = implementation return public_api return decorator
def array_function_dispatch(dispatcher, module=None, verify=True): """Decorator for adding dispatch with the __array_function__ protocol.""" def decorator(implementation): # TODO: only do this check when the appropriate flag is enabled or for # a dev install. We want this check for testing but don't want to # slow down all numpy imports. if verify: verify_matching_signatures(implementation, dispatcher) @functools.wraps(implementation) def public_api(*args, **kwargs): relevant_args = dispatcher(*args, **kwargs) return array_function_implementation_or_override( implementation, public_api, relevant_args, args, kwargs ) if module is not None: public_api.__module__ = module return public_api return decorator
https://github.com/numpy/numpy/issues/12162
In [1]: import numpy as np In [2]: class Sub(np.ndarray): ...: def __array_function__(*args, **kwargs): ...: return NotImplemented ...: In [3]: repr(np.array(1).view(Sub)) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-6-d6ff958f4fcf> in <module>() ----> 1 repr(np.array(1).view(Sub)) ~/dev/numpy/numpy/core/overrides.py in public_api(*args, **kwargs) 149 relevant_args = dispatcher(*args, **kwargs) 150 return array_function_implementation_or_override( --> 151 implementation, public_api, relevant_args, args, kwargs) 152 return public_api 153 ~/dev/numpy/numpy/core/overrides.py in array_function_implementation_or_override(implementation, public_api, relevant_args, args, kwargs) 108 raise TypeError('no implementation found for {} on types that implement ' 109 '__array_function__: {}' --> 110 .format(public_api, list(map(type, overloaded_args)))) 111 112 TypeError: no implementation found for <function array_repr at 0x105692e18> on types that implement __array_function__: [<class '__main__.Sub'>]
TypeError
def decorator(implementation): # TODO: only do this check when the appropriate flag is enabled or for # a dev install. We want this check for testing but don't want to # slow down all numpy imports. if verify: verify_matching_signatures(implementation, dispatcher) @functools.wraps(implementation) def public_api(*args, **kwargs): relevant_args = dispatcher(*args, **kwargs) return array_function_implementation_or_override( implementation, public_api, relevant_args, args, kwargs ) if module is not None: public_api.__module__ = module # TODO: remove this when we drop Python 2 support (functools.wraps # adds __wrapped__ automatically in later versions) public_api.__wrapped__ = implementation return public_api
def decorator(implementation): # TODO: only do this check when the appropriate flag is enabled or for # a dev install. We want this check for testing but don't want to # slow down all numpy imports. if verify: verify_matching_signatures(implementation, dispatcher) @functools.wraps(implementation) def public_api(*args, **kwargs): relevant_args = dispatcher(*args, **kwargs) return array_function_implementation_or_override( implementation, public_api, relevant_args, args, kwargs ) if module is not None: public_api.__module__ = module return public_api
https://github.com/numpy/numpy/issues/12162
In [1]: import numpy as np In [2]: class Sub(np.ndarray): ...: def __array_function__(*args, **kwargs): ...: return NotImplemented ...: In [3]: repr(np.array(1).view(Sub)) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-6-d6ff958f4fcf> in <module>() ----> 1 repr(np.array(1).view(Sub)) ~/dev/numpy/numpy/core/overrides.py in public_api(*args, **kwargs) 149 relevant_args = dispatcher(*args, **kwargs) 150 return array_function_implementation_or_override( --> 151 implementation, public_api, relevant_args, args, kwargs) 152 return public_api 153 ~/dev/numpy/numpy/core/overrides.py in array_function_implementation_or_override(implementation, public_api, relevant_args, args, kwargs) 108 raise TypeError('no implementation found for {} on types that implement ' 109 '__array_function__: {}' --> 110 .format(public_api, list(map(type, overloaded_args)))) 111 112 TypeError: no implementation found for <function array_repr at 0x105692e18> on types that implement __array_function__: [<class '__main__.Sub'>]
TypeError
