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IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
ResourceAllocation.get_jobs
def get_jobs(self, name=None): """Retrieves jobs running on this resource in its instance. Args: name (str, optional): Only return jobs containing property **name** that matches `name`. `name` can be a regular expression. If `name` is not supplied, then all jobs are returned. Returns: list(Job): A list of jobs matching the given `name`. .. note:: If ``applicationResource`` is `False` an empty list is returned. .. versionadded:: 1.9 """ if self.applicationResource: return self._get_elements(self.jobs, 'jobs', Job, None, name) else: return []
python
def get_jobs(self, name=None): """Retrieves jobs running on this resource in its instance. Args: name (str, optional): Only return jobs containing property **name** that matches `name`. `name` can be a regular expression. If `name` is not supplied, then all jobs are returned. Returns: list(Job): A list of jobs matching the given `name`. .. note:: If ``applicationResource`` is `False` an empty list is returned. .. versionadded:: 1.9 """ if self.applicationResource: return self._get_elements(self.jobs, 'jobs', Job, None, name) else: return []
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Retrieves jobs running on this resource in its instance. Args: name (str, optional): Only return jobs containing property **name** that matches `name`. `name` can be a regular expression. If `name` is not supplied, then all jobs are returned. Returns: list(Job): A list of jobs matching the given `name`. .. note:: If ``applicationResource`` is `False` an empty list is returned. .. versionadded:: 1.9
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L1345-L1361
train
44,000
IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
ExportedStream.get_operator_output_port
def get_operator_output_port(self): """Get the output port of this exported stream. Returns: OperatorOutputPort: Output port of this exported stream. """ return OperatorOutputPort(self.rest_client.make_request(self.operatorOutputPort), self.rest_client)
python
def get_operator_output_port(self): """Get the output port of this exported stream. Returns: OperatorOutputPort: Output port of this exported stream. """ return OperatorOutputPort(self.rest_client.make_request(self.operatorOutputPort), self.rest_client)
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L1435-L1441
train
44,001
IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
ExportedStream._as_published_topic
def _as_published_topic(self): """This stream as a PublishedTopic if it is published otherwise None """ oop = self.get_operator_output_port() if not hasattr(oop, 'export'): return export = oop.export if export['type'] != 'properties': return seen_export_type = False topic = None for p in export['properties']: if p['type'] != 'rstring': continue if p['name'] == '__spl_exportType': if p['values'] == ['"topic"']: seen_export_type = True else: return if p['name'] == '__spl_topic': topic = p['values'][0] if seen_export_type and topic is not None: schema = None if hasattr(oop, 'tupleAttributes'): ta_url = oop.tupleAttributes ta_resp = self.rest_client.make_request(ta_url) schema = streamsx.topology.schema.StreamSchema(ta_resp['splType']) return PublishedTopic(topic[1:-1], schema) return
python
def _as_published_topic(self): """This stream as a PublishedTopic if it is published otherwise None """ oop = self.get_operator_output_port() if not hasattr(oop, 'export'): return export = oop.export if export['type'] != 'properties': return seen_export_type = False topic = None for p in export['properties']: if p['type'] != 'rstring': continue if p['name'] == '__spl_exportType': if p['values'] == ['"topic"']: seen_export_type = True else: return if p['name'] == '__spl_topic': topic = p['values'][0] if seen_export_type and topic is not None: schema = None if hasattr(oop, 'tupleAttributes'): ta_url = oop.tupleAttributes ta_resp = self.rest_client.make_request(ta_url) schema = streamsx.topology.schema.StreamSchema(ta_resp['splType']) return PublishedTopic(topic[1:-1], schema) return
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L1443-L1476
train
44,002
IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
Instance.of_service
def of_service(config): """Connect to an IBM Streams service instance running in IBM Cloud Private for Data. The instance is specified in `config`. The configuration may be code injected from the list of services in a Jupyter notebook running in ICPD or manually created. The code that selects a service instance by name is:: # Two lines are code injected in a Jupyter notebook by selecting the service instance from icpd_core import ipcd_util cfg = icpd_util.get_service_details(name='instanceName') instance = Instance.of_service(cfg) SSL host verification is disabled by setting :py:const:`~streamsx.topology.context.ConfigParams.SSL_VERIFY` to ``False`` within `config` before calling this method:: cfg[ConfigParams.SSL_VERIFY] = False instance = Instance.of_service(cfg) Args: config(dict): Configuration of IBM Streams service instance. Returns: Instance: Instance representing for IBM Streams service instance. .. note:: Only supported when running within the ICPD cluster, for example in a Jupyter notebook within a ICPD project. .. versionadded:: 1.12 """ service = Instance._find_service_def(config) if not service: raise ValueError() endpoint = service['connection_info'].get('serviceRestEndpoint') resource_url, name = Instance._root_from_endpoint(endpoint) sc = streamsx.rest.StreamsConnection(resource_url=resource_url, auth=_ICPDAuthHandler(name, service['service_token'])) if streamsx.topology.context.ConfigParams.SSL_VERIFY in config: sc.session.verify = config[streamsx.topology.context.ConfigParams.SSL_VERIFY] return sc.get_instance(name)
python
def of_service(config): """Connect to an IBM Streams service instance running in IBM Cloud Private for Data. The instance is specified in `config`. The configuration may be code injected from the list of services in a Jupyter notebook running in ICPD or manually created. The code that selects a service instance by name is:: # Two lines are code injected in a Jupyter notebook by selecting the service instance from icpd_core import ipcd_util cfg = icpd_util.get_service_details(name='instanceName') instance = Instance.of_service(cfg) SSL host verification is disabled by setting :py:const:`~streamsx.topology.context.ConfigParams.SSL_VERIFY` to ``False`` within `config` before calling this method:: cfg[ConfigParams.SSL_VERIFY] = False instance = Instance.of_service(cfg) Args: config(dict): Configuration of IBM Streams service instance. Returns: Instance: Instance representing for IBM Streams service instance. .. note:: Only supported when running within the ICPD cluster, for example in a Jupyter notebook within a ICPD project. .. versionadded:: 1.12 """ service = Instance._find_service_def(config) if not service: raise ValueError() endpoint = service['connection_info'].get('serviceRestEndpoint') resource_url, name = Instance._root_from_endpoint(endpoint) sc = streamsx.rest.StreamsConnection(resource_url=resource_url, auth=_ICPDAuthHandler(name, service['service_token'])) if streamsx.topology.context.ConfigParams.SSL_VERIFY in config: sc.session.verify = config[streamsx.topology.context.ConfigParams.SSL_VERIFY] return sc.get_instance(name)
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L1541-L1579
train
44,003
IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
Instance.get_job
def get_job(self, id): """Retrieves a job matching the given `id` Args: id (str): Job `id` to match. Returns: Job: Job matching the given `id` Raises: ValueError: No resource matches given `id` or multiple resources matching given `id` """ return self._get_element_by_id(self.jobs, 'jobs', Job, str(id))
python
def get_job(self, id): """Retrieves a job matching the given `id` Args: id (str): Job `id` to match. Returns: Job: Job matching the given `id` Raises: ValueError: No resource matches given `id` or multiple resources matching given `id` """ return self._get_element_by_id(self.jobs, 'jobs', Job, str(id))
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L1717-L1729
train
44,004
IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
Instance.get_published_topics
def get_published_topics(self): """Get a list of published topics for this instance. Streams applications publish streams to a a topic that can be subscribed to by other applications. This allows a microservice approach where publishers and subscribers are independent of each other. A published stream has a topic and a schema. It is recommended that a topic is only associated with a single schema. Streams may be published and subscribed by applications regardless of the implementation language. For example a Python application can publish a stream of JSON tuples that are subscribed to by SPL and Java applications. Returns: list(PublishedTopic): List of currently published topics. """ published_topics = [] # A topic can be published multiple times # (typically with the same schema) but the # returned list only wants to contain a topic,schema # pair once. I.e. the list of topics being published is # being returned, not the list of streams. seen_topics = {} for es in self.get_exported_streams(): pt = es._as_published_topic() if pt is not None: if pt.topic in seen_topics: if pt.schema is None: continue if pt.schema in seen_topics[pt.topic]: continue seen_topics[pt.topic].append(pt.schema) else: seen_topics[pt.topic] = [pt.schema] published_topics.append(pt) return published_topics
python
def get_published_topics(self): """Get a list of published topics for this instance. Streams applications publish streams to a a topic that can be subscribed to by other applications. This allows a microservice approach where publishers and subscribers are independent of each other. A published stream has a topic and a schema. It is recommended that a topic is only associated with a single schema. Streams may be published and subscribed by applications regardless of the implementation language. For example a Python application can publish a stream of JSON tuples that are subscribed to by SPL and Java applications. Returns: list(PublishedTopic): List of currently published topics. """ published_topics = [] # A topic can be published multiple times # (typically with the same schema) but the # returned list only wants to contain a topic,schema # pair once. I.e. the list of topics being published is # being returned, not the list of streams. seen_topics = {} for es in self.get_exported_streams(): pt = es._as_published_topic() if pt is not None: if pt.topic in seen_topics: if pt.schema is None: continue if pt.schema in seen_topics[pt.topic]: continue seen_topics[pt.topic].append(pt.schema) else: seen_topics[pt.topic] = [pt.schema] published_topics.append(pt) return published_topics
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L1765-L1802
train
44,005
IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
Instance.get_application_configurations
def get_application_configurations(self, name=None): """Retrieves application configurations for this instance. Args: name (str, optional): Only return application configurations containing property **name** that matches `name`. `name` can be a regular expression. If `name` is not supplied, then all application configurations are returned. Returns: list(ApplicationConfiguration): A list of application configurations matching the given `name`. .. versionadded 1.12 """ if hasattr(self, 'applicationConfigurations'): return self._get_elements(self.applicationConfigurations, 'applicationConfigurations', ApplicationConfiguration, None, name)
python
def get_application_configurations(self, name=None): """Retrieves application configurations for this instance. Args: name (str, optional): Only return application configurations containing property **name** that matches `name`. `name` can be a regular expression. If `name` is not supplied, then all application configurations are returned. Returns: list(ApplicationConfiguration): A list of application configurations matching the given `name`. .. versionadded 1.12 """ if hasattr(self, 'applicationConfigurations'): return self._get_elements(self.applicationConfigurations, 'applicationConfigurations', ApplicationConfiguration, None, name)
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L1844-L1857
train
44,006
IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
Instance.create_application_configuration
def create_application_configuration(self, name, properties, description=None): """Create an application configuration. Args: name (str, optional): Only return application configurations containing property **name** that matches `name`. `name` can be a .. versionadded 1.12 """ if not hasattr(self, 'applicationConfigurations'): raise NotImplementedError() cv = ApplicationConfiguration._props(name, properties, description) res = self.rest_client.session.post(self.applicationConfigurations, headers = {'Accept' : 'application/json'}, json=cv) _handle_http_errors(res) return ApplicationConfiguration(res.json(), self.rest_client)
python
def create_application_configuration(self, name, properties, description=None): """Create an application configuration. Args: name (str, optional): Only return application configurations containing property **name** that matches `name`. `name` can be a .. versionadded 1.12 """ if not hasattr(self, 'applicationConfigurations'): raise NotImplementedError() cv = ApplicationConfiguration._props(name, properties, description) res = self.rest_client.session.post(self.applicationConfigurations, headers = {'Accept' : 'application/json'}, json=cv) _handle_http_errors(res) return ApplicationConfiguration(res.json(), self.rest_client)
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L1859-L1875
train
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IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
_StreamingAnalyticsServiceV2Delegator._get_jobs_url
def _get_jobs_url(self): """Get & save jobs URL from the status call.""" if self._jobs_url is None: self.get_instance_status() if self._jobs_url is None: raise ValueError("Cannot obtain jobs URL") return self._jobs_url
python
def _get_jobs_url(self): """Get & save jobs URL from the status call.""" if self._jobs_url is None: self.get_instance_status() if self._jobs_url is None: raise ValueError("Cannot obtain jobs URL") return self._jobs_url
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abd67b4757120f6f805787fba390f53e9df9cdd8
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train
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IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
_StreamingAnalyticsServiceV1Delegator.start_instance
def start_instance(self): """Start the instance for this Streaming Analytics service. Returns: dict: JSON response for the instance start operation. """ start_url = self._get_url('start_path') res = self.rest_client.session.put(start_url, json={}) _handle_http_errors(res) return res.json()
python
def start_instance(self): """Start the instance for this Streaming Analytics service. Returns: dict: JSON response for the instance start operation. """ start_url = self._get_url('start_path') res = self.rest_client.session.put(start_url, json={}) _handle_http_errors(res) return res.json()
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L2286-L2295
train
44,009
IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
_StreamingAnalyticsServiceV1Delegator.stop_instance
def stop_instance(self): """Stop the instance for this Streaming Analytics service. Returns: dict: JSON response for the instance stop operation. """ stop_url = self._get_url('stop_path') res = self.rest_client.session.put(stop_url, json={}) _handle_http_errors(res) return res.json()
python
def stop_instance(self): """Stop the instance for this Streaming Analytics service. Returns: dict: JSON response for the instance stop operation. """ stop_url = self._get_url('stop_path') res = self.rest_client.session.put(stop_url, json={}) _handle_http_errors(res) return res.json()
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L2297-L2306
train
44,010
IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
_StreamingAnalyticsServiceV1Delegator.get_instance_status
def get_instance_status(self): """Get the status the instance for this Streaming Analytics service. Returns: dict: JSON response for the instance status operation. """ status_url = self._get_url('status_path') res = self.rest_client.session.get(status_url) _handle_http_errors(res) return res.json()
python
def get_instance_status(self): """Get the status the instance for this Streaming Analytics service. Returns: dict: JSON response for the instance status operation. """ status_url = self._get_url('status_path') res = self.rest_client.session.get(status_url) _handle_http_errors(res) return res.json()
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L2308-L2317
train
44,011
IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
_StreamsV4Delegator._cancel_job
def _cancel_job(self, job, force): """Cancel job using streamtool.""" import streamsx.st as st if st._has_local_install: return st._cancel_job(job.id, force, domain_id=job.get_instance().get_domain().id, instance_id=job.get_instance().id) return False
python
def _cancel_job(self, job, force): """Cancel job using streamtool.""" import streamsx.st as st if st._has_local_install: return st._cancel_job(job.id, force, domain_id=job.get_instance().get_domain().id, instance_id=job.get_instance().id) return False
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L2419-L2425
train
44,012
IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
ApplicationConfiguration.update
def update(self, properties=None, description=None): """Update this application configuration. To create or update a property provide its key-value pair in `properties`. To delete a property provide its key with the value ``None`` in properties. Args: properties (dict): Property values to be updated. If ``None`` the properties are unchanged. description (str): Description for the configuration. If ``None`` the description is unchanged. Returns: ApplicationConfiguration: self """ cv = ApplicationConfiguration._props(properties=properties, description=description) res = self.rest_client.session.patch(self.rest_self, headers = {'Accept' : 'application/json', 'Content-Type' : 'application/json'}, json=cv) _handle_http_errors(res) self.json_rep = res.json() return self
python
def update(self, properties=None, description=None): """Update this application configuration. To create or update a property provide its key-value pair in `properties`. To delete a property provide its key with the value ``None`` in properties. Args: properties (dict): Property values to be updated. If ``None`` the properties are unchanged. description (str): Description for the configuration. If ``None`` the description is unchanged. Returns: ApplicationConfiguration: self """ cv = ApplicationConfiguration._props(properties=properties, description=description) res = self.rest_client.session.patch(self.rest_self, headers = {'Accept' : 'application/json', 'Content-Type' : 'application/json'}, json=cv) _handle_http_errors(res) self.json_rep = res.json() return self
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Update this application configuration. To create or update a property provide its key-value pair in `properties`. To delete a property provide its key with the value ``None`` in properties. Args: properties (dict): Property values to be updated. If ``None`` the properties are unchanged. description (str): Description for the configuration. If ``None`` the description is unchanged. Returns: ApplicationConfiguration: self
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L2465-L2488
train
44,013
IBMStreams/pypi.streamsx
streamsx/rest_primitives.py
ApplicationConfiguration.delete
def delete(self): """Delete this application configuration. """ res = self.rest_client.session.delete(self.rest_self) _handle_http_errors(res)
python
def delete(self): """Delete this application configuration. """ res = self.rest_client.session.delete(self.rest_self) _handle_http_errors(res)
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Delete this application configuration.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest_primitives.py#L2490-L2494
train
44,014
IBMStreams/pypi.streamsx
streamsx/topology/schema.py
_normalize
def _normalize(schema, allow_none=True): """ Normalize a schema. """ if allow_none and schema is None: return schema if isinstance(schema, CommonSchema): return schema if isinstance(schema, StreamSchema): return schema if isinstance(schema, basestring): return StreamSchema(schema) py_types = { _spl_object: CommonSchema.Python, _spl_str: CommonSchema.String, json: CommonSchema.Json, } if schema in py_types: return py_types[schema] # With Python 3 allow a named tuple with type hints # to be used as a schema definition if sys.version_info.major == 3: import typing if isinstance(schema, type) and issubclass(schema, tuple): if hasattr(schema, '_fields') and hasattr(schema, '_field_types'): return _from_named_tuple(schema) raise ValueError("Unknown stream schema type:" + str(schema))
python
def _normalize(schema, allow_none=True): """ Normalize a schema. """ if allow_none and schema is None: return schema if isinstance(schema, CommonSchema): return schema if isinstance(schema, StreamSchema): return schema if isinstance(schema, basestring): return StreamSchema(schema) py_types = { _spl_object: CommonSchema.Python, _spl_str: CommonSchema.String, json: CommonSchema.Json, } if schema in py_types: return py_types[schema] # With Python 3 allow a named tuple with type hints # to be used as a schema definition if sys.version_info.major == 3: import typing if isinstance(schema, type) and issubclass(schema, tuple): if hasattr(schema, '_fields') and hasattr(schema, '_field_types'): return _from_named_tuple(schema) raise ValueError("Unknown stream schema type:" + str(schema))
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Normalize a schema.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/schema.py#L103-L134
train
44,015
IBMStreams/pypi.streamsx
streamsx/topology/schema.py
is_common
def is_common(schema): """ Is `schema` an common schema. Args: schema: Scheme to test. Returns: bool: ``True`` if schema is a common schema, otherwise ``False``. """ if isinstance(schema, StreamSchema): return schema.schema() in _SCHEMA_COMMON if isinstance(schema, CommonSchema): return True if isinstance(schema, basestring): return is_common(StreamSchema(schema)) return False
python
def is_common(schema): """ Is `schema` an common schema. Args: schema: Scheme to test. Returns: bool: ``True`` if schema is a common schema, otherwise ``False``. """ if isinstance(schema, StreamSchema): return schema.schema() in _SCHEMA_COMMON if isinstance(schema, CommonSchema): return True if isinstance(schema, basestring): return is_common(StreamSchema(schema)) return False
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Is `schema` an common schema. Args: schema: Scheme to test. Returns: bool: ``True`` if schema is a common schema, otherwise ``False``.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/schema.py#L136-L153
train
44,016
IBMStreams/pypi.streamsx
streamsx/topology/schema.py
StreamSchema._set
def _set(self, schema): """Set a schema from another schema""" if isinstance(schema, CommonSchema): self._spl_type = False self._schema = schema.schema() self._style = self._default_style() else: self._spl_type = schema._spl_type self._schema = schema._schema self._style = schema._style
python
def _set(self, schema): """Set a schema from another schema""" if isinstance(schema, CommonSchema): self._spl_type = False self._schema = schema.schema() self._style = self._default_style() else: self._spl_type = schema._spl_type self._schema = schema._schema self._style = schema._style
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/schema.py#L464-L473
train
44,017
IBMStreams/pypi.streamsx
streamsx/topology/schema.py
StreamSchema.as_tuple
def as_tuple(self, named=None): """ Create a structured schema that will pass stream tuples into callables as ``tuple`` instances. If this instance represents a common schema then it will be returned without modification. Stream tuples with common schemas are always passed according to their definition. **Passing as tuple** When `named` evaluates to ``False`` then each stream tuple will be passed as a ``tuple``. For example with a structured schema of ``tuple<rstring id, float64 value>`` a value is passed as ``('TempSensor', 27.4)`` and access to the first attribute is ``t[0]`` and the second as ``t[1]`` where ``t`` represents the passed value.. **Passing as named tuple** When `named` is ``True`` or a ``str`` then each stream tuple will be passed as a named tuple. For example with a structured schema of ``tuple<rstring id, float64 value>`` a value is passed as ``('TempSensor', 27.4)`` and access to the first attribute is ``t.id`` (or ``t[0]``) and the second as ``t.value`` (``t[1]``) where ``t`` represents the passed value. .. warning:: If an schema's attribute name is not a valid Python identifier or starts with an underscore then it will be renamed as positional name ``_n``. For example, with the schema ``tuple<int32 a, int32 def, int32 id>`` the field names are ``a``, ``_1``, ``_2``. The value of `named` is used as the name of the named tuple class with ``StreamTuple`` used when `named` is ``True``. It is not guaranteed that the class of the namedtuple is the same for all callables processing tuples with the same structured schema, only that the tuple is a named tuple with the correct field names. Args: named: Pass stream tuples as a named tuple. If not set then stream tuples are passed as instances of ``tuple``. Returns: StreamSchema: Schema passing stream tuples as ``tuple`` if allowed. .. versionadded:: 1.8 .. versionadded:: 1.9 Addition of `named` parameter. """ if not named: return self._copy(tuple) if named == True or isinstance(named, basestring): return self._copy(self._make_named_tuple(name=named)) return self._copy(tuple)
python
def as_tuple(self, named=None): """ Create a structured schema that will pass stream tuples into callables as ``tuple`` instances. If this instance represents a common schema then it will be returned without modification. Stream tuples with common schemas are always passed according to their definition. **Passing as tuple** When `named` evaluates to ``False`` then each stream tuple will be passed as a ``tuple``. For example with a structured schema of ``tuple<rstring id, float64 value>`` a value is passed as ``('TempSensor', 27.4)`` and access to the first attribute is ``t[0]`` and the second as ``t[1]`` where ``t`` represents the passed value.. **Passing as named tuple** When `named` is ``True`` or a ``str`` then each stream tuple will be passed as a named tuple. For example with a structured schema of ``tuple<rstring id, float64 value>`` a value is passed as ``('TempSensor', 27.4)`` and access to the first attribute is ``t.id`` (or ``t[0]``) and the second as ``t.value`` (``t[1]``) where ``t`` represents the passed value. .. warning:: If an schema's attribute name is not a valid Python identifier or starts with an underscore then it will be renamed as positional name ``_n``. For example, with the schema ``tuple<int32 a, int32 def, int32 id>`` the field names are ``a``, ``_1``, ``_2``. The value of `named` is used as the name of the named tuple class with ``StreamTuple`` used when `named` is ``True``. It is not guaranteed that the class of the namedtuple is the same for all callables processing tuples with the same structured schema, only that the tuple is a named tuple with the correct field names. Args: named: Pass stream tuples as a named tuple. If not set then stream tuples are passed as instances of ``tuple``. Returns: StreamSchema: Schema passing stream tuples as ``tuple`` if allowed. .. versionadded:: 1.8 .. versionadded:: 1.9 Addition of `named` parameter. """ if not named: return self._copy(tuple) if named == True or isinstance(named, basestring): return self._copy(self._make_named_tuple(name=named)) return self._copy(tuple)
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Create a structured schema that will pass stream tuples into callables as ``tuple`` instances. If this instance represents a common schema then it will be returned without modification. Stream tuples with common schemas are always passed according to their definition. **Passing as tuple** When `named` evaluates to ``False`` then each stream tuple will be passed as a ``tuple``. For example with a structured schema of ``tuple<rstring id, float64 value>`` a value is passed as ``('TempSensor', 27.4)`` and access to the first attribute is ``t[0]`` and the second as ``t[1]`` where ``t`` represents the passed value.. **Passing as named tuple** When `named` is ``True`` or a ``str`` then each stream tuple will be passed as a named tuple. For example with a structured schema of ``tuple<rstring id, float64 value>`` a value is passed as ``('TempSensor', 27.4)`` and access to the first attribute is ``t.id`` (or ``t[0]``) and the second as ``t.value`` (``t[1]``) where ``t`` represents the passed value. .. warning:: If an schema's attribute name is not a valid Python identifier or starts with an underscore then it will be renamed as positional name ``_n``. For example, with the schema ``tuple<int32 a, int32 def, int32 id>`` the field names are ``a``, ``_1``, ``_2``. The value of `named` is used as the name of the named tuple class with ``StreamTuple`` used when `named` is ``True``. It is not guaranteed that the class of the namedtuple is the same for all callables processing tuples with the same structured schema, only that the tuple is a named tuple with the correct field names. Args: named: Pass stream tuples as a named tuple. If not set then stream tuples are passed as instances of ``tuple``. Returns: StreamSchema: Schema passing stream tuples as ``tuple`` if allowed. .. versionadded:: 1.8 .. versionadded:: 1.9 Addition of `named` parameter.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/schema.py#L537-L594
train
44,018
IBMStreams/pypi.streamsx
streamsx/topology/schema.py
StreamSchema.extend
def extend(self, schema): """ Extend a structured schema by another. For example extending ``tuple<rstring id, timestamp ts, float64 value>`` with ``tuple<float32 score>`` results in ``tuple<rstring id, timestamp ts, float64 value, float32 score>``. Args: schema(StreamSchema): Schema to extend this schema by. Returns: StreamSchema: New schema that is an extension of this schema. """ if self._spl_type: raise TypeError("Not supported for declared SPL types") base = self.schema() extends = schema.schema() new_schema = base[:-1] + ',' + extends[6:] return StreamSchema(new_schema)
python
def extend(self, schema): """ Extend a structured schema by another. For example extending ``tuple<rstring id, timestamp ts, float64 value>`` with ``tuple<float32 score>`` results in ``tuple<rstring id, timestamp ts, float64 value, float32 score>``. Args: schema(StreamSchema): Schema to extend this schema by. Returns: StreamSchema: New schema that is an extension of this schema. """ if self._spl_type: raise TypeError("Not supported for declared SPL types") base = self.schema() extends = schema.schema() new_schema = base[:-1] + ',' + extends[6:] return StreamSchema(new_schema)
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Extend a structured schema by another. For example extending ``tuple<rstring id, timestamp ts, float64 value>`` with ``tuple<float32 score>`` results in ``tuple<rstring id, timestamp ts, float64 value, float32 score>``. Args: schema(StreamSchema): Schema to extend this schema by. Returns: StreamSchema: New schema that is an extension of this schema.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/schema.py#L627-L645
train
44,019
IBMStreams/pypi.streamsx
streamsx/topology/schema.py
StreamSchema._fnop_style
def _fnop_style(schema, op, name): """Set an operator's parameter representing the style of this schema.""" if is_common(schema): if name in op.params: del op.params[name] return if _is_pending(schema): ntp = 'pending' elif schema.style is tuple: ntp = 'tuple' elif schema.style is _spl_dict: ntp = 'dict' elif _is_namedtuple(schema.style) and hasattr(schema.style, '_splpy_namedtuple'): ntp = 'namedtuple:' + schema.style._splpy_namedtuple else: return op.params[name] = ntp
python
def _fnop_style(schema, op, name): """Set an operator's parameter representing the style of this schema.""" if is_common(schema): if name in op.params: del op.params[name] return if _is_pending(schema): ntp = 'pending' elif schema.style is tuple: ntp = 'tuple' elif schema.style is _spl_dict: ntp = 'dict' elif _is_namedtuple(schema.style) and hasattr(schema.style, '_splpy_namedtuple'): ntp = 'namedtuple:' + schema.style._splpy_namedtuple else: return op.params[name] = ntp
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/schema.py#L659-L675
train
44,020
raphaelm/django-hierarkey
hierarkey/forms.py
HierarkeyForm.save
def save(self) -> None: """ Saves all changed values to the database. """ for name, field in self.fields.items(): value = self.cleaned_data[name] if isinstance(value, UploadedFile): # Delete old file fname = self._s.get(name, as_type=File) if fname: try: default_storage.delete(fname.name) except OSError: # pragma: no cover logger.error('Deleting file %s failed.' % fname.name) # Create new file newname = default_storage.save(self.get_new_filename(value.name), value) value._name = newname self._s.set(name, value) elif isinstance(value, File): # file is unchanged continue elif isinstance(field, forms.FileField): # file is deleted fname = self._s.get(name, as_type=File) if fname: try: default_storage.delete(fname.name) except OSError: # pragma: no cover logger.error('Deleting file %s failed.' % fname.name) del self._s[name] elif value is None: del self._s[name] elif self._s.get(name, as_type=type(value)) != value: self._s.set(name, value)
python
def save(self) -> None: """ Saves all changed values to the database. """ for name, field in self.fields.items(): value = self.cleaned_data[name] if isinstance(value, UploadedFile): # Delete old file fname = self._s.get(name, as_type=File) if fname: try: default_storage.delete(fname.name) except OSError: # pragma: no cover logger.error('Deleting file %s failed.' % fname.name) # Create new file newname = default_storage.save(self.get_new_filename(value.name), value) value._name = newname self._s.set(name, value) elif isinstance(value, File): # file is unchanged continue elif isinstance(field, forms.FileField): # file is deleted fname = self._s.get(name, as_type=File) if fname: try: default_storage.delete(fname.name) except OSError: # pragma: no cover logger.error('Deleting file %s failed.' % fname.name) del self._s[name] elif value is None: del self._s[name] elif self._s.get(name, as_type=type(value)) != value: self._s.set(name, value)
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Saves all changed values to the database.
