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apache/airflow | BackfillJob._set_unfinished_dag_runs_to_failed | def _set_unfinished_dag_runs_to_failed(self, dag_runs, session=None):
for dag_run in dag_runs:
dag_run.update_state()
if dag_run.state not in State.finished():
dag_run.set_state(State.FAILED)
session.merge(dag_run) | Go through the dag_runs and update the state based on the task_instance state. Then set DAG runs that are not finished to failed. | def _set_unfinished_dag_runs_to_failed(self, dag_runs, session=None):
"""
Go through the dag_runs and update the state based on the task_instance state.
Then set DAG runs that are not finished to failed.
:param dag_runs: DAG runs
:param session: session
:return: None
"""
for dag_run in dag_runs:
dag_run.update_state()
if dag_run.state not in State.finished():
dag_run.set_state(State.FAILED)
session.merge(dag_run) | airflow/jobs.py |
apache/airflow | BackfillJob._execute | def _execute(self, session=None):
ti_status = BackfillJob._DagRunTaskStatus()
start_date = self.bf_start_date
run_dates = self.dag.get_run_dates(start_date=start_date,
end_date=self.bf_end_date)
if self.run_backwards:
tasks_that_depend_on_past = [t.task_id for t in self.dag.task_dict.values() if t.depends_on_past]
if tasks_that_depend_on_past:
raise AirflowException(
'You cannot backfill backwards because one or more tasks depend_on_past: {}'.format(
",".join(tasks_that_depend_on_past)))
run_dates = run_dates[::-1]
if len(run_dates) == 0:
self.log.info("No run dates were found for the given dates and dag interval.")
return
pickle_id = None
if not self.donot_pickle and self.executor.__class__ not in (
executors.LocalExecutor, executors.SequentialExecutor):
pickle = DagPickle(self.dag)
session.add(pickle)
session.commit()
pickle_id = pickle.id
executor = self.executor
executor.start()
ti_status.total_runs = len(run_dates)
try:
remaining_dates = ti_status.total_runs
while remaining_dates > 0:
dates_to_process = [run_date for run_date in run_dates
if run_date not in ti_status.executed_dag_run_dates]
self._execute_for_run_dates(run_dates=dates_to_process,
ti_status=ti_status,
executor=executor,
pickle_id=pickle_id,
start_date=start_date,
session=session)
remaining_dates = (
ti_status.total_runs - len(ti_status.executed_dag_run_dates)
)
err = self._collect_errors(ti_status=ti_status, session=session)
if err:
raise AirflowException(err)
if remaining_dates > 0:
self.log.info(
"max_active_runs limit for dag %s has been reached "
" - waiting for other dag runs to finish",
self.dag_id
)
time.sleep(self.delay_on_limit_secs)
except (KeyboardInterrupt, SystemExit):
self.log.warning("Backfill terminated by user.")
self._set_unfinished_dag_runs_to_failed(ti_status.active_runs)
finally:
session.commit()
executor.end()
self.log.info("Backfill done. Exiting.") | Initializes all components required to run a dag for a specified date range and calls helper method to execute the tasks. | def _execute(self, session=None):
"""
Initializes all components required to run a dag for a specified date range and
calls helper method to execute the tasks.
"""
ti_status = BackfillJob._DagRunTaskStatus()
start_date = self.bf_start_date
# Get intervals between the start/end dates, which will turn into dag runs
run_dates = self.dag.get_run_dates(start_date=start_date,
end_date=self.bf_end_date)
if self.run_backwards:
tasks_that_depend_on_past = [t.task_id for t in self.dag.task_dict.values() if t.depends_on_past]
if tasks_that_depend_on_past:
raise AirflowException(
'You cannot backfill backwards because one or more tasks depend_on_past: {}'.format(
",".join(tasks_that_depend_on_past)))
run_dates = run_dates[::-1]
if len(run_dates) == 0:
self.log.info("No run dates were found for the given dates and dag interval.")
return
# picklin'
pickle_id = None
if not self.donot_pickle and self.executor.__class__ not in (
executors.LocalExecutor, executors.SequentialExecutor):
pickle = DagPickle(self.dag)
session.add(pickle)
session.commit()
pickle_id = pickle.id
executor = self.executor
executor.start()
ti_status.total_runs = len(run_dates) # total dag runs in backfill
try:
remaining_dates = ti_status.total_runs
while remaining_dates > 0:
dates_to_process = [run_date for run_date in run_dates
if run_date not in ti_status.executed_dag_run_dates]
self._execute_for_run_dates(run_dates=dates_to_process,
ti_status=ti_status,
executor=executor,
pickle_id=pickle_id,
start_date=start_date,
session=session)
remaining_dates = (
ti_status.total_runs - len(ti_status.executed_dag_run_dates)
)
err = self._collect_errors(ti_status=ti_status, session=session)
if err:
raise AirflowException(err)
if remaining_dates > 0:
self.log.info(
"max_active_runs limit for dag %s has been reached "
" - waiting for other dag runs to finish",
self.dag_id
)
time.sleep(self.delay_on_limit_secs)
except (KeyboardInterrupt, SystemExit):
self.log.warning("Backfill terminated by user.")
# TODO: we will need to terminate running task instances and set the
# state to failed.
self._set_unfinished_dag_runs_to_failed(ti_status.active_runs)
finally:
session.commit()
executor.end()
self.log.info("Backfill done. Exiting.") | airflow/jobs.py |
apache/airflow | LocalTaskJob.heartbeat_callback | def heartbeat_callback(self, session=None):
if self.terminating:
self.task_runner.terminate()
return
self.task_instance.refresh_from_db()
ti = self.task_instance
fqdn = get_hostname()
same_hostname = fqdn == ti.hostname
same_process = ti.pid == os.getpid()
if ti.state == State.RUNNING:
if not same_hostname:
self.log.warning("The recorded hostname %s "
"does not match this instance's hostname "
"%s", ti.hostname, fqdn)
raise AirflowException("Hostname of job runner does not match")
elif not same_process:
current_pid = os.getpid()
self.log.warning("Recorded pid %s does not match "
"the current pid %s", ti.pid, current_pid)
raise AirflowException("PID of job runner does not match")
elif (
self.task_runner.return_code() is None and
hasattr(self.task_runner, 'process')
):
self.log.warning(
"State of this instance has been externally set to %s. "
"Taking the poison pill.",
ti.state
)
self.task_runner.terminate()
self.terminating = True | Self destruct task if state has been moved away from running externally | def heartbeat_callback(self, session=None):
"""Self destruct task if state has been moved away from running externally"""
if self.terminating:
# ensure termination if processes are created later
self.task_runner.terminate()
return
self.task_instance.refresh_from_db()
ti = self.task_instance
fqdn = get_hostname()
same_hostname = fqdn == ti.hostname
same_process = ti.pid == os.getpid()
if ti.state == State.RUNNING:
if not same_hostname:
self.log.warning("The recorded hostname %s "
"does not match this instance's hostname "
"%s", ti.hostname, fqdn)
raise AirflowException("Hostname of job runner does not match")
elif not same_process:
current_pid = os.getpid()
self.log.warning("Recorded pid %s does not match "
"the current pid %s", ti.pid, current_pid)
raise AirflowException("PID of job runner does not match")
elif (
self.task_runner.return_code() is None and
hasattr(self.task_runner, 'process')
):
self.log.warning(
"State of this instance has been externally set to %s. "
"Taking the poison pill.",
ti.state
)
self.task_runner.terminate()
self.terminating = True | airflow/jobs.py |
apache/airflow | CloudSpannerHook._get_client | def _get_client(self, project_id):
if not self._client:
self._client = Client(project=project_id, credentials=self._get_credentials())
return self._client | Provides a client for interacting with the Cloud Spanner API. | def _get_client(self, project_id):
"""
Provides a client for interacting with the Cloud Spanner API.
:param project_id: The ID of the GCP project.
:type project_id: str
:return: google.cloud.spanner_v1.client.Client
:rtype: object
"""
if not self._client:
self._client = Client(project=project_id, credentials=self._get_credentials())
return self._client | airflow/contrib/hooks/gcp_spanner_hook.py |
apache/airflow | CloudSpannerHook.get_instance | def get_instance(self, instance_id, project_id=None):
instance = self._get_client(project_id=project_id).instance(instance_id=instance_id)
if not instance.exists():
return None
return instance | Gets information about a particular instance. | def get_instance(self, instance_id, project_id=None):
"""
Gets information about a particular instance.
:param project_id: Optional, The ID of the GCP project that owns the Cloud Spanner
database. If set to None or missing, the default project_id from the GCP connection is used.
:type project_id: str
:param instance_id: The ID of the Cloud Spanner instance.
:type instance_id: str
:return: google.cloud.spanner_v1.instance.Instance
:rtype: object
"""
instance = self._get_client(project_id=project_id).instance(instance_id=instance_id)
if not instance.exists():
return None
return instance | airflow/contrib/hooks/gcp_spanner_hook.py |
apache/airflow | CloudSpannerHook._apply_to_instance | def _apply_to_instance(self, project_id, instance_id, configuration_name, node_count,
display_name, func):
instance = self._get_client(project_id=project_id).instance(
instance_id=instance_id, configuration_name=configuration_name,
node_count=node_count, display_name=display_name)
try:
operation = func(instance)
except GoogleAPICallError as e:
self.log.error('An error occurred: %s. Exiting.', e.message)
raise e
if operation:
result = operation.result()
self.log.info(result) | Invokes a method on a given instance by applying a specified Callable. | def _apply_to_instance(self, project_id, instance_id, configuration_name, node_count,
display_name, func):
"""
Invokes a method on a given instance by applying a specified Callable.
:param project_id: The ID of the GCP project that owns the Cloud Spanner
database.
:type project_id: str
:param instance_id: The ID of the instance.
:type instance_id: str
:param configuration_name: Name of the instance configuration defining how the
instance will be created. Required for instances which do not yet exist.
:type configuration_name: str
:param node_count: (Optional) Number of nodes allocated to the instance.
:type node_count: int
:param display_name: (Optional) The display name for the instance in the Cloud
Console UI. (Must be between 4 and 30 characters.) If this value is not set
in the constructor, will fall back to the instance ID.
:type display_name: str
:param func: Method of the instance to be called.
:type func: Callable
"""
# noinspection PyUnresolvedReferences
instance = self._get_client(project_id=project_id).instance(
instance_id=instance_id, configuration_name=configuration_name,
node_count=node_count, display_name=display_name)
try:
operation = func(instance) # type: Operation
except GoogleAPICallError as e:
self.log.error('An error occurred: %s. Exiting.', e.message)
raise e
if operation:
result = operation.result()
self.log.info(result) | airflow/contrib/hooks/gcp_spanner_hook.py |
apache/airflow | CloudSpannerHook.create_instance | def create_instance(self, instance_id, configuration_name, node_count,
display_name, project_id=None):
self._apply_to_instance(project_id, instance_id, configuration_name,
node_count, display_name, lambda x: x.create()) | Creates a new Cloud Spanner instance. | def create_instance(self, instance_id, configuration_name, node_count,
display_name, project_id=None):
"""
Creates a new Cloud Spanner instance.
:param instance_id: The ID of the Cloud Spanner instance.
:type instance_id: str
:param configuration_name: The name of the instance configuration defining how the
instance will be created. Possible configuration values can be retrieved via
https://cloud.google.com/spanner/docs/reference/rest/v1/projects.instanceConfigs/list
:type configuration_name: str
:param node_count: (Optional) The number of nodes allocated to the Cloud Spanner
instance.
:type node_count: int
:param display_name: (Optional) The display name for the instance in the GCP
Console. Must be between 4 and 30 characters. If this value is not set in
the constructor, the name falls back to the instance ID.
:type display_name: str
:param project_id: Optional, the ID of the GCP project that owns the Cloud Spanner
database. If set to None or missing, the default project_id from the GCP connection is used.
:type project_id: str
:return: None
"""
self._apply_to_instance(project_id, instance_id, configuration_name,
node_count, display_name, lambda x: x.create()) | airflow/contrib/hooks/gcp_spanner_hook.py |
apache/airflow | CloudSpannerHook.update_instance | def update_instance(self, instance_id, configuration_name, node_count,
display_name, project_id=None):
return self._apply_to_instance(project_id, instance_id, configuration_name,
node_count, display_name, lambda x: x.update()) | Updates an existing Cloud Spanner instance. | def update_instance(self, instance_id, configuration_name, node_count,
display_name, project_id=None):
"""
Updates an existing Cloud Spanner instance.
:param instance_id: The ID of the Cloud Spanner instance.
:type instance_id: str
:param configuration_name: The name of the instance configuration defining how the
instance will be created. Possible configuration values can be retrieved via
https://cloud.google.com/spanner/docs/reference/rest/v1/projects.instanceConfigs/list
:type configuration_name: str
:param node_count: (Optional) The number of nodes allocated to the Cloud Spanner
instance.
:type node_count: int
:param display_name: (Optional) The display name for the instance in the GCP
Console. Must be between 4 and 30 characters. If this value is not set in
the constructor, the name falls back to the instance ID.
:type display_name: str
:param project_id: Optional, the ID of the GCP project that owns the Cloud Spanner
database. If set to None or missing, the default project_id from the GCP connection is used.
:type project_id: str
:return: None
"""
return self._apply_to_instance(project_id, instance_id, configuration_name,
node_count, display_name, lambda x: x.update()) | airflow/contrib/hooks/gcp_spanner_hook.py |
apache/airflow | CloudSpannerHook.delete_instance | def delete_instance(self, instance_id, project_id=None):
instance = self._get_client(project_id=project_id).instance(instance_id)
try:
instance.delete()
return
except GoogleAPICallError as e:
self.log.error('An error occurred: %s. Exiting.', e.message)
raise e | Deletes an existing Cloud Spanner instance. | def delete_instance(self, instance_id, project_id=None):
"""
Deletes an existing Cloud Spanner instance.
:param instance_id: The ID of the Cloud Spanner instance.
:type instance_id: str
:param project_id: Optional, the ID of the GCP project that owns the Cloud Spanner
database. If set to None or missing, the default project_id from the GCP connection is used.
:type project_id: str
:return: None
"""
instance = self._get_client(project_id=project_id).instance(instance_id)
try:
instance.delete()
return
except GoogleAPICallError as e:
self.log.error('An error occurred: %s. Exiting.', e.message)
raise e | airflow/contrib/hooks/gcp_spanner_hook.py |
apache/airflow | CloudSpannerHook.get_database | def get_database(self, instance_id, database_id, project_id=None):
instance = self._get_client(project_id=project_id).instance(
instance_id=instance_id)
if not instance.exists():
raise AirflowException("The instance {} does not exist in project {} !".
format(instance_id, project_id))
database = instance.database(database_id=database_id)
if not database.exists():
return None
else:
return database | Retrieves a database in Cloud Spanner. If the database does not exist in the specified instance, it returns None. | def get_database(self, instance_id, database_id, project_id=None):
"""
Retrieves a database in Cloud Spanner. If the database does not exist
in the specified instance, it returns None.
:param instance_id: The ID of the Cloud Spanner instance.
:type instance_id: str
:param database_id: The ID of the database in Cloud Spanner.
:type database_id: str
:param project_id: Optional, the ID of the GCP project that owns the Cloud Spanner
database. If set to None or missing, the default project_id from the GCP connection is used.
:type project_id: str
:return: Database object or None if database does not exist
:rtype: google.cloud.spanner_v1.database.Database or None
"""
instance = self._get_client(project_id=project_id).instance(
instance_id=instance_id)
if not instance.exists():
raise AirflowException("The instance {} does not exist in project {} !".
format(instance_id, project_id))
database = instance.database(database_id=database_id)
if not database.exists():
return None
else:
return database | airflow/contrib/hooks/gcp_spanner_hook.py |
apache/airflow | CloudSpannerHook.create_database | def create_database(self, instance_id, database_id, ddl_statements, project_id=None):
instance = self._get_client(project_id=project_id).instance(
instance_id=instance_id)
if not instance.exists():
raise AirflowException("The instance {} does not exist in project {} !".
format(instance_id, project_id))
database = instance.database(database_id=database_id,
ddl_statements=ddl_statements)
try:
operation = database.create()
except GoogleAPICallError as e:
self.log.error('An error occurred: %s. Exiting.', e.message)
raise e
if operation:
result = operation.result()
self.log.info(result)
return | Creates a new database in Cloud Spanner. | def create_database(self, instance_id, database_id, ddl_statements, project_id=None):
"""
Creates a new database in Cloud Spanner.
:type project_id: str
:param instance_id: The ID of the Cloud Spanner instance.
:type instance_id: str
:param database_id: The ID of the database to create in Cloud Spanner.
:type database_id: str
:param ddl_statements: The string list containing DDL for the new database.
:type ddl_statements: list[str]
:param project_id: Optional, the ID of the GCP project that owns the Cloud Spanner
database. If set to None or missing, the default project_id from the GCP connection is used.
:return: None
"""
instance = self._get_client(project_id=project_id).instance(
instance_id=instance_id)
if not instance.exists():
raise AirflowException("The instance {} does not exist in project {} !".
format(instance_id, project_id))
database = instance.database(database_id=database_id,
ddl_statements=ddl_statements)
try:
operation = database.create() # type: Operation
except GoogleAPICallError as e:
self.log.error('An error occurred: %s. Exiting.', e.message)
raise e
if operation:
result = operation.result()
self.log.info(result)
return | airflow/contrib/hooks/gcp_spanner_hook.py |
apache/airflow | CloudSpannerHook.update_database | def update_database(self, instance_id, database_id, ddl_statements,
project_id=None,
operation_id=None):
instance = self._get_client(project_id=project_id).instance(
instance_id=instance_id)
if not instance.exists():
raise AirflowException("The instance {} does not exist in project {} !".
format(instance_id, project_id))
database = instance.database(database_id=database_id)
try:
operation = database.update_ddl(
ddl_statements=ddl_statements, operation_id=operation_id)
if operation:
result = operation.result()
self.log.info(result)
return
except AlreadyExists as e:
if e.code == 409 and operation_id in e.message:
self.log.info("Replayed update_ddl message - the operation id %s "
"was already done before.", operation_id)
return
except GoogleAPICallError as e:
self.log.error('An error occurred: %s. Exiting.', e.message)
raise e | Updates DDL of a database in Cloud Spanner. | def update_database(self, instance_id, database_id, ddl_statements,
project_id=None,
operation_id=None):
"""
Updates DDL of a database in Cloud Spanner.
