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value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
|---|---|---|---|---|---|---|---|---|---|---|---|
test | S3TaskHandler.s3_read | Returns the log found at the remote_log_location. Returns '' if no
logs are found or there is an error.
:param remote_log_location: the log's location in remote storage
:type remote_log_location: str (path)
:param return_error: if True, returns a string error message if an
er... | airflow/utils/log/s3_task_handler.py | def s3_read(self, remote_log_location, return_error=False):
"""
Returns the log found at the remote_log_location. Returns '' if no
logs are found or there is an error.
:param remote_log_location: the log's location in remote storage
:type remote_log_location: str (path)
:... | def s3_read(self, remote_log_location, return_error=False):
"""
Returns the log found at the remote_log_location. Returns '' if no
logs are found or there is an error.
:param remote_log_location: the log's location in remote storage
:type remote_log_location: str (path)
:... | [
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test | S3TaskHandler.s3_write | Writes the log to the remote_log_location. Fails silently if no hook
was created.
:param log: the log to write to the remote_log_location
:type log: str
:param remote_log_location: the log's location in remote storage
:type remote_log_location: str (path)
:param append: i... | airflow/utils/log/s3_task_handler.py | def s3_write(self, log, remote_log_location, append=True):
"""
Writes the log to the remote_log_location. Fails silently if no hook
was created.
:param log: the log to write to the remote_log_location
:type log: str
:param remote_log_location: the log's location in remote... | def s3_write(self, log, remote_log_location, append=True):
"""
Writes the log to the remote_log_location. Fails silently if no hook
was created.
:param log: the log to write to the remote_log_location
:type log: str
:param remote_log_location: the log's location in remote... | [
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":... | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/log/s3_task_handler.py#L146-L170 | [
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test | WorkerConfiguration._get_init_containers | When using git to retrieve the DAGs, use the GitSync Init Container | airflow/contrib/kubernetes/worker_configuration.py | def _get_init_containers(self):
"""When using git to retrieve the DAGs, use the GitSync Init Container"""
# If we're using volume claims to mount the dags, no init container is needed
if self.kube_config.dags_volume_claim or \
self.kube_config.dags_volume_host or self.kube_config.dags... | def _get_init_containers(self):
"""When using git to retrieve the DAGs, use the GitSync Init Container"""
# If we're using volume claims to mount the dags, no init container is needed
if self.kube_config.dags_volume_claim or \
self.kube_config.dags_volume_host or self.kube_config.dags... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/kubernetes/worker_configuration.py#L45-L131 | [
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... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | WorkerConfiguration._get_environment | Defines any necessary environment variables for the pod executor | airflow/contrib/kubernetes/worker_configuration.py | def _get_environment(self):
"""Defines any necessary environment variables for the pod executor"""
env = {}
for env_var_name, env_var_val in six.iteritems(self.kube_config.kube_env_vars):
env[env_var_name] = env_var_val
env["AIRFLOW__CORE__EXECUTOR"] = "LocalExecutor"
... | def _get_environment(self):
"""Defines any necessary environment variables for the pod executor"""
env = {}
for env_var_name, env_var_val in six.iteritems(self.kube_config.kube_env_vars):
env[env_var_name] = env_var_val
env["AIRFLOW__CORE__EXECUTOR"] = "LocalExecutor"
... | [
"Defines",
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"variables",
"for",
"the",
"pod",
"executor"
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/kubernetes/worker_configuration.py#L133-L156 | [
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test | WorkerConfiguration._get_secrets | Defines any necessary secrets for the pod executor | airflow/contrib/kubernetes/worker_configuration.py | def _get_secrets(self):
"""Defines any necessary secrets for the pod executor"""
worker_secrets = []
for env_var_name, obj_key_pair in six.iteritems(self.kube_config.kube_secrets):
k8s_secret_obj, k8s_secret_key = obj_key_pair.split('=')
worker_secrets.append(
... | def _get_secrets(self):
"""Defines any necessary secrets for the pod executor"""
worker_secrets = []
for env_var_name, obj_key_pair in six.iteritems(self.kube_config.kube_secrets):
k8s_secret_obj, k8s_secret_key = obj_key_pair.split('=')
worker_secrets.append(
... | [
"Defines",
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"secrets",