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3ca822f94fa633c9a6d5abe9c80cb1551299ae46
https://github.com/raphaelm/django-hierarkey/blob/3ca822f94fa633c9a6d5abe9c80cb1551299ae46/hierarkey/forms.py#L30-L64
train
44,021
IBMStreams/pypi.streamsx
streamsx/scripts/service.py
_stop
def _stop(sas, cmd_args): """Stop the service if no jobs are running unless force is set""" if not cmd_args.force: status = sas.get_instance_status() jobs = int(status['job_count']) if jobs: return status return sas.stop_instance()
python
def _stop(sas, cmd_args): """Stop the service if no jobs are running unless force is set""" if not cmd_args.force: status = sas.get_instance_status() jobs = int(status['job_count']) if jobs: return status return sas.stop_instance()
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Stop the service if no jobs are running unless force is set
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/scripts/service.py#L14-L21
train
44,022
IBMStreams/pypi.streamsx
streamsx/scripts/service.py
main
def main(args=None): """ Performs an action against a Streaming Analytics service. """ streamsx._streams._version._mismatch_check('streamsx.topology.context') try: sr = run_cmd(args) sr['return_code'] = 0 except: sr = {'return_code':1, 'error': sys.exc_info()} return sr
python
def main(args=None): """ Performs an action against a Streaming Analytics service. """ streamsx._streams._version._mismatch_check('streamsx.topology.context') try: sr = run_cmd(args) sr['return_code'] = 0 except: sr = {'return_code':1, 'error': sys.exc_info()} return sr
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Performs an action against a Streaming Analytics service.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/scripts/service.py#L39-L48
train
44,023
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Topology.source
def source(self, func, name=None): """ Declare a source stream that introduces tuples into the application. Typically used to create a stream of tuple from an external source, such as a sensor or reading from an external system. Tuples are obtained from an iterator obtained from the passed iterable or callable that returns an iterable. Each tuple that is not None from the iterator is present on the returned stream. Each tuple is a Python object and must be picklable to allow execution of the application to be distributed across available resources in the Streams instance. If the iterator's ``__iter__`` or ``__next__`` block then shutdown, checkpointing or consistent region processing may be delayed. Having ``__next__`` return ``None`` (no available tuples) or tuples to submit will allow such processing to proceed. A shutdown ``threading.Event`` is available through :py:func:`streamsx.ec.shutdown` which becomes set when a shutdown of the processing element has been requested. This event my be waited on to perform a sleep that will terminate upon shutdown. Args: func(callable): An iterable or a zero-argument callable that returns an iterable of tuples. name(str): Name of the stream, defaults to a generated name. Exceptions raised by ``func`` or its iterator will cause its processing element will terminate. If ``func`` is a callable object then it may suppress exceptions by return a true value from its ``__exit__`` method. Suppressing an exception raised by ``func.__iter__`` causes the source to be empty, no tuples are submitted to the stream. Suppressing an exception raised by ``__next__`` on the iterator results in no tuples being submitted for that call to ``__next__``. Processing continues with calls to ``__next__`` to fetch subsequent tuples. Returns: Stream: A stream whose tuples are the result of the iterable obtained from `func`. """ _name = name if inspect.isroutine(func): pass elif callable(func): pass else: if _name is None: _name = type(func).__name__ func = streamsx.topology.runtime._IterableInstance(func) sl = _SourceLocation(_source_info(), "source") _name = self.graph._requested_name(_name, action='source', func=func) # source is always stateful op = self.graph.addOperator(self.opnamespace+"::Source", func, name=_name, sl=sl) op._layout(kind='Source', name=_name, orig_name=name) oport = op.addOutputPort(name=_name) return Stream(self, oport)._make_placeable()
python
def source(self, func, name=None): """ Declare a source stream that introduces tuples into the application. Typically used to create a stream of tuple from an external source, such as a sensor or reading from an external system. Tuples are obtained from an iterator obtained from the passed iterable or callable that returns an iterable. Each tuple that is not None from the iterator is present on the returned stream. Each tuple is a Python object and must be picklable to allow execution of the application to be distributed across available resources in the Streams instance. If the iterator's ``__iter__`` or ``__next__`` block then shutdown, checkpointing or consistent region processing may be delayed. Having ``__next__`` return ``None`` (no available tuples) or tuples to submit will allow such processing to proceed. A shutdown ``threading.Event`` is available through :py:func:`streamsx.ec.shutdown` which becomes set when a shutdown of the processing element has been requested. This event my be waited on to perform a sleep that will terminate upon shutdown. Args: func(callable): An iterable or a zero-argument callable that returns an iterable of tuples. name(str): Name of the stream, defaults to a generated name. Exceptions raised by ``func`` or its iterator will cause its processing element will terminate. If ``func`` is a callable object then it may suppress exceptions by return a true value from its ``__exit__`` method. Suppressing an exception raised by ``func.__iter__`` causes the source to be empty, no tuples are submitted to the stream. Suppressing an exception raised by ``__next__`` on the iterator results in no tuples being submitted for that call to ``__next__``. Processing continues with calls to ``__next__`` to fetch subsequent tuples. Returns: Stream: A stream whose tuples are the result of the iterable obtained from `func`. """ _name = name if inspect.isroutine(func): pass elif callable(func): pass else: if _name is None: _name = type(func).__name__ func = streamsx.topology.runtime._IterableInstance(func) sl = _SourceLocation(_source_info(), "source") _name = self.graph._requested_name(_name, action='source', func=func) # source is always stateful op = self.graph.addOperator(self.opnamespace+"::Source", func, name=_name, sl=sl) op._layout(kind='Source', name=_name, orig_name=name) oport = op.addOutputPort(name=_name) return Stream(self, oport)._make_placeable()
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Declare a source stream that introduces tuples into the application. Typically used to create a stream of tuple from an external source, such as a sensor or reading from an external system. Tuples are obtained from an iterator obtained from the passed iterable or callable that returns an iterable. Each tuple that is not None from the iterator is present on the returned stream. Each tuple is a Python object and must be picklable to allow execution of the application to be distributed across available resources in the Streams instance. If the iterator's ``__iter__`` or ``__next__`` block then shutdown, checkpointing or consistent region processing may be delayed. Having ``__next__`` return ``None`` (no available tuples) or tuples to submit will allow such processing to proceed. A shutdown ``threading.Event`` is available through :py:func:`streamsx.ec.shutdown` which becomes set when a shutdown of the processing element has been requested. This event my be waited on to perform a sleep that will terminate upon shutdown. Args: func(callable): An iterable or a zero-argument callable that returns an iterable of tuples. name(str): Name of the stream, defaults to a generated name. Exceptions raised by ``func`` or its iterator will cause its processing element will terminate. If ``func`` is a callable object then it may suppress exceptions by return a true value from its ``__exit__`` method. Suppressing an exception raised by ``func.__iter__`` causes the source to be empty, no tuples are submitted to the stream. Suppressing an exception raised by ``__next__`` on the iterator results in no tuples being submitted for that call to ``__next__``. Processing continues with calls to ``__next__`` to fetch subsequent tuples. Returns: Stream: A stream whose tuples are the result of the iterable obtained from `func`.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L434-L495
train
44,024
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Topology.subscribe
def subscribe(self, topic, schema=streamsx.topology.schema.CommonSchema.Python, name=None, connect=None, buffer_capacity=None, buffer_full_policy=None): """ Subscribe to a topic published by other Streams applications. A Streams application may publish a stream to allow other Streams applications to subscribe to it. A subscriber matches a publisher if the topic and schema match. By default a stream is subscribed as :py:const:`~streamsx.topology.schema.CommonSchema.Python` objects which connects to streams published to topic by Python Streams applications. Structured schemas are subscribed to using an instance of :py:class:`StreamSchema`. A Streams application publishing structured schema streams may have been implemented in any programming language supported by Streams. JSON streams are subscribed to using schema :py:const:`~streamsx.topology.schema.CommonSchema.Json`. Each tuple on the returned stream will be a Python dictionary object created by ``json.loads(tuple)``. A Streams application publishing JSON streams may have been implemented in any programming language supported by Streams. String streams are subscribed to using schema :py:const:`~streamsx.topology.schema.CommonSchema.String`. Each tuple on the returned stream will be a Python string object. A Streams application publishing string streams may have been implemented in any programming language supported by Streams. Subscribers can ensure they do not slow down matching publishers by using a buffered connection with a buffer full policy that drops tuples. Args: topic(str): Topic to subscribe to. schema(~streamsx.topology.schema.StreamSchema): schema to subscribe to. name(str): Name of the subscribed stream, defaults to a generated name. connect(SubscribeConnection): How subscriber will be connected to matching publishers. Defaults to :py:const:`~SubscribeConnection.Direct` connection. buffer_capacity(int): Buffer capacity in tuples when `connect` is set to :py:const:`~SubscribeConnection.Buffered`. Defaults to 1000 when `connect` is `Buffered`. Ignored when `connect` is `None` or `Direct`. buffer_full_policy(~streamsx.types.CongestionPolicy): Policy when a pulished tuple arrives and the subscriber's buffer is full. Defaults to `Wait` when `connect` is `Buffered`. Ignored when `connect` is `None` or `Direct`. Returns: Stream: A stream whose tuples have been published to the topic by other Streams applications. .. versionchanged:: 1.9 `connect`, `buffer_capacity` and `buffer_full_policy` parameters added. .. seealso:`SubscribeConnection` """ schema = streamsx.topology.schema._normalize(schema) _name = self.graph._requested_name(name, 'subscribe') sl = _SourceLocation(_source_info(), "subscribe") # subscribe is never stateful op = self.graph.addOperator(kind="com.ibm.streamsx.topology.topic::Subscribe", sl=sl, name=_name, stateful=False) oport = op.addOutputPort(schema=schema, name=_name) params = {'topic': topic, 'streamType': schema} if connect is not None and connect != SubscribeConnection.Direct: params['connect'] = connect if buffer_capacity: params['bufferCapacity'] = int(buffer_capacity) if buffer_full_policy: params['bufferFullPolicy'] = buffer_full_policy op.setParameters(params) op._layout_group('Subscribe', name if name else _name) return Stream(self, oport)._make_placeable()
python
def subscribe(self, topic, schema=streamsx.topology.schema.CommonSchema.Python, name=None, connect=None, buffer_capacity=None, buffer_full_policy=None): """ Subscribe to a topic published by other Streams applications. A Streams application may publish a stream to allow other Streams applications to subscribe to it. A subscriber matches a publisher if the topic and schema match. By default a stream is subscribed as :py:const:`~streamsx.topology.schema.CommonSchema.Python` objects which connects to streams published to topic by Python Streams applications. Structured schemas are subscribed to using an instance of :py:class:`StreamSchema`. A Streams application publishing structured schema streams may have been implemented in any programming language supported by Streams. JSON streams are subscribed to using schema :py:const:`~streamsx.topology.schema.CommonSchema.Json`. Each tuple on the returned stream will be a Python dictionary object created by ``json.loads(tuple)``. A Streams application publishing JSON streams may have been implemented in any programming language supported by Streams. String streams are subscribed to using schema :py:const:`~streamsx.topology.schema.CommonSchema.String`. Each tuple on the returned stream will be a Python string object. A Streams application publishing string streams may have been implemented in any programming language supported by Streams. Subscribers can ensure they do not slow down matching publishers by using a buffered connection with a buffer full policy that drops tuples. Args: topic(str): Topic to subscribe to. schema(~streamsx.topology.schema.StreamSchema): schema to subscribe to. name(str): Name of the subscribed stream, defaults to a generated name. connect(SubscribeConnection): How subscriber will be connected to matching publishers. Defaults to :py:const:`~SubscribeConnection.Direct` connection. buffer_capacity(int): Buffer capacity in tuples when `connect` is set to :py:const:`~SubscribeConnection.Buffered`. Defaults to 1000 when `connect` is `Buffered`. Ignored when `connect` is `None` or `Direct`. buffer_full_policy(~streamsx.types.CongestionPolicy): Policy when a pulished tuple arrives and the subscriber's buffer is full. Defaults to `Wait` when `connect` is `Buffered`. Ignored when `connect` is `None` or `Direct`. Returns: Stream: A stream whose tuples have been published to the topic by other Streams applications. .. versionchanged:: 1.9 `connect`, `buffer_capacity` and `buffer_full_policy` parameters added. .. seealso:`SubscribeConnection` """ schema = streamsx.topology.schema._normalize(schema) _name = self.graph._requested_name(name, 'subscribe') sl = _SourceLocation(_source_info(), "subscribe") # subscribe is never stateful op = self.graph.addOperator(kind="com.ibm.streamsx.topology.topic::Subscribe", sl=sl, name=_name, stateful=False) oport = op.addOutputPort(schema=schema, name=_name) params = {'topic': topic, 'streamType': schema} if connect is not None and connect != SubscribeConnection.Direct: params['connect'] = connect if buffer_capacity: params['bufferCapacity'] = int(buffer_capacity) if buffer_full_policy: params['bufferFullPolicy'] = buffer_full_policy op.setParameters(params) op._layout_group('Subscribe', name if name else _name) return Stream(self, oport)._make_placeable()
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Subscribe to a topic published by other Streams applications. A Streams application may publish a stream to allow other Streams applications to subscribe to it. A subscriber matches a publisher if the topic and schema match. By default a stream is subscribed as :py:const:`~streamsx.topology.schema.CommonSchema.Python` objects which connects to streams published to topic by Python Streams applications. Structured schemas are subscribed to using an instance of :py:class:`StreamSchema`. A Streams application publishing structured schema streams may have been implemented in any programming language supported by Streams. JSON streams are subscribed to using schema :py:const:`~streamsx.topology.schema.CommonSchema.Json`. Each tuple on the returned stream will be a Python dictionary object created by ``json.loads(tuple)``. A Streams application publishing JSON streams may have been implemented in any programming language supported by Streams. String streams are subscribed to using schema :py:const:`~streamsx.topology.schema.CommonSchema.String`. Each tuple on the returned stream will be a Python string object. A Streams application publishing string streams may have been implemented in any programming language supported by Streams. Subscribers can ensure they do not slow down matching publishers by using a buffered connection with a buffer full policy that drops tuples. Args: topic(str): Topic to subscribe to. schema(~streamsx.topology.schema.StreamSchema): schema to subscribe to. name(str): Name of the subscribed stream, defaults to a generated name. connect(SubscribeConnection): How subscriber will be connected to matching publishers. Defaults to :py:const:`~SubscribeConnection.Direct` connection. buffer_capacity(int): Buffer capacity in tuples when `connect` is set to :py:const:`~SubscribeConnection.Buffered`. Defaults to 1000 when `connect` is `Buffered`. Ignored when `connect` is `None` or `Direct`. buffer_full_policy(~streamsx.types.CongestionPolicy): Policy when a pulished tuple arrives and the subscriber's buffer is full. Defaults to `Wait` when `connect` is `Buffered`. Ignored when `connect` is `None` or `Direct`. Returns: Stream: A stream whose tuples have been published to the topic by other Streams applications. .. versionchanged:: 1.9 `connect`, `buffer_capacity` and `buffer_full_policy` parameters added. .. seealso:`SubscribeConnection`
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L497-L558
train
44,025
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Topology.add_file_dependency
def add_file_dependency(self, path, location): """ Add a file or directory dependency into an Streams application bundle. Ensures that the file or directory at `path` on the local system will be available at runtime. The file will be copied and made available relative to the application directory. Location determines where the file is relative to the application directory. Two values for location are supported `etc` and `opt`. The runtime path relative to application directory is returned. The copy is made during the submit call thus the contents of the file or directory must remain availble until submit returns. For example calling ``add_file_dependency('/tmp/conf.properties', 'etc')`` will result in contents of the local file `conf.properties` being available at runtime at the path `application directory`/etc/conf.properties. This call returns ``etc/conf.properties``. Python callables can determine the application directory at runtime with :py:func:`~streamsx.ec.get_application_directory`. For example the path above at runtime is ``os.path.join(streamsx.ec.get_application_directory(), 'etc', 'conf.properties')`` Args: path(str): Path of the file on the local system. location(str): Location of the file in the bundle relative to the application directory. Returns: str: Path relative to application directory that can be joined at runtime with ``get_application_directory``. .. versionadded:: 1.7 """ if location not in {'etc', 'opt'}: raise ValueError(location) if not os.path.isfile(path) and not os.path.isdir(path): raise ValueError(path) path = os.path.abspath(path) if location not in self._files: self._files[location] = [path] else: self._files[location].append(path) return location + '/' + os.path.basename(path)
python
def add_file_dependency(self, path, location): """ Add a file or directory dependency into an Streams application bundle. Ensures that the file or directory at `path` on the local system will be available at runtime. The file will be copied and made available relative to the application directory. Location determines where the file is relative to the application directory. Two values for location are supported `etc` and `opt`. The runtime path relative to application directory is returned. The copy is made during the submit call thus the contents of the file or directory must remain availble until submit returns. For example calling ``add_file_dependency('/tmp/conf.properties', 'etc')`` will result in contents of the local file `conf.properties` being available at runtime at the path `application directory`/etc/conf.properties. This call returns ``etc/conf.properties``. Python callables can determine the application directory at runtime with :py:func:`~streamsx.ec.get_application_directory`. For example the path above at runtime is ``os.path.join(streamsx.ec.get_application_directory(), 'etc', 'conf.properties')`` Args: path(str): Path of the file on the local system. location(str): Location of the file in the bundle relative to the application directory. Returns: str: Path relative to application directory that can be joined at runtime with ``get_application_directory``. .. versionadded:: 1.7 """ if location not in {'etc', 'opt'}: raise ValueError(location) if not os.path.isfile(path) and not os.path.isdir(path): raise ValueError(path) path = os.path.abspath(path) if location not in self._files: self._files[location] = [path] else: self._files[location].append(path) return location + '/' + os.path.basename(path)
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Add a file or directory dependency into an Streams application bundle. Ensures that the file or directory at `path` on the local system will be available at runtime. The file will be copied and made available relative to the application directory. Location determines where the file is relative to the application directory. Two values for location are supported `etc` and `opt`. The runtime path relative to application directory is returned. The copy is made during the submit call thus the contents of the file or directory must remain availble until submit returns. For example calling ``add_file_dependency('/tmp/conf.properties', 'etc')`` will result in contents of the local file `conf.properties` being available at runtime at the path `application directory`/etc/conf.properties. This call returns ``etc/conf.properties``. Python callables can determine the application directory at runtime with :py:func:`~streamsx.ec.get_application_directory`. For example the path above at runtime is ``os.path.join(streamsx.ec.get_application_directory(), 'etc', 'conf.properties')`` Args: path(str): Path of the file on the local system. location(str): Location of the file in the bundle relative to the application directory. Returns: str: Path relative to application directory that can be joined at runtime with ``get_application_directory``. .. versionadded:: 1.7
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L560-L607
train
44,026
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Topology.add_pip_package
def add_pip_package(self, requirement): """ Add a Python package dependency for this topology. If the package defined by the requirement specifier is not pre-installed on the build system then the package is installed using `pip` and becomes part of the Streams application bundle (`sab` file). The package is expected to be available from `pypi.org`. If the package is already installed on the build system then it is not added into the `sab` file. The assumption is that the runtime hosts for a Streams instance have the same Python packages installed as the build machines. This is always true for IBM Cloud Private for Data and the Streaming Analytics service on IBM Cloud. The project name extracted from the requirement specifier is added to :py:attr:`~exclude_packages` to avoid the package being added by the dependency resolver. Thus the package should be added before it is used in any stream transformation. When an application is run with trace level ``info`` the available Python packages on the running system are listed to application trace. This includes any packages added by this method. Example:: topo = Topology() # Add dependency on pint package # and astral at version 0.8.1 topo.add_pip_package('pint') topo.add_pip_package('astral==0.8.1') Args: requirement(str): Package requirements specifier. .. warning:: Only supported when using the build service with a Streams instance in IBM Cloud Private for Data or Streaming Analytics service on IBM Cloud. .. note:: Installing packages through `pip` is preferred to the automatic dependency checking performed on local modules. This is because `pip` will perform a full install of the package including any dependent packages and additional files, such as shared libraries, that might be missed by dependency discovery. .. versionadded:: 1.9 """ self._pip_packages.append(str(requirement)) pr = pkg_resources.Requirement.parse(requirement) self.exclude_packages.add(pr.project_name)
python
def add_pip_package(self, requirement): """ Add a Python package dependency for this topology. If the package defined by the requirement specifier is not pre-installed on the build system then the package is installed using `pip` and becomes part of the Streams application bundle (`sab` file). The package is expected to be available from `pypi.org`. If the package is already installed on the build system then it is not added into the `sab` file. The assumption is that the runtime hosts for a Streams instance have the same Python packages installed as the build machines. This is always true for IBM Cloud Private for Data and the Streaming Analytics service on IBM Cloud. The project name extracted from the requirement specifier is added to :py:attr:`~exclude_packages` to avoid the package being added by the dependency resolver. Thus the package should be added before it is used in any stream transformation. When an application is run with trace level ``info`` the available Python packages on the running system are listed to application trace. This includes any packages added by this method. Example:: topo = Topology() # Add dependency on pint package # and astral at version 0.8.1 topo.add_pip_package('pint') topo.add_pip_package('astral==0.8.1') Args: requirement(str): Package requirements specifier. .. warning:: Only supported when using the build service with a Streams instance in IBM Cloud Private for Data or Streaming Analytics service on IBM Cloud. .. note:: Installing packages through `pip` is preferred to the automatic dependency checking performed on local modules. This is because `pip` will perform a full install of the package including any dependent packages and additional files, such as shared libraries, that might be missed by dependency discovery. .. versionadded:: 1.9 """ self._pip_packages.append(str(requirement)) pr = pkg_resources.Requirement.parse(requirement) self.exclude_packages.add(pr.project_name)