:type project_id: str
:param instance_id: The ID of the Cloud Spanner instance.
:type instance_id: str
:param database_id: The ID of the database in Cloud Spanner.
:type database_id: str
:param ddl_statements: The string list containing DDL for the new database.
:type ddl_statements: list[str]
:param project_id: Optional, the ID of the GCP project that owns the Cloud Spanner
database. If set to None or missing, the default project_id from the GCP connection is used.
:param operation_id: (Optional) The unique per database operation ID that can be
specified to implement idempotency check.
:type operation_id: str
:return: None
"""
instance = self._get_client(project_id=project_id).instance(
instance_id=instance_id)
if not instance.exists():
raise AirflowException("The instance {} does not exist in project {} !".
format(instance_id, project_id))
database = instance.database(database_id=database_id)
try:
operation = database.update_ddl(
ddl_statements=ddl_statements, operation_id=operation_id)
if operation:
result = operation.result()
self.log.info(result)
return
except AlreadyExists as e:
if e.code == 409 and operation_id in e.message:
self.log.info("Replayed update_ddl message - the operation id %s "
"was already done before.", operation_id)
return
except GoogleAPICallError as e:
self.log.error('An error occurred: %s. Exiting.', e.message)
raise e | airflow/contrib/hooks/gcp_spanner_hook.py |
apache/airflow | CloudSpannerHook.delete_database | def delete_database(self, instance_id, database_id, project_id=None):
instance = self._get_client(project_id=project_id).\
instance(instance_id=instance_id)
if not instance.exists():
raise AirflowException("The instance {} does not exist in project {} !".
format(instance_id, project_id))
database = instance.database(database_id=database_id)
if not database.exists():
self.log.info("The database {} is already deleted from instance {}. "
"Exiting.".format(database_id, instance_id))
return
try:
operation = database.drop()
except GoogleAPICallError as e:
self.log.error('An error occurred: %s. Exiting.', e.message)
raise e
if operation:
result = operation.result()
self.log.info(result)
return | Drops a database in Cloud Spanner. | def delete_database(self, instance_id, database_id, project_id=None):
"""
Drops a database in Cloud Spanner.
:type project_id: str
:param instance_id: The ID of the Cloud Spanner instance.
:type instance_id: str
:param database_id: The ID of the database in Cloud Spanner.
:type database_id: str
:param project_id: Optional, the ID of the GCP project that owns the Cloud Spanner
database. If set to None or missing, the default project_id from the GCP connection is used.
:return: True if everything succeeded
:rtype: bool
"""
instance = self._get_client(project_id=project_id).\
instance(instance_id=instance_id)
if not instance.exists():
raise AirflowException("The instance {} does not exist in project {} !".
format(instance_id, project_id))
database = instance.database(database_id=database_id)
if not database.exists():
self.log.info("The database {} is already deleted from instance {}. "
"Exiting.".format(database_id, instance_id))
return
try:
operation = database.drop() # type: Operation
except GoogleAPICallError as e:
self.log.error('An error occurred: %s. Exiting.', e.message)
raise e
if operation:
result = operation.result()
self.log.info(result)
return | airflow/contrib/hooks/gcp_spanner_hook.py |
apache/airflow | ImapAttachmentSensor.poke | def poke(self, context):
self.log.info('Poking for %s', self.attachment_name)
with ImapHook(imap_conn_id=self.conn_id) as imap_hook:
return imap_hook.has_mail_attachment(
name=self.attachment_name,
mail_folder=self.mail_folder,
check_regex=self.check_regex
) | Pokes for a mail attachment on the mail server. | def poke(self, context):
"""
Pokes for a mail attachment on the mail server.
:param context: The context that is being provided when poking.
:type context: dict
:return: True if attachment with the given name is present and False if not.
:rtype: bool
"""
self.log.info('Poking for %s', self.attachment_name)
with ImapHook(imap_conn_id=self.conn_id) as imap_hook:
return imap_hook.has_mail_attachment(
name=self.attachment_name,
mail_folder=self.mail_folder,
check_regex=self.check_regex
) | airflow/contrib/sensors/imap_attachment_sensor.py |
apache/airflow | prepare_additional_parameters | def prepare_additional_parameters(additional_properties, language_hints, web_detection_params):
if language_hints is None and web_detection_params is None:
return additional_properties
if additional_properties is None:
return {}
merged_additional_parameters = deepcopy(additional_properties)
if 'image_context' not in merged_additional_parameters:
merged_additional_parameters['image_context'] = {}
merged_additional_parameters['image_context']['language_hints'] = merged_additional_parameters[
'image_context'
].get('language_hints', language_hints)
merged_additional_parameters['image_context']['web_detection_params'] = merged_additional_parameters[
'image_context'
].get('web_detection_params', web_detection_params)
return merged_additional_parameters | Creates additional_properties parameter based on language_hints, web_detection_params and additional_properties parameters specified by the user | def prepare_additional_parameters(additional_properties, language_hints, web_detection_params):
"""
Creates additional_properties parameter based on language_hints, web_detection_params and
additional_properties parameters specified by the user
"""
if language_hints is None and web_detection_params is None:
return additional_properties
if additional_properties is None:
return {}
merged_additional_parameters = deepcopy(additional_properties)
if 'image_context' not in merged_additional_parameters:
merged_additional_parameters['image_context'] = {}
merged_additional_parameters['image_context']['language_hints'] = merged_additional_parameters[
'image_context'
].get('language_hints', language_hints)
merged_additional_parameters['image_context']['web_detection_params'] = merged_additional_parameters[
'image_context'
].get('web_detection_params', web_detection_params)
return merged_additional_parameters | airflow/contrib/operators/gcp_vision_operator.py |
apache/airflow | CassandraHook.table_exists | def table_exists(self, table):
keyspace = self.keyspace
if '.' in table:
keyspace, table = table.split('.', 1)
cluster_metadata = self.get_conn().cluster.metadata
return (keyspace in cluster_metadata.keyspaces and
table in cluster_metadata.keyspaces[keyspace].tables) | Checks if a table exists in Cassandra | def table_exists(self, table):
"""
Checks if a table exists in Cassandra
:param table: Target Cassandra table.
Use dot notation to target a specific keyspace.
:type table: str
"""
keyspace = self.keyspace
if '.' in table:
keyspace, table = table.split('.', 1)
cluster_metadata = self.get_conn().cluster.metadata
return (keyspace in cluster_metadata.keyspaces and
table in cluster_metadata.keyspaces[keyspace].tables) | airflow/contrib/hooks/cassandra_hook.py |
apache/airflow | CassandraHook.record_exists | def record_exists(self, table, keys):
keyspace = self.keyspace
if '.' in table:
keyspace, table = table.split('.', 1)
ks = " AND ".join("{}=%({})s".format(key, key) for key in keys.keys())
cql = "SELECT * FROM {keyspace}.{table} WHERE {keys}".format(
keyspace=keyspace, table=table, keys=ks)
try:
rs = self.get_conn().execute(cql, keys)
return rs.one() is not None
except Exception:
return False | Checks if a record exists in Cassandra | def record_exists(self, table, keys):
"""
Checks if a record exists in Cassandra
:param table: Target Cassandra table.
Use dot notation to target a specific keyspace.
:type table: str
:param keys: The keys and their values to check the existence.
:type keys: dict
"""
keyspace = self.keyspace
if '.' in table:
keyspace, table = table.split('.', 1)
ks = " AND ".join("{}=%({})s".format(key, key) for key in keys.keys())
cql = "SELECT * FROM {keyspace}.{table} WHERE {keys}".format(
keyspace=keyspace, table=table, keys=ks)
try:
rs = self.get_conn().execute(cql, keys)
return rs.one() is not None
except Exception:
return False | airflow/contrib/hooks/cassandra_hook.py |
apache/airflow | SparkSubmitHook._build_track_driver_status_command | def _build_track_driver_status_command(self):
connection_cmd = self._get_spark_binary_path()
connection_cmd += ["--master", self._connection['master']]
if self._driver_id:
connection_cmd += ["--status", self._driver_id]
else:
raise AirflowException(
"Invalid status: attempted to poll driver " +
"status but no driver id is known. Giving up.")
self.log.debug("Poll driver status cmd: %s", connection_cmd)
return connection_cmd | Construct the command to poll the driver status. | def _build_track_driver_status_command(self):
"""
Construct the command to poll the driver status.
:return: full command to be executed
"""
connection_cmd = self._get_spark_binary_path()
# The url ot the spark master
connection_cmd += ["--master", self._connection['master']]
# The driver id so we can poll for its status
if self._driver_id:
connection_cmd += ["--status", self._driver_id]
else:
raise AirflowException(
"Invalid status: attempted to poll driver " +
"status but no driver id is known. Giving up.")
self.log.debug("Poll driver status cmd: %s", connection_cmd)
return connection_cmd | airflow/contrib/hooks/spark_submit_hook.py |
apache/airflow | SparkSubmitHook.submit | def submit(self, application="", **kwargs):
spark_submit_cmd = self._build_spark_submit_command(application)
if hasattr(self, '_env'):
env = os.environ.copy()
env.update(self._env)
kwargs["env"] = env
self._submit_sp = subprocess.Popen(spark_submit_cmd,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
bufsize=-1,
universal_newlines=True,
**kwargs)
self._process_spark_submit_log(iter(self._submit_sp.stdout.readline, ''))
returncode = self._submit_sp.wait()
if returncode or (self._is_kubernetes and self._spark_exit_code != 0):
raise AirflowException(
"Cannot execute: {}. Error code is: {}.".format(
spark_submit_cmd, returncode
)
)
self.log.debug("Should track driver: {}".format(self._should_track_driver_status))
if self._should_track_driver_status:
if self._driver_id is None:
raise AirflowException(
"No driver id is known: something went wrong when executing " +
"the spark submit command"
)
self._driver_status = "SUBMITTED"
self._start_driver_status_tracking()
if self._driver_status != "FINISHED":
raise AirflowException(
"ERROR : Driver {} badly exited with status {}"
.format(self._driver_id, self._driver_status)
) | Remote Popen to execute the spark-submit job | def submit(self, application="", **kwargs):
"""
Remote Popen to execute the spark-submit job
:param application: Submitted application, jar or py file
:type application: str
:param kwargs: extra arguments to Popen (see subprocess.Popen)
"""
spark_submit_cmd = self._build_spark_submit_command(application)
if hasattr(self, '_env'):
env = os.environ.copy()
env.update(self._env)
kwargs["env"] = env
self._submit_sp = subprocess.Popen(spark_submit_cmd,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
bufsize=-1,
universal_newlines=True,
**kwargs)
self._process_spark_submit_log(iter(self._submit_sp.stdout.readline, ''))
returncode = self._submit_sp.wait()
# Check spark-submit return code. In Kubernetes mode, also check the value
# of exit code in the log, as it may differ.
if returncode or (self._is_kubernetes and self._spark_exit_code != 0):
raise AirflowException(
"Cannot execute: {}. Error code is: {}.".format(
spark_submit_cmd, returncode
)
)
self.log.debug("Should track driver: {}".format(self._should_track_driver_status))
# We want the Airflow job to wait until the Spark driver is finished
if self._should_track_driver_status:
if self._driver_id is None:
raise AirflowException(
"No driver id is known: something went wrong when executing " +
"the spark submit command"
)
# We start with the SUBMITTED status as initial status
self._driver_status = "SUBMITTED"
# Start tracking the driver status (blocking function)
self._start_driver_status_tracking()
if self._driver_status != "FINISHED":
raise AirflowException(
"ERROR : Driver {} badly exited with status {}"
.format(self._driver_id, self._driver_status)
) | airflow/contrib/hooks/spark_submit_hook.py |
apache/airflow | SparkSubmitHook._process_spark_submit_log | def _process_spark_submit_log(self, itr):
for line in itr:
line = line.strip()
if self._is_yarn and self._connection['deploy_mode'] == 'cluster':
match = re.search('(application[0-9_]+)', line)
if match:
self._yarn_application_id = match.groups()[0]
self.log.info("Identified spark driver id: %s",
self._yarn_application_id)
elif self._is_kubernetes:
match = re.search(r'\s*pod name: ((.+?)-([a-z0-9]+)-driver)', line)
if match:
self._kubernetes_driver_pod = match.groups()[0]
self.log.info("Identified spark driver pod: %s",
self._kubernetes_driver_pod)
match_exit_code = re.search(r'\s*Exit code: (\d+)', line)
if match_exit_code:
self._spark_exit_code = int(match_exit_code.groups()[0])
elif self._should_track_driver_status and not self._driver_id:
match_driver_id = re.search(r'(driver-[0-9\-]+)', line)
if match_driver_id:
self._driver_id = match_driver_id.groups()[0]
self.log.info("identified spark driver id: {}"
.format(self._driver_id))
else:
self.log.info(line)
self.log.debug("spark submit log: {}".format(line)) | Processes the log files and extracts useful information out of it. If the deploy-mode is 'client', log the output of the submit command as those are the output logs of the Spark worker directly. | def _process_spark_submit_log(self, itr):
"""
Processes the log files and extracts useful information out of it.
If the deploy-mode is 'client', log the output of the submit command as those
are the output logs of the Spark worker directly.
Remark: If the driver needs to be tracked for its status, the log-level of the
spark deploy needs to be at least INFO (log4j.logger.org.apache.spark.deploy=INFO)
:param itr: An iterator which iterates over the input of the subprocess
"""
# Consume the iterator
for line in itr:
line = line.strip()
# If we run yarn cluster mode, we want to extract the application id from
# the logs so we can kill the application when we stop it unexpectedly
if self._is_yarn and self._connection['deploy_mode'] == 'cluster':
match = re.search('(application[0-9_]+)', line)
if match:
self._yarn_application_id = match.groups()[0]
self.log.info("Identified spark driver id: %s",
self._yarn_application_id)
# If we run Kubernetes cluster mode, we want to extract the driver pod id
# from the logs so we can kill the application when we stop it unexpectedly
elif self._is_kubernetes:
match = re.search(r'\s*pod name: ((.+?)-([a-z0-9]+)-driver)', line)
if match:
self._kubernetes_driver_pod = match.groups()[0]
self.log.info("Identified spark driver pod: %s",
self._kubernetes_driver_pod)
# Store the Spark Exit code
match_exit_code = re.search(r'\s*Exit code: (\d+)', line)
if match_exit_code:
self._spark_exit_code = int(match_exit_code.groups()[0])
# if we run in standalone cluster mode and we want to track the driver status
# we need to extract the driver id from the logs. This allows us to poll for
# the status using the driver id. Also, we can kill the driver when needed.
elif self._should_track_driver_status and not self._driver_id:
match_driver_id = re.search(r'(driver-[0-9\-]+)', line)
if match_driver_id:
self._driver_id = match_driver_id.groups()[0]
self.log.info("identified spark driver id: {}"
.format(self._driver_id))
else:
self.log.info(line)
self.log.debug("spark submit log: {}".format(line)) | airflow/contrib/hooks/spark_submit_hook.py |
apache/airflow | SparkSubmitHook._process_spark_status_log | def _process_spark_status_log(self, itr):
for line in itr:
line = line.strip()
if "driverState" in line:
self._driver_status = line.split(' : ')[1] \
.replace(',', '').replace('\"', '').strip()
self.log.debug("spark driver status log: {}".format(line)) | parses the logs of the spark driver status query process | def _process_spark_status_log(self, itr):
"""
parses the logs of the spark driver status query process
:param itr: An iterator which iterates over the input of the subprocess
"""
# Consume the iterator
for line in itr:
line = line.strip()
# Check if the log line is about the driver status and extract the status.
if "driverState" in line:
self._driver_status = line.split(' : ')[1] \
.replace(',', '').replace('\"', '').strip()
self.log.debug("spark driver status log: {}".format(line)) | airflow/contrib/hooks/spark_submit_hook.py |
apache/airflow | get_task_runner | def get_task_runner(local_task_job):
if _TASK_RUNNER == "StandardTaskRunner":
return StandardTaskRunner(local_task_job)
elif _TASK_RUNNER == "CgroupTaskRunner":
from airflow.contrib.task_runner.cgroup_task_runner import CgroupTaskRunner
return CgroupTaskRunner(local_task_job)
else:
raise AirflowException("Unknown task runner type {}".format(_TASK_RUNNER)) | Get the task runner that can be used to run the given job. | def get_task_runner(local_task_job):
"""
Get the task runner that can be used to run the given job.
:param local_task_job: The LocalTaskJob associated with the TaskInstance
that needs to be executed.
:type local_task_job: airflow.jobs.LocalTaskJob
:return: The task runner to use to run the task.
:rtype: airflow.task.task_runner.base_task_runner.BaseTaskRunner
"""
if _TASK_RUNNER == "StandardTaskRunner":
return StandardTaskRunner(local_task_job)
elif _TASK_RUNNER == "CgroupTaskRunner":
from airflow.contrib.task_runner.cgroup_task_runner import CgroupTaskRunner
return CgroupTaskRunner(local_task_job)
else:
raise AirflowException("Unknown task runner type {}".format(_TASK_RUNNER)) | airflow/task/task_runner/__init__.py |
apache/airflow | AWSBatchOperator._wait_for_task_ended | def _wait_for_task_ended(self):
try:
waiter = self.client.get_waiter('job_execution_complete')
waiter.config.max_attempts = sys.maxsize
waiter.wait(jobs=[self.jobId])
except ValueError:
retry = True
retries = 0
while retries < self.max_retries and retry:
self.log.info('AWS Batch retry in the next %s seconds', retries)
response = self.client.describe_jobs(
jobs=[self.jobId]
)
if response['jobs'][-1]['status'] in ['SUCCEEDED', 'FAILED']:
retry = False
sleep(1 + pow(retries * 0.1, 2))
retries += 1 | Try to use a waiter from the below pull request | def _wait_for_task_ended(self):
"""
Try to use a waiter from the below pull request
* https://github.com/boto/botocore/pull/1307
If the waiter is not available apply a exponential backoff
* docs.aws.amazon.com/general/latest/gr/api-retries.html
"""
try:
waiter = self.client.get_waiter('job_execution_complete')
waiter.config.max_attempts = sys.maxsize # timeout is managed by airflow
waiter.wait(jobs=[self.jobId])
except ValueError:
# If waiter not available use expo
retry = True
retries = 0
while retries < self.max_retries and retry:
self.log.info('AWS Batch retry in the next %s seconds', retries)
response = self.client.describe_jobs(
jobs=[self.jobId]
)
if response['jobs'][-1]['status'] in ['SUCCEEDED', 'FAILED']:
retry = False
sleep(1 + pow(retries * 0.1, 2))
retries += 1 | airflow/contrib/operators/awsbatch_operator.py |
apache/airflow | MySqlToGoogleCloudStorageOperator._query_mysql | def _query_mysql(self):
mysql = MySqlHook(mysql_conn_id=self.mysql_conn_id)
conn = mysql.get_conn()
cursor = conn.cursor()
cursor.execute(self.sql)
return cursor | Queries mysql and returns a cursor to the results. | def _query_mysql(self):
"""
Queries mysql and returns a cursor to the results.