"for",
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"executor"
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/kubernetes/worker_configuration.py#L164-L180 | [
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... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | WorkerConfiguration._get_security_context | Defines the security context | airflow/contrib/kubernetes/worker_configuration.py | def _get_security_context(self):
"""Defines the security context"""
security_context = {}
if self.kube_config.worker_run_as_user:
security_context['runAsUser'] = self.kube_config.worker_run_as_user
if self.kube_config.worker_fs_group:
security_context['fsGroup']... | def _get_security_context(self):
"""Defines the security context"""
security_context = {}
if self.kube_config.worker_run_as_user:
security_context['runAsUser'] = self.kube_config.worker_run_as_user
if self.kube_config.worker_fs_group:
security_context['fsGroup']... | [
"Defines",
"the",
"security",
"context"
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/kubernetes/worker_configuration.py#L188-L202 | [
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"... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | QuboleHook.kill | Kill (cancel) a Qubole command
:param ti: Task Instance of the dag, used to determine the Quboles command id
:return: response from Qubole | airflow/contrib/hooks/qubole_hook.py | def kill(self, ti):
"""
Kill (cancel) a Qubole command
:param ti: Task Instance of the dag, used to determine the Quboles command id
:return: response from Qubole
"""
if self.cmd is None:
if not ti and not self.task_instance:
raise Exception("U... | def kill(self, ti):
"""
Kill (cancel) a Qubole command
:param ti: Task Instance of the dag, used to determine the Quboles command id
:return: response from Qubole
"""
if self.cmd is None:
if not ti and not self.task_instance:
raise Exception("U... | [
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... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | QuboleHook.get_results | Get results (or just s3 locations) of a command from Qubole and save into a file
:param ti: Task Instance of the dag, used to determine the Quboles command id
:param fp: Optional file pointer, will create one and return if None passed
:param inline: True to download actual results, False to get ... | airflow/contrib/hooks/qubole_hook.py | def get_results(self, ti=None, fp=None, inline=True, delim=None, fetch=True):
"""
Get results (or just s3 locations) of a command from Qubole and save into a file
:param ti: Task Instance of the dag, used to determine the Quboles command id
:param fp: Optional file pointer, will create o... | def get_results(self, ti=None, fp=None, inline=True, delim=None, fetch=True):
"""
Get results (or just s3 locations) of a command from Qubole and save into a file
:param ti: Task Instance of the dag, used to determine the Quboles command id
:param fp: Optional file pointer, will create o... | [
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test | QuboleHook.get_log | Get Logs of a command from Qubole
:param ti: Task Instance of the dag, used to determine the Quboles command id
:return: command log as text | airflow/contrib/hooks/qubole_hook.py | def get_log(self, ti):
"""
Get Logs of a command from Qubole
:param ti: Task Instance of the dag, used to determine the Quboles command id
:return: command log as text
"""
if self.cmd is None:
cmd_id = ti.xcom_pull(key="qbol_cmd_id", task_ids=self.task_id)
... | def get_log(self, ti):
"""
Get Logs of a command from Qubole
:param ti: Task Instance of the dag, used to determine the Quboles command id
:return: command log as text
"""
if self.cmd is None:
cmd_id = ti.xcom_pull(key="qbol_cmd_id", task_ids=self.task_id)
... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/qubole_hook.py#L192-L200 | [
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"get_log_id... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | QuboleHook.get_jobs_id | Get jobs associated with a Qubole commands
:param ti: Task Instance of the dag, used to determine the Quboles command id
:return: Job information associated with command | airflow/contrib/hooks/qubole_hook.py | def get_jobs_id(self, ti):
"""
Get jobs associated with a Qubole commands
:param ti: Task Instance of the dag, used to determine the Quboles command id
:return: Job information associated with command
"""
if self.cmd is None:
cmd_id = ti.xcom_pull(key="qbol_cm... | def get_jobs_id(self, ti):
"""
Get jobs associated with a Qubole commands
:param ti: Task Instance of the dag, used to determine the Quboles command id
:return: Job information associated with command
"""
if self.cmd is None:
cmd_id = ti.xcom_pull(key="qbol_cm... | [
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"get_jo... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | QuboleHook.get_extra_links | Get link to qubole command result page.