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Add a Python package dependency for this topology. If the package defined by the requirement specifier is not pre-installed on the build system then the package is installed using `pip` and becomes part of the Streams application bundle (`sab` file). The package is expected to be available from `pypi.org`. If the package is already installed on the build system then it is not added into the `sab` file. The assumption is that the runtime hosts for a Streams instance have the same Python packages installed as the build machines. This is always true for IBM Cloud Private for Data and the Streaming Analytics service on IBM Cloud. The project name extracted from the requirement specifier is added to :py:attr:`~exclude_packages` to avoid the package being added by the dependency resolver. Thus the package should be added before it is used in any stream transformation. When an application is run with trace level ``info`` the available Python packages on the running system are listed to application trace. This includes any packages added by this method. Example:: topo = Topology() # Add dependency on pint package # and astral at version 0.8.1 topo.add_pip_package('pint') topo.add_pip_package('astral==0.8.1') Args: requirement(str): Package requirements specifier. .. warning:: Only supported when using the build service with a Streams instance in IBM Cloud Private for Data or Streaming Analytics service on IBM Cloud. .. note:: Installing packages through `pip` is preferred to the automatic dependency checking performed on local modules. This is because `pip` will perform a full install of the package including any dependent packages and additional files, such as shared libraries, that might be missed by dependency discovery. .. versionadded:: 1.9
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L609-L666
train
44,027
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Topology.create_submission_parameter
def create_submission_parameter(self, name, default=None, type_=None): """ Create a submission parameter. A submission parameter is a handle for a value that is not defined until topology submission time. Submission parameters enable the creation of reusable topology bundles. A submission parameter has a `name`. The name must be unique within the topology. The returned parameter is a `callable`. Prior to submitting the topology, while constructing the topology, invoking it returns ``None``. After the topology is submitted, invoking the parameter within the executing topology returns the actual submission time value (or the default value if it was not set at submission time). Submission parameters may be used within functional logic. e.g.:: threshold = topology.create_submission_parameter('threshold', 100); # s is some stream of integers s = ... s = s.filter(lambda v : v > threshold()) .. note:: The parameter (value returned from this method) is only supported within a lambda expression or a callable that is not a function. The default type of a submission parameter's value is a `str` (`unicode` on Python 2.7). When a `default` is specified the type of the value matches the type of the default. If `default` is not set, then the type can be set with `type_`. The types supported are ``str``, ``int``, ``float`` and ``bool``. Topology submission behavior when a submission parameter lacking a default value is created and a value is not provided at submission time is defined by the underlying topology execution runtime. * Submission fails for contexts ``DISTRIBUTED``, ``STANDALONE``, and ``STREAMING_ANALYTICS_SERVICE``. Args: name(str): Name for submission parameter. default: Default parameter when submission parameter is not set. type_: Type of parameter value when default is not set. Supported values are `str`, `int`, `float` and `bool`. .. versionadded:: 1.9 """ if name in self._submission_parameters: raise ValueError("Submission parameter {} already defined.".format(name)) sp = streamsx.topology.runtime._SubmissionParam(name, default, type_) self._submission_parameters[name] = sp return sp
python
def create_submission_parameter(self, name, default=None, type_=None): """ Create a submission parameter. A submission parameter is a handle for a value that is not defined until topology submission time. Submission parameters enable the creation of reusable topology bundles. A submission parameter has a `name`. The name must be unique within the topology. The returned parameter is a `callable`. Prior to submitting the topology, while constructing the topology, invoking it returns ``None``. After the topology is submitted, invoking the parameter within the executing topology returns the actual submission time value (or the default value if it was not set at submission time). Submission parameters may be used within functional logic. e.g.:: threshold = topology.create_submission_parameter('threshold', 100); # s is some stream of integers s = ... s = s.filter(lambda v : v > threshold()) .. note:: The parameter (value returned from this method) is only supported within a lambda expression or a callable that is not a function. The default type of a submission parameter's value is a `str` (`unicode` on Python 2.7). When a `default` is specified the type of the value matches the type of the default. If `default` is not set, then the type can be set with `type_`. The types supported are ``str``, ``int``, ``float`` and ``bool``. Topology submission behavior when a submission parameter lacking a default value is created and a value is not provided at submission time is defined by the underlying topology execution runtime. * Submission fails for contexts ``DISTRIBUTED``, ``STANDALONE``, and ``STREAMING_ANALYTICS_SERVICE``. Args: name(str): Name for submission parameter. default: Default parameter when submission parameter is not set. type_: Type of parameter value when default is not set. Supported values are `str`, `int`, `float` and `bool`. .. versionadded:: 1.9 """ if name in self._submission_parameters: raise ValueError("Submission parameter {} already defined.".format(name)) sp = streamsx.topology.runtime._SubmissionParam(name, default, type_) self._submission_parameters[name] = sp return sp
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Create a submission parameter. A submission parameter is a handle for a value that is not defined until topology submission time. Submission parameters enable the creation of reusable topology bundles. A submission parameter has a `name`. The name must be unique within the topology. The returned parameter is a `callable`. Prior to submitting the topology, while constructing the topology, invoking it returns ``None``. After the topology is submitted, invoking the parameter within the executing topology returns the actual submission time value (or the default value if it was not set at submission time). Submission parameters may be used within functional logic. e.g.:: threshold = topology.create_submission_parameter('threshold', 100); # s is some stream of integers s = ... s = s.filter(lambda v : v > threshold()) .. note:: The parameter (value returned from this method) is only supported within a lambda expression or a callable that is not a function. The default type of a submission parameter's value is a `str` (`unicode` on Python 2.7). When a `default` is specified the type of the value matches the type of the default. If `default` is not set, then the type can be set with `type_`. The types supported are ``str``, ``int``, ``float`` and ``bool``. Topology submission behavior when a submission parameter lacking a default value is created and a value is not provided at submission time is defined by the underlying topology execution runtime. * Submission fails for contexts ``DISTRIBUTED``, ``STANDALONE``, and ``STREAMING_ANALYTICS_SERVICE``. Args: name(str): Name for submission parameter. default: Default parameter when submission parameter is not set. type_: Type of parameter value when default is not set. Supported values are `str`, `int`, `float` and `bool`. .. versionadded:: 1.9
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L668-L725
train
44,028
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Topology._generate_requirements
def _generate_requirements(self): """Generate the info to create requirements.txt in the toookit.""" if not self._pip_packages: return reqs = '' for req in self._pip_packages: reqs += "{}\n".format(req) reqs_include = { 'contents': reqs, 'target':'opt/python/streams', 'name': 'requirements.txt'} if 'opt' not in self._files: self._files['opt'] = [reqs_include] else: self._files['opt'].append(reqs_include)
python
def _generate_requirements(self): """Generate the info to create requirements.txt in the toookit.""" if not self._pip_packages: return reqs = '' for req in self._pip_packages: reqs += "{}\n".format(req) reqs_include = { 'contents': reqs, 'target':'opt/python/streams', 'name': 'requirements.txt'} if 'opt' not in self._files: self._files['opt'] = [reqs_include] else: self._files['opt'].append(reqs_include)
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Generate the info to create requirements.txt in the toookit.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L775-L791
train
44,029
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Topology._add_job_control_plane
def _add_job_control_plane(self): """ Add a JobControlPlane operator to the topology, if one has not already been added. If a JobControlPlane operator has already been added, this has no effect. """ if not self._has_jcp: jcp = self.graph.addOperator(kind="spl.control::JobControlPlane", name="JobControlPlane") jcp.viewable = False self._has_jcp = True
python
def _add_job_control_plane(self): """ Add a JobControlPlane operator to the topology, if one has not already been added. If a JobControlPlane operator has already been added, this has no effect. """ if not self._has_jcp: jcp = self.graph.addOperator(kind="spl.control::JobControlPlane", name="JobControlPlane") jcp.viewable = False self._has_jcp = True
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Add a JobControlPlane operator to the topology, if one has not already been added. If a JobControlPlane operator has already been added, this has no effect.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L793-L802
train
44,030
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Stream.aliased_as
def aliased_as(self, name): """ Create an alias of this stream. Returns an alias of this stream with name `name`. When invocation of an SPL operator requires an :py:class:`~streamsx.spl.op.Expression` against an input port this can be used to ensure expression matches the input port alias regardless of the name of the actual stream. Example use where the filter expression for a ``Filter`` SPL operator uses ``IN`` to access input tuple attribute ``seq``:: s = ... s = s.aliased_as('IN') params = {'filter': op.Expression.expression('IN.seq % 4ul == 0ul')} f = op.Map('spl.relational::Filter', stream, params = params) Args: name(str): Name for returned stream. Returns: Stream: Alias of this stream with ``name`` equal to `name`. .. versionadded:: 1.9 """ stream = copy.copy(self) stream._alias = name return stream
python
def aliased_as(self, name): """ Create an alias of this stream. Returns an alias of this stream with name `name`. When invocation of an SPL operator requires an :py:class:`~streamsx.spl.op.Expression` against an input port this can be used to ensure expression matches the input port alias regardless of the name of the actual stream. Example use where the filter expression for a ``Filter`` SPL operator uses ``IN`` to access input tuple attribute ``seq``:: s = ... s = s.aliased_as('IN') params = {'filter': op.Expression.expression('IN.seq % 4ul == 0ul')} f = op.Map('spl.relational::Filter', stream, params = params) Args: name(str): Name for returned stream. Returns: Stream: Alias of this stream with ``name`` equal to `name`. .. versionadded:: 1.9 """ stream = copy.copy(self) stream._alias = name return stream
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Create an alias of this stream. Returns an alias of this stream with name `name`. When invocation of an SPL operator requires an :py:class:`~streamsx.spl.op.Expression` against an input port this can be used to ensure expression matches the input port alias regardless of the name of the actual stream. Example use where the filter expression for a ``Filter`` SPL operator uses ``IN`` to access input tuple attribute ``seq``:: s = ... s = s.aliased_as('IN') params = {'filter': op.Expression.expression('IN.seq % 4ul == 0ul')} f = op.Map('spl.relational::Filter', stream, params = params) Args: name(str): Name for returned stream. Returns: Stream: Alias of this stream with ``name`` equal to `name`. .. versionadded:: 1.9
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L844-L874
train
44,031
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Stream.view
def view(self, buffer_time = 10.0, sample_size = 10000, name=None, description=None, start=False): """ Defines a view on a stream. A view is a continually updated sampled buffer of a streams's tuples. Views allow visibility into a stream from external clients such as Jupyter Notebooks, the Streams console, `Microsoft Excel <https://www.ibm.com/support/knowledgecenter/SSCRJU_4.2.0/com.ibm.streams.excel.doc/doc/excel_overview.html>`_ or REST clients. The view created by this method can be used by external clients and through the returned :py:class:`~streamsx.topology.topology.View` object after the topology is submitted. For example a Jupyter Notebook can declare and submit an application with views, and then use the resultant `View` objects to visualize live data within the streams. When the stream contains Python objects then they are converted to JSON. Args: buffer_time: Specifies the buffer size to use measured in seconds. sample_size: Specifies the number of tuples to sample per second. name(str): Name of the view. Name must be unique within the topology. Defaults to a generated name. description: Description of the view. start(bool): Start buffering data when the job is submitted. If `False` then the view starts buffering data when the first remote client accesses it to retrieve data. Returns: streamsx.topology.topology.View: View object which can be used to access the data when the topology is submitted. .. note:: Views are only supported when submitting to distributed contexts including Streaming Analytics service. """ if name is None: name = ''.join(random.choice('0123456789abcdef') for x in range(16)) if self.oport.schema == streamsx.topology.schema.CommonSchema.Python: if self._json_stream: view_stream = self._json_stream else: self._json_stream = self.as_json(force_object=False)._layout(hidden=True) view_stream = self._json_stream # colocate map operator with stream that is being viewed. if self._placeable: self._colocate(view_stream, 'view') else: view_stream = self port = view_stream.oport.name view_config = { 'name': name, 'port': port, 'description': description, 'bufferTime': buffer_time, 'sampleSize': sample_size} if start: view_config['activateOption'] = 'automatic' view_stream.oport.operator.addViewConfig(view_config) _view = View(name) self.topology.graph._views.append(_view) return _view
python
def view(self, buffer_time = 10.0, sample_size = 10000, name=None, description=None, start=False): """ Defines a view on a stream. A view is a continually updated sampled buffer of a streams's tuples. Views allow visibility into a stream from external clients such as Jupyter Notebooks, the Streams console, `Microsoft Excel <https://www.ibm.com/support/knowledgecenter/SSCRJU_4.2.0/com.ibm.streams.excel.doc/doc/excel_overview.html>`_ or REST clients. The view created by this method can be used by external clients and through the returned :py:class:`~streamsx.topology.topology.View` object after the topology is submitted. For example a Jupyter Notebook can declare and submit an application with views, and then use the resultant `View` objects to visualize live data within the streams. When the stream contains Python objects then they are converted to JSON. Args: buffer_time: Specifies the buffer size to use measured in seconds. sample_size: Specifies the number of tuples to sample per second. name(str): Name of the view. Name must be unique within the topology. Defaults to a generated name. description: Description of the view. start(bool): Start buffering data when the job is submitted. If `False` then the view starts buffering data when the first remote client accesses it to retrieve data. Returns: streamsx.topology.topology.View: View object which can be used to access the data when the topology is submitted. .. note:: Views are only supported when submitting to distributed contexts including Streaming Analytics service. """ if name is None: name = ''.join(random.choice('0123456789abcdef') for x in range(16)) if self.oport.schema == streamsx.topology.schema.CommonSchema.Python: if self._json_stream: view_stream = self._json_stream else: self._json_stream = self.as_json(force_object=False)._layout(hidden=True) view_stream = self._json_stream # colocate map operator with stream that is being viewed. if self._placeable: self._colocate(view_stream, 'view') else: view_stream = self port = view_stream.oport.name view_config = { 'name': name, 'port': port, 'description': description, 'bufferTime': buffer_time, 'sampleSize': sample_size} if start: view_config['activateOption'] = 'automatic' view_stream.oport.operator.addViewConfig(view_config) _view = View(name) self.topology.graph._views.append(_view) return _view
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Defines a view on a stream. A view is a continually updated sampled buffer of a streams's tuples. Views allow visibility into a stream from external clients such as Jupyter Notebooks, the Streams console, `Microsoft Excel <https://www.ibm.com/support/knowledgecenter/SSCRJU_4.2.0/com.ibm.streams.excel.doc/doc/excel_overview.html>`_ or REST clients. The view created by this method can be used by external clients and through the returned :py:class:`~streamsx.topology.topology.View` object after the topology is submitted. For example a Jupyter Notebook can declare and submit an application with views, and then use the resultant `View` objects to visualize live data within the streams. When the stream contains Python objects then they are converted to JSON. Args: buffer_time: Specifies the buffer size to use measured in seconds. sample_size: Specifies the number of tuples to sample per second. name(str): Name of the view. Name must be unique within the topology. Defaults to a generated name. description: Description of the view. start(bool): Start buffering data when the job is submitted. If `False` then the view starts buffering data when the first remote client accesses it to retrieve data. Returns: streamsx.topology.topology.View: View object which can be used to access the data when the topology is submitted. .. note:: Views are only supported when submitting to distributed contexts including Streaming Analytics service.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L963-L1023
train
44,032
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Stream.map
def map(self, func=None, name=None, schema=None): """ Maps each tuple from this stream into 0 or 1 stream tuples. For each tuple on this stream ``result = func(tuple)`` is called. If `result` is not `None` then the result will be submitted as a tuple on the returned stream. If `result` is `None` then no tuple submission will occur. By default the submitted tuple is ``result`` without modification resulting in a stream of picklable Python objects. Setting the `schema` parameter changes the type of the stream and modifies each ``result`` before submission. * ``object`` or :py:const:`~streamsx.topology.schema.CommonSchema.Python` - The default: `result` is submitted. * ``str`` type (``unicode`` 2.7) or :py:const:`~streamsx.topology.schema.CommonSchema.String` - A stream of strings: ``str(result)`` is submitted. * ``json`` or :py:const:`~streamsx.topology.schema.CommonSchema.Json` - A stream of JSON objects: ``result`` must be convertable to a JSON object using `json` package. * :py:const:`~streamsx.topology.schema.StreamSchema` - A structured stream. `result` must be a `dict` or (Python) `tuple`. When a `dict` is returned the outgoing stream tuple attributes are set by name, when a `tuple` is returned stream tuple attributes are set by position. * string value - Equivalent to passing ``StreamSchema(schema)`` Args: func: A callable that takes a single parameter for the tuple. If not supplied then a function equivalent to ``lambda tuple_ : tuple_`` is used. name(str): Name of the mapped stream, defaults to a generated name. schema(StreamSchema|CommonSchema|str): Schema of the resulting stream. If invoking ``func`` for a tuple on the stream raises an exception then its processing element will terminate. By default the processing element will automatically restart though tuples may be lost. If ``func`` is a callable object then it may suppress exceptions by return a true value from its ``__exit__`` method. When an exception is suppressed no tuple is submitted to the mapped stream corresponding to the input tuple that caused the exception. Returns: Stream: A stream containing tuples mapped by `func`. .. versionadded:: 1.7 `schema` argument added to allow conversion to a structured stream. .. versionadded:: 1.8 Support for submitting `dict` objects as stream tuples to a structured stream (in addition to existing support for `tuple` objects). .. versionchanged:: 1.11 `func` is optional. """ if schema is None: schema = streamsx.topology.schema.CommonSchema.Python if func is None: func = streamsx.topology.runtime._identity if name is None: name = 'identity' ms = self._map(func, schema=schema, name=name)._layout('Map') ms.oport.operator.sl = _SourceLocation(_source_info(), 'map') return ms
python
def map(self, func=None, name=None, schema=None): """ Maps each tuple from this stream into 0 or 1 stream tuples. For each tuple on this stream ``result = func(tuple)`` is called. If `result` is not `None` then the result will be submitted as a tuple on the returned stream. If `result` is `None` then no tuple submission will occur. By default the submitted tuple is ``result`` without modification resulting in a stream of picklable Python objects. Setting the `schema` parameter changes the type of the stream and modifies each ``result`` before submission. * ``object`` or :py:const:`~streamsx.topology.schema.CommonSchema.Python` - The default: `result` is submitted. * ``str`` type (``unicode`` 2.7) or :py:const:`~streamsx.topology.schema.CommonSchema.String` - A stream of strings: ``str(result)`` is submitted. * ``json`` or :py:const:`~streamsx.topology.schema.CommonSchema.Json` - A stream of JSON objects: ``result`` must be convertable to a JSON object using `json` package. * :py:const:`~streamsx.topology.schema.StreamSchema` - A structured stream. `result` must be a `dict` or (Python) `tuple`. When a `dict` is returned the outgoing stream tuple attributes are set by name, when a `tuple` is returned stream tuple attributes are set by position. * string value - Equivalent to passing ``StreamSchema(schema)`` Args: func: A callable that takes a single parameter for the tuple. If not supplied then a function equivalent to ``lambda tuple_ : tuple_`` is used. name(str): Name of the mapped stream, defaults to a generated name. schema(StreamSchema|CommonSchema|str): Schema of the resulting stream. If invoking ``func`` for a tuple on the stream raises an exception then its processing element will terminate. By default the processing element will automatically restart though tuples may be lost. If ``func`` is a callable object then it may suppress exceptions by return a true value from its ``__exit__`` method. When an exception is suppressed no tuple is submitted to the mapped stream corresponding to the input tuple that caused the exception. Returns: Stream: A stream containing tuples mapped by `func`. .. versionadded:: 1.7 `schema` argument added to allow conversion to a structured stream. .. versionadded:: 1.8 Support for submitting `dict` objects as stream tuples to a structured stream (in addition to existing support for `tuple` objects). .. versionchanged:: 1.11 `func` is optional. """ if schema is None: schema = streamsx.topology.schema.CommonSchema.Python if func is None: func = streamsx.topology.runtime._identity if name is None: name = 'identity' ms = self._map(func, schema=schema, name=name)._layout('Map') ms.oport.operator.sl = _SourceLocation(_source_info(), 'map') return ms
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Maps each tuple from this stream into 0 or 1 stream tuples. For each tuple on this stream ``result = func(tuple)`` is called. If `result` is not `None` then the result will be submitted as a tuple on the returned stream. If `result` is `None` then no tuple submission will occur. By default the submitted tuple is ``result`` without modification resulting in a stream of picklable Python objects. Setting the `schema` parameter changes the type of the stream and modifies each ``result`` before submission. * ``object`` or :py:const:`~streamsx.topology.schema.CommonSchema.Python` - The default: `result` is submitted. * ``str`` type (``unicode`` 2.7) or :py:const:`~streamsx.topology.schema.CommonSchema.String` - A stream of strings: ``str(result)`` is submitted. * ``json`` or :py:const:`~streamsx.topology.schema.CommonSchema.Json` - A stream of JSON objects: ``result`` must be convertable to a JSON object using `json` package. * :py:const:`~streamsx.topology.schema.StreamSchema` - A structured stream. `result` must be a `dict` or (Python) `tuple`. When a `dict` is returned the outgoing stream tuple attributes are set by name, when a `tuple` is returned stream tuple attributes are set by position. * string value - Equivalent to passing ``StreamSchema(schema)`` Args: func: A callable that takes a single parameter for the tuple. If not supplied then a function equivalent to ``lambda tuple_ : tuple_`` is used. name(str): Name of the mapped stream, defaults to a generated name. schema(StreamSchema|CommonSchema|str): Schema of the resulting stream. If invoking ``func`` for a tuple on the stream raises an exception then its processing element will terminate. By default the processing element will automatically restart though tuples may be lost. If ``func`` is a callable object then it may suppress exceptions by return a true value from its ``__exit__`` method. When an exception is suppressed no tuple is submitted to the mapped stream corresponding to the input tuple that caused the exception. Returns: Stream: A stream containing tuples mapped by `func`. .. versionadded:: 1.7 `schema` argument added to allow conversion to a structured stream. .. versionadded:: 1.8 Support for submitting `dict` objects as stream tuples to a structured stream (in addition to existing support for `tuple` objects). .. versionchanged:: 1.11 `func` is optional.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1025-L1078
train
44,033
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Stream.flat_map