def _check_fill_value(fill_value, ndtype): """ Private function validating the given `fill_value` for the given dtype. If fill_value is None, it is set to the default corresponding to the dtype. If fill_value is not None, its value is forced to the given dtype. The result is always a 0d array. """ ndtype = np.dtype(ndtype) fields = ndtype.fields if fill_value is None: fill_value = default_fill_value(ndtype) elif fields: fdtype = [(_[0], _[1]) for _ in ndtype.descr] if isinstance(fill_value, (ndarray, np.void)): try: fill_value = np.array(fill_value, copy=False, dtype=fdtype) except ValueError: err_msg = "Unable to transform %s to dtype %s" raise ValueError(err_msg % (fill_value, fdtype)) else: fill_value = np.asarray(fill_value, dtype=object) fill_value = np.array( _recursive_set_fill_value(fill_value, ndtype), dtype=ndtype ) else: if isinstance(fill_value, basestring) and (ndtype.char not in "OSVU"): # Note this check doesn't work if fill_value is not a scalar err_msg = "Cannot set fill value of string with array of dtype %s" raise TypeError(err_msg % ndtype) else: # In case we want to convert 1e20 to int. # Also in case of converting string arrays. try: fill_value = np.array(fill_value, copy=False, dtype=ndtype) except (OverflowError, ValueError): # Raise TypeError instead of OverflowError or ValueError. # OverflowError is seldom used, and the real problem here is # that the passed fill_value is not compatible with the ndtype. err_msg = "Cannot convert fill_value %s to dtype %s" raise TypeError(err_msg % (fill_value, ndtype)) return np.array(fill_value)
def _check_fill_value(fill_value, ndtype): """ Private function validating the given `fill_value` for the given dtype. If fill_value is None, it is set to the default corresponding to the dtype. If fill_value is not None, its value is forced to the given dtype. The result is always a 0d array. """ ndtype = np.dtype(ndtype) fields = ndtype.fields if fill_value is None: fill_value = default_fill_value(ndtype) elif fields: fdtype = [(_[0], _[1]) for _ in ndtype.descr] if isinstance(fill_value, (ndarray, np.void)): try: fill_value = np.array(fill_value, copy=False, dtype=fdtype) except ValueError: err_msg = "Unable to transform %s to dtype %s" raise ValueError(err_msg % (fill_value, fdtype)) else: fill_value = np.asarray(fill_value, dtype=object) fill_value = np.array( _recursive_set_fill_value(fill_value, ndtype), dtype=ndtype ) else: if isinstance(fill_value, basestring) and (ndtype.char not in "OSVU"): err_msg = "Cannot set fill value of string with array of dtype %s" raise TypeError(err_msg % ndtype) else: # In case we want to convert 1e20 to int. try: fill_value = np.array(fill_value, copy=False, dtype=ndtype) except OverflowError: # Raise TypeError instead of OverflowError. OverflowError # is seldom used, and the real problem here is that the # passed fill_value is not compatible with the ndtype. err_msg = "Fill value %s overflows dtype %s" raise TypeError(err_msg % (fill_value, ndtype)) return np.array(fill_value)
https://github.com/numpy/numpy/issues/12248
(np.ma.array(['A', 'B', 'C'], fill_value='N') == 'A') | (np.ma.array(['A', 'B', 'C'], fill_value='N') == 'A') Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Users/tom/miniconda3/envs/np1153/lib/python3.6/site-packages/numpy/ma/core.py", line 3016, in __array_finalize__ self._fill_value = _check_fill_value(self._fill_value, self.dtype) File "/Users/tom/miniconda3/envs/np1153/lib/python3.6/site-packages/numpy/ma/core.py", line 476, in _check_fill_value fill_value = np.array(fill_value, copy=False, dtype=ndtype) ValueError: invalid literal for int() with base 10: 'N'
ValueError
def _comparison(self, other, compare): """Compare self with other using operator.eq or operator.ne. When either of the elements is masked, the result is masked as well, but the underlying boolean data are still set, with self and other considered equal if both are masked, and unequal otherwise. For structured arrays, all fields are combined, with masked values ignored. The result is masked if all fields were masked, with self and other considered equal only if both were fully masked. """ omask = getmask(other) smask = self.mask mask = mask_or(smask, omask, copy=True) odata = getdata(other) if mask.dtype.names is not None: # For possibly masked structured arrays we need to be careful, # since the standard structured array comparison will use all # fields, masked or not. To avoid masked fields influencing the # outcome, we set all masked fields in self to other, so they'll # count as equal. To prepare, we ensure we have the right shape. broadcast_shape = np.broadcast(self, odata).shape