:param operator: operator
:param dttm: datetime
:return: url link | airflow/contrib/hooks/qubole_hook.py | def get_extra_links(self, operator, dttm):
"""
Get link to qubole command result page.
:param operator: operator
:param dttm: datetime
:return: url link
"""
conn = BaseHook.get_connection(operator.kwargs['qubole_conn_id'])
if conn and conn.host:
... | def get_extra_links(self, operator, dttm):
"""
Get link to qubole command result page.
:param operator: operator
:param dttm: datetime
:return: url link
"""
conn = BaseHook.get_connection(operator.kwargs['qubole_conn_id'])
if conn and conn.host:
... | [
"Get",
"link",
"to",
"qubole",
"command",
"result",
"page",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/qubole_hook.py#L212-L229 | [
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... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | BaseJob.heartbeat | Heartbeats update the job's entry in the database with a timestamp
for the latest_heartbeat and allows for the job to be killed
externally. This allows at the system level to monitor what is
actually active.
For instance, an old heartbeat for SchedulerJob would mean something
is... | airflow/jobs.py | def heartbeat(self):
"""
Heartbeats update the job's entry in the database with a timestamp
for the latest_heartbeat and allows for the job to be killed
externally. This allows at the system level to monitor what is
actually active.
For instance, an old heartbeat for Sch... | def heartbeat(self):
"""
Heartbeats update the job's entry in the database with a timestamp
for the latest_heartbeat and allows for the job to be killed
externally. This allows at the system level to monitor what is
actually active.
For instance, an old heartbeat for Sch... | [
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... | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L139-L189 | [
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... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | BaseJob.reset_state_for_orphaned_tasks | This function checks if there are any tasks in the dagrun (or all)
that have a scheduled state but are not known by the
executor. If it finds those it will reset the state to None
so they will get picked up again.
The batch option is for performance reasons as the queries are made in
... | airflow/jobs.py | def reset_state_for_orphaned_tasks(self, filter_by_dag_run=None, session=None):
"""
This function checks if there are any tasks in the dagrun (or all)
that have a scheduled state but are not known by the
executor. If it finds those it will reset the state to None
so they will get... | def reset_state_for_orphaned_tasks(self, filter_by_dag_run=None, session=None):
"""
This function checks if there are any tasks in the dagrun (or all)
that have a scheduled state but are not known by the
executor. If it finds those it will reset the state to None
so they will get... | [
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"# also consider running as the state might not have changed in the db yet",
... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | DagFileProcessor._launch_process | Launch a process to process the given file.
:param result_queue: the queue to use for passing back the result
:type result_queue: multiprocessing.Queue
:param file_path: the file to process
:type file_path: unicode
:param pickle_dags: whether to pickle the DAGs found in the file... | airflow/jobs.py | def _launch_process(result_queue,
file_path,
pickle_dags,
dag_id_white_list,
thread_name,
zombies):
"""
Launch a process to process the given file.
:param result_queue: the qu... | def _launch_process(result_queue,
file_path,
pickle_dags,
dag_id_white_list,
thread_name,
zombies):
"""
Launch a process to process the given file.
:param result_queue: the qu... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L342-L417 | [
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test | DagFileProcessor.start | Launch the process and start processing the DAG. | airflow/jobs.py | def start(self):
"""
Launch the process and start processing the DAG.
"""
self._process = DagFileProcessor._launch_process(
self._result_queue,
self.file_path,
self._pickle_dags,
self._dag_id_white_list,
"DagFileProcessor{}".for... | def start(self):
"""
Launch the process and start processing the DAG.