def flat_map(self, func=None, name=None): """ Maps and flatterns each tuple from this stream into 0 or more tuples. For each tuple on this stream ``func(tuple)`` is called. If the result is not `None` then the the result is iterated over with each value from the iterator that is not `None` will be submitted to the return stream. If the result is `None` or an empty iterable then no tuples are submitted to the returned stream. Args: func: A callable that takes a single parameter for the tuple. If not supplied then a function equivalent to ``lambda tuple_ : tuple_`` is used. This is suitable when each tuple on this stream is an iterable to be flattened. name(str): Name of the flattened stream, defaults to a generated name. If invoking ``func`` for a tuple on the stream raises an exception then its processing element will terminate. By default the processing element will automatically restart though tuples may be lost. If ``func`` is a callable object then it may suppress exceptions by return a true value from its ``__exit__`` method. When an exception is suppressed no tuples are submitted to the flattened and mapped stream corresponding to the input tuple that caused the exception. Returns: Stream: A Stream containing flattened and mapped tuples. Raises: TypeError: if `func` does not return an iterator nor None .. versionchanged:: 1.11 `func` is optional. """ if func is None: func = streamsx.topology.runtime._identity if name is None: name = 'flatten' sl = _SourceLocation(_source_info(), 'flat_map') _name = self.topology.graph._requested_name(name, action='flat_map', func=func) stateful = self._determine_statefulness(func) op = self.topology.graph.addOperator(self.topology.opnamespace+"::FlatMap", func, name=_name, sl=sl, stateful=stateful) op.addInputPort(outputPort=self.oport) streamsx.topology.schema.StreamSchema._fnop_style(self.oport.schema, op, 'pyStyle') oport = op.addOutputPort(name=_name) return Stream(self.topology, oport)._make_placeable()._layout('FlatMap', name=_name, orig_name=name)
python
def flat_map(self, func=None, name=None): """ Maps and flatterns each tuple from this stream into 0 or more tuples. For each tuple on this stream ``func(tuple)`` is called. If the result is not `None` then the the result is iterated over with each value from the iterator that is not `None` will be submitted to the return stream. If the result is `None` or an empty iterable then no tuples are submitted to the returned stream. Args: func: A callable that takes a single parameter for the tuple. If not supplied then a function equivalent to ``lambda tuple_ : tuple_`` is used. This is suitable when each tuple on this stream is an iterable to be flattened. name(str): Name of the flattened stream, defaults to a generated name. If invoking ``func`` for a tuple on the stream raises an exception then its processing element will terminate. By default the processing element will automatically restart though tuples may be lost. If ``func`` is a callable object then it may suppress exceptions by return a true value from its ``__exit__`` method. When an exception is suppressed no tuples are submitted to the flattened and mapped stream corresponding to the input tuple that caused the exception. Returns: Stream: A Stream containing flattened and mapped tuples. Raises: TypeError: if `func` does not return an iterator nor None .. versionchanged:: 1.11 `func` is optional. """ if func is None: func = streamsx.topology.runtime._identity if name is None: name = 'flatten' sl = _SourceLocation(_source_info(), 'flat_map') _name = self.topology.graph._requested_name(name, action='flat_map', func=func) stateful = self._determine_statefulness(func) op = self.topology.graph.addOperator(self.topology.opnamespace+"::FlatMap", func, name=_name, sl=sl, stateful=stateful) op.addInputPort(outputPort=self.oport) streamsx.topology.schema.StreamSchema._fnop_style(self.oport.schema, op, 'pyStyle') oport = op.addOutputPort(name=_name) return Stream(self.topology, oport)._make_placeable()._layout('FlatMap', name=_name, orig_name=name)
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Maps and flatterns each tuple from this stream into 0 or more tuples. For each tuple on this stream ``func(tuple)`` is called. If the result is not `None` then the the result is iterated over with each value from the iterator that is not `None` will be submitted to the return stream. If the result is `None` or an empty iterable then no tuples are submitted to the returned stream. Args: func: A callable that takes a single parameter for the tuple. If not supplied then a function equivalent to ``lambda tuple_ : tuple_`` is used. This is suitable when each tuple on this stream is an iterable to be flattened. name(str): Name of the flattened stream, defaults to a generated name. If invoking ``func`` for a tuple on the stream raises an exception then its processing element will terminate. By default the processing element will automatically restart though tuples may be lost. If ``func`` is a callable object then it may suppress exceptions by return a true value from its ``__exit__`` method. When an exception is suppressed no tuples are submitted to the flattened and mapped stream corresponding to the input tuple that caused the exception. Returns: Stream: A Stream containing flattened and mapped tuples. Raises: TypeError: if `func` does not return an iterator nor None .. versionchanged:: 1.11 `func` is optional.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1089-L1138
train
44,034
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Stream.end_parallel
def end_parallel(self): """ Ends a parallel region by merging the channels into a single stream. Returns: Stream: Stream for which subsequent transformations are no longer parallelized. .. seealso:: :py:meth:`set_parallel`, :py:meth:`parallel` """ outport = self.oport if isinstance(self.oport.operator, streamsx.topology.graph.Marker): if self.oport.operator.kind == "$Union$": pto = self.topology.graph.addPassThruOperator() pto.addInputPort(outputPort=self.oport) outport = pto.addOutputPort(schema=self.oport.schema) op = self.topology.graph.addOperator("$EndParallel$") op.addInputPort(outputPort=outport) oport = op.addOutputPort(schema=self.oport.schema) endP = Stream(self.topology, oport) return endP
python
def end_parallel(self): """ Ends a parallel region by merging the channels into a single stream. Returns: Stream: Stream for which subsequent transformations are no longer parallelized. .. seealso:: :py:meth:`set_parallel`, :py:meth:`parallel` """ outport = self.oport if isinstance(self.oport.operator, streamsx.topology.graph.Marker): if self.oport.operator.kind == "$Union$": pto = self.topology.graph.addPassThruOperator() pto.addInputPort(outputPort=self.oport) outport = pto.addOutputPort(schema=self.oport.schema) op = self.topology.graph.addOperator("$EndParallel$") op.addInputPort(outputPort=outport) oport = op.addOutputPort(schema=self.oport.schema) endP = Stream(self.topology, oport) return endP
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Ends a parallel region by merging the channels into a single stream. Returns: Stream: Stream for which subsequent transformations are no longer parallelized. .. seealso:: :py:meth:`set_parallel`, :py:meth:`parallel`
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1335-L1354
train
44,035
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Stream.set_parallel
def set_parallel(self, width, name=None): """ Set this source stream to be split into multiple channels as the start of a parallel region. Calling ``set_parallel`` on a stream created by :py:meth:`~Topology.source` results in the stream having `width` channels, each created by its own instance of the callable:: s = topo.source(S()) s.set_parallel(3) f = s.filter(F()) e = f.end_parallel() Each channel has independent instances of ``S`` and ``F``. Tuples created by the instance of ``S`` in channel 0 are passed to the instance of ``F`` in channel 0, and so on for channels 1 and 2. Callable transforms instances within the channel can use the runtime functions :py:func:`~streamsx.ec.channel`, :py:func:`~streamsx.ec.local_channel`, :py:func:`~streamsx.ec.max_channels` & :py:func:`~streamsx.ec.local_max_channels` to adapt to being invoked in parallel. For example a source callable can use its channel number to determine which partition to read from in a partitioned external system. Calling ``set_parallel`` on a stream created by :py:meth:`~Topology.subscribe` results in the stream having `width` channels. Subscribe ensures that the stream will contain all published tuples matching the topic subscription and type. A published tuple will appear on one of the channels though the specific channel is not known in advance. A parallel region is terminated by :py:meth:`end_parallel` or :py:meth:`for_each`. The number of channels is set by `width` which may be an `int` greater than zero or a submission parameter created by :py:meth:`Topology.create_submission_parameter`. With IBM Streams 4.3 or later the number of channels can be dynamically changed at runtime. Parallel regions are started on non-source streams using :py:meth:`parallel`. Args: width: The degree of parallelism for the parallel region. name(str): Name of the parallel region. Defaults to the name of this stream. Returns: Stream: Returns this stream. .. seealso:: :py:meth:`parallel`, :py:meth:`end_parallel` .. versionadded:: 1.9 .. versionchanged:: 1.11 `name` parameter added. """ self.oport.operator.config['parallel'] = True self.oport.operator.config['width'] = streamsx.topology.graph._as_spl_json(width, int) if name: name = self.topology.graph._requested_name(str(name), action='set_parallel') self.oport.operator.config['regionName'] = name return self
python
def set_parallel(self, width, name=None): """ Set this source stream to be split into multiple channels as the start of a parallel region. Calling ``set_parallel`` on a stream created by :py:meth:`~Topology.source` results in the stream having `width` channels, each created by its own instance of the callable:: s = topo.source(S()) s.set_parallel(3) f = s.filter(F()) e = f.end_parallel() Each channel has independent instances of ``S`` and ``F``. Tuples created by the instance of ``S`` in channel 0 are passed to the instance of ``F`` in channel 0, and so on for channels 1 and 2. Callable transforms instances within the channel can use the runtime functions :py:func:`~streamsx.ec.channel`, :py:func:`~streamsx.ec.local_channel`, :py:func:`~streamsx.ec.max_channels` & :py:func:`~streamsx.ec.local_max_channels` to adapt to being invoked in parallel. For example a source callable can use its channel number to determine which partition to read from in a partitioned external system. Calling ``set_parallel`` on a stream created by :py:meth:`~Topology.subscribe` results in the stream having `width` channels. Subscribe ensures that the stream will contain all published tuples matching the topic subscription and type. A published tuple will appear on one of the channels though the specific channel is not known in advance. A parallel region is terminated by :py:meth:`end_parallel` or :py:meth:`for_each`. The number of channels is set by `width` which may be an `int` greater than zero or a submission parameter created by :py:meth:`Topology.create_submission_parameter`. With IBM Streams 4.3 or later the number of channels can be dynamically changed at runtime. Parallel regions are started on non-source streams using :py:meth:`parallel`. Args: width: The degree of parallelism for the parallel region. name(str): Name of the parallel region. Defaults to the name of this stream. Returns: Stream: Returns this stream. .. seealso:: :py:meth:`parallel`, :py:meth:`end_parallel` .. versionadded:: 1.9 .. versionchanged:: 1.11 `name` parameter added. """ self.oport.operator.config['parallel'] = True self.oport.operator.config['width'] = streamsx.topology.graph._as_spl_json(width, int) if name: name = self.topology.graph._requested_name(str(name), action='set_parallel') self.oport.operator.config['regionName'] = name return self
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Set this source stream to be split into multiple channels as the start of a parallel region. Calling ``set_parallel`` on a stream created by :py:meth:`~Topology.source` results in the stream having `width` channels, each created by its own instance of the callable:: s = topo.source(S()) s.set_parallel(3) f = s.filter(F()) e = f.end_parallel() Each channel has independent instances of ``S`` and ``F``. Tuples created by the instance of ``S`` in channel 0 are passed to the instance of ``F`` in channel 0, and so on for channels 1 and 2. Callable transforms instances within the channel can use the runtime functions :py:func:`~streamsx.ec.channel`, :py:func:`~streamsx.ec.local_channel`, :py:func:`~streamsx.ec.max_channels` & :py:func:`~streamsx.ec.local_max_channels` to adapt to being invoked in parallel. For example a source callable can use its channel number to determine which partition to read from in a partitioned external system. Calling ``set_parallel`` on a stream created by :py:meth:`~Topology.subscribe` results in the stream having `width` channels. Subscribe ensures that the stream will contain all published tuples matching the topic subscription and type. A published tuple will appear on one of the channels though the specific channel is not known in advance. A parallel region is terminated by :py:meth:`end_parallel` or :py:meth:`for_each`. The number of channels is set by `width` which may be an `int` greater than zero or a submission parameter created by :py:meth:`Topology.create_submission_parameter`. With IBM Streams 4.3 or later the number of channels can be dynamically changed at runtime. Parallel regions are started on non-source streams using :py:meth:`parallel`. Args: width: The degree of parallelism for the parallel region. name(str): Name of the parallel region. Defaults to the name of this stream. Returns: Stream: Returns this stream. .. seealso:: :py:meth:`parallel`, :py:meth:`end_parallel` .. versionadded:: 1.9 .. versionchanged:: 1.11 `name` parameter added.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1356-L1423
train
44,036
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Stream.set_consistent
def set_consistent(self, consistent_config): """ Indicates that the stream is the start of a consistent region. Args: consistent_config(consistent.ConsistentRegionConfig): the configuration of the consistent region. Returns: Stream: Returns this stream. .. versionadded:: 1.11 """ # add job control plane if needed self.topology._add_job_control_plane() self.oport.operator.consistent(consistent_config) return self._make_placeable()
python
def set_consistent(self, consistent_config): """ Indicates that the stream is the start of a consistent region. Args: consistent_config(consistent.ConsistentRegionConfig): the configuration of the consistent region. Returns: Stream: Returns this stream. .. versionadded:: 1.11 """ # add job control plane if needed self.topology._add_job_control_plane() self.oport.operator.consistent(consistent_config) return self._make_placeable()
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Indicates that the stream is the start of a consistent region. Args: consistent_config(consistent.ConsistentRegionConfig): the configuration of the consistent region. Returns: Stream: Returns this stream. .. versionadded:: 1.11
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1425-L1440
train
44,037
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Stream.last
def last(self, size=1): """ Declares a slding window containing most recent tuples on this stream. The number of tuples maintained in the window is defined by `size`. If `size` is an `int` then it is the count of tuples in the window. For example, with ``size=10`` the window always contains the last (most recent) ten tuples. If `size` is an `datetime.timedelta` then it is the duration of the window. With a `timedelta` representing five minutes then the window contains any tuples that arrived in the last five minutes. Args: size: The size of the window, either an `int` to define the number of tuples or `datetime.timedelta` to define the duration of the window. Examples:: # Create a window against stream s of the last 100 tuples w = s.last(size=100) :: # Create a window against stream s of tuples # arrived on the stream in the last five minutes w = s.last(size=datetime.timedelta(minutes=5)) Returns: Window: Window of the last (most recent) tuples on this stream. """ win = Window(self, 'SLIDING') if isinstance(size, datetime.timedelta): win._evict_time(size) elif isinstance(size, int): win._evict_count(size) else: raise ValueError(size) return win
python
def last(self, size=1): """ Declares a slding window containing most recent tuples on this stream. The number of tuples maintained in the window is defined by `size`. If `size` is an `int` then it is the count of tuples in the window. For example, with ``size=10`` the window always contains the last (most recent) ten tuples. If `size` is an `datetime.timedelta` then it is the duration of the window. With a `timedelta` representing five minutes then the window contains any tuples that arrived in the last five minutes. Args: size: The size of the window, either an `int` to define the number of tuples or `datetime.timedelta` to define the duration of the window. Examples:: # Create a window against stream s of the last 100 tuples w = s.last(size=100) :: # Create a window against stream s of tuples # arrived on the stream in the last five minutes w = s.last(size=datetime.timedelta(minutes=5)) Returns: Window: Window of the last (most recent) tuples on this stream. """ win = Window(self, 'SLIDING') if isinstance(size, datetime.timedelta): win._evict_time(size) elif isinstance(size, int): win._evict_count(size) else: raise ValueError(size) return win
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Declares a slding window containing most recent tuples on this stream. The number of tuples maintained in the window is defined by `size`. If `size` is an `int` then it is the count of tuples in the window. For example, with ``size=10`` the window always contains the last (most recent) ten tuples. If `size` is an `datetime.timedelta` then it is the duration of the window. With a `timedelta` representing five minutes then the window contains any tuples that arrived in the last five minutes. Args: size: The size of the window, either an `int` to define the number of tuples or `datetime.timedelta` to define the duration of the window. Examples:: # Create a window against stream s of the last 100 tuples w = s.last(size=100) :: # Create a window against stream s of tuples # arrived on the stream in the last five minutes w = s.last(size=datetime.timedelta(minutes=5)) Returns: Window: Window of the last (most recent) tuples on this stream.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1442-L1483
train
44,038
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Stream.print
def print(self, tag=None, name=None): """ Prints each tuple to stdout flushing after each tuple. If `tag` is not `None` then each tuple has "tag: " prepended to it before printing. Args: tag: A tag to prepend to each tuple. name(str): Name of the resulting stream. When `None` defaults to a generated name. Returns: streamsx.topology.topology.Sink: Stream termination. .. versionadded:: 1.6.1 `tag`, `name` parameters. .. versionchanged:: 1.7 Now returns a :py:class:`Sink` instance. """ _name = name if _name is None: _name = 'print' fn = streamsx.topology.functions.print_flush if tag is not None: tag = str(tag) + ': ' fn = lambda v : streamsx.topology.functions.print_flush(tag + str(v)) sp = self.for_each(fn, name=_name) sp._op().sl = _SourceLocation(_source_info(), 'print') return sp
python
def print(self, tag=None, name=None): """ Prints each tuple to stdout flushing after each tuple. If `tag` is not `None` then each tuple has "tag: " prepended to it before printing. Args: tag: A tag to prepend to each tuple. name(str): Name of the resulting stream. When `None` defaults to a generated name. Returns: streamsx.topology.topology.Sink: Stream termination. .. versionadded:: 1.6.1 `tag`, `name` parameters. .. versionchanged:: 1.7 Now returns a :py:class:`Sink` instance. """ _name = name if _name is None: _name = 'print' fn = streamsx.topology.functions.print_flush if tag is not None: tag = str(tag) + ': ' fn = lambda v : streamsx.topology.functions.print_flush(tag + str(v)) sp = self.for_each(fn, name=_name) sp._op().sl = _SourceLocation(_source_info(), 'print') return sp
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Prints each tuple to stdout flushing after each tuple. If `tag` is not `None` then each tuple has "tag: " prepended to it before printing. Args: tag: A tag to prepend to each tuple. name(str): Name of the resulting stream. When `None` defaults to a generated name. Returns: streamsx.topology.topology.Sink: Stream termination. .. versionadded:: 1.6.1 `tag`, `name` parameters. .. versionchanged:: 1.7 Now returns a :py:class:`Sink` instance.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1571-L1599
train
44,039
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Stream.publish
def publish(self, topic, schema=None, name=None): """ Publish this stream on a topic for other Streams applications to subscribe to. A Streams application may publish a stream to allow other Streams applications to subscribe to it. A subscriber matches a publisher if the topic and schema match. By default a stream is published using its schema. A stream of :py:const:`Python objects <streamsx.topology.schema.CommonSchema.Python>` can be subscribed to by other Streams Python applications. If a stream is published setting `schema` to :py:const:`~streamsx.topology.schema.CommonSchema.Json` then it is published as a stream of JSON objects. Other Streams applications may subscribe to it regardless of their implementation language. If a stream is published setting `schema` to :py:const:`~streamsx.topology.schema.CommonSchema.String` then it is published as strings Other Streams applications may subscribe to it regardless of their implementation language. Supported values of `schema` are only :py:const:`~streamsx.topology.schema.CommonSchema.Json` and :py:const:`~streamsx.topology.schema.CommonSchema.String`. Args: topic(str): Topic to publish this stream to. schema: Schema to publish. Defaults to the schema of this stream. name(str): Name of the publish operator, defaults to a generated name. Returns: streamsx.topology.topology.Sink: Stream termination. .. versionadded:: 1.6.1 `name` parameter. .. versionchanged:: 1.7 Now returns a :py:class:`Sink` instance. """ sl = _SourceLocation(_source_info(), 'publish') schema = streamsx.topology.schema._normalize(schema) if schema is not None and self.oport.schema.schema() != schema.schema(): nc = None if schema == streamsx.topology.schema.CommonSchema.Json: schema_change = self.as_json() elif schema == streamsx.topology.schema.CommonSchema.String: schema_change = self.as_string() else: raise ValueError(schema) if self._placeable: self._colocate(schema_change, 'publish') sp = schema_change.publish(topic, schema=schema, name=name) sp._op().sl = sl return sp _name = self.topology.graph._requested_name(name, action="publish") # publish is never stateful op = self.topology.graph.addOperator("com.ibm.streamsx.topology.topic::Publish", params={'topic': topic}, sl=sl, name=_name, stateful=False) op.addInputPort(outputPort=self.oport) op._layout_group('Publish', name if name else _name) sink = Sink(op) if self._placeable: self._colocate(sink, 'publish') return sink
python
def publish(self, topic, schema=None, name=None): """ Publish this stream on a topic for other Streams applications to subscribe to. A Streams application may publish a stream to allow other Streams applications to subscribe to it. A subscriber matches a publisher if the topic and schema match. By default a stream is published using its schema. A stream of :py:const:`Python objects <streamsx.topology.schema.CommonSchema.Python>` can be subscribed to by other Streams Python applications. If a stream is published setting `schema` to :py:const:`~streamsx.topology.schema.CommonSchema.Json` then it is published as a stream of JSON objects. Other Streams applications may subscribe to it regardless of their implementation language. If a stream is published setting `schema` to :py:const:`~streamsx.topology.schema.CommonSchema.String` then it is published as strings Other Streams applications may subscribe to it regardless of their implementation language. Supported values of `schema` are only :py:const:`~streamsx.topology.schema.CommonSchema.Json` and :py:const:`~streamsx.topology.schema.CommonSchema.String`. Args: topic(str): Topic to publish this stream to. schema: Schema to publish. Defaults to the schema of this stream. name(str): Name of the publish operator, defaults to a generated name. Returns: streamsx.topology.topology.Sink: Stream termination. .. versionadded:: 1.6.1 `name` parameter. .. versionchanged:: 1.7 Now returns a :py:class:`Sink` instance. """ sl = _SourceLocation(_source_info(), 'publish') schema = streamsx.topology.schema._normalize(schema) if schema is not None and self.oport.schema.schema() != schema.schema(): nc = None if schema == streamsx.topology.schema.CommonSchema.Json: schema_change = self.as_json() elif schema == streamsx.topology.schema.CommonSchema.String: schema_change = self.as_string() else: raise ValueError(schema) if self._placeable: self._colocate(schema_change, 'publish') sp = schema_change.publish(topic, schema=schema, name=name) sp._op().sl = sl return sp _name = self.topology.graph._requested_name(name, action="publish") # publish is never stateful op = self.topology.graph.addOperator("com.ibm.streamsx.topology.topic::Publish", params={'topic': topic}, sl=sl, name=_name, stateful=False) op.addInputPort(outputPort=self.oport) op._layout_group('Publish', name if name else _name) sink = Sink(op) if self._placeable: self._colocate(sink, 'publish') return sink
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Publish this stream on a topic for other Streams applications to subscribe to. A Streams application may publish a stream to allow other Streams applications to subscribe to it. A subscriber matches a publisher if the topic and schema match. By default a stream is published using its schema. A stream of :py:const:`Python objects <streamsx.topology.schema.CommonSchema.Python>` can be subscribed to by other Streams Python applications. If a stream is published setting `schema` to :py:const:`~streamsx.topology.schema.CommonSchema.Json` then it is published as a stream of JSON objects. Other Streams applications may subscribe to it regardless of their implementation language. If a stream is published setting `schema` to :py:const:`~streamsx.topology.schema.CommonSchema.String` then it is published as strings Other Streams applications may subscribe to it regardless of their implementation language. Supported values of `schema` are only :py:const:`~streamsx.topology.schema.CommonSchema.Json` and :py:const:`~streamsx.topology.schema.CommonSchema.String`. Args: topic(str): Topic to publish this stream to. schema: Schema to publish. Defaults to the schema of this stream. name(str): Name of the publish operator, defaults to a generated name. Returns: streamsx.topology.topology.Sink: Stream termination. .. versionadded:: 1.6.1 `name` parameter. .. versionchanged:: 1.7 Now returns a :py:class:`Sink` instance.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1601-L1667
train
44,040