"""
mysql = MySqlHook(mysql_conn_id=self.mysql_conn_id)
conn = mysql.get_conn()
cursor = conn.cursor()
cursor.execute(self.sql)
return cursor | airflow/contrib/operators/mysql_to_gcs.py |
apache/airflow | MySqlToGoogleCloudStorageOperator._configure_csv_file | def _configure_csv_file(self, file_handle, schema):
csv_writer = csv.writer(file_handle, encoding='utf-8',
delimiter=self.field_delimiter)
csv_writer.writerow(schema)
return csv_writer | Configure a csv writer with the file_handle and write schema as headers for the new file. | def _configure_csv_file(self, file_handle, schema):
"""Configure a csv writer with the file_handle and write schema
as headers for the new file.
"""
csv_writer = csv.writer(file_handle, encoding='utf-8',
delimiter=self.field_delimiter)
csv_writer.writerow(schema)
return csv_writer | airflow/contrib/operators/mysql_to_gcs.py |
apache/airflow | MySqlToGoogleCloudStorageOperator._write_local_schema_file | def _write_local_schema_file(self, cursor):
schema_str = None
schema_file_mime_type = 'application/json'
tmp_schema_file_handle = NamedTemporaryFile(delete=True)
if self.schema is not None and isinstance(self.schema, string_types):
schema_str = self.schema.encode('utf-8')
elif self.schema is not None and isinstance(self.schema, list):
schema_str = json.dumps(self.schema).encode('utf-8')
else:
schema = []
for field in cursor.description:
field_name = field[0]
field_type = self.type_map(field[1])
if field[6] or field_type == 'TIMESTAMP':
field_mode = 'NULLABLE'
else:
field_mode = 'REQUIRED'
schema.append({
'name': field_name,
'type': field_type,
'mode': field_mode,
})
schema_str = json.dumps(schema, sort_keys=True).encode('utf-8')
tmp_schema_file_handle.write(schema_str)
self.log.info('Using schema for %s: %s', self.schema_filename, schema_str)
schema_file_to_upload = {
'file_name': self.schema_filename,
'file_handle': tmp_schema_file_handle,
'file_mime_type': schema_file_mime_type
}
return schema_file_to_upload | Takes a cursor, and writes the BigQuery schema in .json format for the results to a local file system. | def _write_local_schema_file(self, cursor):
"""
Takes a cursor, and writes the BigQuery schema in .json format for the
results to a local file system.
:return: A dictionary where key is a filename to be used as an object
name in GCS, and values are file handles to local files that
contains the BigQuery schema fields in .json format.
"""
schema_str = None
schema_file_mime_type = 'application/json'
tmp_schema_file_handle = NamedTemporaryFile(delete=True)
if self.schema is not None and isinstance(self.schema, string_types):
schema_str = self.schema.encode('utf-8')
elif self.schema is not None and isinstance(self.schema, list):
schema_str = json.dumps(self.schema).encode('utf-8')
else:
schema = []
for field in cursor.description:
# See PEP 249 for details about the description tuple.
field_name = field[0]
field_type = self.type_map(field[1])
# Always allow TIMESTAMP to be nullable. MySQLdb returns None types
# for required fields because some MySQL timestamps can't be
# represented by Python's datetime (e.g. 0000-00-00 00:00:00).
if field[6] or field_type == 'TIMESTAMP':
field_mode = 'NULLABLE'
else:
field_mode = 'REQUIRED'
schema.append({
'name': field_name,
'type': field_type,
'mode': field_mode,
})
schema_str = json.dumps(schema, sort_keys=True).encode('utf-8')
tmp_schema_file_handle.write(schema_str)
self.log.info('Using schema for %s: %s', self.schema_filename, schema_str)
schema_file_to_upload = {
'file_name': self.schema_filename,
'file_handle': tmp_schema_file_handle,
'file_mime_type': schema_file_mime_type
}
return schema_file_to_upload | airflow/contrib/operators/mysql_to_gcs.py |
apache/airflow | MySqlToGoogleCloudStorageOperator._get_col_type_dict | def _get_col_type_dict(self):
schema = []
if isinstance(self.schema, string_types):
schema = json.loads(self.schema)
elif isinstance(self.schema, list):
schema = self.schema
elif self.schema is not None:
self.log.warn('Using default schema due to unexpected type.'
'Should be a string or list.')
col_type_dict = {}
try:
col_type_dict = {col['name']: col['type'] for col in schema}
except KeyError:
self.log.warn('Using default schema due to missing name or type. Please '
'refer to: https://cloud.google.com/bigquery/docs/schemas'
'#specifying_a_json_schema_file')
return col_type_dict | Return a dict of column name and column type based on self.schema if not None. | def _get_col_type_dict(self):
"""
Return a dict of column name and column type based on self.schema if not None.
"""
schema = []
if isinstance(self.schema, string_types):
schema = json.loads(self.schema)
elif isinstance(self.schema, list):
schema = self.schema
elif self.schema is not None:
self.log.warn('Using default schema due to unexpected type.'
'Should be a string or list.')
col_type_dict = {}
try:
col_type_dict = {col['name']: col['type'] for col in schema}
except KeyError:
self.log.warn('Using default schema due to missing name or type. Please '
'refer to: https://cloud.google.com/bigquery/docs/schemas'
'#specifying_a_json_schema_file')
return col_type_dict | airflow/contrib/operators/mysql_to_gcs.py |
apache/airflow | MySqlToGoogleCloudStorageOperator.type_map | def type_map(cls, mysql_type):
d = {
FIELD_TYPE.INT24: 'INTEGER',
FIELD_TYPE.TINY: 'INTEGER',
FIELD_TYPE.BIT: 'INTEGER',
FIELD_TYPE.DATETIME: 'TIMESTAMP',
FIELD_TYPE.DATE: 'TIMESTAMP',
FIELD_TYPE.DECIMAL: 'FLOAT',
FIELD_TYPE.NEWDECIMAL: 'FLOAT',
FIELD_TYPE.DOUBLE: 'FLOAT',
FIELD_TYPE.FLOAT: 'FLOAT',
FIELD_TYPE.LONG: 'INTEGER',
FIELD_TYPE.LONGLONG: 'INTEGER',
FIELD_TYPE.SHORT: 'INTEGER',
FIELD_TYPE.TIMESTAMP: 'TIMESTAMP',
FIELD_TYPE.YEAR: 'INTEGER',
}
return d[mysql_type] if mysql_type in d else 'STRING' | Helper function that maps from MySQL fields to BigQuery fields. Used when a schema_filename is set. | def type_map(cls, mysql_type):
"""
Helper function that maps from MySQL fields to BigQuery fields. Used
when a schema_filename is set.
"""
d = {
FIELD_TYPE.INT24: 'INTEGER',
FIELD_TYPE.TINY: 'INTEGER',
FIELD_TYPE.BIT: 'INTEGER',
FIELD_TYPE.DATETIME: 'TIMESTAMP',
FIELD_TYPE.DATE: 'TIMESTAMP',
FIELD_TYPE.DECIMAL: 'FLOAT',
FIELD_TYPE.NEWDECIMAL: 'FLOAT',
FIELD_TYPE.DOUBLE: 'FLOAT',
FIELD_TYPE.FLOAT: 'FLOAT',
FIELD_TYPE.LONG: 'INTEGER',
FIELD_TYPE.LONGLONG: 'INTEGER',
FIELD_TYPE.SHORT: 'INTEGER',
FIELD_TYPE.TIMESTAMP: 'TIMESTAMP',
FIELD_TYPE.YEAR: 'INTEGER',
}
return d[mysql_type] if mysql_type in d else 'STRING' | airflow/contrib/operators/mysql_to_gcs.py |
apache/airflow | SqoopOperator.execute | def execute(self, context):
self.hook = SqoopHook(
conn_id=self.conn_id,
verbose=self.verbose,
num_mappers=self.num_mappers,
hcatalog_database=self.hcatalog_database,
hcatalog_table=self.hcatalog_table,
properties=self.properties
)
if self.cmd_type == 'export':
self.hook.export_table(
table=self.table,
export_dir=self.export_dir,
input_null_string=self.input_null_string,
input_null_non_string=self.input_null_non_string,
staging_table=self.staging_table,
clear_staging_table=self.clear_staging_table,
enclosed_by=self.enclosed_by,
escaped_by=self.escaped_by,
input_fields_terminated_by=self.input_fields_terminated_by,
input_lines_terminated_by=self.input_lines_terminated_by,
input_optionally_enclosed_by=self.input_optionally_enclosed_by,
batch=self.batch,
relaxed_isolation=self.relaxed_isolation,
extra_export_options=self.extra_export_options)
elif self.cmd_type == 'import':
if self.create_hcatalog_table:
self.extra_import_options['create-hcatalog-table'] = ''
if self.table and self.query:
raise AirflowException(
'Cannot specify query and table together. Need to specify either or.'
)
if self.table:
self.hook.import_table(
table=self.table,
target_dir=self.target_dir,
append=self.append,
file_type=self.file_type,
columns=self.columns,
split_by=self.split_by,
where=self.where,
direct=self.direct,
driver=self.driver,
extra_import_options=self.extra_import_options)
elif self.query:
self.hook.import_query(
query=self.query,
target_dir=self.target_dir,
append=self.append,
file_type=self.file_type,
split_by=self.split_by,
direct=self.direct,
driver=self.driver,
extra_import_options=self.extra_import_options)
else:
raise AirflowException(
"Provide query or table parameter to import using Sqoop"
)
else:
raise AirflowException("cmd_type should be 'import' or 'export'") | Execute sqoop job | def execute(self, context):
"""
Execute sqoop job
"""
self.hook = SqoopHook(
conn_id=self.conn_id,
verbose=self.verbose,
num_mappers=self.num_mappers,
hcatalog_database=self.hcatalog_database,
hcatalog_table=self.hcatalog_table,
properties=self.properties
)
if self.cmd_type == 'export':
self.hook.export_table(
table=self.table,
export_dir=self.export_dir,
input_null_string=self.input_null_string,
input_null_non_string=self.input_null_non_string,
staging_table=self.staging_table,
clear_staging_table=self.clear_staging_table,
enclosed_by=self.enclosed_by,
escaped_by=self.escaped_by,
input_fields_terminated_by=self.input_fields_terminated_by,
input_lines_terminated_by=self.input_lines_terminated_by,
input_optionally_enclosed_by=self.input_optionally_enclosed_by,
batch=self.batch,
relaxed_isolation=self.relaxed_isolation,
extra_export_options=self.extra_export_options)
elif self.cmd_type == 'import':
# add create hcatalog table to extra import options if option passed
# if new params are added to constructor can pass them in here
# so don't modify sqoop_hook for each param
if self.create_hcatalog_table:
self.extra_import_options['create-hcatalog-table'] = ''
if self.table and self.query:
raise AirflowException(
'Cannot specify query and table together. Need to specify either or.'
)
if self.table:
self.hook.import_table(
table=self.table,
target_dir=self.target_dir,
append=self.append,
file_type=self.file_type,
columns=self.columns,
split_by=self.split_by,
where=self.where,
direct=self.direct,
driver=self.driver,
extra_import_options=self.extra_import_options)
elif self.query:
self.hook.import_query(
query=self.query,
target_dir=self.target_dir,
append=self.append,
file_type=self.file_type,
split_by=self.split_by,
direct=self.direct,
driver=self.driver,
extra_import_options=self.extra_import_options)
else:
raise AirflowException(
"Provide query or table parameter to import using Sqoop"
)
else:
raise AirflowException("cmd_type should be 'import' or 'export'") | airflow/contrib/operators/sqoop_operator.py |
apache/airflow | apply_lineage | def apply_lineage(func):
backend = _get_backend()
@wraps(func)
def wrapper(self, context, *args, **kwargs):
self.log.debug("Backend: %s, Lineage called with inlets: %s, outlets: %s",
backend, self.inlets, self.outlets)
ret_val = func(self, context, *args, **kwargs)
outlets = [x.as_dict() for x in self.outlets]
inlets = [x.as_dict() for x in self.inlets]
if len(self.outlets) > 0:
self.xcom_push(context,
key=PIPELINE_OUTLETS,
value=outlets,
execution_date=context['ti'].execution_date)
if len(self.inlets) > 0:
self.xcom_push(context,
key=PIPELINE_INLETS,
value=inlets,
execution_date=context['ti'].execution_date)
if backend:
backend.send_lineage(operator=self, inlets=self.inlets,
outlets=self.outlets, context=context)
return ret_val
return wrapper | Saves the lineage to XCom and if configured to do so sends it to the backend. | def apply_lineage(func):
"""
Saves the lineage to XCom and if configured to do so sends it
to the backend.
"""
backend = _get_backend()
@wraps(func)
def wrapper(self, context, *args, **kwargs):
self.log.debug("Backend: %s, Lineage called with inlets: %s, outlets: %s",
backend, self.inlets, self.outlets)
ret_val = func(self, context, *args, **kwargs)
outlets = [x.as_dict() for x in self.outlets]
inlets = [x.as_dict() for x in self.inlets]
if len(self.outlets) > 0:
self.xcom_push(context,
key=PIPELINE_OUTLETS,
value=outlets,
execution_date=context['ti'].execution_date)
if len(self.inlets) > 0:
self.xcom_push(context,
key=PIPELINE_INLETS,
value=inlets,
execution_date=context['ti'].execution_date)
if backend:
backend.send_lineage(operator=self, inlets=self.inlets,
outlets=self.outlets, context=context)
return ret_val
return wrapper | airflow/lineage/__init__.py |
apache/airflow | date_range | def date_range(start_date, end_date=None, num=None, delta=None):
if not delta:
return []
if end_date and start_date > end_date:
raise Exception("Wait. start_date needs to be before end_date")
if end_date and num:
raise Exception("Wait. Either specify end_date OR num")
if not end_date and not num:
end_date = timezone.utcnow()
delta_iscron = False
tz = start_date.tzinfo
if isinstance(delta, six.string_types):
delta_iscron = True
start_date = timezone.make_naive(start_date, tz)
cron = croniter(delta, start_date)
elif isinstance(delta, timedelta):
delta = abs(delta)
dates = []
if end_date:
if timezone.is_naive(start_date):
end_date = timezone.make_naive(end_date, tz)
while start_date <= end_date:
if timezone.is_naive(start_date):
dates.append(timezone.make_aware(start_date, tz))
else:
dates.append(start_date)
if delta_iscron:
start_date = cron.get_next(datetime)
else:
start_date += delta
else:
for _ in range(abs(num)):
if timezone.is_naive(start_date):
dates.append(timezone.make_aware(start_date, tz))
else:
dates.append(start_date)
if delta_iscron:
if num > 0:
start_date = cron.get_next(datetime)
else:
start_date = cron.get_prev(datetime)
else:
if num > 0:
start_date += delta
else:
start_date -= delta
return sorted(dates) | Get a set of dates as a list based on a start, end and delta, delta can be something that can be added to `datetime.datetime` or a cron expression as a `str` | def date_range(start_date, end_date=None, num=None, delta=None):
"""
Get a set of dates as a list based on a start, end and delta, delta
can be something that can be added to `datetime.datetime`
or a cron expression as a `str`
:Example::
date_range(datetime(2016, 1, 1), datetime(2016, 1, 3), delta=timedelta(1))
[datetime.datetime(2016, 1, 1, 0, 0), datetime.datetime(2016, 1, 2, 0, 0),
datetime.datetime(2016, 1, 3, 0, 0)]
date_range(datetime(2016, 1, 1), datetime(2016, 1, 3), delta='0 0 * * *')
[datetime.datetime(2016, 1, 1, 0, 0), datetime.datetime(2016, 1, 2, 0, 0),
datetime.datetime(2016, 1, 3, 0, 0)]
date_range(datetime(2016, 1, 1), datetime(2016, 3, 3), delta="0 0 0 * *")
[datetime.datetime(2016, 1, 1, 0, 0), datetime.datetime(2016, 2, 1, 0, 0),
datetime.datetime(2016, 3, 1, 0, 0)]
:param start_date: anchor date to start the series from
:type start_date: datetime.datetime
:param end_date: right boundary for the date range
:type end_date: datetime.datetime
:param num: alternatively to end_date, you can specify the number of
number of entries you want in the range. This number can be negative,
output will always be sorted regardless
:type num: int
"""
if not delta:
return []
if end_date and start_date > end_date:
raise Exception("Wait. start_date needs to be before end_date")
if end_date and num:
raise Exception("Wait. Either specify end_date OR num")
if not end_date and not num:
end_date = timezone.utcnow()
delta_iscron = False
tz = start_date.tzinfo
if isinstance(delta, six.string_types):
delta_iscron = True
start_date = timezone.make_naive(start_date, tz)
cron = croniter(delta, start_date)
elif isinstance(delta, timedelta):
delta = abs(delta)
dates = []
if end_date:
if timezone.is_naive(start_date):
end_date = timezone.make_naive(end_date, tz)
while start_date <= end_date:
if timezone.is_naive(start_date):
dates.append(timezone.make_aware(start_date, tz))
else:
dates.append(start_date)
if delta_iscron:
start_date = cron.get_next(datetime)
else:
start_date += delta
else:
for _ in range(abs(num)):
if timezone.is_naive(start_date):
dates.append(timezone.make_aware(start_date, tz))
else:
dates.append(start_date)
if delta_iscron:
if num > 0:
start_date = cron.get_next(datetime)
else:
start_date = cron.get_prev(datetime)
else:
if num > 0:
start_date += delta
else:
start_date -= delta
return sorted(dates) | airflow/utils/dates.py |
apache/airflow | scale_time_units | def scale_time_units(time_seconds_arr, unit):
if unit == 'minutes':
return list(map(lambda x: x * 1.0 / 60, time_seconds_arr))
elif unit == 'hours':
return list(map(lambda x: x * 1.0 / (60 * 60), time_seconds_arr))
elif unit == 'days':
return list(map(lambda x: x * 1.0 / (24 * 60 * 60), time_seconds_arr))
return time_seconds_arr | Convert an array of time durations in seconds to the specified time unit. | def scale_time_units(time_seconds_arr, unit):
"""
Convert an array of time durations in seconds to the specified time unit.