"""
self._process = DagFileProcessor._launch_process(
self._result_queue,
self.file_path,
self._pickle_dags,
self._dag_id_white_list,
"DagFileProcessor{}".for... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L419-L430 | [
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test | DagFileProcessor.terminate | Terminate (and then kill) the process launched to process the file.
:param sigkill: whether to issue a SIGKILL if SIGTERM doesn't work.
:type sigkill: bool | airflow/jobs.py | def terminate(self, sigkill=False):
"""
Terminate (and then kill) the process launched to process the file.
:param sigkill: whether to issue a SIGKILL if SIGTERM doesn't work.
:type sigkill: bool
"""
if self._process is None:
raise AirflowException("Tried to ... | def terminate(self, sigkill=False):
"""
Terminate (and then kill) the process launched to process the file.
:param sigkill: whether to issue a SIGKILL if SIGTERM doesn't work.
:type sigkill: bool
"""
if self._process is None:
raise AirflowException("Tried to ... | [
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test | DagFileProcessor.done | Check if the process launched to process this file is done.
:return: whether the process is finished running
:rtype: bool | airflow/jobs.py | def done(self):
"""
Check if the process launched to process this file is done.
:return: whether the process is finished running
:rtype: bool
"""
if self._process is None:
raise AirflowException("Tried to see if it's done before starting!")
if self._... | def done(self):
"""
Check if the process launched to process this file is done.
:return: whether the process is finished running
:rtype: bool
"""
if self._process is None:
raise AirflowException("Tried to see if it's done before starting!")
if self._... | [
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test | SchedulerJob._exit_gracefully | Helper method to clean up processor_agent to avoid leaving orphan processes. | airflow/jobs.py | def _exit_gracefully(self, signum, frame):
"""
Helper method to clean up processor_agent to avoid leaving orphan processes.
"""
self.log.info("Exiting gracefully upon receiving signal %s", signum)
if self.processor_agent:
self.processor_agent.end()
sys.exit(os... | def _exit_gracefully(self, signum, frame):
"""
Helper method to clean up processor_agent to avoid leaving orphan processes.
"""
self.log.info("Exiting gracefully upon receiving signal %s", signum)
if self.processor_agent:
self.processor_agent.end()
sys.exit(os... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L599-L606 | [
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"processor_agent",... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | SchedulerJob.manage_slas | Finding all tasks that have SLAs defined, and sending alert emails
where needed. New SLA misses are also recorded in the database.
Where assuming that the scheduler runs often, so we only check for
tasks that should have succeeded in the past hour. | airflow/jobs.py | def manage_slas(self, dag, session=None):
"""
Finding all tasks that have SLAs defined, and sending alert emails
where needed. New SLA misses are also recorded in the database.
Where assuming that the scheduler runs often, so we only check for
tasks that should have succeeded in... | def manage_slas(self, dag, session=None):
"""
Finding all tasks that have SLAs defined, and sending alert emails
where needed. New SLA misses are also recorded in the database.
Where assuming that the scheduler runs often, so we only check for
tasks that should have succeeded in... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L609-L738 | [
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test | SchedulerJob.update_import_errors | For the DAGs in the given DagBag, record any associated import errors and clears
errors for files that no longer have them. These are usually displayed through the
Airflow UI so that users know that there are issues parsing DAGs.
:param session: session for ORM operations
:type session:... | airflow/jobs.py | def update_import_errors(session, dagbag):
"""
For the DAGs in the given DagBag, record any associated import errors and clears
errors for files that no longer have them. These are usually displayed through the
Airflow UI so that users know that there are issues parsing DAGs.
:p... | def update_import_errors(session, dagbag):
"""
For the DAGs in the given DagBag, record any associated import errors and clears
errors for files that no longer have them. These are usually displayed through the
Airflow UI so that users know that there are issues parsing DAGs.
:p... | [
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"Airflo... | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L741-L763 | [
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... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | SchedulerJob.create_dag_run | This method checks whether a new DagRun needs to be created
for a DAG based on scheduling interval.