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Stream.as_json
def as_json(self, force_object=True, name=None): """ Declares a stream converting each tuple on this stream into a JSON value. The stream is typed as a :py:const:`JSON stream <streamsx.topology.schema.CommonSchema.Json>`. Each tuple must be supported by `JSONEncoder`. If `force_object` is `True` then each tuple that not a `dict` will be converted to a JSON object with a single key `payload` containing the tuple. Thus each object on the stream will be a JSON object. If `force_object` is `False` then each tuple is converted to a JSON value directly using `json` package. If this stream is already typed as a JSON stream then it will be returned (with no additional processing against it and `force_object` and `name` are ignored). Args: force_object(bool): Force conversion of non dicts to JSON objects. name(str): Name of the resulting stream. When `None` defaults to a generated name. .. versionadded:: 1.6.1 Returns: Stream: Stream containing the JSON representations of tuples on this stream. """ func = streamsx.topology.runtime._json_force_object if force_object else None saj = self._change_schema(streamsx.topology.schema.CommonSchema.Json, 'as_json', name, func)._layout('AsJson') saj.oport.operator.sl = _SourceLocation(_source_info(), 'as_json') return saj
python
def as_json(self, force_object=True, name=None): """ Declares a stream converting each tuple on this stream into a JSON value. The stream is typed as a :py:const:`JSON stream <streamsx.topology.schema.CommonSchema.Json>`. Each tuple must be supported by `JSONEncoder`. If `force_object` is `True` then each tuple that not a `dict` will be converted to a JSON object with a single key `payload` containing the tuple. Thus each object on the stream will be a JSON object. If `force_object` is `False` then each tuple is converted to a JSON value directly using `json` package. If this stream is already typed as a JSON stream then it will be returned (with no additional processing against it and `force_object` and `name` are ignored). Args: force_object(bool): Force conversion of non dicts to JSON objects. name(str): Name of the resulting stream. When `None` defaults to a generated name. .. versionadded:: 1.6.1 Returns: Stream: Stream containing the JSON representations of tuples on this stream. """ func = streamsx.topology.runtime._json_force_object if force_object else None saj = self._change_schema(streamsx.topology.schema.CommonSchema.Json, 'as_json', name, func)._layout('AsJson') saj.oport.operator.sl = _SourceLocation(_source_info(), 'as_json') return saj
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Declares a stream converting each tuple on this stream into a JSON value. The stream is typed as a :py:const:`JSON stream <streamsx.topology.schema.CommonSchema.Json>`. Each tuple must be supported by `JSONEncoder`. If `force_object` is `True` then each tuple that not a `dict` will be converted to a JSON object with a single key `payload` containing the tuple. Thus each object on the stream will be a JSON object. If `force_object` is `False` then each tuple is converted to a JSON value directly using `json` package. If this stream is already typed as a JSON stream then it will be returned (with no additional processing against it and `force_object` and `name` are ignored). Args: force_object(bool): Force conversion of non dicts to JSON objects. name(str): Name of the resulting stream. When `None` defaults to a generated name. .. versionadded:: 1.6.1 Returns: Stream: Stream containing the JSON representations of tuples on this stream.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1718-L1753
train
44,041
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Stream._change_schema
def _change_schema(self, schema, action, name=None, func=None): """Internal method to change a schema. """ if self.oport.schema.schema() == schema.schema(): return self if func is None: func = streamsx.topology.functions.identity _name = name if _name is None: _name = action css = self._map(func, schema, name=_name) if self._placeable: self._colocate(css, action) return css
python
def _change_schema(self, schema, action, name=None, func=None): """Internal method to change a schema. """ if self.oport.schema.schema() == schema.schema(): return self if func is None: func = streamsx.topology.functions.identity _name = name if _name is None: _name = action css = self._map(func, schema, name=_name) if self._placeable: self._colocate(css, action) return css
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1755-L1770
train
44,042
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
View._initialize_rest
def _initialize_rest(self): """Used to initialize the View object on first use. """ if self._submit_context is None: raise ValueError("View has not been created.") job = self._submit_context._job_access() self._view_object = job.get_views(name=self.name)[0]
python
def _initialize_rest(self): """Used to initialize the View object on first use. """ if self._submit_context is None: raise ValueError("View has not been created.") job = self._submit_context._job_access() self._view_object = job.get_views(name=self.name)[0]
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1814-L1820
train
44,043
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
PendingStream.complete
def complete(self, stream): """Complete the pending stream. Any connections made to :py:attr:`stream` are connected to `stream` once this method returns. Args: stream(Stream): Stream that completes the connection. """ assert not self.is_complete() self._marker.addInputPort(outputPort=stream.oport) self.stream.oport.schema = stream.oport.schema # Update the pending schema to the actual schema # Any downstream filters that took the reference # will be automatically updated to the correct schema self._pending_schema._set(self.stream.oport.schema) # Mark the operator with the pending stream # a start point for graph travesal stream.oport.operator._start_op = True
python
def complete(self, stream): """Complete the pending stream. Any connections made to :py:attr:`stream` are connected to `stream` once this method returns. Args: stream(Stream): Stream that completes the connection. """ assert not self.is_complete() self._marker.addInputPort(outputPort=stream.oport) self.stream.oport.schema = stream.oport.schema # Update the pending schema to the actual schema # Any downstream filters that took the reference # will be automatically updated to the correct schema self._pending_schema._set(self.stream.oport.schema) # Mark the operator with the pending stream # a start point for graph travesal stream.oport.operator._start_op = True
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1933-L1952
train
44,044
IBMStreams/pypi.streamsx
streamsx/topology/topology.py
Window.trigger
def trigger(self, when=1): """Declare a window with this window's size and a trigger policy. When the window is triggered is defined by `when`. If `when` is an `int` then the window is triggered every `when` tuples. For example, with ``when=5`` the window will be triggered every five tuples. If `when` is an `datetime.timedelta` then it is the period of the trigger. With a `timedelta` representing one minute then the window is triggered every minute. By default, when `trigger` has not been called on a `Window` it triggers for every tuple inserted into the window (equivalent to ``when=1``). Args: when: The size of the window, either an `int` to define the number of tuples or `datetime.timedelta` to define the duration of the window. Returns: Window: Window that will be triggered. .. warning:: A trigger is only supported for a sliding window such as one created by :py:meth:`last`. """ tw = Window(self.stream, self._config['type']) tw._config['evictPolicy'] = self._config['evictPolicy'] tw._config['evictConfig'] = self._config['evictConfig'] if self._config['evictPolicy'] == 'TIME': tw._config['evictTimeUnit'] = 'MILLISECONDS' if isinstance(when, datetime.timedelta): tw._config['triggerPolicy'] = 'TIME' tw._config['triggerConfig'] = int(when.total_seconds() * 1000.0) tw._config['triggerTimeUnit'] = 'MILLISECONDS' elif isinstance(when, int): tw._config['triggerPolicy'] = 'COUNT' tw._config['triggerConfig'] = when else: raise ValueError(when) return tw
python
def trigger(self, when=1): """Declare a window with this window's size and a trigger policy. When the window is triggered is defined by `when`. If `when` is an `int` then the window is triggered every `when` tuples. For example, with ``when=5`` the window will be triggered every five tuples. If `when` is an `datetime.timedelta` then it is the period of the trigger. With a `timedelta` representing one minute then the window is triggered every minute. By default, when `trigger` has not been called on a `Window` it triggers for every tuple inserted into the window (equivalent to ``when=1``). Args: when: The size of the window, either an `int` to define the number of tuples or `datetime.timedelta` to define the duration of the window. Returns: Window: Window that will be triggered. .. warning:: A trigger is only supported for a sliding window such as one created by :py:meth:`last`. """ tw = Window(self.stream, self._config['type']) tw._config['evictPolicy'] = self._config['evictPolicy'] tw._config['evictConfig'] = self._config['evictConfig'] if self._config['evictPolicy'] == 'TIME': tw._config['evictTimeUnit'] = 'MILLISECONDS' if isinstance(when, datetime.timedelta): tw._config['triggerPolicy'] = 'TIME' tw._config['triggerConfig'] = int(when.total_seconds() * 1000.0) tw._config['triggerTimeUnit'] = 'MILLISECONDS' elif isinstance(when, int): tw._config['triggerPolicy'] = 'COUNT' tw._config['triggerConfig'] = when else: raise ValueError(when) return tw
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/topology.py#L1991-L2034
train
44,045
IBMStreams/pypi.streamsx
streamsx/st.py
get_rest_api
def get_rest_api(): """ Get the root URL for the IBM Streams REST API. """ assert _has_local_install url=[] ok = _run_st(['geturl', '--api'], lines=url) if not ok: raise ChildProcessError('streamtool geturl') return url[0]
python
def get_rest_api(): """ Get the root URL for the IBM Streams REST API. """ assert _has_local_install url=[] ok = _run_st(['geturl', '--api'], lines=url) if not ok: raise ChildProcessError('streamtool geturl') return url[0]
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Get the root URL for the IBM Streams REST API.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/st.py#L25-L35
train
44,046
IBMStreams/pypi.streamsx
streamsx/topology/dependency.py
_is_builtin_module
def _is_builtin_module(module): """Is builtin or part of standard library """ if (not hasattr(module, '__file__')) or module.__name__ in sys.builtin_module_names: return True if module.__name__ in _stdlib._STD_LIB_MODULES: return True amp = os.path.abspath(module.__file__) if 'site-packages' in amp: return False if amp.startswith(_STD_MODULE_DIR): return True if not '.' in module.__name__: return False mn_top = module.__name__.split('.')[0] return mn_top in _stdlib._STD_LIB_MODULES
python
def _is_builtin_module(module): """Is builtin or part of standard library """ if (not hasattr(module, '__file__')) or module.__name__ in sys.builtin_module_names: return True if module.__name__ in _stdlib._STD_LIB_MODULES: return True amp = os.path.abspath(module.__file__) if 'site-packages' in amp: return False if amp.startswith(_STD_MODULE_DIR): return True if not '.' in module.__name__: return False mn_top = module.__name__.split('.')[0] return mn_top in _stdlib._STD_LIB_MODULES
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Is builtin or part of standard library
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/dependency.py#L252-L267
train
44,047
IBMStreams/pypi.streamsx
streamsx/topology/dependency.py
_DependencyResolver._find_dependent_modules
def _find_dependent_modules(self, module): """ Return the set of dependent modules for used modules, classes and routines. """ dms = set() for um in inspect.getmembers(module, inspect.ismodule): dms.add(um[1]) for uc in inspect.getmembers(module, inspect.isclass): self._add_obj_module(dms, uc[1]) for ur in inspect.getmembers(module, inspect.isroutine): self._add_obj_module(dms, ur[1]) return dms
python
def _find_dependent_modules(self, module): """ Return the set of dependent modules for used modules, classes and routines. """ dms = set() for um in inspect.getmembers(module, inspect.ismodule): dms.add(um[1]) for uc in inspect.getmembers(module, inspect.isclass): self._add_obj_module(dms, uc[1]) for ur in inspect.getmembers(module, inspect.isroutine): self._add_obj_module(dms, ur[1]) return dms
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Return the set of dependent modules for used modules, classes and routines.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/dependency.py#L35-L49
train
44,048
IBMStreams/pypi.streamsx
streamsx/topology/dependency.py
_DependencyResolver.add_dependencies
def add_dependencies(self, module): """ Adds a module and its dependencies to the list of dependencies. Top-level entry point for adding a module and its dependecies. """ if module in self._processed_modules: return None if hasattr(module, "__name__"): mn = module.__name__ else: mn = '<unknown>' _debug.debug("add_dependencies:module=%s", module) # If the module in which the class/function is defined is __main__, don't add it. Just add its dependencies. if mn == "__main__": self._processed_modules.add(module) # add the module as a dependency elif not self._add_dependency(module, mn): _debug.debug("add_dependencies:not added:module=%s", mn) return None _debug.debug("add_dependencies:ADDED:module=%s", mn) # recursively get the module's imports and add those as dependencies for dm in self._find_dependent_modules(module): _debug.debug("add_dependencies:adding dependent module %s for %s", dm, mn) self.add_dependencies(dm)
python
def add_dependencies(self, module): """ Adds a module and its dependencies to the list of dependencies. Top-level entry point for adding a module and its dependecies. """ if module in self._processed_modules: return None if hasattr(module, "__name__"): mn = module.__name__ else: mn = '<unknown>' _debug.debug("add_dependencies:module=%s", module) # If the module in which the class/function is defined is __main__, don't add it. Just add its dependencies. if mn == "__main__": self._processed_modules.add(module) # add the module as a dependency elif not self._add_dependency(module, mn): _debug.debug("add_dependencies:not added:module=%s", mn) return None _debug.debug("add_dependencies:ADDED:module=%s", mn) # recursively get the module's imports and add those as dependencies for dm in self._find_dependent_modules(module): _debug.debug("add_dependencies:adding dependent module %s for %s", dm, mn) self.add_dependencies(dm)
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Adds a module and its dependencies to the list of dependencies. Top-level entry point for adding a module and its dependecies.
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/dependency.py#L56-L87
train
44,049
IBMStreams/pypi.streamsx
streamsx/topology/dependency.py
_DependencyResolver._include_module
def _include_module(self, module, mn): """ See if a module should be included or excluded based upon included_packages and excluded_packages. As some packages have the following format: scipy.special.specfun scipy.linalg Where the top-level package name is just a prefix to a longer package name, we don't want to do a direct comparison. Instead, we want to exclude packages which are either exactly "<package_name>", or start with "<package_name>". """ if mn in self.topology.include_packages: _debug.debug("_include_module:explicit using __include_packages: module=%s", mn) return True if '.' in mn: for include_package in self.topology.include_packages: if mn.startswith(include_package + '.'): _debug.debug("_include_module:explicit pattern using __include_packages: module=%s pattern=%s", mn, \ include_package + '.') return True if mn in self.topology.exclude_packages: _debug.debug("_include_module:explicit using __exclude_packages: module=%s", mn) return False if '.' in mn: for exclude_package in self.topology.exclude_packages: if mn.startswith(exclude_package + '.'): _debug.debug("_include_module:explicit pattern using __exclude_packages: module=%s pattern=%s", mn, \ exclude_package + '.') return False _debug.debug("_include_module:including: module=%s", mn) return True
python
def _include_module(self, module, mn): """ See if a module should be included or excluded based upon included_packages and excluded_packages. As some packages have the following format: scipy.special.specfun scipy.linalg Where the top-level package name is just a prefix to a longer package name, we don't want to do a direct comparison. Instead, we want to exclude packages which are either exactly "<package_name>", or start with "<package_name>". """ if mn in self.topology.include_packages: _debug.debug("_include_module:explicit using __include_packages: module=%s", mn) return True if '.' in mn: for include_package in self.topology.include_packages: if mn.startswith(include_package + '.'): _debug.debug("_include_module:explicit pattern using __include_packages: module=%s pattern=%s", mn, \ include_package + '.') return True if mn in self.topology.exclude_packages: _debug.debug("_include_module:explicit using __exclude_packages: module=%s", mn) return False if '.' in mn: for exclude_package in self.topology.exclude_packages: if mn.startswith(exclude_package + '.'): _debug.debug("_include_module:explicit pattern using __exclude_packages: module=%s pattern=%s", mn, \ exclude_package + '.') return False _debug.debug("_include_module:including: module=%s", mn) return True
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See if a module should be included or excluded based upon included_packages and excluded_packages. As some packages have the following format: scipy.special.specfun scipy.linalg Where the top-level package name is just a prefix to a longer package name, we don't want to do a direct comparison. Instead, we want to exclude packages which are either exactly "<package_name>", or start with "<package_name>".
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/dependency.py#L103-L138
train
44,050
IBMStreams/pypi.streamsx
streamsx/topology/dependency.py
_DependencyResolver._add_dependency
def _add_dependency(self, module, mn): """ Adds a module to the list of dependencies without handling the modules dependences. Modules in site-packages are excluded from being added into the toolkit. This mimics dill. """ _debug.debug("_add_dependency:module=%s", mn) if _is_streamsx_module(module): _debug.debug("_add_dependency:streamsx module=%s", mn) return False if _is_builtin_module(module): _debug.debug("_add_dependency:builtin module=%s", mn) return False if not self._include_module(module, mn): #print ("ignoring dependencies for {0} {1}".format(module.__name__, module)) return False package_name = _get_package_name(module) top_package_name = module.__name__.split('.')[0] if package_name and top_package_name in sys.modules: # module is part of a package # get the top-level package top_package = sys.modules[top_package_name] if "__path__" in top_package.__dict__: # for regular packages, there is one top-level directory # for namespace packages, there can be more than one. # they will be merged in the bundle seen_non_site_package = False for top_package_path in reversed(list(top_package.__path__)): top_package_path = os.path.abspath(top_package_path) if 'site-packages' in top_package_path: continue seen_non_site_package = True self._add_package(top_package_path) if not seen_non_site_package: _debug.debug("_add_dependency:site-packages path module=%s", mn) return False elif hasattr(top_package, '__file__'): # package that is an individual python file with empty __path__ if 'site-packages' in top_package.__file__: _debug.debug("_add_dependency:site-packages module=%s", mn) return False self._add_package(os.path.abspath(top_package.__file__)) elif hasattr(module, '__file__'): # individual Python module module_path = os.path.abspath(module.__file__) if 'site-packages' in module_path: _debug.debug("_add_dependency:site-packages module=%s", mn) return False self._modules.add(module_path) self._processed_modules.add(module) return True
python
def _add_dependency(self, module, mn): """ Adds a module to the list of dependencies without handling the modules dependences. Modules in site-packages are excluded from being added into the toolkit. This mimics dill. """ _debug.debug("_add_dependency:module=%s", mn) if _is_streamsx_module(module): _debug.debug("_add_dependency:streamsx module=%s", mn) return False if _is_builtin_module(module): _debug.debug("_add_dependency:builtin module=%s", mn) return False if not self._include_module(module, mn): #print ("ignoring dependencies for {0} {1}".format(module.__name__, module)) return False package_name = _get_package_name(module) top_package_name = module.__name__.split('.')[0] if package_name and top_package_name in sys.modules: # module is part of a package # get the top-level package top_package = sys.modules[top_package_name] if "__path__" in top_package.__dict__: # for regular packages, there is one top-level directory # for namespace packages, there can be more than one. # they will be merged in the bundle seen_non_site_package = False for top_package_path in reversed(list(top_package.__path__)): top_package_path = os.path.abspath(top_package_path) if 'site-packages' in top_package_path: continue seen_non_site_package = True self._add_package(top_package_path) if not seen_non_site_package: _debug.debug("_add_dependency:site-packages path module=%s", mn) return False elif hasattr(top_package, '__file__'): # package that is an individual python file with empty __path__ if 'site-packages' in top_package.__file__: _debug.debug("_add_dependency:site-packages module=%s", mn) return False self._add_package(os.path.abspath(top_package.__file__)) elif hasattr(module, '__file__'): # individual Python module module_path = os.path.abspath(module.__file__) if 'site-packages' in module_path: _debug.debug("_add_dependency:site-packages module=%s", mn) return False self._modules.add(module_path) self._processed_modules.add(module) return True
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/topology/dependency.py#L140-L199
train
44,051
raphaelm/django-hierarkey
hierarkey/proxy.py
HierarkeyProxy.freeze
def freeze(self) -> dict: """ Returns a dictionary of all settings set for this object, including any values of its parents or hardcoded defaults. """ settings = {} for key, v in self._h.defaults.items(): settings[key] = self._unserialize(v.value, v.type) if self._parent: settings.update(getattr(self._parent, self._h.attribute_name).freeze()) for key in self._cache(): settings[key] = self.get(key) return settings
python
def freeze(self) -> dict: """ Returns a dictionary of all settings set for this object, including any values of its parents or hardcoded defaults. """ settings = {} for key, v in self._h.defaults.items(): settings[key] = self._unserialize(v.value, v.type) if self._parent: settings.update(getattr(self._parent, self._h.attribute_name).freeze()) for key in self._cache(): settings[key] = self.get(key) return settings
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Returns a dictionary of all settings set for this object, including any values of its parents or hardcoded defaults.
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3ca822f94fa633c9a6d5abe9c80cb1551299ae46
https://github.com/raphaelm/django-hierarkey/blob/3ca822f94fa633c9a6d5abe9c80cb1551299ae46/hierarkey/proxy.py#L72-L84
train
44,052
raphaelm/django-hierarkey
hierarkey/proxy.py
HierarkeyProxy.get
def get(self, key: str, default=None, as_type: type = None, binary_file=False): """ Get a setting specified by key ``key``. Normally, settings are strings, but if you put non-strings into the settings object, you can request unserialization by specifying ``as_type``. If the key does not have a harcdoded default type, omitting ``as_type`` always will get you a string. If the setting with the specified name does not exist on this object, any parent object up to the global settings layer (if configured) will be queried. If still no value is found, a default value set in ths source code will be returned if one exists. If not, the value of the ``default`` argument of this method will be returned instead. If you receive a ``File`` object, it will already be opened. You can specify the ``binary_file`` flag to indicate that it should be opened in binary mode. """ if as_type is None and key in self._h.defaults: as_type = self._h.defaults[key].type if key in self._cache(): value = self._cache()[key] else: value = None if self._parent: value = getattr(self._parent, self._h.attribute_name).get(key, as_type=str) if value is None and key in self._h.defaults: value = self._h.defaults[key].value if value is None and default is not None: value = default return self._unserialize(value, as_type, binary_file=binary_file)
python
def get(self, key: str, default=None, as_type: type = None, binary_file=False): """ Get a setting specified by key ``key``. Normally, settings are strings, but if you put non-strings into the settings object, you can request unserialization by specifying ``as_type``. If the key does not have a harcdoded default type, omitting ``as_type`` always will get you a string. If the setting with the specified name does not exist on this object, any parent object up to the global settings layer (if configured) will be queried. If still no value is found, a default value set in ths source code will be returned if one exists. If not, the value of the ``default`` argument of this method will be returned instead. If you receive a ``File`` object, it will already be opened. You can specify the ``binary_file`` flag to indicate that it should be opened in binary mode. """ if as_type is None and key in self._h.defaults: as_type = self._h.defaults[key].type if key in self._cache(): value = self._cache()[key] else: value = None if self._parent: value = getattr(self._parent, self._h.attribute_name).get(key, as_type=str) if value is None and key in self._h.defaults: value = self._h.defaults[key].value if value is None and default is not None: value = default return self._unserialize(value, as_type, binary_file=binary_file)
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Get a setting specified by key ``key``. Normally, settings are strings, but if you put non-strings into the settings object, you can request unserialization by specifying ``as_type``. If the key does not have a harcdoded default type, omitting ``as_type`` always will get you a string. If the setting with the specified name does not exist on this object, any parent object up to the global settings layer (if configured) will be queried. If still no value is found, a default value set in ths source code will be returned if one exists. If not, the value of the ``default`` argument of this method will be returned instead. If you receive a ``File`` object, it will already be opened. You can specify the ``binary_file`` flag to indicate that it should be opened in binary mode.