"""
if unit == 'minutes':
return list(map(lambda x: x * 1.0 / 60, time_seconds_arr))
elif unit == 'hours':
return list(map(lambda x: x * 1.0 / (60 * 60), time_seconds_arr))
elif unit == 'days':
return list(map(lambda x: x * 1.0 / (24 * 60 * 60), time_seconds_arr))
return time_seconds_arr | airflow/utils/dates.py |
apache/airflow | days_ago | def days_ago(n, hour=0, minute=0, second=0, microsecond=0):
today = timezone.utcnow().replace(
hour=hour,
minute=minute,
second=second,
microsecond=microsecond)
return today - timedelta(days=n) | Get a datetime object representing `n` days ago. By default the time is set to midnight. | def days_ago(n, hour=0, minute=0, second=0, microsecond=0):
"""
Get a datetime object representing `n` days ago. By default the time is
set to midnight.
"""
today = timezone.utcnow().replace(
hour=hour,
minute=minute,
second=second,
microsecond=microsecond)
return today - timedelta(days=n) | airflow/utils/dates.py |
apache/airflow | AirflowSecurityManager.init_role | def init_role(self, role_name, role_vms, role_perms):
pvms = self.get_session.query(sqla_models.PermissionView).all()
pvms = [p for p in pvms if p.permission and p.view_menu]
role = self.find_role(role_name)
if not role:
role = self.add_role(role_name)
if len(role.permissions) == 0:
self.log.info('Initializing permissions for role:%s in the database.', role_name)
role_pvms = set()
for pvm in pvms:
if pvm.view_menu.name in role_vms and pvm.permission.name in role_perms:
role_pvms.add(pvm)
role.permissions = list(role_pvms)
self.get_session.merge(role)
self.get_session.commit()
else:
self.log.debug('Existing permissions for the role:%s '
'within the database will persist.', role_name) | Initialize the role with the permissions and related view-menus. | def init_role(self, role_name, role_vms, role_perms):
"""
Initialize the role with the permissions and related view-menus.
:param role_name:
:param role_vms:
:param role_perms:
:return:
"""
pvms = self.get_session.query(sqla_models.PermissionView).all()
pvms = [p for p in pvms if p.permission and p.view_menu]
role = self.find_role(role_name)
if not role:
role = self.add_role(role_name)
if len(role.permissions) == 0:
self.log.info('Initializing permissions for role:%s in the database.', role_name)
role_pvms = set()
for pvm in pvms:
if pvm.view_menu.name in role_vms and pvm.permission.name in role_perms:
role_pvms.add(pvm)
role.permissions = list(role_pvms)
self.get_session.merge(role)
self.get_session.commit()
else:
self.log.debug('Existing permissions for the role:%s '
'within the database will persist.', role_name) | airflow/www/security.py |
apache/airflow | AirflowSecurityManager.delete_role | def delete_role(self, role_name):
session = self.get_session
role = session.query(sqla_models.Role)\
.filter(sqla_models.Role.name == role_name)\
.first()
if role:
self.log.info("Deleting role '%s'", role_name)
session.delete(role)
session.commit()
else:
raise AirflowException("Role named '{}' does not exist".format(
role_name)) | Delete the given Role | def delete_role(self, role_name):
"""Delete the given Role
:param role_name: the name of a role in the ab_role table
"""
session = self.get_session
role = session.query(sqla_models.Role)\
.filter(sqla_models.Role.name == role_name)\
.first()
if role:
self.log.info("Deleting role '%s'", role_name)
session.delete(role)
session.commit()
else:
raise AirflowException("Role named '{}' does not exist".format(
role_name)) | airflow/www/security.py |
apache/airflow | AirflowSecurityManager.get_user_roles | def get_user_roles(self, user=None):
if user is None:
user = g.user
if user.is_anonymous:
public_role = appbuilder.config.get('AUTH_ROLE_PUBLIC')
return [appbuilder.security_manager.find_role(public_role)] \
if public_role else []
return user.roles | Get all the roles associated with the user. | def get_user_roles(self, user=None):
"""
Get all the roles associated with the user.
:param user: the ab_user in FAB model.
:return: a list of roles associated with the user.
"""
if user is None:
user = g.user
if user.is_anonymous:
public_role = appbuilder.config.get('AUTH_ROLE_PUBLIC')
return [appbuilder.security_manager.find_role(public_role)] \
if public_role else []
return user.roles | airflow/www/security.py |
apache/airflow | AirflowSecurityManager._has_role | def _has_role(self, role_name_or_list):
if not isinstance(role_name_or_list, list):
role_name_or_list = [role_name_or_list]
return any(
[r.name in role_name_or_list for r in self.get_user_roles()]) | Whether the user has this role name | def _has_role(self, role_name_or_list):
"""
Whether the user has this role name
"""
if not isinstance(role_name_or_list, list):
role_name_or_list = [role_name_or_list]
return any(
[r.name in role_name_or_list for r in self.get_user_roles()]) | airflow/www/security.py |
apache/airflow | AirflowSecurityManager._has_perm | def _has_perm(self, permission_name, view_menu_name):
if hasattr(self, 'perms'):
if (permission_name, view_menu_name) in self.perms:
return True
self._get_and_cache_perms()
return (permission_name, view_menu_name) in self.perms | Whether the user has this perm | def _has_perm(self, permission_name, view_menu_name):
"""
Whether the user has this perm
"""
if hasattr(self, 'perms'):
if (permission_name, view_menu_name) in self.perms:
return True
# rebuild the permissions set
self._get_and_cache_perms()
return (permission_name, view_menu_name) in self.perms | airflow/www/security.py |
apache/airflow | AirflowSecurityManager.clean_perms | def clean_perms(self):
self.log.debug('Cleaning faulty perms')
sesh = self.get_session
pvms = (
sesh.query(sqla_models.PermissionView)
.filter(or_(
sqla_models.PermissionView.permission == None,
sqla_models.PermissionView.view_menu == None,
))
)
deleted_count = pvms.delete()
sesh.commit()
if deleted_count:
self.log.info('Deleted %s faulty permissions', deleted_count) | FAB leaves faulty permissions that need to be cleaned up | def clean_perms(self):
"""
FAB leaves faulty permissions that need to be cleaned up
"""
self.log.debug('Cleaning faulty perms')
sesh = self.get_session
pvms = (
sesh.query(sqla_models.PermissionView)
.filter(or_(
sqla_models.PermissionView.permission == None, # NOQA
sqla_models.PermissionView.view_menu == None, # NOQA
))
)
deleted_count = pvms.delete()
sesh.commit()
if deleted_count:
self.log.info('Deleted %s faulty permissions', deleted_count) | airflow/www/security.py |
apache/airflow | AirflowSecurityManager._merge_perm | def _merge_perm(self, permission_name, view_menu_name):
permission = self.find_permission(permission_name)
view_menu = self.find_view_menu(view_menu_name)
pv = None
if permission and view_menu:
pv = self.get_session.query(self.permissionview_model).filter_by(
permission=permission, view_menu=view_menu).first()
if not pv and permission_name and view_menu_name:
self.add_permission_view_menu(permission_name, view_menu_name) | Add the new permission , view_menu to ab_permission_view_role if not exists. It will add the related entry to ab_permission and ab_view_menu two meta tables as well. | def _merge_perm(self, permission_name, view_menu_name):
"""
Add the new permission , view_menu to ab_permission_view_role if not exists.
It will add the related entry to ab_permission
and ab_view_menu two meta tables as well.
:param permission_name: Name of the permission.
:type permission_name: str
:param view_menu_name: Name of the view-menu
:type view_menu_name: str
:return:
"""
permission = self.find_permission(permission_name)
view_menu = self.find_view_menu(view_menu_name)
pv = None
if permission and view_menu:
pv = self.get_session.query(self.permissionview_model).filter_by(
permission=permission, view_menu=view_menu).first()
if not pv and permission_name and view_menu_name:
self.add_permission_view_menu(permission_name, view_menu_name) | airflow/www/security.py |
apache/airflow | AirflowSecurityManager.update_admin_perm_view | def update_admin_perm_view(self):
pvms = self.get_session.query(sqla_models.PermissionView).all()
pvms = [p for p in pvms if p.permission and p.view_menu]
admin = self.find_role('Admin')
admin.permissions = list(set(admin.permissions) | set(pvms))
self.get_session.commit() | Admin should have all the permission-views. Add the missing ones to the table for admin. | def update_admin_perm_view(self):
"""
Admin should have all the permission-views.
Add the missing ones to the table for admin.
:return: None.
"""
pvms = self.get_session.query(sqla_models.PermissionView).all()
pvms = [p for p in pvms if p.permission and p.view_menu]
admin = self.find_role('Admin')
admin.permissions = list(set(admin.permissions) | set(pvms))
self.get_session.commit() | airflow/www/security.py |
apache/airflow | AirflowSecurityManager._sync_dag_view_permissions | def _sync_dag_view_permissions(self, dag_id, access_control):
def _get_or_create_dag_permission(perm_name):
dag_perm = self.find_permission_view_menu(perm_name, dag_id)
if not dag_perm:
self.log.info(
"Creating new permission '%s' on view '%s'",
perm_name, dag_id
)
dag_perm = self.add_permission_view_menu(perm_name, dag_id)
return dag_perm
def _revoke_stale_permissions(dag_view):
existing_dag_perms = self.find_permissions_view_menu(dag_view)
for perm in existing_dag_perms:
non_admin_roles = [role for role in perm.role
if role.name != 'Admin']
for role in non_admin_roles:
target_perms_for_role = access_control.get(role.name, {})
if perm.permission.name not in target_perms_for_role:
self.log.info(
"Revoking '%s' on DAG '%s' for role '%s'",
perm.permission, dag_id, role.name
)
self.del_permission_role(role, perm)
dag_view = self.find_view_menu(dag_id)
if dag_view:
_revoke_stale_permissions(dag_view)
for rolename, perms in access_control.items():
role = self.find_role(rolename)
if not role:
raise AirflowException(
"The access_control mapping for DAG '{}' includes a role "
"named '{}', but that role does not exist".format(
dag_id,
rolename))
perms = set(perms)
invalid_perms = perms - self.DAG_PERMS
if invalid_perms:
raise AirflowException(
"The access_control map for DAG '{}' includes the following "
"invalid permissions: {}; The set of valid permissions "
"is: {}".format(dag_id,
(perms - self.DAG_PERMS),
self.DAG_PERMS))
for perm_name in perms:
dag_perm = _get_or_create_dag_permission(perm_name)
self.add_permission_role(role, dag_perm) | Set the access policy on the given DAG's ViewModel. | def _sync_dag_view_permissions(self, dag_id, access_control):
"""Set the access policy on the given DAG's ViewModel.
:param dag_id: the ID of the DAG whose permissions should be updated
:type dag_id: string
:param access_control: a dict where each key is a rolename and
each value is a set() of permission names (e.g.,
{'can_dag_read'}
:type access_control: dict
"""
def _get_or_create_dag_permission(perm_name):
dag_perm = self.find_permission_view_menu(perm_name, dag_id)
if not dag_perm:
self.log.info(
"Creating new permission '%s' on view '%s'",
perm_name, dag_id
)
dag_perm = self.add_permission_view_menu(perm_name, dag_id)
return dag_perm
def _revoke_stale_permissions(dag_view):
existing_dag_perms = self.find_permissions_view_menu(dag_view)
for perm in existing_dag_perms:
non_admin_roles = [role for role in perm.role
if role.name != 'Admin']
for role in non_admin_roles:
target_perms_for_role = access_control.get(role.name, {})
if perm.permission.name not in target_perms_for_role:
self.log.info(
"Revoking '%s' on DAG '%s' for role '%s'",
perm.permission, dag_id, role.name
)
self.del_permission_role(role, perm)
dag_view = self.find_view_menu(dag_id)
if dag_view:
_revoke_stale_permissions(dag_view)
for rolename, perms in access_control.items():
role = self.find_role(rolename)
if not role:
raise AirflowException(
"The access_control mapping for DAG '{}' includes a role "
"named '{}', but that role does not exist".format(
dag_id,
rolename))
perms = set(perms)
invalid_perms = perms - self.DAG_PERMS
if invalid_perms:
raise AirflowException(
"The access_control map for DAG '{}' includes the following "
"invalid permissions: {}; The set of valid permissions "
"is: {}".format(dag_id,
(perms - self.DAG_PERMS),
self.DAG_PERMS))
for perm_name in perms:
dag_perm = _get_or_create_dag_permission(perm_name)
self.add_permission_role(role, dag_perm) | airflow/www/security.py |
apache/airflow | AirflowSecurityManager.create_perm_vm_for_all_dag | def create_perm_vm_for_all_dag(self):
for dag_vm in self.DAG_VMS:
for perm in self.DAG_PERMS:
self._merge_perm(permission_name=perm,
view_menu_name=dag_vm) | Create perm-vm if not exist and insert into FAB security model for all-dags. | def create_perm_vm_for_all_dag(self):
"""
Create perm-vm if not exist and insert into FAB security model for all-dags.
"""
# create perm for global logical dag
for dag_vm in self.DAG_VMS:
for perm in self.DAG_PERMS:
self._merge_perm(permission_name=perm,
view_menu_name=dag_vm) | airflow/www/security.py |
apache/airflow | get_fernet | def get_fernet():
global _fernet
log = LoggingMixin().log
if _fernet:
return _fernet
try:
from cryptography.fernet import Fernet, MultiFernet, InvalidToken
global InvalidFernetToken
InvalidFernetToken = InvalidToken
except BuiltinImportError:
log.warning(
"cryptography not found - values will not be stored encrypted."
)
_fernet = NullFernet()
return _fernet
try:
fernet_key = configuration.conf.get('core', 'FERNET_KEY')
if not fernet_key:
log.warning(
"empty cryptography key - values will not be stored encrypted."
)
_fernet = NullFernet()
else:
_fernet = MultiFernet([
Fernet(fernet_part.encode('utf-8'))
for fernet_part in fernet_key.split(',')
])
_fernet.is_encrypted = True
except (ValueError, TypeError) as ve:
raise AirflowException("Could not create Fernet object: {}".format(ve))
return _fernet | Deferred load of Fernet key. This function could fail either because Cryptography is not installed or because the Fernet key is invalid. | def get_fernet():
"""
Deferred load of Fernet key.
This function could fail either because Cryptography is not installed
or because the Fernet key is invalid.
:return: Fernet object
:raises: airflow.exceptions.AirflowException if there's a problem trying to load Fernet
"""
global _fernet
log = LoggingMixin().log
if _fernet:
return _fernet
try:
from cryptography.fernet import Fernet, MultiFernet, InvalidToken
global InvalidFernetToken
InvalidFernetToken = InvalidToken
except BuiltinImportError:
log.warning(
"cryptography not found - values will not be stored encrypted."
)
_fernet = NullFernet()
return _fernet
try:
fernet_key = configuration.conf.get('core', 'FERNET_KEY')
if not fernet_key:
log.warning(
"empty cryptography key - values will not be stored encrypted."