sbroadcast = np.broadcast_to(self, broadcast_shape, subok=True) sbroadcast._mask = mask sdata = sbroadcast.filled(odata) # Now take care of the mask; the merged mask should have an item # masked if all fields were masked (in one and/or other). mask = mask == np.ones((), mask.dtype) else: # For regular arrays, just use the data as they come. sdata = self.data check = compare(sdata, odata) if isinstance(check, (np.bool_, bool)): return masked if mask else check if mask is not nomask: # Adjust elements that were masked, which should be treated # as equal if masked in both, unequal if masked in one. # Note that this works automatically for structured arrays too. check = np.where(mask, compare(smask, omask), check) if mask.shape != check.shape: # Guarantee consistency of the shape, making a copy since the # the mask may need to get written to later. mask = np.broadcast_to(mask, check.shape).copy() check = check.view(type(self)) check._update_from(self) check._mask = mask # Cast fill value to bool_ if needed. If it cannot be cast, the # default boolean fill value is used. if check._fill_value is not None: try: fill = _check_fill_value(check._fill_value, np.bool_) except (TypeError, ValueError): fill = _check_fill_value(None, np.bool_) check._fill_value = fill return check
def _comparison(self, other, compare): """Compare self with other using operator.eq or operator.ne. When either of the elements is masked, the result is masked as well, but the underlying boolean data are still set, with self and other considered equal if both are masked, and unequal otherwise. For structured arrays, all fields are combined, with masked values ignored. The result is masked if all fields were masked, with self and other considered equal only if both were fully masked. """ omask = getmask(other) smask = self.mask mask = mask_or(smask, omask, copy=True) odata = getdata(other) if mask.dtype.names is not None: # For possibly masked structured arrays we need to be careful, # since the standard structured array comparison will use all # fields, masked or not. To avoid masked fields influencing the # outcome, we set all masked fields in self to other, so they'll # count as equal. To prepare, we ensure we have the right shape. broadcast_shape = np.broadcast(self, odata).shape sbroadcast = np.broadcast_to(self, broadcast_shape, subok=True) sbroadcast._mask = mask sdata = sbroadcast.filled(odata) # Now take care of the mask; the merged mask should have an item # masked if all fields were masked (in one and/or other). mask = mask == np.ones((), mask.dtype) else: # For regular arrays, just use the data as they come. sdata = self.data check = compare(sdata, odata) if isinstance(check, (np.bool_, bool)): return masked if mask else check if mask is not nomask: # Adjust elements that were masked, which should be treated # as equal if masked in both, unequal if masked in one. # Note that this works automatically for structured arrays too. check = np.where(mask, compare(smask, omask), check) if mask.shape != check.shape: # Guarantee consistency of the shape, making a copy since the # the mask may need to get written to later. mask = np.broadcast_to(mask, check.shape).copy() check = check.view(type(self)) check._update_from(self) check._mask = mask return check
https://github.com/numpy/numpy/issues/12248
(np.ma.array(['A', 'B', 'C'], fill_value='N') == 'A') | (np.ma.array(['A', 'B', 'C'], fill_value='N') == 'A') Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Users/tom/miniconda3/envs/np1153/lib/python3.6/site-packages/numpy/ma/core.py", line 3016, in __array_finalize__ self._fill_value = _check_fill_value(self._fill_value, self.dtype) File "/Users/tom/miniconda3/envs/np1153/lib/python3.6/site-packages/numpy/ma/core.py", line 476, in _check_fill_value fill_value = np.array(fill_value, copy=False, dtype=ndtype) ValueError: invalid literal for int() with base 10: 'N'
ValueError