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3ca822f94fa633c9a6d5abe9c80cb1551299ae46
https://github.com/raphaelm/django-hierarkey/blob/3ca822f94fa633c9a6d5abe9c80cb1551299ae46/hierarkey/proxy.py#L144-L173
train
44,053
raphaelm/django-hierarkey
hierarkey/proxy.py
HierarkeyProxy.set
def set(self, key: str, value: Any) -> None: """ Stores a setting to the database of its object. The write to the database is performed immediately and the cache in the cache backend is flushed. The cache within this object will be updated correctly. """ wc = self._write_cache() if key in wc: s = wc[key] else: s = self._type(object=self._obj, key=key) s.value = self._serialize(value) s.save() self._cache()[key] = s.value wc[key] = s self._flush_external_cache()
python
def set(self, key: str, value: Any) -> None: """ Stores a setting to the database of its object. The write to the database is performed immediately and the cache in the cache backend is flushed. The cache within this object will be updated correctly. """ wc = self._write_cache() if key in wc: s = wc[key] else: s = self._type(object=self._obj, key=key) s.value = self._serialize(value) s.save() self._cache()[key] = s.value wc[key] = s self._flush_external_cache()
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3ca822f94fa633c9a6d5abe9c80cb1551299ae46
https://github.com/raphaelm/django-hierarkey/blob/3ca822f94fa633c9a6d5abe9c80cb1551299ae46/hierarkey/proxy.py#L191-L207
train
44,054
raphaelm/django-hierarkey
hierarkey/proxy.py
HierarkeyProxy.delete
def delete(self, key: str) -> None: """ Deletes a setting from this object's storage. The write to the database is performed immediately and the cache in the cache backend is flushed. The cache within this object will be updated correctly. """ if key in self._write_cache(): self._write_cache()[key].delete() del self._write_cache()[key] if key in self._cache(): del self._cache()[key] self._flush_external_cache()
python
def delete(self, key: str) -> None: """ Deletes a setting from this object's storage. The write to the database is performed immediately and the cache in the cache backend is flushed. The cache within this object will be updated correctly. """ if key in self._write_cache(): self._write_cache()[key].delete() del self._write_cache()[key] if key in self._cache(): del self._cache()[key] self._flush_external_cache()
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3ca822f94fa633c9a6d5abe9c80cb1551299ae46
https://github.com/raphaelm/django-hierarkey/blob/3ca822f94fa633c9a6d5abe9c80cb1551299ae46/hierarkey/proxy.py#L217-L231
train
44,055
IBMStreams/pypi.streamsx
streamsx/rest.py
_get_vcap_services
def _get_vcap_services(vcap_services=None): """Retrieves the VCAP Services information from the `ConfigParams.VCAP_SERVICES` field in the config object. If `vcap_services` is not specified, it takes the information from VCAP_SERVICES environment variable. Args: vcap_services (str): Try to parse as a JSON string, otherwise, try open it as a file. vcap_services (dict): Return the dict as is. Returns: dict: A dict representation of the VCAP Services information. Raises: ValueError: * if `vcap_services` nor VCAP_SERVICES environment variable are specified. * cannot parse `vcap_services` as a JSON string nor as a filename. """ vcap_services = vcap_services or os.environ.get('VCAP_SERVICES') if not vcap_services: raise ValueError( "VCAP_SERVICES information must be supplied as a parameter or as environment variable 'VCAP_SERVICES'") # If it was passed to config as a dict, simply return it if isinstance(vcap_services, dict): return vcap_services try: # Otherwise, if it's a string, try to load it as json vcap_services = json.loads(vcap_services) except json.JSONDecodeError: # If that doesn't work, attempt to open it as a file path to the json config. try: with open(vcap_services) as vcap_json_data: vcap_services = json.load(vcap_json_data) except: raise ValueError("VCAP_SERVICES information is not JSON or a file containing JSON:", vcap_services) return vcap_services
python
def _get_vcap_services(vcap_services=None): """Retrieves the VCAP Services information from the `ConfigParams.VCAP_SERVICES` field in the config object. If `vcap_services` is not specified, it takes the information from VCAP_SERVICES environment variable. Args: vcap_services (str): Try to parse as a JSON string, otherwise, try open it as a file. vcap_services (dict): Return the dict as is. Returns: dict: A dict representation of the VCAP Services information. Raises: ValueError: * if `vcap_services` nor VCAP_SERVICES environment variable are specified. * cannot parse `vcap_services` as a JSON string nor as a filename. """ vcap_services = vcap_services or os.environ.get('VCAP_SERVICES') if not vcap_services: raise ValueError( "VCAP_SERVICES information must be supplied as a parameter or as environment variable 'VCAP_SERVICES'") # If it was passed to config as a dict, simply return it if isinstance(vcap_services, dict): return vcap_services try: # Otherwise, if it's a string, try to load it as json vcap_services = json.loads(vcap_services) except json.JSONDecodeError: # If that doesn't work, attempt to open it as a file path to the json config. try: with open(vcap_services) as vcap_json_data: vcap_services = json.load(vcap_json_data) except: raise ValueError("VCAP_SERVICES information is not JSON or a file containing JSON:", vcap_services) return vcap_services
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest.py#L309-L342
train
44,056
IBMStreams/pypi.streamsx
streamsx/rest.py
_get_credentials
def _get_credentials(vcap_services, service_name=None): """Retrieves the credentials of the VCAP Service of the specified `service_name`. If `service_name` is not specified, it takes the information from STREAMING_ANALYTICS_SERVICE_NAME environment variable. Args: vcap_services (dict): A dict representation of the VCAP Services information. service_name (str): One of the service name stored in `vcap_services` Returns: dict: A dict representation of the credentials. Raises: ValueError: Cannot find `service_name` in `vcap_services` """ service_name = service_name or os.environ.get('STREAMING_ANALYTICS_SERVICE_NAME', None) # Get the service corresponding to the SERVICE_NAME services = vcap_services['streaming-analytics'] creds = None for service in services: if service['name'] == service_name: creds = service['credentials'] break # If no corresponding service is found, error if creds is None: raise ValueError("Streaming Analytics service " + str(service_name) + " was not found in VCAP_SERVICES") return creds
python
def _get_credentials(vcap_services, service_name=None): """Retrieves the credentials of the VCAP Service of the specified `service_name`. If `service_name` is not specified, it takes the information from STREAMING_ANALYTICS_SERVICE_NAME environment variable. Args: vcap_services (dict): A dict representation of the VCAP Services information. service_name (str): One of the service name stored in `vcap_services` Returns: dict: A dict representation of the credentials. Raises: ValueError: Cannot find `service_name` in `vcap_services` """ service_name = service_name or os.environ.get('STREAMING_ANALYTICS_SERVICE_NAME', None) # Get the service corresponding to the SERVICE_NAME services = vcap_services['streaming-analytics'] creds = None for service in services: if service['name'] == service_name: creds = service['credentials'] break # If no corresponding service is found, error if creds is None: raise ValueError("Streaming Analytics service " + str(service_name) + " was not found in VCAP_SERVICES") return creds
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest.py#L345-L372
train
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IBMStreams/pypi.streamsx
streamsx/rest.py
StreamsConnection.get_domains
def get_domains(self): """Retrieves available domains. Returns: :py:obj:`list` of :py:class:`~.rest_primitives.Domain`: List of available domains """ # Domains are fixed and actually only one per REST api. if self._domains is None: self._domains = self._get_elements('domains', Domain) return self._domains
python
def get_domains(self): """Retrieves available domains. Returns: :py:obj:`list` of :py:class:`~.rest_primitives.Domain`: List of available domains """ # Domains are fixed and actually only one per REST api. if self._domains is None: self._domains = self._get_elements('domains', Domain) return self._domains
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Retrieves available domains. Returns: :py:obj:`list` of :py:class:`~.rest_primitives.Domain`: List of available domains
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest.py#L163-L172
train
44,058
IBMStreams/pypi.streamsx
streamsx/rest.py
StreamsConnection.get_resources
def get_resources(self): """Retrieves a list of all known Streams high-level REST resources. Returns: :py:obj:`list` of :py:class:`~.rest_primitives.RestResource`: List of all Streams high-level REST resources. """ json_resources = self.rest_client.make_request(self.resource_url)['resources'] return [RestResource(resource, self.rest_client) for resource in json_resources]
python
def get_resources(self): """Retrieves a list of all known Streams high-level REST resources. Returns: :py:obj:`list` of :py:class:`~.rest_primitives.RestResource`: List of all Streams high-level REST resources. """ json_resources = self.rest_client.make_request(self.resource_url)['resources'] return [RestResource(resource, self.rest_client) for resource in json_resources]
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest.py#L218-L225
train
44,059
IBMStreams/pypi.streamsx
streamsx/rest.py
StreamingAnalyticsConnection.of_definition
def of_definition(service_def): """Create a connection to a Streaming Analytics service. The single service is defined by `service_def` which can be one of * The `service credentials` copied from the `Service credentials` page of the service console (not the Streams console). Credentials are provided in JSON format. They contain such as the API key and secret, as well as connection information for the service. * A JSON object (`dict`) of the form: ``{ "type": "streaming-analytics", "name": "service name", "credentials": {...} }`` with the `service credentials` as the value of the ``credentials`` key. Args: service_def(dict): Definition of the service to connect to. Returns: StreamingAnalyticsConnection: Connection to defined service. """ vcap_services = streamsx.topology.context._vcap_from_service_definition(service_def) service_name = streamsx.topology.context._name_from_service_definition(service_def) return StreamingAnalyticsConnection(vcap_services, service_name)
python
def of_definition(service_def): """Create a connection to a Streaming Analytics service. The single service is defined by `service_def` which can be one of * The `service credentials` copied from the `Service credentials` page of the service console (not the Streams console). Credentials are provided in JSON format. They contain such as the API key and secret, as well as connection information for the service. * A JSON object (`dict`) of the form: ``{ "type": "streaming-analytics", "name": "service name", "credentials": {...} }`` with the `service credentials` as the value of the ``credentials`` key. Args: service_def(dict): Definition of the service to connect to. Returns: StreamingAnalyticsConnection: Connection to defined service. """ vcap_services = streamsx.topology.context._vcap_from_service_definition(service_def) service_name = streamsx.topology.context._name_from_service_definition(service_def) return StreamingAnalyticsConnection(vcap_services, service_name)
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abd67b4757120f6f805787fba390f53e9df9cdd8
https://github.com/IBMStreams/pypi.streamsx/blob/abd67b4757120f6f805787fba390f53e9df9cdd8/streamsx/rest.py#L271-L287
train
44,060
orcasgit/django-tastypie-oauth
tastypie_oauth/authentication.py
OAuth20Authentication.is_authenticated
def is_authenticated(self, request, **kwargs): """ Verify 2-legged oauth request. Parameters accepted as values in the "Authorization" header, as a GET request parameter, or in a POST body. """ log.info("OAuth20Authentication") try: key = request.GET.get('oauth_consumer_key') if not key: for header in ['Authorization', 'HTTP_AUTHORIZATION']: auth_header_value = request.META.get(header) if auth_header_value: key = auth_header_value.split(' ', 1)[1] break if not key and request.method == 'POST': if request.META.get('CONTENT_TYPE') == 'application/json': decoded_body = request.body.decode('utf8') key = json.loads(decoded_body)['oauth_consumer_key'] if not key: log.info('OAuth20Authentication. No consumer_key found.') return None """ If verify_access_token() does not pass, it will raise an error """ token = self.verify_access_token(key, request, **kwargs) # If OAuth authentication is successful, set the request user to # the token user for authorization request.user = token.user # If OAuth authentication is successful, set oauth_consumer_key on # request in case we need it later request.META['oauth_consumer_key'] = key return True except KeyError: log.exception("Error in OAuth20Authentication.") request.user = AnonymousUser() return False except Exception: log.exception("Error in OAuth20Authentication.") return False
python
def is_authenticated(self, request, **kwargs): """ Verify 2-legged oauth request. Parameters accepted as values in the "Authorization" header, as a GET request parameter, or in a POST body. """ log.info("OAuth20Authentication") try: key = request.GET.get('oauth_consumer_key') if not key: for header in ['Authorization', 'HTTP_AUTHORIZATION']: auth_header_value = request.META.get(header) if auth_header_value: key = auth_header_value.split(' ', 1)[1] break if not key and request.method == 'POST': if request.META.get('CONTENT_TYPE') == 'application/json': decoded_body = request.body.decode('utf8') key = json.loads(decoded_body)['oauth_consumer_key'] if not key: log.info('OAuth20Authentication. No consumer_key found.') return None """ If verify_access_token() does not pass, it will raise an error """ token = self.verify_access_token(key, request, **kwargs) # If OAuth authentication is successful, set the request user to # the token user for authorization request.user = token.user # If OAuth authentication is successful, set oauth_consumer_key on # request in case we need it later request.META['oauth_consumer_key'] = key return True except KeyError: log.exception("Error in OAuth20Authentication.") request.user = AnonymousUser() return False except Exception: log.exception("Error in OAuth20Authentication.") return False
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01c40de7b86ae3c6cc9e9463ec9bcecbb22b897e
https://github.com/orcasgit/django-tastypie-oauth/blob/01c40de7b86ae3c6cc9e9463ec9bcecbb22b897e/tastypie_oauth/authentication.py#L39-L80
train
44,061
orcasgit/django-tastypie-oauth
tastypie_oauth/authentication.py
OAuth2ScopedAuthentication.check_scope
def check_scope(self, token, request): http_method = request.method if not hasattr(self, http_method): raise OAuthError("HTTP method is not recognized") required_scopes = getattr(self, http_method) # a None scope means always allowed if required_scopes is None: return True """ The required scope is either a string or an iterable. If string, check if it is allowed for our access token otherwise, iterate through the required_scopes to see which scopes are allowed """ # for non iterable types if isinstance(required_scopes, six.string_types): if token.allow_scopes(required_scopes.split()): return [required_scopes] return [] allowed_scopes = [] try: for scope in required_scopes: if token.allow_scopes(scope.split()): allowed_scopes.append(scope) except: raise Exception('Invalid required scope values') else: return allowed_scopes
python
def check_scope(self, token, request): http_method = request.method if not hasattr(self, http_method): raise OAuthError("HTTP method is not recognized") required_scopes = getattr(self, http_method) # a None scope means always allowed if required_scopes is None: return True """ The required scope is either a string or an iterable. If string, check if it is allowed for our access token otherwise, iterate through the required_scopes to see which scopes are allowed """ # for non iterable types if isinstance(required_scopes, six.string_types): if token.allow_scopes(required_scopes.split()): return [required_scopes] return [] allowed_scopes = [] try: for scope in required_scopes: if token.allow_scopes(scope.split()): allowed_scopes.append(scope) except: raise Exception('Invalid required scope values') else: return allowed_scopes
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The required scope is either a string or an iterable. If string, check if it is allowed for our access token otherwise, iterate through the required_scopes to see which scopes are allowed
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01c40de7b86ae3c6cc9e9463ec9bcecbb22b897e
https://github.com/orcasgit/django-tastypie-oauth/blob/01c40de7b86ae3c6cc9e9463ec9bcecbb22b897e/tastypie_oauth/authentication.py#L140-L166
train
44,062
feluxe/sty
sty/primitive.py
Base.as_dict
def as_dict(self) -> Dict[str, str]: """ Export color register as dict. """ items: Dict[str, str] = {} for k, v in self.items(): if type(v) is str: items.update({k: v}) return items
python
def as_dict(self) -> Dict[str, str]: """ Export color register as dict. """ items: Dict[str, str] = {} for k, v in self.items(): if type(v) is str: items.update({k: v}) return items
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60af9c1c59556a6f285d3d0ba4b8e125f8adc107
https://github.com/feluxe/sty/blob/60af9c1c59556a6f285d3d0ba4b8e125f8adc107/sty/primitive.py#L170-L181
train
44,063
feluxe/sty
sty/primitive.py
Base.as_namedtuple
def as_namedtuple(self): """ Export color register as namedtuple. """ d = self.as_dict() return namedtuple('ColorRegister', d.keys())(*d.values())
python
def as_namedtuple(self): """ Export color register as namedtuple. """ d = self.as_dict() return namedtuple('ColorRegister', d.keys())(*d.values())
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60af9c1c59556a6f285d3d0ba4b8e125f8adc107
https://github.com/feluxe/sty/blob/60af9c1c59556a6f285d3d0ba4b8e125f8adc107/sty/primitive.py#L183-L188
train
44,064
tomduck/pandoc-fignos
pandoc_fignos.py
_extract_attrs
def _extract_attrs(x, n): """Extracts attributes for an image. n is the index where the attributes begin. Extracted elements are deleted from the element list x. Attrs are returned in pandoc format. """ try: return extract_attrs(x, n) except (ValueError, IndexError): if PANDOCVERSION < '1.16': # Look for attributes attached to the image path, as occurs with # image references for pandoc < 1.16 (pandoc-fignos Issue #14). # See http://pandoc.org/MANUAL.html#images for the syntax. # Note: This code does not handle the "optional title" for # image references (search for link_attributes in pandoc's docs). assert x[n-1]['t'] == 'Image' image = x[n-1] s = image['c'][-1][0] if '%20%7B' in s: path = s[:s.index('%20%7B')] attrs = unquote(s[s.index('%7B'):]) image['c'][-1][0] = path # Remove attr string from the path return PandocAttributes(attrs.strip(), 'markdown').to_pandoc() raise
python
def _extract_attrs(x, n): """Extracts attributes for an image. n is the index where the attributes begin. Extracted elements are deleted from the element list x. Attrs are returned in pandoc format. """ try: return extract_attrs(x, n) except (ValueError, IndexError): if PANDOCVERSION < '1.16': # Look for attributes attached to the image path, as occurs with # image references for pandoc < 1.16 (pandoc-fignos Issue #14). # See http://pandoc.org/MANUAL.html#images for the syntax. # Note: This code does not handle the "optional title" for # image references (search for link_attributes in pandoc's docs). assert x[n-1]['t'] == 'Image' image = x[n-1] s = image['c'][-1][0] if '%20%7B' in s: path = s[:s.index('%20%7B')] attrs = unquote(s[s.index('%7B'):]) image['c'][-1][0] = path # Remove attr string from the path return PandocAttributes(attrs.strip(), 'markdown').to_pandoc() raise
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44776d885b8101d9d6aeb6845b17ad1625e88e6f
https://github.com/tomduck/pandoc-fignos/blob/44776d885b8101d9d6aeb6845b17ad1625e88e6f/pandoc_fignos.py#L93-L117
train
44,065
tomduck/pandoc-fignos
pandoc_fignos.py
process_figures
def process_figures(key, value, fmt, meta): # pylint: disable=unused-argument """Processes the figures.""" global has_unnumbered_figures # pylint: disable=global-statement # Process figures wrapped in Para elements if key == 'Para' and len(value) == 1 and \ value[0]['t'] == 'Image' and value[0]['c'][-1][1].startswith('fig:'): # Inspect the image if len(value[0]['c']) == 2: # Unattributed, bail out has_unnumbered_figures = True if fmt == 'latex': return [RawBlock('tex', r'\begin{no-prefix-figure-caption}'), Para(value), RawBlock('tex', r'\end{no-prefix-figure-caption}')] return None # Process the figure fig = _process_figure(value, fmt) # Context-dependent output attrs = fig['attrs'] if fig['is_unnumbered']: # Unnumbered is also unreferenceable if fmt == 'latex': return [ RawBlock('tex', r'\begin{no-prefix-figure-caption}'), Para(value), RawBlock('tex', r'\end{no-prefix-figure-caption}')] elif fmt in ['latex', 'beamer']: key = attrs[0] if PANDOCVERSION >= '1.17': # Remove id from the image attributes. It is incorrectly # handled by pandoc's TeX writer for these versions. if LABEL_PATTERN.match(attrs[0]): attrs[0] = '' if fig['is_tagged']: # Code in the tags tex = '\n'.join([r'\let\oldthefigure=\thefigure', r'\renewcommand\thefigure{%s}'%\ references[key]]) pre = RawBlock('tex', tex) tex = '\n'.join([r'\let\thefigure=\oldthefigure', r'\addtocounter{figure}{-1}']) post = RawBlock('tex', tex) return [pre, Para(value), post] elif fig['is_unreferenceable']: attrs[0] = '' # The label isn't needed any further elif PANDOCVERSION < '1.16' and fmt in ('html', 'html5') \ and LABEL_PATTERN.match(attrs[0]): # Insert anchor anchor = RawBlock('html', '<a name="%s"></a>'%attrs[0]) return [anchor, Para(value)] elif fmt == 'docx': # As per http://officeopenxml.com/WPhyperlink.php bookmarkstart = \ RawBlock('openxml', '<w:bookmarkStart w:id="0" w:name="%s"/>' %attrs[0]) bookmarkend = \ RawBlock('openxml', '<w:bookmarkEnd w:id="0"/>') return [bookmarkstart, Para(value), bookmarkend] return None
python
def process_figures(key, value, fmt, meta): # pylint: disable=unused-argument """Processes the figures.""" global has_unnumbered_figures # pylint: disable=global-statement # Process figures wrapped in Para elements if key == 'Para' and len(value) == 1 and \ value[0]['t'] == 'Image' and value[0]['c'][-1][1].startswith('fig:'): # Inspect the image if len(value[0]['c']) == 2: # Unattributed, bail out has_unnumbered_figures = True if fmt == 'latex': return [RawBlock('tex', r'\begin{no-prefix-figure-caption}'), Para(value), RawBlock('tex', r'\end{no-prefix-figure-caption}')] return None # Process the figure fig = _process_figure(value, fmt) # Context-dependent output attrs = fig['attrs'] if fig['is_unnumbered']: # Unnumbered is also unreferenceable if fmt == 'latex': return [ RawBlock('tex', r'\begin{no-prefix-figure-caption}'), Para(value), RawBlock('tex', r'\end{no-prefix-figure-caption}')] elif fmt in ['latex', 'beamer']: key = attrs[0] if PANDOCVERSION >= '1.17': # Remove id from the image attributes. It is incorrectly # handled by pandoc's TeX writer for these versions. if LABEL_PATTERN.match(attrs[0]): attrs[0] = '' if fig['is_tagged']: # Code in the tags tex = '\n'.join([r'\let\oldthefigure=\thefigure', r'\renewcommand\thefigure{%s}'%\ references[key]]) pre = RawBlock('tex', tex) tex = '\n'.join([r'\let\thefigure=\oldthefigure', r'\addtocounter{figure}{-1}']) post = RawBlock('tex', tex) return [pre, Para(value), post] elif fig['is_unreferenceable']: attrs[0] = '' # The label isn't needed any further elif PANDOCVERSION < '1.16' and fmt in ('html', 'html5') \ and LABEL_PATTERN.match(attrs[0]): # Insert anchor anchor = RawBlock('html', '<a name="%s"></a>'%attrs[0]) return [anchor, Para(value)] elif fmt == 'docx': # As per http://officeopenxml.com/WPhyperlink.php bookmarkstart = \ RawBlock('openxml', '<w:bookmarkStart w:id="0" w:name="%s"/>' %attrs[0]) bookmarkend = \ RawBlock('openxml', '<w:bookmarkEnd w:id="0"/>') return [bookmarkstart, Para(value), bookmarkend] return None
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Processes the figures.
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44776d885b8101d9d6aeb6845b17ad1625e88e6f
https://github.com/tomduck/pandoc-fignos/blob/44776d885b8101d9d6aeb6845b17ad1625e88e6f/pandoc_fignos.py#L204-L266
train
44,066
samluescher/django-media-tree
media_tree/admin/filenode_admin.py
FileNodeAdmin.i18n_javascript
def i18n_javascript(self, request): """ Displays the i18n JavaScript that the Django admin requires. This takes into account the USE_I18N setting. If it's set to False, the generated JavaScript will be leaner and faster. """ if settings.USE_I18N: from django.views.i18n import javascript_catalog else: from django.views.i18n import null_javascript_catalog as javascript_catalog return javascript_catalog(request, packages=['media_tree'])
python
def i18n_javascript(self, request): """ Displays the i18n JavaScript that the Django admin requires. This takes into account the USE_I18N setting. If it's set to False, the generated JavaScript will be leaner and faster. """ if settings.USE_I18N: from django.views.i18n import javascript_catalog else: from django.views.i18n import null_javascript_catalog as javascript_catalog return javascript_catalog(request, packages=['media_tree'])
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/admin/filenode_admin.py#L364-L375
train
44,067
samluescher/django-media-tree
media_tree/admin/change_list.py
MediaTreeChangeList.get_results
def get_results(self, request): """ Temporarily decreases the `level` attribute of all search results in order to prevent indendation when displaying them. """ super(MediaTreeChangeList, self).get_results(request) try: reduce_levels = abs(int(get_request_attr(request, 'reduce_levels', 0))) except TypeError: reduce_levels = 0 is_filtered = self.is_filtered(request) if is_filtered or reduce_levels: for item in self.result_list: item.prevent_save() item.actual_level = item.level if is_filtered: item.reduce_levels = item.level item.level = 0 else: item.reduce_levels = reduce_levels item.level = max(0, item.level - reduce_levels)
python
def get_results(self, request): """ Temporarily decreases the `level` attribute of all search results in order to prevent indendation when displaying them. """ super(MediaTreeChangeList, self).get_results(request) try: reduce_levels = abs(int(get_request_attr(request, 'reduce_levels', 0))) except TypeError: reduce_levels = 0 is_filtered = self.is_filtered(request) if is_filtered or reduce_levels: for item in self.result_list: item.prevent_save() item.actual_level = item.level if is_filtered: item.reduce_levels = item.level item.level = 0 else: item.reduce_levels = reduce_levels item.level = max(0, item.level - reduce_levels)
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/admin/change_list.py#L57-L77
train
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samluescher/django-media-tree
media_tree/media_backends/__init__.py
get_media_backend
def get_media_backend(fail_silently=True, handles_media_types=None, handles_file_extensions=None, supports_thumbnails=None): """ Returns the MediaBackend subclass that is configured for use with media_tree. """ backends = app_settings.MEDIA_TREE_MEDIA_BACKENDS if not len(backends): if not fail_silently: raise ImproperlyConfigured('There is no media backend configured.' \ + ' Please define `MEDIA_TREE_MEDIA_BACKENDS` in your settings.') else: return False for path in backends: # Traverse backends until there is one supporting what's requested: backend = get_module_attr(path) if (not handles_media_types or backend.handles_media_types(handles_media_types)) \ and (not handles_file_extensions or backend.handles_file_extensions(handles_file_extensions)) \ and (not supports_thumbnails or backend.supports_thumbnails()): return backend if not fail_silently: raise ImproperlyConfigured('There is no media backend configured to handle' \ ' the specified file types.') return False
python
def get_media_backend(fail_silently=True, handles_media_types=None, handles_file_extensions=None, supports_thumbnails=None): """ Returns the MediaBackend subclass that is configured for use with media_tree. """ backends = app_settings.MEDIA_TREE_MEDIA_BACKENDS if not len(backends): if not fail_silently: raise ImproperlyConfigured('There is no media backend configured.' \ + ' Please define `MEDIA_TREE_MEDIA_BACKENDS` in your settings.') else: return False for path in backends: # Traverse backends until there is one supporting what's requested: backend = get_module_attr(path) if (not handles_media_types or backend.handles_media_types(handles_media_types)) \ and (not handles_file_extensions or backend.handles_file_extensions(handles_file_extensions)) \ and (not supports_thumbnails or backend.supports_thumbnails()): return backend if not fail_silently: raise ImproperlyConfigured('There is no media backend configured to handle' \ ' the specified file types.') return False
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/media_backends/__init__.py#L11-L36
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samluescher/django-media-tree
media_tree/templatetags/media_tree_thumbnail.py
thumbnail_size
def thumbnail_size(parser, token): """Returns a pre-configured thumbnail size, or assigns it to a context variable. Basic tag syntax:: {% thumbnail_size [size_name] [as var_name] %} The ``size`` parameter can be any of the size names configured using the setting ``MEDIA_TREE_THUMBNAIL_SIZES``. If omitted, the default size will be returned. If the ``as var_name`` clause is present, the size will be assigned to the respective context variable instead of being returned. You can use this template tag in conjunction with :func:`thumbnail` in order to use pre-configured thumbnail sizes in your templates. For example:: {% thumbnail_size "large" as large_size %} {% thumbnail some_file large_size as large_thumb %} <img src="{{ large_thumb.url }} width="{{ large_thumb.width }} ... /> """ args = token.split_contents() tag = args.pop(0) if len(args) >= 2 and args[-2] == 'as': context_name = args[-1] args = args[:-2] else: context_name = None if len(args) > 1: raise template.TemplateSyntaxError("Invalid syntax. Expected " "'{%% %s [\"size_name\"] [as context_var] %%}'" % tag) elif len(args) == 1: size_name = args[0] else: size_name = None return ThumbnailSizeNode(size_name=size_name, context_name=context_name)