)
_fernet = NullFernet()
else:
_fernet = MultiFernet([
Fernet(fernet_part.encode('utf-8'))
for fernet_part in fernet_key.split(',')
])
_fernet.is_encrypted = True
except (ValueError, TypeError) as ve:
raise AirflowException("Could not create Fernet object: {}".format(ve))
return _fernet | airflow/models/crypto.py |
apache/airflow | AwsGlueCatalogPartitionSensor.poke | def poke(self, context):
if '.' in self.table_name:
self.database_name, self.table_name = self.table_name.split('.')
self.log.info(
'Poking for table %s. %s, expression %s', self.database_name, self.table_name, self.expression
)
return self.get_hook().check_for_partition(
self.database_name, self.table_name, self.expression) | Checks for existence of the partition in the AWS Glue Catalog table | def poke(self, context):
"""
Checks for existence of the partition in the AWS Glue Catalog table
"""
if '.' in self.table_name:
self.database_name, self.table_name = self.table_name.split('.')
self.log.info(
'Poking for table %s. %s, expression %s', self.database_name, self.table_name, self.expression
)
return self.get_hook().check_for_partition(
self.database_name, self.table_name, self.expression) | airflow/contrib/sensors/aws_glue_catalog_partition_sensor.py |
apache/airflow | AwsGlueCatalogPartitionSensor.get_hook | def get_hook(self):
if not hasattr(self, 'hook'):
from airflow.contrib.hooks.aws_glue_catalog_hook import AwsGlueCatalogHook
self.hook = AwsGlueCatalogHook(
aws_conn_id=self.aws_conn_id,
region_name=self.region_name)
return self.hook | Gets the AwsGlueCatalogHook | def get_hook(self):
"""
Gets the AwsGlueCatalogHook
"""
if not hasattr(self, 'hook'):
from airflow.contrib.hooks.aws_glue_catalog_hook import AwsGlueCatalogHook
self.hook = AwsGlueCatalogHook(
aws_conn_id=self.aws_conn_id,
region_name=self.region_name)
return self.hook | airflow/contrib/sensors/aws_glue_catalog_partition_sensor.py |
apache/airflow | SQSSensor.poke | def poke(self, context):
sqs_hook = SQSHook(aws_conn_id=self.aws_conn_id)
sqs_conn = sqs_hook.get_conn()
self.log.info('SQSSensor checking for message on queue: %s', self.sqs_queue)
messages = sqs_conn.receive_message(QueueUrl=self.sqs_queue,
MaxNumberOfMessages=self.max_messages,
WaitTimeSeconds=self.wait_time_seconds)
self.log.info("reveived message %s", str(messages))
if 'Messages' in messages and len(messages['Messages']) > 0:
entries = [{'Id': message['MessageId'], 'ReceiptHandle': message['ReceiptHandle']}
for message in messages['Messages']]
result = sqs_conn.delete_message_batch(QueueUrl=self.sqs_queue,
Entries=entries)
if 'Successful' in result:
context['ti'].xcom_push(key='messages', value=messages)
return True
else:
raise AirflowException(
'Delete SQS Messages failed ' + str(result) + ' for messages ' + str(messages))
return False | Check for message on subscribed queue and write to xcom the message with key ``messages`` | def poke(self, context):
"""
Check for message on subscribed queue and write to xcom the message with key ``messages``
:param context: the context object
:type context: dict
:return: ``True`` if message is available or ``False``
"""
sqs_hook = SQSHook(aws_conn_id=self.aws_conn_id)
sqs_conn = sqs_hook.get_conn()
self.log.info('SQSSensor checking for message on queue: %s', self.sqs_queue)
messages = sqs_conn.receive_message(QueueUrl=self.sqs_queue,
MaxNumberOfMessages=self.max_messages,
WaitTimeSeconds=self.wait_time_seconds)
self.log.info("reveived message %s", str(messages))
if 'Messages' in messages and len(messages['Messages']) > 0:
entries = [{'Id': message['MessageId'], 'ReceiptHandle': message['ReceiptHandle']}
for message in messages['Messages']]
result = sqs_conn.delete_message_batch(QueueUrl=self.sqs_queue,
Entries=entries)
if 'Successful' in result:
context['ti'].xcom_push(key='messages', value=messages)
return True
else:
raise AirflowException(
'Delete SQS Messages failed ' + str(result) + ' for messages ' + str(messages))
return False | airflow/contrib/sensors/aws_sqs_sensor.py |
apache/airflow | WebHDFSHook.get_conn | def get_conn(self):
connections = self.get_connections(self.webhdfs_conn_id)
for connection in connections:
try:
self.log.debug('Trying namenode %s', connection.host)
client = self._get_client(connection)
client.status('/')
self.log.debug('Using namenode %s for hook', connection.host)
return client
except HdfsError as hdfs_error:
self.log.debug('Read operation on namenode %s failed with error: %s',
connection.host, hdfs_error)
hosts = [connection.host for connection in connections]
error_message = 'Read operations failed on the namenodes below:\n{hosts}'.format(
hosts='\n'.join(hosts))
raise AirflowWebHDFSHookException(error_message) | Establishes a connection depending on the security mode set via config or environment variable. | def get_conn(self):
"""
Establishes a connection depending on the security mode set via config or environment variable.
:return: a hdfscli InsecureClient or KerberosClient object.
:rtype: hdfs.InsecureClient or hdfs.ext.kerberos.KerberosClient
"""
connections = self.get_connections(self.webhdfs_conn_id)
for connection in connections:
try:
self.log.debug('Trying namenode %s', connection.host)
client = self._get_client(connection)
client.status('/')
self.log.debug('Using namenode %s for hook', connection.host)
return client
except HdfsError as hdfs_error:
self.log.debug('Read operation on namenode %s failed with error: %s',
connection.host, hdfs_error)
hosts = [connection.host for connection in connections]
error_message = 'Read operations failed on the namenodes below:\n{hosts}'.format(
hosts='\n'.join(hosts))
raise AirflowWebHDFSHookException(error_message) | airflow/hooks/webhdfs_hook.py |
apache/airflow | WebHDFSHook.check_for_path | def check_for_path(self, hdfs_path):
conn = self.get_conn()
status = conn.status(hdfs_path, strict=False)
return bool(status) | Check for the existence of a path in HDFS by querying FileStatus. | def check_for_path(self, hdfs_path):
"""
Check for the existence of a path in HDFS by querying FileStatus.
:param hdfs_path: The path to check.
:type hdfs_path: str
:return: True if the path exists and False if not.
:rtype: bool
"""
conn = self.get_conn()
status = conn.status(hdfs_path, strict=False)
return bool(status) | airflow/hooks/webhdfs_hook.py |
apache/airflow | WebHDFSHook.load_file | def load_file(self, source, destination, overwrite=True, parallelism=1, **kwargs):
rconn = self.get_conn()
conn.upload(hdfs_path=destination,
local_path=source,
overwrite=overwrite,
n_threads=parallelism,
**kwargs)
self.log.debug("Uploaded file %s to %s", source, destination) | r""" Uploads a file to HDFS. | def load_file(self, source, destination, overwrite=True, parallelism=1, **kwargs):
r"""
Uploads a file to HDFS.
:param source: Local path to file or folder.
If it's a folder, all the files inside of it will be uploaded.
.. note:: This implies that folders empty of files will not be created remotely.
:type source: str
:param destination: PTarget HDFS path.
If it already exists and is a directory, files will be uploaded inside.
:type destination: str
:param overwrite: Overwrite any existing file or directory.
:type overwrite: bool
:param parallelism: Number of threads to use for parallelization.
A value of `0` (or negative) uses as many threads as there are files.
:type parallelism: int
:param \**kwargs: Keyword arguments forwarded to :meth:`hdfs.client.Client.upload`.
"""
conn = self.get_conn()
conn.upload(hdfs_path=destination,
local_path=source,
overwrite=overwrite,
n_threads=parallelism,
**kwargs)
self.log.debug("Uploaded file %s to %s", source, destination) | airflow/hooks/webhdfs_hook.py |
apache/airflow | PinotDbApiHook.get_conn | def get_conn(self):
conn = self.get_connection(self.pinot_broker_conn_id)
pinot_broker_conn = connect(
host=conn.host,
port=conn.port,
path=conn.extra_dejson.get('endpoint', '/pql'),
scheme=conn.extra_dejson.get('schema', 'http')
)
self.log.info('Get the connection to pinot '
'broker on {host}'.format(host=conn.host))
return pinot_broker_conn | Establish a connection to pinot broker through pinot dbqpi. | def get_conn(self):
"""
Establish a connection to pinot broker through pinot dbqpi.
"""
conn = self.get_connection(self.pinot_broker_conn_id)
pinot_broker_conn = connect(
host=conn.host,
port=conn.port,
path=conn.extra_dejson.get('endpoint', '/pql'),
scheme=conn.extra_dejson.get('schema', 'http')
)
self.log.info('Get the connection to pinot '
'broker on {host}'.format(host=conn.host))
return pinot_broker_conn | airflow/contrib/hooks/pinot_hook.py |
apache/airflow | PinotDbApiHook.get_uri | def get_uri(self):
conn = self.get_connection(getattr(self, self.conn_name_attr))
host = conn.host
if conn.port is not None:
host += ':{port}'.format(port=conn.port)
conn_type = 'http' if not conn.conn_type else conn.conn_type
endpoint = conn.extra_dejson.get('endpoint', 'pql')
return '{conn_type}://{host}/{endpoint}'.format(
conn_type=conn_type, host=host, endpoint=endpoint) | Get the connection uri for pinot broker. e.g: | def get_uri(self):
"""
Get the connection uri for pinot broker.
e.g: http://localhost:9000/pql
"""
conn = self.get_connection(getattr(self, self.conn_name_attr))
host = conn.host
if conn.port is not None:
host += ':{port}'.format(port=conn.port)
conn_type = 'http' if not conn.conn_type else conn.conn_type
endpoint = conn.extra_dejson.get('endpoint', 'pql')
return '{conn_type}://{host}/{endpoint}'.format(
conn_type=conn_type, host=host, endpoint=endpoint) | airflow/contrib/hooks/pinot_hook.py |
apache/airflow | TransferJobPreprocessor._convert_date_to_dict | def _convert_date_to_dict(field_date):
return {DAY: field_date.day, MONTH: field_date.month, YEAR: field_date.year} | Convert native python ``datetime.date`` object to a format supported by the API | def _convert_date_to_dict(field_date):
"""
Convert native python ``datetime.date`` object to a format supported by the API
"""
return {DAY: field_date.day, MONTH: field_date.month, YEAR: field_date.year} | airflow/contrib/operators/gcp_transfer_operator.py |
apache/airflow | TransferJobPreprocessor._convert_time_to_dict | def _convert_time_to_dict(time):
return {HOURS: time.hour, MINUTES: time.minute, SECONDS: time.second} | Convert native python ``datetime.time`` object to a format supported by the API | def _convert_time_to_dict(time):
"""
Convert native python ``datetime.time`` object to a format supported by the API
"""
return {HOURS: time.hour, MINUTES: time.minute, SECONDS: time.second} | airflow/contrib/operators/gcp_transfer_operator.py |
apache/airflow | DbApiHook.get_pandas_df | def get_pandas_df(self, sql, parameters=None):
import pandas.io.sql as psql
with closing(self.get_conn()) as conn:
return psql.read_sql(sql, con=conn, params=parameters) | Executes the sql and returns a pandas dataframe | def get_pandas_df(self, sql, parameters=None):
"""
Executes the sql and returns a pandas dataframe
:param sql: the sql statement to be executed (str) or a list of
sql statements to execute
:type sql: str or list
:param parameters: The parameters to render the SQL query with.
:type parameters: mapping or iterable
"""
import pandas.io.sql as psql
with closing(self.get_conn()) as conn:
return psql.read_sql(sql, con=conn, params=parameters) | airflow/hooks/dbapi_hook.py |
apache/airflow | DbApiHook.run | def run(self, sql, autocommit=False, parameters=None):
if isinstance(sql, basestring):
sql = [sql]
with closing(self.get_conn()) as conn:
if self.supports_autocommit:
self.set_autocommit(conn, autocommit)
with closing(conn.cursor()) as cur:
for s in sql:
if parameters is not None:
self.log.info("{} with parameters {}".format(s, parameters))
cur.execute(s, parameters)
else:
self.log.info(s)
cur.execute(s)
if not self.get_autocommit(conn):
conn.commit() | Runs a command or a list of commands. Pass a list of sql statements to the sql parameter to get them to execute sequentially | def run(self, sql, autocommit=False, parameters=None):
"""
Runs a command or a list of commands. Pass a list of sql
statements to the sql parameter to get them to execute
sequentially
:param sql: the sql statement to be executed (str) or a list of
sql statements to execute
:type sql: str or list
:param autocommit: What to set the connection's autocommit setting to
before executing the query.
:type autocommit: bool
:param parameters: The parameters to render the SQL query with.
:type parameters: mapping or iterable
"""
if isinstance(sql, basestring):
sql = [sql]
with closing(self.get_conn()) as conn:
if self.supports_autocommit:
self.set_autocommit(conn, autocommit)
with closing(conn.cursor()) as cur:
for s in sql:
if parameters is not None:
self.log.info("{} with parameters {}".format(s, parameters))
cur.execute(s, parameters)
else:
self.log.info(s)
cur.execute(s)
# If autocommit was set to False for db that supports autocommit,
# or if db does not supports autocommit, we do a manual commit.
if not self.get_autocommit(conn):
conn.commit() | airflow/hooks/dbapi_hook.py |
apache/airflow | DbApiHook.set_autocommit | def set_autocommit(self, conn, autocommit):
if not self.supports_autocommit and autocommit:
self.log.warn(
("%s connection doesn't support "
"autocommit but autocommit activated."),
getattr(self, self.conn_name_attr))
conn.autocommit = autocommit | Sets the autocommit flag on the connection | def set_autocommit(self, conn, autocommit):
"""
Sets the autocommit flag on the connection
"""
if not self.supports_autocommit and autocommit:
self.log.warn(
("%s connection doesn't support "
"autocommit but autocommit activated."),
getattr(self, self.conn_name_attr))
conn.autocommit = autocommit | airflow/hooks/dbapi_hook.py |
apache/airflow | DbApiHook.insert_rows | def insert_rows(self, table, rows, target_fields=None, commit_every=1000,
replace=False):
if target_fields:
target_fields = ", ".join(target_fields)
target_fields = "({})".format(target_fields)
else:
target_fields = ''
i = 0
with closing(self.get_conn()) as conn:
if self.supports_autocommit:
self.set_autocommit(conn, False)
conn.commit()
with closing(conn.cursor()) as cur:
for i, row in enumerate(rows, 1):
lst = []
for cell in row:
lst.append(self._serialize_cell(cell, conn))
values = tuple(lst)
placeholders = ["%s", ] * len(values)
if not replace:
sql = "INSERT INTO "
else:
sql = "REPLACE INTO "
sql += "{0} {1} VALUES ({2})".format(
table,
target_fields,
",".join(placeholders))
cur.execute(sql, values)
if commit_every and i % commit_every == 0:
conn.commit()
self.log.info(
"Loaded %s into %s rows so far", i, table
)
conn.commit()
self.log.info("Done loading. Loaded a total of %s rows", i) | A generic way to insert a set of tuples into a table, a new transaction is created every commit_every rows | def insert_rows(self, table, rows, target_fields=None, commit_every=1000,
replace=False):
"""
A generic way to insert a set of tuples into a table,
a new transaction is created every commit_every rows
:param table: Name of the target table
:type table: str
:param rows: The rows to insert into the table
:type rows: iterable of tuples
:param target_fields: The names of the columns to fill in the table
:type target_fields: iterable of strings
:param commit_every: The maximum number of rows to insert in one
transaction. Set to 0 to insert all rows in one transaction.
:type commit_every: int
:param replace: Whether to replace instead of insert
:type replace: bool
"""
if target_fields:
target_fields = ", ".join(target_fields)
target_fields = "({})".format(target_fields)
else:
target_fields = ''
i = 0
with closing(self.get_conn()) as conn:
if self.supports_autocommit:
self.set_autocommit(conn, False)
conn.commit()
with closing(conn.cursor()) as cur:
for i, row in enumerate(rows, 1):
lst = []
for cell in row:
lst.append(self._serialize_cell(cell, conn))
values = tuple(lst)
placeholders = ["%s", ] * len(values)
if not replace:
sql = "INSERT INTO "
else:
sql = "REPLACE INTO "
sql += "{0} {1} VALUES ({2})".format(
table,
target_fields,
",".join(placeholders))
cur.execute(sql, values)
if commit_every and i % commit_every == 0:
conn.commit()
self.log.info(
"Loaded %s into %s rows so far", i, table
)
conn.commit()
self.log.info("Done loading. Loaded a total of %s rows", i) | airflow/hooks/dbapi_hook.py |
apache/airflow | Airflow.health | def health(self, session=None):
BJ = jobs.BaseJob
payload = {}
scheduler_health_check_threshold = timedelta(seconds=conf.getint('scheduler',
'scheduler_health_check_threshold'
))
latest_scheduler_heartbeat = None
payload['metadatabase'] = {'status': 'healthy'}
try:
latest_scheduler_heartbeat = session.query(func.max(BJ.latest_heartbeat)).\
filter(BJ.state == 'running', BJ.job_type == 'SchedulerJob').\
scalar()
except Exception:
payload['metadatabase']['status'] = 'unhealthy'
if not latest_scheduler_heartbeat:
scheduler_status = 'unhealthy'
else:
if timezone.utcnow() - latest_scheduler_heartbeat <= scheduler_health_check_threshold:
scheduler_status = 'healthy'
else:
scheduler_status = 'unhealthy'
payload['scheduler'] = {'status': scheduler_status,
'latest_scheduler_heartbeat': str(latest_scheduler_heartbeat)}
return wwwutils.json_response(payload) | An endpoint helping check the health status of the Airflow instance, including metadatabase and scheduler. | def health(self, session=None):
"""
An endpoint helping check the health status of the Airflow instance,
including metadatabase and scheduler.
"""
BJ = jobs.BaseJob
payload = {}
scheduler_health_check_threshold = timedelta(seconds=conf.getint('scheduler',
'scheduler_health_check_threshold'
))
latest_scheduler_heartbeat = None
payload['metadatabase'] = {'status': 'healthy'}
try:
latest_scheduler_heartbeat = session.query(func.max(BJ.latest_heartbeat)).\
filter(BJ.state == 'running', BJ.job_type == 'SchedulerJob').\
scalar()
except Exception:
payload['metadatabase']['status'] = 'unhealthy'
if not latest_scheduler_heartbeat:
scheduler_status = 'unhealthy'
else:
if timezone.utcnow() - latest_scheduler_heartbeat <= scheduler_health_check_threshold:
scheduler_status = 'healthy'
else:
scheduler_status = 'unhealthy'
payload['scheduler'] = {'status': scheduler_status,
'latest_scheduler_heartbeat': str(latest_scheduler_heartbeat)}
return wwwutils.json_response(payload) | airflow/www/views.py |
apache/airflow | Airflow.extra_links | def extra_links(self):
dag_id = request.args.get('dag_id')
task_id = request.args.get('task_id')
execution_date = request.args.get('execution_date')
link_name = request.args.get('link_name')
dttm = airflow.utils.timezone.parse(execution_date)
dag = dagbag.get_dag(dag_id)
if not dag or task_id not in dag.task_ids:
response = jsonify(
{'url': None,
'error': "can't find dag {dag} or task_id {task_id}".format(
dag=dag,
task_id=task_id
)}
)
response.status_code = 404
return response
task = dag.get_task(task_id)
try:
url = task.get_extra_links(dttm, link_name)
except ValueError as err:
response = jsonify({'url': None, 'error': str(err)})
response.status_code = 404
return response
if url:
response = jsonify({'error': None, 'url': url})
response.status_code = 200
return response
else:
response = jsonify(
{'url': None, 'error': 'No URL found for {dest}'.format(dest=link_name)})
response.status_code = 404
return response | A restful endpoint that returns external links for a given Operator It queries the operator that sent the request for the links it wishes to provide for a given external link name. | def extra_links(self):
"""
A restful endpoint that returns external links for a given Operator
It queries the operator that sent the request for the links it wishes
to provide for a given external link name.