Returns DagRun if one is scheduled. Otherwise returns None. | airflow/jobs.py | def create_dag_run(self, dag, session=None):
"""
This method checks whether a new DagRun needs to be created
for a DAG based on scheduling interval.
Returns DagRun if one is scheduled. Otherwise returns None.
"""
if dag.schedule_interval and conf.getboolean('scheduler', '... | def create_dag_run(self, dag, session=None):
"""
This method checks whether a new DagRun needs to be created
for a DAG based on scheduling interval.
Returns DagRun if one is scheduled. Otherwise returns None.
"""
if dag.schedule_interval and conf.getboolean('scheduler', '... | [
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test | SchedulerJob._process_task_instances | This method schedules the tasks for a single DAG by looking at the
active DAG runs and adding task instances that should run to the
queue. | airflow/jobs.py | def _process_task_instances(self, dag, queue, session=None):
"""
This method schedules the tasks for a single DAG by looking at the
active DAG runs and adding task instances that should run to the
queue.
"""
# update the state of the previously active dag runs
da... | def _process_task_instances(self, dag, queue, session=None):
"""
This method schedules the tasks for a single DAG by looking at the
active DAG runs and adding task instances that should run to the
queue.
"""
# update the state of the previously active dag runs
da... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L897-L954 | [
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test | SchedulerJob._change_state_for_tis_without_dagrun | For all DAG IDs in the SimpleDagBag, look for task instances in the
old_states and set them to new_state if the corresponding DagRun
does not exist or exists but is not in the running state. This
normally should not happen, but it can if the state of DagRuns are
changed manually.
... | airflow/jobs.py | def _change_state_for_tis_without_dagrun(self,
simple_dag_bag,
old_states,
new_state,
session=None):
"""
For all DAG IDs in ... | def _change_state_for_tis_without_dagrun(self,
simple_dag_bag,
old_states,
new_state,
session=None):
"""
For all DAG IDs in ... | [
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test | SchedulerJob.__get_concurrency_maps | Get the concurrency maps.
:param states: List of states to query for
:type states: list[airflow.utils.state.State]
:return: A map from (dag_id, task_id) to # of task instances and
a map from (dag_id, task_id) to # of task instances in the given state list
:rtype: dict[tuple[str... | airflow/jobs.py | def __get_concurrency_maps(self, states, session=None):
"""
Get the concurrency maps.
:param states: List of states to query for
:type states: list[airflow.utils.state.State]
:return: A map from (dag_id, task_id) to # of task instances and
a map from (dag_id, task_id) t... | def __get_concurrency_maps(self, states, session=None):
"""
Get the concurrency maps.
:param states: List of states to query for
:type states: list[airflow.utils.state.State]
:return: A map from (dag_id, task_id) to # of task instances and
a map from (dag_id, task_id) t... | [
"Get",
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"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1015-L1039 | [
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... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | SchedulerJob._find_executable_task_instances | Finds TIs that are ready for execution with respect to pool limits,
dag concurrency, executor state, and priority.
:param simple_dag_bag: TaskInstances associated with DAGs in the
simple_dag_bag will be fetched from the DB and executed
:type simple_dag_bag: airflow.utils.dag_process... | airflow/jobs.py | def _find_executable_task_instances(self, simple_dag_bag, states, session=None):
"""
Finds TIs that are ready for execution with respect to pool limits,
dag concurrency, executor state, and priority.
:param simple_dag_bag: TaskInstances associated with DAGs in the
simple_dag... | def _find_executable_task_instances(self, simple_dag_bag, states, session=None):
"""
Finds TIs that are ready for execution with respect to pool limits,
dag concurrency, executor state, and priority.
:param simple_dag_bag: TaskInstances associated with DAGs in the
simple_dag... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1042-L1214 | [
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test | SchedulerJob._change_state_for_executable_task_instances | Changes the state of task instances in the list with one of the given states
to QUEUED atomically, and returns the TIs changed in SimpleTaskInstance format.