python
def thumbnail_size(parser, token): """Returns a pre-configured thumbnail size, or assigns it to a context variable. Basic tag syntax:: {% thumbnail_size [size_name] [as var_name] %} The ``size`` parameter can be any of the size names configured using the setting ``MEDIA_TREE_THUMBNAIL_SIZES``. If omitted, the default size will be returned. If the ``as var_name`` clause is present, the size will be assigned to the respective context variable instead of being returned. You can use this template tag in conjunction with :func:`thumbnail` in order to use pre-configured thumbnail sizes in your templates. For example:: {% thumbnail_size "large" as large_size %} {% thumbnail some_file large_size as large_thumb %} <img src="{{ large_thumb.url }} width="{{ large_thumb.width }} ... /> """ args = token.split_contents() tag = args.pop(0) if len(args) >= 2 and args[-2] == 'as': context_name = args[-1] args = args[:-2] else: context_name = None if len(args) > 1: raise template.TemplateSyntaxError("Invalid syntax. Expected " "'{%% %s [\"size_name\"] [as context_var] %%}'" % tag) elif len(args) == 1: size_name = args[0] else: size_name = None return ThumbnailSizeNode(size_name=size_name, context_name=context_name)
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/templatetags/media_tree_thumbnail.py#L63-L105
train
44,070
analyzere/analyzere-python
analyzere/utils.py
file_length
def file_length(file_obj): """ Returns the length in bytes of a given file object. Necessary because os.fstat only works on real files and not file-like objects. This works on more types of streams, primarily StringIO. """ file_obj.seek(0, 2) length = file_obj.tell() file_obj.seek(0) return length
python
def file_length(file_obj): """ Returns the length in bytes of a given file object. Necessary because os.fstat only works on real files and not file-like objects. This works on more types of streams, primarily StringIO. """ file_obj.seek(0, 2) length = file_obj.tell() file_obj.seek(0) return length
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0593d5b7b69c4df6d6dbc80387cc6ff5dc5f4e8f
https://github.com/analyzere/analyzere-python/blob/0593d5b7b69c4df6d6dbc80387cc6ff5dc5f4e8f/analyzere/utils.py#L55-L64
train
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analyzere/analyzere-python
analyzere/utils.py
parse_href
def parse_href(href): """Parses an Analyze Re href into collection name and ID""" url = urlparse(href) path = url.path.split('/') collection_name = path[1] id_ = path[2] return collection_name, id_
python
def parse_href(href): """Parses an Analyze Re href into collection name and ID""" url = urlparse(href) path = url.path.split('/') collection_name = path[1] id_ = path[2] return collection_name, id_
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0593d5b7b69c4df6d6dbc80387cc6ff5dc5f4e8f
https://github.com/analyzere/analyzere-python/blob/0593d5b7b69c4df6d6dbc80387cc6ff5dc5f4e8f/analyzere/utils.py#L78-L84
train
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analyzere/analyzere-python
analyzere/utils.py
vectorize
def vectorize(values): """ Takes a value or list of values and returns a single result, joined by "," if necessary. """ if isinstance(values, list): return ','.join(str(v) for v in values) return values
python
def vectorize(values): """ Takes a value or list of values and returns a single result, joined by "," if necessary. """ if isinstance(values, list): return ','.join(str(v) for v in values) return values
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0593d5b7b69c4df6d6dbc80387cc6ff5dc5f4e8f
https://github.com/analyzere/analyzere-python/blob/0593d5b7b69c4df6d6dbc80387cc6ff5dc5f4e8f/analyzere/utils.py#L87-L94
train
44,073
analyzere/analyzere-python
analyzere/utils.py
vectorize_range
def vectorize_range(values): """ This function is for url encoding. Takes a value or a tuple or list of tuples and returns a single result, tuples are joined by "," if necessary, elements in tuple are joined by '_' """ if isinstance(values, tuple): return '_'.join(str(i) for i in values) if isinstance(values, list): if not all([isinstance(item, tuple) for item in values]): raise TypeError('Items in the list must be tuples') return ','.join('_'.join(str(i) for i in v) for v in values) return str(values)
python
def vectorize_range(values): """ This function is for url encoding. Takes a value or a tuple or list of tuples and returns a single result, tuples are joined by "," if necessary, elements in tuple are joined by '_' """ if isinstance(values, tuple): return '_'.join(str(i) for i in values) if isinstance(values, list): if not all([isinstance(item, tuple) for item in values]): raise TypeError('Items in the list must be tuples') return ','.join('_'.join(str(i) for i in v) for v in values) return str(values)
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0593d5b7b69c4df6d6dbc80387cc6ff5dc5f4e8f
https://github.com/analyzere/analyzere-python/blob/0593d5b7b69c4df6d6dbc80387cc6ff5dc5f4e8f/analyzere/utils.py#L97-L109
train
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samluescher/django-media-tree
media_tree/admin/actions/maintenance_actions.py
delete_orphaned_files
def delete_orphaned_files(modeladmin, request, queryset=None): """ Deletes orphaned files, i.e. media files existing in storage that are not in the database. """ execute = request.POST.get('execute') storage = get_media_storage() broken_node_links = [] orphaned_files_choices = [] broken_nodes, orphaned_files = get_broken_media() for node in broken_nodes: link = mark_safe('<a href="%s">%s</a>' % (node.get_admin_url(), node.__unicode__())) broken_node_links.append(link) for storage_name in orphaned_files: file_path = storage.path(storage_name) link = mark_safe('<a href="%s">%s</a>' % ( storage.url(storage_name), file_path)) orphaned_files_choices.append((storage_name, link)) if not len(orphaned_files_choices) and not len(broken_node_links): messages.success(request, message=_('There are no orphaned files.')) return HttpResponseRedirect('') if execute: form = DeleteOrphanedFilesForm(queryset, orphaned_files_choices, request.POST) if form.is_valid(): form.save() node = FileNode.get_top_node() messages.success(request, message=ungettext('Deleted %i file from storage.', 'Deleted %i files from storage.', len(form.success_files)) % len(form.success_files)) if form.error_files: messages.error(request, message=_('The following files could not be deleted from storage:')+' '+repr(form.error_files)) return HttpResponseRedirect(node.get_admin_url()) if not execute: if len(orphaned_files_choices) > 0: form = DeleteOrphanedFilesForm(queryset, orphaned_files_choices) else: form = None c = get_actions_context(modeladmin) c.update({ 'title': _('Orphaned files'), 'submit_label': _('Delete selected files'), 'form': form, 'select_all': 'selected_files', 'node_list_title': _('The following files in the database do not exist in storage. You should fix these media objects:'), 'node_list': broken_node_links, }) return render_to_response('admin/media_tree/filenode/actions_form.html', c, context_instance=RequestContext(request))
python
def delete_orphaned_files(modeladmin, request, queryset=None): """ Deletes orphaned files, i.e. media files existing in storage that are not in the database. """ execute = request.POST.get('execute') storage = get_media_storage() broken_node_links = [] orphaned_files_choices = [] broken_nodes, orphaned_files = get_broken_media() for node in broken_nodes: link = mark_safe('<a href="%s">%s</a>' % (node.get_admin_url(), node.__unicode__())) broken_node_links.append(link) for storage_name in orphaned_files: file_path = storage.path(storage_name) link = mark_safe('<a href="%s">%s</a>' % ( storage.url(storage_name), file_path)) orphaned_files_choices.append((storage_name, link)) if not len(orphaned_files_choices) and not len(broken_node_links): messages.success(request, message=_('There are no orphaned files.')) return HttpResponseRedirect('') if execute: form = DeleteOrphanedFilesForm(queryset, orphaned_files_choices, request.POST) if form.is_valid(): form.save() node = FileNode.get_top_node() messages.success(request, message=ungettext('Deleted %i file from storage.', 'Deleted %i files from storage.', len(form.success_files)) % len(form.success_files)) if form.error_files: messages.error(request, message=_('The following files could not be deleted from storage:')+' '+repr(form.error_files)) return HttpResponseRedirect(node.get_admin_url()) if not execute: if len(orphaned_files_choices) > 0: form = DeleteOrphanedFilesForm(queryset, orphaned_files_choices) else: form = None c = get_actions_context(modeladmin) c.update({ 'title': _('Orphaned files'), 'submit_label': _('Delete selected files'), 'form': form, 'select_all': 'selected_files', 'node_list_title': _('The following files in the database do not exist in storage. You should fix these media objects:'), 'node_list': broken_node_links, }) return render_to_response('admin/media_tree/filenode/actions_form.html', c, context_instance=RequestContext(request))
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/admin/actions/maintenance_actions.py#L17-L69
train
44,075
samluescher/django-media-tree
media_tree/admin/actions/maintenance_actions.py
rebuild_tree
def rebuild_tree(modeladmin, request, queryset=None): """ Rebuilds whole tree in database using `parent` link. """ tree = FileNode.tree.rebuild() messages.success(request, message=_('The node tree was rebuilt.')) return HttpResponseRedirect('')
python
def rebuild_tree(modeladmin, request, queryset=None): """ Rebuilds whole tree in database using `parent` link. """ tree = FileNode.tree.rebuild() messages.success(request, message=_('The node tree was rebuilt.')) return HttpResponseRedirect('')
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/admin/actions/maintenance_actions.py#L74-L80
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samluescher/django-media-tree
media_tree/admin/actions/maintenance_actions.py
clear_cache
def clear_cache(modeladmin, request, queryset=None): """ Clears media cache files such as thumbnails. """ execute = request.POST.get('execute') files_in_storage = [] storage = get_media_storage() cache_files_choices = [] for storage_name in get_cache_files(): link = mark_safe('<a href="%s">%s</a>' % ( storage.url(storage_name), storage_name)) cache_files_choices.append((storage_name, link)) if not len(cache_files_choices): messages.warning(request, message=_('There are no cache files.')) return HttpResponseRedirect('') if execute: form = DeleteCacheFilesForm(queryset, cache_files_choices, request.POST) if form.is_valid(): form.save() node = FileNode.get_top_node() message = ungettext('Deleted %i cache file.', 'Deleted %i cache files.', len(form.success_files)) % len(form.success_files) if len(form.success_files) == len(cache_files_choices): message = '%s %s' % (_('The cache was cleared.'), message) messages.success(request, message=message) if form.error_files: messages.error(request, message=_('The following files could not be deleted:')+' '+repr(form.error_files)) return HttpResponseRedirect(node.get_admin_url()) if not execute: if len(cache_files_choices) > 0: form = DeleteCacheFilesForm(queryset, cache_files_choices) else: form = None c = get_actions_context(modeladmin) c.update({ 'title': _('Clear cache'), 'submit_label': _('Delete selected files'), 'form': form, 'select_all': 'selected_files', }) return render_to_response('admin/media_tree/filenode/actions_form.html', c, context_instance=RequestContext(request)) return HttpResponseRedirect('')
python
def clear_cache(modeladmin, request, queryset=None): """ Clears media cache files such as thumbnails. """ execute = request.POST.get('execute') files_in_storage = [] storage = get_media_storage() cache_files_choices = [] for storage_name in get_cache_files(): link = mark_safe('<a href="%s">%s</a>' % ( storage.url(storage_name), storage_name)) cache_files_choices.append((storage_name, link)) if not len(cache_files_choices): messages.warning(request, message=_('There are no cache files.')) return HttpResponseRedirect('') if execute: form = DeleteCacheFilesForm(queryset, cache_files_choices, request.POST) if form.is_valid(): form.save() node = FileNode.get_top_node() message = ungettext('Deleted %i cache file.', 'Deleted %i cache files.', len(form.success_files)) % len(form.success_files) if len(form.success_files) == len(cache_files_choices): message = '%s %s' % (_('The cache was cleared.'), message) messages.success(request, message=message) if form.error_files: messages.error(request, message=_('The following files could not be deleted:')+' '+repr(form.error_files)) return HttpResponseRedirect(node.get_admin_url()) if not execute: if len(cache_files_choices) > 0: form = DeleteCacheFilesForm(queryset, cache_files_choices) else: form = None c = get_actions_context(modeladmin) c.update({ 'title': _('Clear cache'), 'submit_label': _('Delete selected files'), 'form': form, 'select_all': 'selected_files', }) return render_to_response('admin/media_tree/filenode/actions_form.html', c, context_instance=RequestContext(request)) return HttpResponseRedirect('')
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Clears media cache files such as thumbnails.
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/admin/actions/maintenance_actions.py#L85-L132
train
44,077
samluescher/django-media-tree
media_tree/utils/__init__.py
autodiscover_media_extensions
def autodiscover_media_extensions(): """ Auto-discover INSTALLED_APPS media_extensions.py modules and fail silently when not present. This forces an import on them to register any media extension bits they may want. Rip of django.contrib.admin.autodiscover() """ import copy from django.conf import settings from django.utils.module_loading import module_has_submodule for app in settings.INSTALLED_APPS: mod = import_module(app) try: import_module('%s.media_extension' % app) except: if module_has_submodule(mod, 'media_extension'): raise
python
def autodiscover_media_extensions(): """ Auto-discover INSTALLED_APPS media_extensions.py modules and fail silently when not present. This forces an import on them to register any media extension bits they may want. Rip of django.contrib.admin.autodiscover() """ import copy from django.conf import settings from django.utils.module_loading import module_has_submodule for app in settings.INSTALLED_APPS: mod = import_module(app) try: import_module('%s.media_extension' % app) except: if module_has_submodule(mod, 'media_extension'): raise
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/utils/__init__.py#L37-L55
train
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samluescher/django-media-tree
media_tree/utils/__init__.py
join_formatted
def join_formatted(text, new_text, glue_format_if_true = u'%s%s', glue_format_if_false = u'%s%s', condition=None, format = u'%s', escape=False): """ Joins two strings, optionally escaping the second, and using one of two string formats for glueing them together, depending on whether a condition is True or False. This function is a shorthand for complicated code blocks when you want to format some strings and link them together. A typical use case might be: Wrap string B with <strong> tags, but only if it is not empty, and join it with A with a comma in between, but only if A is not empty, etc. """ if condition is None: condition = text and new_text add_text = new_text if escape: add_text = conditional_escape(add_text) if add_text: add_text = format % add_text glue_format = glue_format_if_true if condition else glue_format_if_false return glue_format % (text, add_text)
python
def join_formatted(text, new_text, glue_format_if_true = u'%s%s', glue_format_if_false = u'%s%s', condition=None, format = u'%s', escape=False): """ Joins two strings, optionally escaping the second, and using one of two string formats for glueing them together, depending on whether a condition is True or False. This function is a shorthand for complicated code blocks when you want to format some strings and link them together. A typical use case might be: Wrap string B with <strong> tags, but only if it is not empty, and join it with A with a comma in between, but only if A is not empty, etc. """ if condition is None: condition = text and new_text add_text = new_text if escape: add_text = conditional_escape(add_text) if add_text: add_text = format % add_text glue_format = glue_format_if_true if condition else glue_format_if_false return glue_format % (text, add_text)
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/utils/__init__.py#L90-L109
train
44,079
psss/fmf
fmf/base.py
Tree._initialize
def _initialize(self, path): """ Find metadata tree root, detect format version """ # Find the tree root root = os.path.abspath(path) try: while ".fmf" not in next(os.walk(root))[1]: if root == "/": raise utils.RootError( "Unable to find tree root for '{0}'.".format( os.path.abspath(path))) root = os.path.abspath(os.path.join(root, os.pardir)) except StopIteration: raise utils.FileError("Invalid directory path: {0}".format(root)) log.info("Root directory found: {0}".format(root)) self.root = root # Detect format version try: with open(os.path.join(self.root, ".fmf", "version")) as version: self.version = int(version.read()) log.info("Format version detected: {0}".format(self.version)) except IOError as error: raise utils.FormatError( "Unable to detect format version: {0}".format(error)) except ValueError: raise utils.FormatError("Invalid version format")
python
def _initialize(self, path): """ Find metadata tree root, detect format version """ # Find the tree root root = os.path.abspath(path) try: while ".fmf" not in next(os.walk(root))[1]: if root == "/": raise utils.RootError( "Unable to find tree root for '{0}'.".format( os.path.abspath(path))) root = os.path.abspath(os.path.join(root, os.pardir)) except StopIteration: raise utils.FileError("Invalid directory path: {0}".format(root)) log.info("Root directory found: {0}".format(root)) self.root = root # Detect format version try: with open(os.path.join(self.root, ".fmf", "version")) as version: self.version = int(version.read()) log.info("Format version detected: {0}".format(self.version)) except IOError as error: raise utils.FormatError( "Unable to detect format version: {0}".format(error)) except ValueError: raise utils.FormatError("Invalid version format")
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Find metadata tree root, detect format version
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419f2f195d92339b8f9e5d11c0bea0f303e5fd75
https://github.com/psss/fmf/blob/419f2f195d92339b8f9e5d11c0bea0f303e5fd75/fmf/base.py#L85-L109
train
44,080
psss/fmf
fmf/base.py
Tree.merge
def merge(self, parent=None): """ Merge parent data """ # Check parent, append source files if parent is None: parent = self.parent if parent is None: return self.sources = parent.sources + self.sources # Merge child data with parent data data = copy.deepcopy(parent.data) for key, value in sorted(self.data.items()): # Handle attribute adding if key.endswith('+'): key = key.rstrip('+') if key in data: # Use dict.update() for merging dictionaries if type(data[key]) == type(value) == dict: data[key].update(value) continue try: value = data[key] + value except TypeError as error: raise utils.MergeError( "MergeError: Key '{0}' in {1} ({2}).".format( key, self.name, str(error))) # And finally update the value data[key] = value self.data = data
python
def merge(self, parent=None): """ Merge parent data """ # Check parent, append source files if parent is None: parent = self.parent if parent is None: return self.sources = parent.sources + self.sources # Merge child data with parent data data = copy.deepcopy(parent.data) for key, value in sorted(self.data.items()): # Handle attribute adding if key.endswith('+'): key = key.rstrip('+') if key in data: # Use dict.update() for merging dictionaries if type(data[key]) == type(value) == dict: data[key].update(value) continue try: value = data[key] + value except TypeError as error: raise utils.MergeError( "MergeError: Key '{0}' in {1} ({2}).".format( key, self.name, str(error))) # And finally update the value data[key] = value self.data = data
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Merge parent data
[ "Merge", "parent", "data" ]
419f2f195d92339b8f9e5d11c0bea0f303e5fd75
https://github.com/psss/fmf/blob/419f2f195d92339b8f9e5d11c0bea0f303e5fd75/fmf/base.py#L111-L138
train
44,081
psss/fmf
fmf/base.py
Tree.update
def update(self, data): """ Update metadata, handle virtual hierarchy """ # Nothing to do if no data if data is None: return for key, value in sorted(data.items()): # Handle child attributes if key.startswith('/'): name = key.lstrip('/') # Handle deeper nesting (e.g. keys like /one/two/three) by # extracting only the first level of the hierarchy as name match = re.search("([^/]+)(/.*)", name) if match: name = match.groups()[0] value = {match.groups()[1]: value} # Update existing child or create a new one self.child(name, value) # Update regular attributes else: self.data[key] = value log.debug("Data for '{0}' updated.".format(self)) log.data(pretty(self.data))
python
def update(self, data): """ Update metadata, handle virtual hierarchy """ # Nothing to do if no data if data is None: return for key, value in sorted(data.items()): # Handle child attributes if key.startswith('/'): name = key.lstrip('/') # Handle deeper nesting (e.g. keys like /one/two/three) by # extracting only the first level of the hierarchy as name match = re.search("([^/]+)(/.*)", name) if match: name = match.groups()[0] value = {match.groups()[1]: value} # Update existing child or create a new one self.child(name, value) # Update regular attributes else: self.data[key] = value log.debug("Data for '{0}' updated.".format(self)) log.data(pretty(self.data))
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Update metadata, handle virtual hierarchy
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419f2f195d92339b8f9e5d11c0bea0f303e5fd75
https://github.com/psss/fmf/blob/419f2f195d92339b8f9e5d11c0bea0f303e5fd75/fmf/base.py#L152-L173
train
44,082
psss/fmf
fmf/base.py
Tree.get
def get(self, name=None, default=None): """ Get attribute value or return default Whole data dictionary is returned when no attribute provided. Supports direct values retrieval from deep dictionaries as well. Dictionary path should be provided as list. The following two examples are equal: tree.data['hardware']['memory']['size'] tree.get(['hardware', 'memory', 'size']) However the latter approach will also correctly handle providing default value when any of the dictionary keys does not exist. """ # Return the whole dictionary if no attribute specified if name is None: return self.data if not isinstance(name, list): name = [name] data = self.data try: for key in name: data = data[key] except KeyError: return default return data
python
def get(self, name=None, default=None): """ Get attribute value or return default Whole data dictionary is returned when no attribute provided. Supports direct values retrieval from deep dictionaries as well. Dictionary path should be provided as list. The following two examples are equal: tree.data['hardware']['memory']['size'] tree.get(['hardware', 'memory', 'size']) However the latter approach will also correctly handle providing default value when any of the dictionary keys does not exist. """ # Return the whole dictionary if no attribute specified if name is None: return self.data if not isinstance(name, list): name = [name] data = self.data try: for key in name: data = data[key] except KeyError: return default return data
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Get attribute value or return default Whole data dictionary is returned when no attribute provided. Supports direct values retrieval from deep dictionaries as well. Dictionary path should be provided as list. The following two examples are equal: tree.data['hardware']['memory']['size'] tree.get(['hardware', 'memory', 'size']) However the latter approach will also correctly handle providing default value when any of the dictionary keys does not exist.
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419f2f195d92339b8f9e5d11c0bea0f303e5fd75
https://github.com/psss/fmf/blob/419f2f195d92339b8f9e5d11c0bea0f303e5fd75/fmf/base.py#L175-L202
train
44,083
psss/fmf
fmf/base.py
Tree.child
def child(self, name, data, source=None): """ Create or update child with given data """ try: if isinstance(data, dict): self.children[name].update(data) else: self.children[name].grow(data) except KeyError: self.children[name] = Tree(data, name, parent=self) # Save source file if source is not None: self.children[name].sources.append(source)
python
def child(self, name, data, source=None): """ Create or update child with given data """ try: if isinstance(data, dict): self.children[name].update(data) else: self.children[name].grow(data) except KeyError: self.children[name] = Tree(data, name, parent=self) # Save source file if source is not None: self.children[name].sources.append(source)
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Create or update child with given data
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419f2f195d92339b8f9e5d11c0bea0f303e5fd75
https://github.com/psss/fmf/blob/419f2f195d92339b8f9e5d11c0bea0f303e5fd75/fmf/base.py#L204-L215
train
44,084
psss/fmf
fmf/base.py
Tree.grow
def grow(self, path): """ Grow the metadata tree for the given directory path Note: For each path, grow() should be run only once. Growing the tree from the same path multiple times with attribute adding using the "+" sign leads to adding the value more than once! """ if path is None: return path = path.rstrip("/") log.info("Walking through directory {0}".format( os.path.abspath(path))) dirpath, dirnames, filenames = next(os.walk(path)) # Investigate main.fmf as the first file (for correct inheritance) filenames = sorted( [filename for filename in filenames if filename.endswith(SUFFIX)]) try: filenames.insert(0, filenames.pop(filenames.index(MAIN))) except ValueError: pass # Check every metadata file and load data (ignore hidden) for filename in filenames: if filename.startswith("."): continue fullpath = os.path.abspath(os.path.join(dirpath, filename)) log.info("Checking file {0}".format(fullpath)) try: with open(fullpath) as datafile: data = yaml.load(datafile, Loader=FullLoader) except yaml.scanner.ScannerError as error: raise(utils.FileError("Failed to parse '{0}'\n{1}".format( fullpath, error))) log.data(pretty(data)) # Handle main.fmf as data for self if filename == MAIN: self.sources.append(fullpath) self.update(data) # Handle other *.fmf files as children else: self.child(os.path.splitext(filename)[0], data, fullpath) # Explore every child directory (ignore hidden dirs and subtrees) for dirname in sorted(dirnames): if dirname.startswith("."): continue # Ignore metadata subtrees if os.path.isdir(os.path.join(path, dirname, SUFFIX)): log.debug("Ignoring metadata tree '{0}'.".format(dirname)) continue self.child(dirname, os.path.join(path, dirname)) # Remove empty children (ignore directories without metadata) for name in list(self.children.keys()): child = self.children[name] if not child.data and not child.children: del(self.children[name]) log.debug("Empty tree '{0}' removed.".format(child.name)) # Apply inheritance when all scattered data are gathered. # This is done only once, from the top parent object. if self.parent is None: self.inherit()
python
def grow(self, path): """ Grow the metadata tree for the given directory path Note: For each path, grow() should be run only once. Growing the tree from the same path multiple times with attribute adding using the "+" sign leads to adding the value more than once! """ if path is None: return path = path.rstrip("/") log.info("Walking through directory {0}".format( os.path.abspath(path))) dirpath, dirnames, filenames = next(os.walk(path)) # Investigate main.fmf as the first file (for correct inheritance) filenames = sorted( [filename for filename in filenames if filename.endswith(SUFFIX)]) try: filenames.insert(0, filenames.pop(filenames.index(MAIN))) except ValueError: pass # Check every metadata file and load data (ignore hidden) for filename in filenames: if filename.startswith("."): continue fullpath = os.path.abspath(os.path.join(dirpath, filename)) log.info("Checking file {0}".format(fullpath)) try: with open(fullpath) as datafile: data = yaml.load(datafile, Loader=FullLoader) except yaml.scanner.ScannerError as error: raise(utils.FileError("Failed to parse '{0}'\n{1}".format( fullpath, error))) log.data(pretty(data)) # Handle main.fmf as data for self if filename == MAIN: self.sources.append(fullpath) self.update(data) # Handle other *.fmf files as children else: self.child(os.path.splitext(filename)[0], data, fullpath) # Explore every child directory (ignore hidden dirs and subtrees) for dirname in sorted(dirnames): if dirname.startswith("."): continue # Ignore metadata subtrees if os.path.isdir(os.path.join(path, dirname, SUFFIX)): log.debug("Ignoring metadata tree '{0}'.".format(dirname)) continue self.child(dirname, os.path.join(path, dirname)) # Remove empty children (ignore directories without metadata) for name in list(self.children.keys()): child = self.children[name] if not child.data and not child.children: del(self.children[name]) log.debug("Empty tree '{0}' removed.".format(child.name)) # Apply inheritance when all scattered data are gathered. # This is done only once, from the top parent object. if self.parent is None: self.inherit()
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Grow the metadata tree for the given directory path Note: For each path, grow() should be run only once. Growing the tree from the same path multiple times with attribute adding using the "+" sign leads to adding the value more than once!