def _comparison(self, other, compare): """Compare self with other using operator.eq or operator.ne. When either of the elements is masked, the result is masked as well, but the underlying boolean data are still set, with self and other considered equal if both are masked, and unequal otherwise. For structured arrays, all fields are combined, with masked values ignored. The result is masked if all fields were masked, with self and other considered equal only if both were fully masked. """ omask = getmask(other) smask = self.mask mask = mask_or(smask, omask, copy=True) odata = getdata(other) if mask.dtype.names: # For possibly masked structured arrays we need to be careful, # since the standard structured array comparison will use all # fields, masked or not. To avoid masked fields influencing the # outcome, we set all masked fields in self to other, so they'll # count as equal. To prepare, we ensure we have the right shape. broadcast_shape = np.broadcast(self, odata).shape sbroadcast = np.broadcast_to(self, broadcast_shape, subok=True) sbroadcast._mask = mask sdata = sbroadcast.filled(odata) # Now take care of the mask; the merged mask should have an item # masked if all fields were masked (in one and/or other). mask = mask == np.ones((), mask.dtype) else: # For regular arrays, just use the data as they come. sdata = self.data check = compare(sdata, odata) if isinstance(check, (np.bool_, bool)): return masked if mask else check if mask is not nomask: # Adjust elements that were masked, which should be treated # as equal if masked in both, unequal if masked in one. # Note that this works automatically for structured arrays too. check = np.where(mask, compare(smask, omask), check) if mask.shape != check.shape: # Guarantee consistency of the shape, making a copy since the # the mask may need to get written to later. mask = np.broadcast_to(mask, check.shape).copy() check = check.view(type(self)) check._update_from(self) check._mask = mask # Cast fill value to bool_ if needed. If it cannot be cast, the # default boolean fill value is used. if check._fill_value is not None: try: fill = _check_fill_value(check._fill_value, np.bool_) except (TypeError, ValueError): fill = _check_fill_value(None, np.bool_) check._fill_value = fill return check
def _comparison(self, other, compare): """Compare self with other using operator.eq or operator.ne. When either of the elements is masked, the result is masked as well, but the underlying boolean data are still set, with self and other considered equal if both are masked, and unequal otherwise. For structured arrays, all fields are combined, with masked values ignored. The result is masked if all fields were masked, with self and other considered equal only if both were fully masked. """ omask = getmask(other) smask = self.mask mask = mask_or(smask, omask, copy=True) odata = getdata(other) if mask.dtype.names: # For possibly masked structured arrays we need to be careful, # since the standard structured array comparison will use all # fields, masked or not. To avoid masked fields influencing the # outcome, we set all masked fields in self to other, so they'll # count as equal. To prepare, we ensure we have the right shape. broadcast_shape = np.broadcast(self, odata).shape sbroadcast = np.broadcast_to(self, broadcast_shape, subok=True) sbroadcast._mask = mask sdata = sbroadcast.filled(odata) # Now take care of the mask; the merged mask should have an item # masked if all fields were masked (in one and/or other). mask = mask == np.ones((), mask.dtype) else: # For regular arrays, just use the data as they come. sdata = self.data check = compare(sdata, odata) if isinstance(check, (np.bool_, bool)): return masked if mask else check if mask is not nomask: # Adjust elements that were masked, which should be treated # as equal if masked in both, unequal if masked in one. # Note that this works automatically for structured arrays too. check = np.where(mask, compare(smask, omask), check) if mask.shape != check.shape: # Guarantee consistency of the shape, making a copy since the # the mask may need to get written to later. mask = np.broadcast_to(mask, check.shape).copy() check = check.view(type(self)) check._update_from(self) check._mask = mask return check
https://github.com/numpy/numpy/issues/12248
(np.ma.array(['A', 'B', 'C'], fill_value='N') == 'A') | (np.ma.array(['A', 'B', 'C'], fill_value='N') == 'A') Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Users/tom/miniconda3/envs/np1153/lib/python3.6/site-packages/numpy/ma/core.py", line 3016, in __array_finalize__ self._fill_value = _check_fill_value(self._fill_value, self.dtype) File "/Users/tom/miniconda3/envs/np1153/lib/python3.6/site-packages/numpy/ma/core.py", line 476, in _check_fill_value fill_value = np.array(fill_value, copy=False, dtype=ndtype) ValueError: invalid literal for int() with base 10: 'N'
ValueError