:param task_instances: TaskInstances to change the state of
:type task_instances: list[airflow.models.TaskInstance]
:param accepta... | airflow/jobs.py | def _change_state_for_executable_task_instances(self, task_instances,
acceptable_states, session=None):
"""
Changes the state of task instances in the list with one of the given states
to QUEUED atomically, and returns the TIs changed in Simple... | def _change_state_for_executable_task_instances(self, task_instances,
acceptable_states, session=None):
"""
Changes the state of task instances in the list with one of the given states
to QUEUED atomically, and returns the TIs changed in Simple... | [
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test | SchedulerJob._enqueue_task_instances_with_queued_state | Takes task_instances, which should have been set to queued, and enqueues them
with the executor.
:param simple_task_instances: TaskInstances to enqueue
:type simple_task_instances: list[SimpleTaskInstance]
:param simple_dag_bag: Should contains all of the task_instances' dags
:t... | airflow/jobs.py | def _enqueue_task_instances_with_queued_state(self, simple_dag_bag,
simple_task_instances):
"""
Takes task_instances, which should have been set to queued, and enqueues them
with the executor.
:param simple_task_instances: TaskInstances ... | def _enqueue_task_instances_with_queued_state(self, simple_dag_bag,
simple_task_instances):
"""
Takes task_instances, which should have been set to queued, and enqueues them
with the executor.
:param simple_task_instances: TaskInstances ... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1282-L1322 | [
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"simple_da... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | SchedulerJob._execute_task_instances | Attempts to execute TaskInstances that should be executed by the scheduler.
There are three steps:
1. Pick TIs by priority with the constraint that they are in the expected states
and that we do exceed max_active_runs or pool limits.
2. Change the state for the TIs above atomically.
... | airflow/jobs.py | def _execute_task_instances(self,
simple_dag_bag,
states,
session=None):
"""
Attempts to execute TaskInstances that should be executed by the scheduler.
There are three steps:
1. Pick TIs by ... | def _execute_task_instances(self,
simple_dag_bag,
states,
session=None):
"""
Attempts to execute TaskInstances that should be executed by the scheduler.
There are three steps:
1. Pick TIs by ... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1325-L1359 | [
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test | SchedulerJob._change_state_for_tasks_failed_to_execute | If there are tasks left over in the executor,
we set them back to SCHEDULED to avoid creating hanging tasks.
:param session: session for ORM operations | airflow/jobs.py | def _change_state_for_tasks_failed_to_execute(self, session):
"""
If there are tasks left over in the executor,
we set them back to SCHEDULED to avoid creating hanging tasks.
:param session: session for ORM operations
"""
if self.executor.queued_tasks:
TI = m... | def _change_state_for_tasks_failed_to_execute(self, session):
"""
If there are tasks left over in the executor,
we set them back to SCHEDULED to avoid creating hanging tasks.
:param session: session for ORM operations
"""
if self.executor.queued_tasks:
TI = m... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1362-L1399 | [
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"... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | SchedulerJob._process_dags | Iterates over the dags and processes them. Processing includes:
1. Create appropriate DagRun(s) in the DB.
2. Create appropriate TaskInstance(s) in the DB.
3. Send emails for tasks that have missed SLAs.
:param dagbag: a collection of DAGs to process
:type dagbag: airflow.model... | airflow/jobs.py | def _process_dags(self, dagbag, dags, tis_out):
"""
Iterates over the dags and processes them. Processing includes:
1. Create appropriate DagRun(s) in the DB.
2. Create appropriate TaskInstance(s) in the DB.
3. Send emails for tasks that have missed SLAs.
:param dagbag:... | def _process_dags(self, dagbag, dags, tis_out):
"""
Iterates over the dags and processes them. Processing includes:
1. Create appropriate DagRun(s) in the DB.
2. Create appropriate TaskInstance(s) in the DB.
3. Send emails for tasks that have missed SLAs.
:param dagbag:... | [
"Iterates",
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1401-L1439 | [
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"e... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | SchedulerJob._process_executor_events | Respond to executor events. | airflow/jobs.py | def _process_executor_events(self, simple_dag_bag, session=None):
"""
Respond to executor events.