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419f2f195d92339b8f9e5d11c0bea0f303e5fd75
https://github.com/psss/fmf/blob/419f2f195d92339b8f9e5d11c0bea0f303e5fd75/fmf/base.py#L217-L276
train
44,085
psss/fmf
fmf/base.py
Tree.find
def find(self, name): """ Find node with given name """ for node in self.climb(whole=True): if node.name == name: return node return None
python
def find(self, name): """ Find node with given name """ for node in self.climb(whole=True): if node.name == name: return node return None
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Find node with given name
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419f2f195d92339b8f9e5d11c0bea0f303e5fd75
https://github.com/psss/fmf/blob/419f2f195d92339b8f9e5d11c0bea0f303e5fd75/fmf/base.py#L286-L291
train
44,086
psss/fmf
fmf/base.py
Tree.prune
def prune(self, whole=False, keys=[], names=[], filters=[]): """ Filter tree nodes based on given criteria """ for node in self.climb(whole): # Select only nodes with key content if not all([key in node.data for key in keys]): continue # Select nodes with name matching regular expression if names and not any( [re.search(name, node.name) for name in names]): continue # Apply advanced filters if given try: if not all([utils.filter(filter, node.data, regexp=True) for filter in filters]): continue # Handle missing attribute as if filter failed except utils.FilterError: continue # All criteria met, thus yield the node yield node
python
def prune(self, whole=False, keys=[], names=[], filters=[]): """ Filter tree nodes based on given criteria """ for node in self.climb(whole): # Select only nodes with key content if not all([key in node.data for key in keys]): continue # Select nodes with name matching regular expression if names and not any( [re.search(name, node.name) for name in names]): continue # Apply advanced filters if given try: if not all([utils.filter(filter, node.data, regexp=True) for filter in filters]): continue # Handle missing attribute as if filter failed except utils.FilterError: continue # All criteria met, thus yield the node yield node
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Filter tree nodes based on given criteria
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419f2f195d92339b8f9e5d11c0bea0f303e5fd75
https://github.com/psss/fmf/blob/419f2f195d92339b8f9e5d11c0bea0f303e5fd75/fmf/base.py#L293-L312
train
44,087
samluescher/django-media-tree
media_tree/contrib/legacy_mptt_support/forms.py
MoveNodeForm.save
def save(self): """ Attempts to move the node using the selected target and position. If an invalid move is attempted, the related error message will be added to the form's non-field errors and the error will be re-raised. Callers should attempt to catch ``InvalidNode`` to redisplay the form with the error, should it occur. """ try: self.node.move_to(self.cleaned_data['target'], self.cleaned_data['position']) return self.node except InvalidMove, e: self.errors[NON_FIELD_ERRORS] = ErrorList(e) raise
python
def save(self): """ Attempts to move the node using the selected target and position. If an invalid move is attempted, the related error message will be added to the form's non-field errors and the error will be re-raised. Callers should attempt to catch ``InvalidNode`` to redisplay the form with the error, should it occur. """ try: self.node.move_to(self.cleaned_data['target'], self.cleaned_data['position']) return self.node except InvalidMove, e: self.errors[NON_FIELD_ERRORS] = ErrorList(e) raise
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Attempts to move the node using the selected target and position. If an invalid move is attempted, the related error message will be added to the form's non-field errors and the error will be re-raised. Callers should attempt to catch ``InvalidNode`` to redisplay the form with the error, should it occur.
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/contrib/legacy_mptt_support/forms.py#L136-L152
train
44,088
psss/fmf
fmf/cli.py
Parser.show
def show(self, brief=False): """ Show metadata for each path given """ output = [] for path in self.options.paths or ["."]: if self.options.verbose: utils.info("Checking {0} for metadata.".format(path)) tree = fmf.Tree(path) for node in tree.prune( self.options.whole, self.options.keys, self.options.names, self.options.filters): if brief: show = node.show(brief=True) else: show = node.show( brief=False, formatting=self.options.formatting, values=self.options.values) # List source files when in debug mode if self.options.debug: for source in node.sources: show += utils.color("{0}\n".format(source), "blue") if show is not None: output.append(show) # Print output and summary if brief or self.options.formatting: joined = "".join(output) else: joined = "\n".join(output) try: # pragma: no cover print(joined, end="") except UnicodeEncodeError: # pragma: no cover print(joined.encode('utf-8'), end="") if self.options.verbose: utils.info("Found {0}.".format( utils.listed(len(output), "object"))) self.output = joined
python
def show(self, brief=False): """ Show metadata for each path given """ output = [] for path in self.options.paths or ["."]: if self.options.verbose: utils.info("Checking {0} for metadata.".format(path)) tree = fmf.Tree(path) for node in tree.prune( self.options.whole, self.options.keys, self.options.names, self.options.filters): if brief: show = node.show(brief=True) else: show = node.show( brief=False, formatting=self.options.formatting, values=self.options.values) # List source files when in debug mode if self.options.debug: for source in node.sources: show += utils.color("{0}\n".format(source), "blue") if show is not None: output.append(show) # Print output and summary if brief or self.options.formatting: joined = "".join(output) else: joined = "\n".join(output) try: # pragma: no cover print(joined, end="") except UnicodeEncodeError: # pragma: no cover print(joined.encode('utf-8'), end="") if self.options.verbose: utils.info("Found {0}.".format( utils.listed(len(output), "object"))) self.output = joined
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Show metadata for each path given
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419f2f195d92339b8f9e5d11c0bea0f303e5fd75
https://github.com/psss/fmf/blob/419f2f195d92339b8f9e5d11c0bea0f303e5fd75/fmf/cli.py#L150-L186
train
44,089
psss/fmf
fmf/utils.py
filter
def filter(filter, data, sensitive=True, regexp=False): """ Return true if provided filter matches given dictionary of values Filter supports disjunctive normal form with '|' used for OR, '&' for AND and '-' for negation. Individual values are prefixed with 'value:', leading/trailing white-space is stripped. For example:: tag: Tier1 | tag: Tier2 | tag: Tier3 category: Sanity, Security & tag: -destructive Note that multiple comma-separated values can be used as a syntactic sugar to shorten the filter notation:: tag: A, B, C ---> tag: A | tag: B | tag: C Values should be provided as a dictionary of lists each describing the values against which the filter is to be matched. For example:: data = {tag: ["Tier1", "TIPpass"], category: ["Sanity"]} Other types of dictionary values are converted into a string. A FilterError exception is raised when a dimension parsed from the filter is not found in the data dictionary. Set option 'sensitive' to False to enable case-insensitive matching. If 'regexp' option is True, regular expressions can be used in the filter values as well. """ def match_value(pattern, text): """ Match value against data (simple or regexp) """ if regexp: return re.match("^{0}$".format(pattern), text) else: return pattern == text def check_value(dimension, value): """ Check whether the value matches data """ # E.g. value = 'A, B' or value = "C" or value = "-D" # If there are multiple values, at least one must match for atom in re.split("\s*,\s*", value): # Handle negative values (check the whole data for non-presence) if atom.startswith("-"): atom = atom[1:] # Check each value for given dimension for dato in data[dimension]: if match_value(atom, dato): break # Pattern not found ---> good else: return True # Handle positive values (return True upon first successful match) else: # Check each value for given dimension for dato in data[dimension]: if match_value(atom, dato): # Pattern found ---> good return True # No value matched the data return False def check_dimension(dimension, values): """ Check whether all values for given dimension match data """ # E.g. dimension = 'tag', values = ['A, B', 'C', '-D'] # Raise exception upon unknown dimension if dimension not in data: raise FilterError("Invalid filter '{0}'".format(dimension)) # Every value must match at least one value for data return all([check_value(dimension, value) for value in values]) def check_clause(clause): """ Split into literals and check whether all match """ # E.g. clause = 'tag: A, B & tag: C & tag: -D' # Split into individual literals by dimension literals = dict() for literal in re.split("\s*&\s*", clause): # E.g. literal = 'tag: A, B' # Make sure the literal matches dimension:value format matched = re.match("^(.*)\s*:\s*(.*)$", literal) if not matched: raise FilterError("Invalid filter '{0}'".format(literal)) dimension, value = matched.groups() values = [value] # Append the literal value(s) to corresponding dimension list literals.setdefault(dimension, []).extend(values) # For each dimension all literals must match given data return all([check_dimension(dimension, values) for dimension, values in literals.items()]) # Default to True if no filter given, bail out if weird data given if filter is None or filter == "": return True if not isinstance(data, dict): raise FilterError("Invalid data type '{0}'".format(type(data))) # Make sure that data dictionary contains lists of strings data = copy.deepcopy(data) try: # pragma: no cover for key in data: if isinstance(data[key], list): data[key] = [unicode(item) for item in data[key]] else: data[key] = [unicode(data[key])] except NameError: # pragma: no cover for key in data: if isinstance(data[key], list): data[key] = [str(item) for item in data[key]] else: data[key] = [str(data[key])] # Turn all data into lowercase if sensitivity is off if not sensitive: filter = filter.lower() lowered = dict() for key, values in data.items(): lowered[key.lower()] = [value.lower() for value in values] data = lowered # At least one clause must be true return any([check_clause(clause) for clause in re.split("\s*\|\s*", filter)])
python
def filter(filter, data, sensitive=True, regexp=False): """ Return true if provided filter matches given dictionary of values Filter supports disjunctive normal form with '|' used for OR, '&' for AND and '-' for negation. Individual values are prefixed with 'value:', leading/trailing white-space is stripped. For example:: tag: Tier1 | tag: Tier2 | tag: Tier3 category: Sanity, Security & tag: -destructive Note that multiple comma-separated values can be used as a syntactic sugar to shorten the filter notation:: tag: A, B, C ---> tag: A | tag: B | tag: C Values should be provided as a dictionary of lists each describing the values against which the filter is to be matched. For example:: data = {tag: ["Tier1", "TIPpass"], category: ["Sanity"]} Other types of dictionary values are converted into a string. A FilterError exception is raised when a dimension parsed from the filter is not found in the data dictionary. Set option 'sensitive' to False to enable case-insensitive matching. If 'regexp' option is True, regular expressions can be used in the filter values as well. """ def match_value(pattern, text): """ Match value against data (simple or regexp) """ if regexp: return re.match("^{0}$".format(pattern), text) else: return pattern == text def check_value(dimension, value): """ Check whether the value matches data """ # E.g. value = 'A, B' or value = "C" or value = "-D" # If there are multiple values, at least one must match for atom in re.split("\s*,\s*", value): # Handle negative values (check the whole data for non-presence) if atom.startswith("-"): atom = atom[1:] # Check each value for given dimension for dato in data[dimension]: if match_value(atom, dato): break # Pattern not found ---> good else: return True # Handle positive values (return True upon first successful match) else: # Check each value for given dimension for dato in data[dimension]: if match_value(atom, dato): # Pattern found ---> good return True # No value matched the data return False def check_dimension(dimension, values): """ Check whether all values for given dimension match data """ # E.g. dimension = 'tag', values = ['A, B', 'C', '-D'] # Raise exception upon unknown dimension if dimension not in data: raise FilterError("Invalid filter '{0}'".format(dimension)) # Every value must match at least one value for data return all([check_value(dimension, value) for value in values]) def check_clause(clause): """ Split into literals and check whether all match """ # E.g. clause = 'tag: A, B & tag: C & tag: -D' # Split into individual literals by dimension literals = dict() for literal in re.split("\s*&\s*", clause): # E.g. literal = 'tag: A, B' # Make sure the literal matches dimension:value format matched = re.match("^(.*)\s*:\s*(.*)$", literal) if not matched: raise FilterError("Invalid filter '{0}'".format(literal)) dimension, value = matched.groups() values = [value] # Append the literal value(s) to corresponding dimension list literals.setdefault(dimension, []).extend(values) # For each dimension all literals must match given data return all([check_dimension(dimension, values) for dimension, values in literals.items()]) # Default to True if no filter given, bail out if weird data given if filter is None or filter == "": return True if not isinstance(data, dict): raise FilterError("Invalid data type '{0}'".format(type(data))) # Make sure that data dictionary contains lists of strings data = copy.deepcopy(data) try: # pragma: no cover for key in data: if isinstance(data[key], list): data[key] = [unicode(item) for item in data[key]] else: data[key] = [unicode(data[key])] except NameError: # pragma: no cover for key in data: if isinstance(data[key], list): data[key] = [str(item) for item in data[key]] else: data[key] = [str(data[key])] # Turn all data into lowercase if sensitivity is off if not sensitive: filter = filter.lower() lowered = dict() for key, values in data.items(): lowered[key.lower()] = [value.lower() for value in values] data = lowered # At least one clause must be true return any([check_clause(clause) for clause in re.split("\s*\|\s*", filter)])
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419f2f195d92339b8f9e5d11c0bea0f303e5fd75
https://github.com/psss/fmf/blob/419f2f195d92339b8f9e5d11c0bea0f303e5fd75/fmf/utils.py#L150-L267
train
44,090
psss/fmf
fmf/utils.py
color
def color(text, color=None, background=None, light=False, enabled="auto"): """ Return text in desired color if coloring enabled Available colors: black red green yellow blue magenta cyan white. Alternatively color can be prefixed with "light", e.g. lightgreen. """ colors = {"black": 30, "red": 31, "green": 32, "yellow": 33, "blue": 34, "magenta": 35, "cyan": 36, "white": 37} # Nothing do do if coloring disabled if enabled == "auto": enabled = Coloring().enabled() if not enabled: return text # Prepare colors (strip 'light' if present in color) if color and color.startswith("light"): light = True color = color[5:] color = color and ";{0}".format(colors[color]) or "" background = background and ";{0}".format(colors[background] + 10) or "" light = light and 1 or 0 # Starting and finishing sequence start = "\033[{0}{1}{2}m".format(light, color, background) finish = "\033[1;m" return "".join([start, text, finish])
python
def color(text, color=None, background=None, light=False, enabled="auto"): """ Return text in desired color if coloring enabled Available colors: black red green yellow blue magenta cyan white. Alternatively color can be prefixed with "light", e.g. lightgreen. """ colors = {"black": 30, "red": 31, "green": 32, "yellow": 33, "blue": 34, "magenta": 35, "cyan": 36, "white": 37} # Nothing do do if coloring disabled if enabled == "auto": enabled = Coloring().enabled() if not enabled: return text # Prepare colors (strip 'light' if present in color) if color and color.startswith("light"): light = True color = color[5:] color = color and ";{0}".format(colors[color]) or "" background = background and ";{0}".format(colors[background] + 10) or "" light = light and 1 or 0 # Starting and finishing sequence start = "\033[{0}{1}{2}m".format(light, color, background) finish = "\033[1;m" return "".join([start, text, finish])
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Return text in desired color if coloring enabled Available colors: black red green yellow blue magenta cyan white. Alternatively color can be prefixed with "light", e.g. lightgreen.
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419f2f195d92339b8f9e5d11c0bea0f303e5fd75
https://github.com/psss/fmf/blob/419f2f195d92339b8f9e5d11c0bea0f303e5fd75/fmf/utils.py#L391-L415
train
44,091
psss/fmf
fmf/utils.py
Logging._create_logger
def _create_logger(name='fmf', level=None): """ Create fmf logger """ # Create logger, handler and formatter logger = logging.getLogger(name) handler = logging.StreamHandler() handler.setFormatter(Logging.ColoredFormatter()) logger.addHandler(handler) # Save log levels in the logger itself (backward compatibility) for level in Logging.LEVELS: setattr(logger, level, getattr(logging, level)) # Additional logging constants and methods for cache and xmlrpc logger.DATA = LOG_DATA logger.CACHE = LOG_CACHE logger.ALL = LOG_ALL logger.cache = lambda message: logger.log(LOG_CACHE, message) # NOQA logger.data = lambda message: logger.log(LOG_DATA, message) # NOQA logger.all = lambda message: logger.log(LOG_ALL, message) # NOQA return logger
python
def _create_logger(name='fmf', level=None): """ Create fmf logger """ # Create logger, handler and formatter logger = logging.getLogger(name) handler = logging.StreamHandler() handler.setFormatter(Logging.ColoredFormatter()) logger.addHandler(handler) # Save log levels in the logger itself (backward compatibility) for level in Logging.LEVELS: setattr(logger, level, getattr(logging, level)) # Additional logging constants and methods for cache and xmlrpc logger.DATA = LOG_DATA logger.CACHE = LOG_CACHE logger.ALL = LOG_ALL logger.cache = lambda message: logger.log(LOG_CACHE, message) # NOQA logger.data = lambda message: logger.log(LOG_DATA, message) # NOQA logger.all = lambda message: logger.log(LOG_ALL, message) # NOQA return logger
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419f2f195d92339b8f9e5d11c0bea0f303e5fd75
https://github.com/psss/fmf/blob/419f2f195d92339b8f9e5d11c0bea0f303e5fd75/fmf/utils.py#L338-L355
train
44,092
samluescher/django-media-tree
media_tree/models.py
FileNode.get_admin_url
def get_admin_url(self, query_params=None, use_path=False): """Returns the URL for viewing a FileNode in the admin.""" if not query_params: query_params = {} url = '' if self.is_top_node(): url = reverse('admin:media_tree_filenode_changelist'); elif use_path and (self.is_folder() or self.pk): url = reverse('admin:media_tree_filenode_open_path', args=(self.get_path(),)); elif self.is_folder(): url = reverse('admin:media_tree_filenode_changelist'); query_params['folder_id'] = self.pk elif self.pk: return reverse('admin:media_tree_filenode_change', args=(self.pk,)); if len(query_params): params = ['%s=%s' % (key, value) for key, value in query_params.items()] url = '%s?%s' % (url, "&".join(params)) return url
python
def get_admin_url(self, query_params=None, use_path=False): """Returns the URL for viewing a FileNode in the admin.""" if not query_params: query_params = {} url = '' if self.is_top_node(): url = reverse('admin:media_tree_filenode_changelist'); elif use_path and (self.is_folder() or self.pk): url = reverse('admin:media_tree_filenode_open_path', args=(self.get_path(),)); elif self.is_folder(): url = reverse('admin:media_tree_filenode_changelist'); query_params['folder_id'] = self.pk elif self.pk: return reverse('admin:media_tree_filenode_change', args=(self.pk,)); if len(query_params): params = ['%s=%s' % (key, value) for key, value in query_params.items()] url = '%s?%s' % (url, "&".join(params)) return url
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/models.py#L482-L503
train
44,093
samluescher/django-media-tree
media_tree/models.py
FileNode.get_caption_formatted
def get_caption_formatted(self, field_formats = app_settings.MEDIA_TREE_METADATA_FORMATS, escape=True): """Returns object metadata that has been selected to be displayed to users, compiled as a string including default formatting, for example bold titles. You can use this method in templates where you want to output image captions. """ if self.override_caption != '': return self.override_caption else: return mark_safe(self.get_metadata_display(field_formats, escape=escape))
python
def get_caption_formatted(self, field_formats = app_settings.MEDIA_TREE_METADATA_FORMATS, escape=True): """Returns object metadata that has been selected to be displayed to users, compiled as a string including default formatting, for example bold titles. You can use this method in templates where you want to output image captions. """ if self.override_caption != '': return self.override_caption else: return mark_safe(self.get_metadata_display(field_formats, escape=escape))
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/models.py#L693-L704
train
44,094
samluescher/django-media-tree
media_tree/admin/actions/forms.py
MoveSelectedForm.save
def save(self): """ Attempts to move the nodes using the selected target and position. If an invalid move is attempted, the related error message will be added to the form's non-field errors and the error will be re-raised. Callers should attempt to catch ``InvalidMove`` to redisplay the form with the error, should it occur. """ self.success_count = 0 for node in self.get_selected_nodes(): self.move_node(node, self.cleaned_data['target_node'])
python
def save(self): """ Attempts to move the nodes using the selected target and position. If an invalid move is attempted, the related error message will be added to the form's non-field errors and the error will be re-raised. Callers should attempt to catch ``InvalidMove`` to redisplay the form with the error, should it occur. """ self.success_count = 0 for node in self.get_selected_nodes(): self.move_node(node, self.cleaned_data['target_node'])
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Attempts to move the nodes using the selected target and position. If an invalid move is attempted, the related error message will be added to the form's non-field errors and the error will be re-raised. Callers should attempt to catch ``InvalidMove`` to redisplay the form with the error, should it occur.
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/admin/actions/forms.py#L86-L98
train
44,095
samluescher/django-media-tree
media_tree/admin/actions/forms.py
DeleteStorageFilesForm.save
def save(self): """ Deletes the selected files from storage """ storage = get_media_storage() for storage_name in self.cleaned_data['selected_files']: full_path = storage.path(storage_name) try: storage.delete(storage_name) self.success_files.append(full_path) except OSError: self.error_files.append(full_path)
python
def save(self): """ Deletes the selected files from storage """ storage = get_media_storage() for storage_name in self.cleaned_data['selected_files']: full_path = storage.path(storage_name) try: storage.delete(storage_name) self.success_files.append(full_path) except OSError: self.error_files.append(full_path)
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Deletes the selected files from storage
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/admin/actions/forms.py#L204-L215
train
44,096
samluescher/django-media-tree
media_tree/utils/filenode.py
get_file_link
def get_file_link(node, use_metadata=False, include_size=False, include_extension=False, include_icon=False, href=None, extra_class='', extra=''): """ Returns a formatted HTML link tag to the FileNode's file, optionally including some meta information about the file. """ link_text = None if use_metadata: link_text = node.get_metadata_display() if not link_text: link_text = node.__unicode__() if node.node_type != media_types.FOLDER: if include_extension: if extra != '': extra += ' ' extra = '<span class="file-extension">%s</span>' % node.extension.upper() if include_size: if extra != '': extra += ', ' extra += '<span class="file-size">%s</span>' % filesizeformat(node.size) if extra: extra = ' <span class="details">(%s)</span>' % extra link_class = 'file %s' % node.extension else: link_class = 'folder' if extra_class: link_class = '%s %s' % (link_class, extra_class) if node.node_type != media_types.FOLDER and not href: href = node.file.url icon = '' if include_icon: icon_file = node.get_icon_file() if icon_file: icon = '<span class="icon"><img src="%s" alt="%s" /></span>' % ( icon_file.url, node.alt) if href: link = u'<a class="%s" href="%s">%s%s</a>%s' % ( link_class, href, icon, link_text, extra) else: link = u'<span class="%s">%s%s</span>%s' % ( link_class, icon, link_text, extra) return force_unicode(mark_safe(link))
python
def get_file_link(node, use_metadata=False, include_size=False, include_extension=False, include_icon=False, href=None, extra_class='', extra=''): """ Returns a formatted HTML link tag to the FileNode's file, optionally including some meta information about the file. """ link_text = None if use_metadata: link_text = node.get_metadata_display() if not link_text: link_text = node.__unicode__() if node.node_type != media_types.FOLDER: if include_extension: if extra != '': extra += ' ' extra = '<span class="file-extension">%s</span>' % node.extension.upper() if include_size: if extra != '': extra += ', ' extra += '<span class="file-size">%s</span>' % filesizeformat(node.size) if extra: extra = ' <span class="details">(%s)</span>' % extra link_class = 'file %s' % node.extension else: link_class = 'folder' if extra_class: link_class = '%s %s' % (link_class, extra_class) if node.node_type != media_types.FOLDER and not href: href = node.file.url icon = '' if include_icon: icon_file = node.get_icon_file() if icon_file: icon = '<span class="icon"><img src="%s" alt="%s" /></span>' % ( icon_file.url, node.alt) if href: link = u'<a class="%s" href="%s">%s%s</a>%s' % ( link_class, href, icon, link_text, extra) else: link = u'<span class="%s">%s%s</span>%s' % ( link_class, icon, link_text, extra) return force_unicode(mark_safe(link))
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Returns a formatted HTML link tag to the FileNode's file, optionally including some meta information about the file.
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3eb6345faaf57e2fbe35ca431d4d133f950f2b5f
https://github.com/samluescher/django-media-tree/blob/3eb6345faaf57e2fbe35ca431d4d133f950f2b5f/media_tree/utils/filenode.py#L134-L177
train
44,097
resonai/ybt
yabt/target_utils.py
norm_name
def norm_name(build_module: str, target_name: str): """Return a normalized canonical target name for the `target_name` observed in build module `build_module`. A normalized canonical target name is of the form "<build module>:<name>", where <build module> is the relative normalized path from the project root to the target build module (POSIX), and <name> is a valid target name (see `validate_name()`). """ if ':' not in target_name: raise ValueError( "Must provide fully-qualified target name (with `:') to avoid " "possible ambiguity - `{}' not valid".format(target_name)) mod, name = split(target_name) return '{}:{}'.format( PurePath(norm_proj_path(mod, build_module)).as_posix().strip('.'), validate_name(name))
python
def norm_name(build_module: str, target_name: str): """Return a normalized canonical target name for the `target_name` observed in build module `build_module`. A normalized canonical target name is of the form "<build module>:<name>", where <build module> is the relative normalized path from the project root to the target build module (POSIX), and <name> is a valid target name (see `validate_name()`). """ if ':' not in target_name: raise ValueError( "Must provide fully-qualified target name (with `:') to avoid " "possible ambiguity - `{}' not valid".format(target_name)) mod, name = split(target_name) return '{}:{}'.format( PurePath(norm_proj_path(mod, build_module)).as_posix().strip('.'), validate_name(name))
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Return a normalized canonical target name for the `target_name` observed in build module `build_module`. A normalized canonical target name is of the form "<build module>:<name>", where <build module> is the relative normalized path from the project root to the target build module (POSIX), and <name> is a valid target name (see `validate_name()`).
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5b40df0922ef3383eb85f2b04a26a2db4b81b3fd
https://github.com/resonai/ybt/blob/5b40df0922ef3383eb85f2b04a26a2db4b81b3fd/yabt/target_utils.py#L75-L92
train
44,098
resonai/ybt
yabt/target_utils.py
hashify_targets
def hashify_targets(targets: list, build_context) -> list: """Return sorted hashes of `targets`.""" return sorted(build_context.targets[target_name].hash(build_context) for target_name in listify(targets))
python
def hashify_targets(targets: list, build_context) -> list: """Return sorted hashes of `targets`.""" return sorted(build_context.targets[target_name].hash(build_context) for target_name in listify(targets))
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Return sorted hashes of `targets`.
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5b40df0922ef3383eb85f2b04a26a2db4b81b3fd
https://github.com/resonai/ybt/blob/5b40df0922ef3383eb85f2b04a26a2db4b81b3fd/yabt/target_utils.py#L129-L132
train
44,099