API: GET
Args: dag_id: The id of the dag containing the task in question
task_id: The id of the task in question
execution_date: The date of execution of the task
link_name: The name of the link reference to find the actual URL for
Returns:
200: {url: <url of link>, error: None} - returned when there was no problem
finding the URL
404: {url: None, error: <error message>} - returned when the operator does
not return a URL
"""
dag_id = request.args.get('dag_id')
task_id = request.args.get('task_id')
execution_date = request.args.get('execution_date')
link_name = request.args.get('link_name')
dttm = airflow.utils.timezone.parse(execution_date)
dag = dagbag.get_dag(dag_id)
if not dag or task_id not in dag.task_ids:
response = jsonify(
{'url': None,
'error': "can't find dag {dag} or task_id {task_id}".format(
dag=dag,
task_id=task_id
)}
)
response.status_code = 404
return response
task = dag.get_task(task_id)
try:
url = task.get_extra_links(dttm, link_name)
except ValueError as err:
response = jsonify({'url': None, 'error': str(err)})
response.status_code = 404
return response
if url:
response = jsonify({'error': None, 'url': url})
response.status_code = 200
return response
else:
response = jsonify(
{'url': None, 'error': 'No URL found for {dest}'.format(dest=link_name)})
response.status_code = 404
return response | airflow/www/views.py |
apache/airflow | CloudantHook.get_conn | def get_conn(self):
conn = self.get_connection(self.cloudant_conn_id)
self._validate_connection(conn)
cloudant_session = cloudant(user=conn.login, passwd=conn.password, account=conn.host)
return cloudant_session | Opens a connection to the cloudant service and closes it automatically if used as context manager. | def get_conn(self):
"""
Opens a connection to the cloudant service and closes it automatically if used as context manager.
.. note::
In the connection form:
- 'host' equals the 'Account' (optional)
- 'login' equals the 'Username (or API Key)' (required)
- 'password' equals the 'Password' (required)
:return: an authorized cloudant session context manager object.
:rtype: cloudant
"""
conn = self.get_connection(self.cloudant_conn_id)
self._validate_connection(conn)
cloudant_session = cloudant(user=conn.login, passwd=conn.password, account=conn.host)
return cloudant_session | airflow/contrib/hooks/cloudant_hook.py |
apache/airflow | SlackWebhookOperator.execute | def execute(self, context):
self.hook = SlackWebhookHook(
self.http_conn_id,
self.webhook_token,
self.message,
self.attachments,
self.channel,
self.username,
self.icon_emoji,
self.link_names,
self.proxy
)
self.hook.execute() | Call the SlackWebhookHook to post the provided Slack message | def execute(self, context):
"""
Call the SlackWebhookHook to post the provided Slack message
"""
self.hook = SlackWebhookHook(
self.http_conn_id,
self.webhook_token,
self.message,
self.attachments,
self.channel,
self.username,
self.icon_emoji,
self.link_names,
self.proxy
)
self.hook.execute() | airflow/contrib/operators/slack_webhook_operator.py |
apache/airflow | GoogleCloudBaseHook.catch_http_exception | def catch_http_exception(func):
@functools.wraps(func)
def wrapper_decorator(self, *args, **kwargs):
try:
return func(self, *args, **kwargs)
except GoogleAPICallError as e:
if isinstance(e, AlreadyExists):
raise e
else:
self.log.error('The request failed:\n%s', str(e))
raise AirflowException(e)
except RetryError as e:
self.log.error('The request failed due to a retryable error and retry attempts failed.')
raise AirflowException(e)
except ValueError as e:
self.log.error('The request failed, the parameters are invalid.')
raise AirflowException(e)
except HttpError as e:
self.log.error('The request failed:\n%s', str(e))
raise AirflowException(e)
return wrapper_decorator | Function decorator that intercepts HTTP Errors and raises AirflowException with more informative message. | def catch_http_exception(func):
"""
Function decorator that intercepts HTTP Errors and raises AirflowException
with more informative message.
"""
@functools.wraps(func)
def wrapper_decorator(self, *args, **kwargs):
try:
return func(self, *args, **kwargs)
except GoogleAPICallError as e:
if isinstance(e, AlreadyExists):
raise e
else:
self.log.error('The request failed:\n%s', str(e))
raise AirflowException(e)
except RetryError as e:
self.log.error('The request failed due to a retryable error and retry attempts failed.')
raise AirflowException(e)
except ValueError as e:
self.log.error('The request failed, the parameters are invalid.')
raise AirflowException(e)
except HttpError as e:
self.log.error('The request failed:\n%s', str(e))
raise AirflowException(e)
return wrapper_decorator | airflow/contrib/hooks/gcp_api_base_hook.py |
apache/airflow | State.unfinished | def unfinished(cls):
return [
cls.NONE,
cls.SCHEDULED,
cls.QUEUED,
cls.RUNNING,
cls.SHUTDOWN,
cls.UP_FOR_RETRY,
cls.UP_FOR_RESCHEDULE
] | A list of states indicating that a task either has not completed a run or has not even started. | def unfinished(cls):
"""
A list of states indicating that a task either has not completed
a run or has not even started.
"""
return [
cls.NONE,
cls.SCHEDULED,
cls.QUEUED,
cls.RUNNING,
cls.SHUTDOWN,
cls.UP_FOR_RETRY,
cls.UP_FOR_RESCHEDULE
] | airflow/utils/state.py |
apache/airflow | SparkSqlHook._prepare_command | def _prepare_command(self, cmd):
connection_cmd = ["spark-sql"]
if self._conf:
for conf_el in self._conf.split(","):
connection_cmd += ["--conf", conf_el]
if self._total_executor_cores:
connection_cmd += ["--total-executor-cores", str(self._total_executor_cores)]
if self._executor_cores:
connection_cmd += ["--executor-cores", str(self._executor_cores)]
if self._executor_memory:
connection_cmd += ["--executor-memory", self._executor_memory]
if self._keytab:
connection_cmd += ["--keytab", self._keytab]
if self._principal:
connection_cmd += ["--principal", self._principal]
if self._num_executors:
connection_cmd += ["--num-executors", str(self._num_executors)]
if self._sql:
sql = self._sql.strip()
if sql.endswith(".sql") or sql.endswith(".hql"):
connection_cmd += ["-f", sql]
else:
connection_cmd += ["-e", sql]
if self._master:
connection_cmd += ["--master", self._master]
if self._name:
connection_cmd += ["--name", self._name]
if self._verbose:
connection_cmd += ["--verbose"]
if self._yarn_queue:
connection_cmd += ["--queue", self._yarn_queue]
connection_cmd += cmd
self.log.debug("Spark-Sql cmd: %s", connection_cmd)
return connection_cmd | Construct the spark-sql command to execute. Verbose output is enabled as default. | def _prepare_command(self, cmd):
"""
Construct the spark-sql command to execute. Verbose output is enabled
as default.
:param cmd: command to append to the spark-sql command
:type cmd: str
:return: full command to be executed
"""
connection_cmd = ["spark-sql"]
if self._conf:
for conf_el in self._conf.split(","):
connection_cmd += ["--conf", conf_el]
if self._total_executor_cores:
connection_cmd += ["--total-executor-cores", str(self._total_executor_cores)]
if self._executor_cores:
connection_cmd += ["--executor-cores", str(self._executor_cores)]
if self._executor_memory:
connection_cmd += ["--executor-memory", self._executor_memory]
if self._keytab:
connection_cmd += ["--keytab", self._keytab]
if self._principal:
connection_cmd += ["--principal", self._principal]
if self._num_executors:
connection_cmd += ["--num-executors", str(self._num_executors)]
if self._sql:
sql = self._sql.strip()
if sql.endswith(".sql") or sql.endswith(".hql"):
connection_cmd += ["-f", sql]
else:
connection_cmd += ["-e", sql]
if self._master:
connection_cmd += ["--master", self._master]
if self._name:
connection_cmd += ["--name", self._name]
if self._verbose:
connection_cmd += ["--verbose"]
if self._yarn_queue:
connection_cmd += ["--queue", self._yarn_queue]
connection_cmd += cmd
self.log.debug("Spark-Sql cmd: %s", connection_cmd)
return connection_cmd | airflow/contrib/hooks/spark_sql_hook.py |
Azure/azure-sdk-for-python | Message.schedule | def schedule(self, schedule_time):
if not self.properties.message_id:
self.properties.message_id = str(uuid.uuid4())
if not self.message.annotations:
self.message.annotations = {}
self.message.annotations[types.AMQPSymbol(self._x_OPT_SCHEDULED_ENQUEUE_TIME)] = schedule_time | Add a specific enqueue time to the message. | def schedule(self, schedule_time):
"""Add a specific enqueue time to the message.
:param schedule_time: The scheduled time to enqueue the message.
:type schedule_time: ~datetime.datetime
"""
if not self.properties.message_id:
self.properties.message_id = str(uuid.uuid4())
if not self.message.annotations:
self.message.annotations = {}
self.message.annotations[types.AMQPSymbol(self._x_OPT_SCHEDULED_ENQUEUE_TIME)] = schedule_time | azure-servicebus/azure/servicebus/common/message.py |
Azure/azure-sdk-for-python | VpnSitesConfigurationOperations.download | def download(
self, resource_group_name, virtual_wan_name, vpn_sites=None, output_blob_sas_url=None, custom_headers=None, raw=False, polling=True, **operation_config):
raw_result = self._download_initial(
resource_group_name=resource_group_name,
virtual_wan_name=virtual_wan_name,
vpn_sites=vpn_sites,
output_blob_sas_url=output_blob_sas_url,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method) | Gives the sas-url to download the configurations for vpn-sites in a resource group. | def download(
self, resource_group_name, virtual_wan_name, vpn_sites=None, output_blob_sas_url=None, custom_headers=None, raw=False, polling=True, **operation_config):
"""Gives the sas-url to download the configurations for vpn-sites in a
resource group.
:param resource_group_name: The resource group name.
:type resource_group_name: str
:param virtual_wan_name: The name of the VirtualWAN for which
configuration of all vpn-sites is needed.
:type virtual_wan_name: str
:param vpn_sites: List of resource-ids of the vpn-sites for which
config is to be downloaded.
:type vpn_sites:
list[~azure.mgmt.network.v2018_04_01.models.SubResource]
:param output_blob_sas_url: The sas-url to download the configurations
for vpn-sites
:type output_blob_sas_url: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: The poller return type is ClientRawResponse, the
direct response alongside the deserialized response
:param polling: True for ARMPolling, False for no polling, or a
polling object for personal polling strategy
:return: An instance of LROPoller that returns None or
ClientRawResponse<None> if raw==True
:rtype: ~msrestazure.azure_operation.AzureOperationPoller[None] or
~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[None]]
:raises:
:class:`ErrorException<azure.mgmt.network.v2018_04_01.models.ErrorException>`
"""
raw_result = self._download_initial(
resource_group_name=resource_group_name,
virtual_wan_name=virtual_wan_name,
vpn_sites=vpn_sites,
output_blob_sas_url=output_blob_sas_url,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method) | azure-mgmt-network/azure/mgmt/network/v2018_04_01/operations/vpn_sites_configuration_operations.py |
Azure/azure-sdk-for-python | guess_service_info_from_path | def guess_service_info_from_path(spec_path):
spec_path = spec_path.lower()
spec_path = spec_path[spec_path.index("specification"):]
split_spec_path = spec_path.split("/")
rp_name = split_spec_path[1]
is_arm = split_spec_path[2] == "resource-manager"
return {
"rp_name": rp_name,
"is_arm": is_arm
} | Guess Python Autorest options based on the spec path. Expected | def guess_service_info_from_path(spec_path):
"""Guess Python Autorest options based on the spec path.
Expected path:
specification/compute/resource-manager/readme.md
"""
spec_path = spec_path.lower()
spec_path = spec_path[spec_path.index("specification"):] # Might raise and it's ok
split_spec_path = spec_path.split("/")
rp_name = split_spec_path[1]
is_arm = split_spec_path[2] == "resource-manager"
return {
"rp_name": rp_name,
"is_arm": is_arm
} | scripts/build_sdk.py |
Azure/azure-sdk-for-python | PowerShellOperations.update_command | def update_command(
self, resource_group_name, node_name, session, pssession, custom_headers=None, raw=False, polling=True, **operation_config):
raw_result = self._update_command_initial(
resource_group_name=resource_group_name,
node_name=node_name,
session=session,
pssession=pssession,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
deserialized = self._deserialize('PowerShellCommandResults', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method) | Updates a running PowerShell command with more data. | def update_command(
self, resource_group_name, node_name, session, pssession, custom_headers=None, raw=False, polling=True, **operation_config):
"""Updates a running PowerShell command with more data.
:param resource_group_name: The resource group name uniquely
identifies the resource group within the user subscriptionId.
:type resource_group_name: str
:param node_name: The node name (256 characters maximum).
:type node_name: str
:param session: The sessionId from the user.
:type session: str
:param pssession: The PowerShell sessionId from the user.
:type pssession: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: The poller return type is ClientRawResponse, the
direct response alongside the deserialized response
:param polling: True for ARMPolling, False for no polling, or a
polling object for personal polling strategy
:return: An instance of LROPoller that returns
PowerShellCommandResults or
ClientRawResponse<PowerShellCommandResults> if raw==True
:rtype:
~msrestazure.azure_operation.AzureOperationPoller[~azure.mgmt.servermanager.models.PowerShellCommandResults]
or
~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[~azure.mgmt.servermanager.models.PowerShellCommandResults]]
:raises:
:class:`ErrorException<azure.mgmt.servermanager.models.ErrorException>`
"""
raw_result = self._update_command_initial(
resource_group_name=resource_group_name,
node_name=node_name,
session=session,
pssession=pssession,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
deserialized = self._deserialize('PowerShellCommandResults', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method) | azure-mgmt-servermanager/azure/mgmt/servermanager/operations/power_shell_operations.py |
Azure/azure-sdk-for-python | ApplicationDefinitionsOperations.delete_by_id | def delete_by_id(
self, application_definition_id, custom_headers=None, raw=False, polling=True, **operation_config):
raw_result = self._delete_by_id_initial(
application_definition_id=application_definition_id,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method) | Deletes the managed application definition. | def delete_by_id(
self, application_definition_id, custom_headers=None, raw=False, polling=True, **operation_config):
"""Deletes the managed application definition.
:param application_definition_id: The fully qualified ID of the
managed application definition, including the managed application name
and the managed application definition resource type. Use the format,
/subscriptions/{guid}/resourceGroups/{resource-group-name}/Microsoft.Solutions/applicationDefinitions/{applicationDefinition-name}
:type application_definition_id: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: The poller return type is ClientRawResponse, the
direct response alongside the deserialized response
:param polling: True for ARMPolling, False for no polling, or a
polling object for personal polling strategy
:return: An instance of LROPoller that returns None or
ClientRawResponse<None> if raw==True
:rtype: ~msrestazure.azure_operation.AzureOperationPoller[None] or
~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[None]]
:raises:
:class:`ErrorResponseException<azure.mgmt.resource.managedapplications.models.ErrorResponseException>`
"""
raw_result = self._delete_by_id_initial(
application_definition_id=application_definition_id,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method) | azure-mgmt-resource/azure/mgmt/resource/managedapplications/operations/application_definitions_operations.py |
Azure/azure-sdk-for-python | ApplicationDefinitionsOperations.create_or_update_by_id | def create_or_update_by_id(
self, application_definition_id, parameters, custom_headers=None, raw=False, polling=True, **operation_config):
raw_result = self._create_or_update_by_id_initial(
application_definition_id=application_definition_id,
parameters=parameters,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
deserialized = self._deserialize('ApplicationDefinition', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method) | Creates a new managed application definition. | def create_or_update_by_id(
self, application_definition_id, parameters, custom_headers=None, raw=False, polling=True, **operation_config):
"""Creates a new managed application definition.
:param application_definition_id: The fully qualified ID of the
managed application definition, including the managed application name
and the managed application definition resource type. Use the format,
/subscriptions/{guid}/resourceGroups/{resource-group-name}/Microsoft.Solutions/applicationDefinitions/{applicationDefinition-name}
:type application_definition_id: str
:param parameters: Parameters supplied to the create or update a
managed application definition.
:type parameters:
~azure.mgmt.resource.managedapplications.models.ApplicationDefinition
:param dict custom_headers: headers that will be added to the request
:param bool raw: The poller return type is ClientRawResponse, the
direct response alongside the deserialized response
:param polling: True for ARMPolling, False for no polling, or a
polling object for personal polling strategy
:return: An instance of LROPoller that returns ApplicationDefinition
or ClientRawResponse<ApplicationDefinition> if raw==True
:rtype:
~msrestazure.azure_operation.AzureOperationPoller[~azure.mgmt.resource.managedapplications.models.ApplicationDefinition]
or
~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[~azure.mgmt.resource.managedapplications.models.ApplicationDefinition]]
:raises:
:class:`ErrorResponseException<azure.mgmt.resource.managedapplications.models.ErrorResponseException>`
"""
raw_result = self._create_or_update_by_id_initial(
application_definition_id=application_definition_id,
parameters=parameters,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
deserialized = self._deserialize('ApplicationDefinition', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method) | azure-mgmt-resource/azure/mgmt/resource/managedapplications/operations/application_definitions_operations.py |
Azure/azure-sdk-for-python | _HTTPClient.get_uri | def get_uri(self, request):
protocol = request.protocol_override \
if request.protocol_override else self.protocol
protocol = protocol.lower()
port = HTTP_PORT if protocol == 'http' else HTTPS_PORT
return protocol + '://' + request.host + ':' + str(port) + request.path | Return the target uri for the request. | def get_uri(self, request):
''' Return the target uri for the request.'''
protocol = request.protocol_override \
if request.protocol_override else self.protocol
protocol = protocol.lower()
port = HTTP_PORT if protocol == 'http' else HTTPS_PORT
return protocol + '://' + request.host + ':' + str(port) + request.path | azure-servicebus/azure/servicebus/control_client/_http/httpclient.py |
Azure/azure-sdk-for-python | _HTTPClient.get_connection | def get_connection(self, request):
protocol = request.protocol_override \
if request.protocol_override else self.protocol
protocol = protocol.lower()
target_host = request.host
connection = _RequestsConnection(
target_host, protocol, self.request_session, self.timeout)
proxy_host = self.proxy_host
proxy_port = self.proxy_port
if self.proxy_host:
headers = None
if self.proxy_user and self.proxy_password:
auth = base64.b64encode("{0}:{1}".format(self.proxy_user, self.proxy_password).encode())
headers = {'Proxy-Authorization': 'Basic {0}'.format(auth.decode())}
connection.set_tunnel(proxy_host, int(proxy_port), headers)
return connection | Create connection for the request. | def get_connection(self, request):
''' Create connection for the request. '''
protocol = request.protocol_override \
if request.protocol_override else self.protocol
protocol = protocol.lower()
target_host = request.host
# target_port = HTTP_PORT if protocol == 'http' else HTTPS_PORT
connection = _RequestsConnection(
target_host, protocol, self.request_session, self.timeout)
proxy_host = self.proxy_host
proxy_port = self.proxy_port
if self.proxy_host:
headers = None
if self.proxy_user and self.proxy_password:
auth = base64.b64encode("{0}:{1}".format(self.proxy_user, self.proxy_password).encode())
headers = {'Proxy-Authorization': 'Basic {0}'.format(auth.decode())}
connection.set_tunnel(proxy_host, int(proxy_port), headers)
return connection | azure-servicebus/azure/servicebus/control_client/_http/httpclient.py |
Azure/azure-sdk-for-python | _HTTPClient.perform_request | def perform_request(self, request):
connection = self.get_connection(request)
try:
connection.putrequest(request.method, request.path)
self.send_request_headers(connection, request.headers)
self.send_request_body(connection, request.body)
if DEBUG_REQUESTS and request.body:
print('request:')
try:
print(request.body)
except:
pass
resp = connection.getresponse()
status = int(resp.status)
message = resp.reason
respheaders = resp.getheaders()
for i, value in enumerate(respheaders):
respheaders[i] = (value[0].lower(), value[1])
respbody = None
if resp.length is None:
respbody = resp.read()
elif resp.length > 0:
respbody = resp.read(resp.length)
if DEBUG_RESPONSES and respbody:
print('response:')
try:
print(respbody)
except:
pass
response = HTTPResponse(
status, resp.reason, respheaders, respbody)
if status == 307:
new_url = urlparse(dict(respheaders)['location'])
request.host = new_url.hostname
request.path = new_url.path
request.path, request.query = self._update_request_uri_query(request)
return self.perform_request(request)
if status >= 300:
raise HTTPError(status, message, respheaders, respbody)
return response
finally:
connection.close() | Sends request to cloud service server and return the response. | def perform_request(self, request):
''' Sends request to cloud service server and return the response. '''
connection = self.get_connection(request)
try:
connection.putrequest(request.method, request.path)
self.send_request_headers(connection, request.headers)
self.send_request_body(connection, request.body)
if DEBUG_REQUESTS and request.body:
print('request:')
try:
print(request.body)
except: # pylint: disable=bare-except
pass
resp = connection.getresponse()
status = int(resp.status)
message = resp.reason
respheaders = resp.getheaders()
# for consistency across platforms, make header names lowercase
for i, value in enumerate(respheaders):
respheaders[i] = (value[0].lower(), value[1])
respbody = None
if resp.length is None:
respbody = resp.read()
elif resp.length > 0:
respbody = resp.read(resp.length)
if DEBUG_RESPONSES and respbody:
print('response:')
try:
print(respbody)
except: # pylint: disable=bare-except
pass
response = HTTPResponse(
status, resp.reason, respheaders, respbody)
if status == 307:
new_url = urlparse(dict(respheaders)['location'])
request.host = new_url.hostname
request.path = new_url.path
request.path, request.query = self._update_request_uri_query(request)
return self.perform_request(request)
if status >= 300:
raise HTTPError(status, message, respheaders, respbody)
return response
finally:
connection.close() | azure-servicebus/azure/servicebus/control_client/_http/httpclient.py |
Azure/azure-sdk-for-python | ClustersOperations.execute_script_actions | def execute_script_actions(
self, resource_group_name, cluster_name, persist_on_success, script_actions=None, custom_headers=None, raw=False, polling=True, **operation_config):
raw_result = self._execute_script_actions_initial(
resource_group_name=resource_group_name,
cluster_name=cluster_name,
persist_on_success=persist_on_success,
script_actions=script_actions,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method) | Executes script actions on the specified HDInsight cluster. | def execute_script_actions(
self, resource_group_name, cluster_name, persist_on_success, script_actions=None, custom_headers=None, raw=False, polling=True, **operation_config):
"""Executes script actions on the specified HDInsight cluster.
:param resource_group_name: The name of the resource group.
:type resource_group_name: str
:param cluster_name: The name of the cluster.
:type cluster_name: str
:param persist_on_success: Gets or sets if the scripts needs to be
persisted.
:type persist_on_success: bool
:param script_actions: The list of run time script actions.
:type script_actions:
list[~azure.mgmt.hdinsight.models.RuntimeScriptAction]
:param dict custom_headers: headers that will be added to the request
:param bool raw: The poller return type is ClientRawResponse, the
direct response alongside the deserialized response
:param polling: True for ARMPolling, False for no polling, or a
polling object for personal polling strategy
:return: An instance of LROPoller that returns None or
ClientRawResponse<None> if raw==True
:rtype: ~msrestazure.azure_operation.AzureOperationPoller[None] or
~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[None]]
:raises:
:class:`ErrorResponseException<azure.mgmt.hdinsight.models.ErrorResponseException>`
"""
raw_result = self._execute_script_actions_initial(
resource_group_name=resource_group_name,
cluster_name=cluster_name,
persist_on_success=persist_on_success,
script_actions=script_actions,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method) | azure-mgmt-hdinsight/azure/mgmt/hdinsight/operations/clusters_operations.py |
Azure/azure-sdk-for-python | FrontDoorManagementClient.check_front_door_name_availability | def check_front_door_name_availability(
self, name, type, custom_headers=None, raw=False, **operation_config):
check_front_door_name_availability_input = models.CheckNameAvailabilityInput(name=name, type=type)
api_version = "2018-08-01"
url = self.check_front_door_name_availability.metadata['url']
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str')
header_parameters = {}
header_parameters['Accept'] = 'application/json'
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
body_content = self._serialize.body(check_front_door_name_availability_input, 'CheckNameAvailabilityInput')
request = self._client.post(url, query_parameters, header_parameters, body_content)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.ErrorResponseException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('CheckNameAvailabilityOutput', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized | Check the availability of a Front Door resource name. | def check_front_door_name_availability(
self, name, type, custom_headers=None, raw=False, **operation_config):
"""Check the availability of a Front Door resource name.
:param name: The resource name to validate.
:type name: str
:param type: The type of the resource whose name is to be validated.
Possible values include: 'Microsoft.Network/frontDoors',
'Microsoft.Network/frontDoors/frontendEndpoints'
:type type: str or ~azure.mgmt.frontdoor.models.ResourceType
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: CheckNameAvailabilityOutput or ClientRawResponse if raw=true
:rtype: ~azure.mgmt.frontdoor.models.CheckNameAvailabilityOutput or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`ErrorResponseException<azure.mgmt.frontdoor.models.ErrorResponseException>`
"""
check_front_door_name_availability_input = models.CheckNameAvailabilityInput(name=name, type=type)
api_version = "2018-08-01"
# Construct URL
url = self.check_front_door_name_availability.metadata['url']
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str')
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct body
body_content = self._serialize.body(check_front_door_name_availability_input, 'CheckNameAvailabilityInput')
# Construct and send request
request = self._client.post(url, query_parameters, header_parameters, body_content)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.ErrorResponseException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('CheckNameAvailabilityOutput', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized | azure-mgmt-frontdoor/azure/mgmt/frontdoor/front_door_management_client.py |
Azure/azure-sdk-for-python | VaultsOperations.purge_deleted | def purge_deleted(
self, vault_name, location, custom_headers=None, raw=False, polling=True, **operation_config):
raw_result = self._purge_deleted_initial(
vault_name=vault_name,
location=location,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method) | Permanently deletes the specified vault. aka Purges the deleted Azure key vault. | def purge_deleted(
self, vault_name, location, custom_headers=None, raw=False, polling=True, **operation_config):
"""Permanently deletes the specified vault. aka Purges the deleted Azure
key vault.
:param vault_name: The name of the soft-deleted vault.
:type vault_name: str
:param location: The location of the soft-deleted vault.
:type location: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: The poller return type is ClientRawResponse, the
direct response alongside the deserialized response
:param polling: True for ARMPolling, False for no polling, or a
polling object for personal polling strategy
:return: An instance of LROPoller that returns None or
ClientRawResponse<None> if raw==True
:rtype: ~msrestazure.azure_operation.AzureOperationPoller[None] or
~msrestazure.azure_operation.AzureOperationPoller[~msrest.pipeline.ClientRawResponse[None]]
:raises: :class:`CloudError<msrestazure.azure_exceptions.CloudError>`
"""
raw_result = self._purge_deleted_initial(
vault_name=vault_name,
location=location,
custom_headers=custom_headers,
raw=True,
**operation_config
)
def get_long_running_output(response):
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
lro_delay = operation_config.get(
'long_running_operation_timeout',
self.config.long_running_operation_timeout)
if polling is True: polling_method = ARMPolling(lro_delay, **operation_config)
elif polling is False: polling_method = NoPolling()
else: polling_method = polling
return LROPoller(self._client, raw_result, get_long_running_output, polling_method) | azure-mgmt-keyvault/azure/mgmt/keyvault/v2016_10_01/operations/vaults_operations.py |
Azure/azure-sdk-for-python | HttpChallenge._validate_request_uri | def _validate_request_uri(self, uri):
if not uri:
raise ValueError('request_uri cannot be empty')
uri = parse.urlparse(uri)
if not uri.netloc:
raise ValueError('request_uri must be an absolute URI')
if uri.scheme.lower() not in ['http', 'https']:
raise ValueError('request_uri must be HTTP or HTTPS')
return uri.netloc | Extracts the host authority from the given URI. | def _validate_request_uri(self, uri):
""" Extracts the host authority from the given URI. """
if not uri:
raise ValueError('request_uri cannot be empty')
uri = parse.urlparse(uri)
if not uri.netloc:
raise ValueError('request_uri must be an absolute URI')
if uri.scheme.lower() not in ['http', 'https']:
raise ValueError('request_uri must be HTTP or HTTPS')
return uri.netloc | azure-keyvault/azure/keyvault/http_challenge.py |
Azure/azure-sdk-for-python | get_cli_profile | def get_cli_profile():
try:
from azure.cli.core._profile import Profile
from azure.cli.core._session import ACCOUNT
from azure.cli.core._environment import get_config_dir
except ImportError:
raise ImportError("You need to install 'azure-cli-core' to load CLI credentials")
azure_folder = get_config_dir()
ACCOUNT.load(os.path.join(azure_folder, 'azureProfile.json'))
return Profile(storage=ACCOUNT) | Return a CLI profile class. | def get_cli_profile():
"""Return a CLI profile class.
.. versionadded:: 1.1.6
:return: A CLI Profile
:rtype: azure.cli.core._profile.Profile
:raises: ImportError if azure-cli-core package is not available
"""
try:
from azure.cli.core._profile import Profile
from azure.cli.core._session import ACCOUNT
from azure.cli.core._environment import get_config_dir
except ImportError:
raise ImportError("You need to install 'azure-cli-core' to load CLI credentials")
azure_folder = get_config_dir()
ACCOUNT.load(os.path.join(azure_folder, 'azureProfile.json'))
return Profile(storage=ACCOUNT) | azure-common/azure/common/credentials.py |
Azure/azure-sdk-for-python | get_azure_cli_credentials | def get_azure_cli_credentials(resource=None, with_tenant=False):
profile = get_cli_profile()
cred, subscription_id, tenant_id = profile.get_login_credentials(resource=resource)
if with_tenant:
return cred, subscription_id, tenant_id
else:
return cred, subscription_id | Return Credentials and default SubscriptionID of current loaded profile of the CLI. Credentials will be the "az login" | def get_azure_cli_credentials(resource=None, with_tenant=False):
"""Return Credentials and default SubscriptionID of current loaded profile of the CLI.
Credentials will be the "az login" command:
https://docs.microsoft.com/cli/azure/authenticate-azure-cli
Default subscription ID is either the only one you have, or you can define it:
https://docs.microsoft.com/cli/azure/manage-azure-subscriptions-azure-cli
.. versionadded:: 1.1.6
:param str resource: The alternative resource for credentials if not ARM (GraphRBac, etc.)
:param bool with_tenant: If True, return a three-tuple with last as tenant ID
:return: tuple of Credentials and SubscriptionID (and tenant ID if with_tenant)
:rtype: tuple
"""
profile = get_cli_profile()
cred, subscription_id, tenant_id = profile.get_login_credentials(resource=resource)
if with_tenant:
return cred, subscription_id, tenant_id
else:
return cred, subscription_id | azure-common/azure/common/credentials.py |
Azure/azure-sdk-for-python | PredictionOperations.resolve | def resolve(
self, app_id, query, timezone_offset=None, verbose=None, staging=None, spell_check=None, bing_spell_check_subscription_key=None, log=None, custom_headers=None, raw=False, **operation_config):
url = self.resolve.metadata['url']
path_format_arguments = {
'Endpoint': self._serialize.url("self.config.endpoint", self.config.endpoint, 'str', skip_quote=True),
'appId': self._serialize.url("app_id", app_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
if timezone_offset is not None:
query_parameters['timezoneOffset'] = self._serialize.query("timezone_offset", timezone_offset, 'float')
if verbose is not None:
query_parameters['verbose'] = self._serialize.query("verbose", verbose, 'bool')
if staging is not None:
query_parameters['staging'] = self._serialize.query("staging", staging, 'bool')
if spell_check is not None:
query_parameters['spellCheck'] = self._serialize.query("spell_check", spell_check, 'bool')
if bing_spell_check_subscription_key is not None:
query_parameters['bing-spell-check-subscription-key'] = self._serialize.query("bing_spell_check_subscription_key", bing_spell_check_subscription_key, 'str')
if log is not None:
query_parameters['log'] = self._serialize.query("log", log, 'bool')
header_parameters = {}
header_parameters['Accept'] = 'application/json'
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
body_content = self._serialize.body(query, 'str')
request = self._client.post(url, query_parameters, header_parameters, body_content)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.APIErrorException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('LuisResult', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized | Gets predictions for a given utterance, in the form of intents and entities. The current maximum query size is 500 characters. | def resolve(
self, app_id, query, timezone_offset=None, verbose=None, staging=None, spell_check=None, bing_spell_check_subscription_key=None, log=None, custom_headers=None, raw=False, **operation_config):
"""Gets predictions for a given utterance, in the form of intents and
entities. The current maximum query size is 500 characters.
:param app_id: The LUIS application ID (Guid).
:type app_id: str
:param query: The utterance to predict.
:type query: str
:param timezone_offset: The timezone offset for the location of the
request.
:type timezone_offset: float
:param verbose: If true, return all intents instead of just the top
scoring intent.
:type verbose: bool
:param staging: Use the staging endpoint slot.
:type staging: bool
:param spell_check: Enable spell checking.
:type spell_check: bool
:param bing_spell_check_subscription_key: The subscription key to use
when enabling Bing spell check
:type bing_spell_check_subscription_key: str
:param log: Log query (default is true)
:type log: bool
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: LuisResult or ClientRawResponse if raw=true
:rtype:
~azure.cognitiveservices.language.luis.runtime.models.LuisResult or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`APIErrorException<azure.cognitiveservices.language.luis.runtime.models.APIErrorException>`
"""
# Construct URL
url = self.resolve.metadata['url']
path_format_arguments = {
'Endpoint': self._serialize.url("self.config.endpoint", self.config.endpoint, 'str', skip_quote=True),
'appId': self._serialize.url("app_id", app_id, 'str')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
if timezone_offset is not None:
query_parameters['timezoneOffset'] = self._serialize.query("timezone_offset", timezone_offset, 'float')
if verbose is not None:
query_parameters['verbose'] = self._serialize.query("verbose", verbose, 'bool')
if staging is not None:
query_parameters['staging'] = self._serialize.query("staging", staging, 'bool')
if spell_check is not None:
query_parameters['spellCheck'] = self._serialize.query("spell_check", spell_check, 'bool')
if bing_spell_check_subscription_key is not None:
query_parameters['bing-spell-check-subscription-key'] = self._serialize.query("bing_spell_check_subscription_key", bing_spell_check_subscription_key, 'str')
if log is not None:
query_parameters['log'] = self._serialize.query("log", log, 'bool')
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
body_content = self._serialize.body(query, 'str')
# Construct and send request
request = self._client.post(url, query_parameters, header_parameters, body_content)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.APIErrorException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('LuisResult', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized | azure-cognitiveservices-language-luis/azure/cognitiveservices/language/luis/runtime/operations/prediction_operations.py |
Azure/azure-sdk-for-python | MixedRealityClient.check_name_availability_local | def check_name_availability_local(
self, location, name, type, custom_headers=None, raw=False, **operation_config):
check_name_availability = models.CheckNameAvailabilityRequest(name=name, type=type)
url = self.check_name_availability_local.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str'),
'location': self._serialize.url("location", location, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$')
}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str')
header_parameters = {}
header_parameters['Accept'] = 'application/json'
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
body_content = self._serialize.body(check_name_availability, 'CheckNameAvailabilityRequest')
request = self._client.post(url, query_parameters, header_parameters, body_content)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.ErrorResponseException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('CheckNameAvailabilityResponse', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized | Check Name Availability for global uniqueness. | def check_name_availability_local(
self, location, name, type, custom_headers=None, raw=False, **operation_config):
"""Check Name Availability for global uniqueness.
:param location: The location in which uniqueness will be verified.
:type location: str
:param name: Resource Name To Verify
:type name: str
:param type: Fully qualified resource type which includes provider
namespace
:type type: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: CheckNameAvailabilityResponse or ClientRawResponse if
raw=true
:rtype: ~azure.mgmt.mixedreality.models.CheckNameAvailabilityResponse
or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`ErrorResponseException<azure.mgmt.mixedreality.models.ErrorResponseException>`
"""
check_name_availability = models.CheckNameAvailabilityRequest(name=name, type=type)
# Construct URL
url = self.check_name_availability_local.metadata['url']
path_format_arguments = {
'subscriptionId': self._serialize.url("self.config.subscription_id", self.config.subscription_id, 'str'),
'location': self._serialize.url("location", location, 'str', max_length=90, min_length=1, pattern=r'^[-\w\._\(\)]+$')
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
query_parameters['api-version'] = self._serialize.query("self.api_version", self.api_version, 'str')
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if self.config.generate_client_request_id:
header_parameters['x-ms-client-request-id'] = str(uuid.uuid1())
if custom_headers:
header_parameters.update(custom_headers)
if self.config.accept_language is not None:
header_parameters['accept-language'] = self._serialize.header("self.config.accept_language", self.config.accept_language, 'str')
# Construct body
body_content = self._serialize.body(check_name_availability, 'CheckNameAvailabilityRequest')
# Construct and send request
request = self._client.post(url, query_parameters, header_parameters, body_content)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.ErrorResponseException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('CheckNameAvailabilityResponse', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized | azure-mgmt-mixedreality/azure/mgmt/mixedreality/mixed_reality_client.py |
Azure/azure-sdk-for-python | _WinHttpRequest.open | def open(self, method, url):
flag = VARIANT.create_bool_false()
_method = BSTR(method)
_url = BSTR(url)
_WinHttpRequest._Open(self, _method, _url, flag) | Opens the request. | def open(self, method, url):
'''
Opens the request.
method:
the request VERB 'GET', 'POST', etc.
url:
the url to connect
'''
flag = VARIANT.create_bool_false()
_method = BSTR(method)
_url = BSTR(url)
_WinHttpRequest._Open(self, _method, _url, flag) | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _WinHttpRequest.set_timeout | def set_timeout(self, timeout_in_seconds):
timeout_in_ms = int(timeout_in_seconds * 1000)
_WinHttpRequest._SetTimeouts(
self, 0, timeout_in_ms, timeout_in_ms, timeout_in_ms) | Sets up the timeout for the request. | def set_timeout(self, timeout_in_seconds):
''' Sets up the timeout for the request. '''
timeout_in_ms = int(timeout_in_seconds * 1000)
_WinHttpRequest._SetTimeouts(
self, 0, timeout_in_ms, timeout_in_ms, timeout_in_ms) | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _WinHttpRequest.set_request_header | def set_request_header(self, name, value):
_name = BSTR(name)
_value = BSTR(value)
_WinHttpRequest._SetRequestHeader(self, _name, _value) | Sets the request header. | def set_request_header(self, name, value):
''' Sets the request header. '''
_name = BSTR(name)
_value = BSTR(value)
_WinHttpRequest._SetRequestHeader(self, _name, _value) | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _WinHttpRequest.get_all_response_headers | def get_all_response_headers(self):
bstr_headers = c_void_p()
_WinHttpRequest._GetAllResponseHeaders(self, byref(bstr_headers))
bstr_headers = ctypes.cast(bstr_headers, c_wchar_p)
headers = bstr_headers.value
_SysFreeString(bstr_headers)
return headers | Gets back all response headers. | def get_all_response_headers(self):
''' Gets back all response headers. '''
bstr_headers = c_void_p()
_WinHttpRequest._GetAllResponseHeaders(self, byref(bstr_headers))
bstr_headers = ctypes.cast(bstr_headers, c_wchar_p)
headers = bstr_headers.value
_SysFreeString(bstr_headers)
return headers | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _WinHttpRequest.send | def send(self, request=None):
if request is None:
var_empty = VARIANT.create_empty()
_WinHttpRequest._Send(self, var_empty)
else:
_request = VARIANT.create_safearray_from_str(request)
_WinHttpRequest._Send(self, _request) | Sends the request body. | def send(self, request=None):
''' Sends the request body. '''
# Sends VT_EMPTY if it is GET, HEAD request.
if request is None:
var_empty = VARIANT.create_empty()
_WinHttpRequest._Send(self, var_empty)
else: # Sends request body as SAFEArray.
_request = VARIANT.create_safearray_from_str(request)
_WinHttpRequest._Send(self, _request) | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _WinHttpRequest.status | def status(self):
status = c_long()
_WinHttpRequest._Status(self, byref(status))
return int(status.value) | Gets status of response. | def status(self):
''' Gets status of response. '''
status = c_long()
_WinHttpRequest._Status(self, byref(status))
return int(status.value) | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _WinHttpRequest.status_text | def status_text(self):
bstr_status_text = c_void_p()
_WinHttpRequest._StatusText(self, byref(bstr_status_text))
bstr_status_text = ctypes.cast(bstr_status_text, c_wchar_p)
status_text = bstr_status_text.value
_SysFreeString(bstr_status_text)
return status_text | Gets status text of response. | def status_text(self):
''' Gets status text of response. '''
bstr_status_text = c_void_p()
_WinHttpRequest._StatusText(self, byref(bstr_status_text))
bstr_status_text = ctypes.cast(bstr_status_text, c_wchar_p)
status_text = bstr_status_text.value
_SysFreeString(bstr_status_text)
return status_text | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _WinHttpRequest.response_body | def response_body(self):
var_respbody = VARIANT()
_WinHttpRequest._ResponseBody(self, byref(var_respbody))
if var_respbody.is_safearray_of_bytes():
respbody = var_respbody.str_from_safearray()
return respbody
else:
return '' | Gets response body as a SAFEARRAY and converts the SAFEARRAY to str. | def response_body(self):
'''
Gets response body as a SAFEARRAY and converts the SAFEARRAY to str.
'''
var_respbody = VARIANT()
_WinHttpRequest._ResponseBody(self, byref(var_respbody))
if var_respbody.is_safearray_of_bytes():
respbody = var_respbody.str_from_safearray()
return respbody
else:
return '' | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _WinHttpRequest.set_client_certificate | def set_client_certificate(self, certificate):
_certificate = BSTR(certificate)
_WinHttpRequest._SetClientCertificate(self, _certificate) | Sets client certificate for the request. | def set_client_certificate(self, certificate):
'''Sets client certificate for the request. '''
_certificate = BSTR(certificate)
_WinHttpRequest._SetClientCertificate(self, _certificate) | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _HTTPConnection.putrequest | def putrequest(self, method, uri):
protocol = unicode(self.protocol + '://')
url = protocol + self.host + unicode(uri)
self._httprequest.set_timeout(self.timeout)
self._httprequest.open(unicode(method), url)
if self.cert_file is not None:
self._httprequest.set_client_certificate(unicode(self.cert_file)) | Connects to host and sends the request. | def putrequest(self, method, uri):
''' Connects to host and sends the request. '''
protocol = unicode(self.protocol + '://')
url = protocol + self.host + unicode(uri)
self._httprequest.set_timeout(self.timeout)
self._httprequest.open(unicode(method), url)
# sets certificate for the connection if cert_file is set.
if self.cert_file is not None:
self._httprequest.set_client_certificate(unicode(self.cert_file)) | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _HTTPConnection.putheader | def putheader(self, name, value):
if sys.version_info < (3,):
name = str(name).decode('utf-8')
value = str(value).decode('utf-8')
self._httprequest.set_request_header(name, value) | Sends the headers of request. | def putheader(self, name, value):
''' Sends the headers of request. '''
if sys.version_info < (3,):
name = str(name).decode('utf-8')
value = str(value).decode('utf-8')
self._httprequest.set_request_header(name, value) | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _HTTPConnection.send | def send(self, request_body):
if not request_body:
self._httprequest.send()
else:
self._httprequest.send(request_body) | Sends request body. | def send(self, request_body):
''' Sends request body. '''
if not request_body:
self._httprequest.send()
else:
self._httprequest.send(request_body) | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _HTTPConnection.getresponse | def getresponse(self):
status = self._httprequest.status()
status_text = self._httprequest.status_text()
resp_headers = self._httprequest.get_all_response_headers()
fixed_headers = []
for resp_header in resp_headers.split('\n'):
if (resp_header.startswith('\t') or\
resp_header.startswith(' ')) and fixed_headers:
fixed_headers[-1] += resp_header
else:
fixed_headers.append(resp_header)
headers = []
for resp_header in fixed_headers:
if ':' in resp_header:
pos = resp_header.find(':')
headers.append(
(resp_header[:pos].lower(), resp_header[pos + 1:].strip()))
body = self._httprequest.response_body()
length = len(body)
return _Response(status, status_text, length, headers, body) | Gets the response and generates the _Response object | def getresponse(self):
''' Gets the response and generates the _Response object'''
status = self._httprequest.status()
status_text = self._httprequest.status_text()
resp_headers = self._httprequest.get_all_response_headers()
fixed_headers = []
for resp_header in resp_headers.split('\n'):
if (resp_header.startswith('\t') or\
resp_header.startswith(' ')) and fixed_headers:
# append to previous header
fixed_headers[-1] += resp_header
else:
fixed_headers.append(resp_header)
headers = []
for resp_header in fixed_headers:
if ':' in resp_header:
pos = resp_header.find(':')
headers.append(
(resp_header[:pos].lower(), resp_header[pos + 1:].strip()))
body = self._httprequest.response_body()
length = len(body)
return _Response(status, status_text, length, headers, body) | azure-servicemanagement-legacy/azure/servicemanagement/_http/winhttp.py |
Azure/azure-sdk-for-python | _get_readable_id | def _get_readable_id(id_name, id_prefix_to_skip):
pos = id_name.find('//')
if pos != -1:
pos += 2
if id_prefix_to_skip:
pos = id_name.find(id_prefix_to_skip, pos)
if pos != -1:
pos += len(id_prefix_to_skip)
pos = id_name.find('/', pos)
if pos != -1:
return id_name[pos + 1:]
return id_name | simplified an id to be more friendly for us people | def _get_readable_id(id_name, id_prefix_to_skip):
"""simplified an id to be more friendly for us people"""
# id_name is in the form 'https://namespace.host.suffix/name'
# where name may contain a forward slash!
pos = id_name.find('//')
if pos != -1:
pos += 2
if id_prefix_to_skip:
pos = id_name.find(id_prefix_to_skip, pos)
if pos != -1:
pos += len(id_prefix_to_skip)
pos = id_name.find('/', pos)
if pos != -1:
return id_name[pos + 1:]
return id_name | azure-servicemanagement-legacy/azure/servicemanagement/_common_serialization.py |
Azure/azure-sdk-for-python | _get_serialization_name | def _get_serialization_name(element_name):
known = _KNOWN_SERIALIZATION_XFORMS.get(element_name)
if known is not None:
return known
if element_name.startswith('x_ms_'):
return element_name.replace('_', '-')
if element_name.endswith('_id'):
element_name = element_name.replace('_id', 'ID')
for name in ['content_', 'last_modified', 'if_', 'cache_control']:
if element_name.startswith(name):
element_name = element_name.replace('_', '-_')
return ''.join(name.capitalize() for name in element_name.split('_')) | converts a Python name into a serializable name | def _get_serialization_name(element_name):
"""converts a Python name into a serializable name"""
known = _KNOWN_SERIALIZATION_XFORMS.get(element_name)
if known is not None:
return known
if element_name.startswith('x_ms_'):
return element_name.replace('_', '-')
if element_name.endswith('_id'):
element_name = element_name.replace('_id', 'ID')
for name in ['content_', 'last_modified', 'if_', 'cache_control']:
if element_name.startswith(name):
element_name = element_name.replace('_', '-_')
return ''.join(name.capitalize() for name in element_name.split('_')) | azure-servicemanagement-legacy/azure/servicemanagement/_common_serialization.py |
Azure/azure-sdk-for-python | FaceOperations.verify_face_to_person | def verify_face_to_person(
self, face_id, person_id, person_group_id=None, large_person_group_id=None, custom_headers=None, raw=False, **operation_config):
body = models.VerifyFaceToPersonRequest(face_id=face_id, person_group_id=person_group_id, large_person_group_id=large_person_group_id, person_id=person_id)
url = self.verify_face_to_person.metadata['url']
path_format_arguments = {
'Endpoint': self._serialize.url("self.config.endpoint", self.config.endpoint, 'str', skip_quote=True)
}
url = self._client.format_url(url, **path_format_arguments)
query_parameters = {}
header_parameters = {}
header_parameters['Accept'] = 'application/json'
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
body_content = self._serialize.body(body, 'VerifyFaceToPersonRequest')
request = self._client.post(url, query_parameters, header_parameters, body_content)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.APIErrorException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('VerifyResult', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized | Verify whether two faces belong to a same person. Compares a face Id with a Person Id. | def verify_face_to_person(
self, face_id, person_id, person_group_id=None, large_person_group_id=None, custom_headers=None, raw=False, **operation_config):
"""Verify whether two faces belong to a same person. Compares a face Id
with a Person Id.
:param face_id: FaceId of the face, comes from Face - Detect
:type face_id: str
:param person_id: Specify a certain person in a person group or a
large person group. personId is created in PersonGroup Person - Create
or LargePersonGroup Person - Create.
:type person_id: str
:param person_group_id: Using existing personGroupId and personId for
fast loading a specified person. personGroupId is created in
PersonGroup - Create. Parameter personGroupId and largePersonGroupId
should not be provided at the same time.
:type person_group_id: str
:param large_person_group_id: Using existing largePersonGroupId and
personId for fast loading a specified person. largePersonGroupId is
created in LargePersonGroup - Create. Parameter personGroupId and
largePersonGroupId should not be provided at the same time.
:type large_person_group_id: str
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: VerifyResult or ClientRawResponse if raw=true
:rtype: ~azure.cognitiveservices.vision.face.models.VerifyResult or
~msrest.pipeline.ClientRawResponse
:raises:
:class:`APIErrorException<azure.cognitiveservices.vision.face.models.APIErrorException>`
"""
body = models.VerifyFaceToPersonRequest(face_id=face_id, person_group_id=person_group_id, large_person_group_id=large_person_group_id, person_id=person_id)
# Construct URL
url = self.verify_face_to_person.metadata['url']
path_format_arguments = {
'Endpoint': self._serialize.url("self.config.endpoint", self.config.endpoint, 'str', skip_quote=True)
}
url = self._client.format_url(url, **path_format_arguments)
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Accept'] = 'application/json'
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
body_content = self._serialize.body(body, 'VerifyFaceToPersonRequest')
# Construct and send request
request = self._client.post(url, query_parameters, header_parameters, body_content)
response = self._client.send(request, stream=False, **operation_config)
if response.status_code not in [200]:
raise models.APIErrorException(self._deserialize, response)
deserialized = None
if response.status_code == 200:
deserialized = self._deserialize('VerifyResult', response)
if raw:
client_raw_response = ClientRawResponse(deserialized, response)
return client_raw_response
return deserialized | azure-cognitiveservices-vision-face/azure/cognitiveservices/vision/face/operations/face_operations.py |
Azure/azure-sdk-for-python | _MinidomXmlToObject.get_entry_properties_from_node | def get_entry_properties_from_node(entry, include_id, id_prefix_to_skip=None, use_title_as_id=False):
properties = {}
etag = entry.getAttributeNS(METADATA_NS, 'etag')
if etag:
properties['etag'] = etag
for updated in _MinidomXmlToObject.get_child_nodes(entry, 'updated'):
properties['updated'] = updated.firstChild.nodeValue
for name in _MinidomXmlToObject.get_children_from_path(entry, 'author', 'name'):
if name.firstChild is not None:
properties['author'] = name.firstChild.nodeValue
if include_id:
if use_title_as_id:
for title in _MinidomXmlToObject.get_child_nodes(entry, 'title'):
properties['name'] = title.firstChild.nodeValue
else:
for id in _MinidomXmlToObject.get_child_nodes(entry, 'id'):
properties['name'] = _get_readable_id(
id.firstChild.nodeValue, id_prefix_to_skip)
return properties | get properties from entry xml | def get_entry_properties_from_node(entry, include_id, id_prefix_to_skip=None, use_title_as_id=False):
''' get properties from entry xml '''
properties = {}
etag = entry.getAttributeNS(METADATA_NS, 'etag')
if etag:
properties['etag'] = etag
for updated in _MinidomXmlToObject.get_child_nodes(entry, 'updated'):
properties['updated'] = updated.firstChild.nodeValue
for name in _MinidomXmlToObject.get_children_from_path(entry, 'author', 'name'):
if name.firstChild is not None:
properties['author'] = name.firstChild.nodeValue
if include_id:
if use_title_as_id:
for title in _MinidomXmlToObject.get_child_nodes(entry, 'title'):
properties['name'] = title.firstChild.nodeValue
else:
# TODO: check if this is used
for id in _MinidomXmlToObject.get_child_nodes(entry, 'id'):
properties['name'] = _get_readable_id(
id.firstChild.nodeValue, id_prefix_to_skip)
return properties | azure-servicemanagement-legacy/azure/servicemanagement/_serialization.py |
Azure/azure-sdk-for-python | _MinidomXmlToObject.get_children_from_path | def get_children_from_path(node, *path):
cur = node
for index, child in enumerate(path):
if isinstance(child, _strtype):
next = _MinidomXmlToObject.get_child_nodes(cur, child)
else:
next = _MinidomXmlToObject._get_child_nodesNS(cur, *child)
if index == len(path) - 1:
return next
elif not next:
break
cur = next[0]
return [] | descends through a hierarchy of nodes returning the list of children at the inner most level. Only returns children who share a common parent, not cousins. | def get_children_from_path(node, *path):
'''descends through a hierarchy of nodes returning the list of children
at the inner most level. Only returns children who share a common parent,
not cousins.'''
cur = node
for index, child in enumerate(path):
if isinstance(child, _strtype):
next = _MinidomXmlToObject.get_child_nodes(cur, child)
else:
next = _MinidomXmlToObject._get_child_nodesNS(cur, *child)
if index == len(path) - 1:
return next
elif not next:
break
cur = next[0]
return [] | azure-servicemanagement-legacy/azure/servicemanagement/_serialization.py |