"""
# TODO: this shares quite a lot of code with _manage_executor_state
TI = models.TaskInstance
for key, state in list(self.executor.get_event_buffer(simple_dag_bag.dag_ids... | def _process_executor_events(self, simple_dag_bag, session=None):
"""
Respond to executor events.
"""
# TODO: this shares quite a lot of code with _manage_executor_state
TI = models.TaskInstance
for key, state in list(self.executor.get_event_buffer(simple_dag_bag.dag_ids... | [
"Respond",
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"events",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1442-L1484 | [
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test | SchedulerJob._execute_helper | The actual scheduler loop. The main steps in the loop are:
#. Harvest DAG parsing results through DagFileProcessorAgent
#. Find and queue executable tasks
#. Change task instance state in DB
#. Queue tasks in executor
#. Heartbeat executor
... | airflow/jobs.py | def _execute_helper(self):
"""
The actual scheduler loop. The main steps in the loop are:
#. Harvest DAG parsing results through DagFileProcessorAgent
#. Find and queue executable tasks
#. Change task instance state in DB
#. Queue tasks in executor... | def _execute_helper(self):
"""
The actual scheduler loop. The main steps in the loop are:
#. Harvest DAG parsing results through DagFileProcessorAgent
#. Find and queue executable tasks
#. Change task instance state in DB
#. Queue tasks in executor... | [
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"# Start after... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | SchedulerJob.process_file | Process a Python file containing Airflow DAGs.
This includes:
1. Execute the file and look for DAG objects in the namespace.
2. Pickle the DAG and save it to the DB (if necessary).
3. For each DAG, see what tasks should run and create appropriate task
instances in the DB.
... | airflow/jobs.py | def process_file(self, file_path, zombies, pickle_dags=False, session=None):
"""
Process a Python file containing Airflow DAGs.
This includes:
1. Execute the file and look for DAG objects in the namespace.
2. Pickle the DAG and save it to the DB (if necessary).
3. For e... | def process_file(self, file_path, zombies, pickle_dags=False, session=None):
"""
Process a Python file containing Airflow DAGs.
This includes:
1. Execute the file and look for DAG objects in the namespace.
2. Pickle the DAG and save it to the DB (if necessary).
3. For e... | [
"Process",
"a",
"Python",
"file",
"containing",
"Airflow",
"DAGs",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1669-L1787 | [
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",",
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"# As DAGs ... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | BackfillJob._update_counters | Updates the counters per state of the tasks that were running. Can re-add
to tasks to run in case required.
:param ti_status: the internal status of the backfill job tasks
:type ti_status: BackfillJob._DagRunTaskStatus | airflow/jobs.py | def _update_counters(self, ti_status):
"""
Updates the counters per state of the tasks that were running. Can re-add
to tasks to run in case required.
:param ti_status: the internal status of the backfill job tasks
:type ti_status: BackfillJob._DagRunTaskStatus
"""
... | def _update_counters(self, ti_status):
"""
Updates the counters per state of the tasks that were running. Can re-add
to tasks to run in case required.
:param ti_status: the internal status of the backfill job tasks
:type ti_status: BackfillJob._DagRunTaskStatus
"""
... | [
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"add",
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"to",
"run",
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1929-L1977 | [
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"... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | BackfillJob._manage_executor_state | Checks if the executor agrees with the state of task instances
that are running
:param running: dict of key, task to verify | airflow/jobs.py | def _manage_executor_state(self, running):
"""
Checks if the executor agrees with the state of task instances
that are running
:param running: dict of key, task to verify
"""
executor = self.executor
for key, state in list(executor.get_event_buffer().items()):
... | def _manage_executor_state(self, running):
"""
Checks if the executor agrees with the state of task instances
that are running
:param running: dict of key, task to verify
"""
executor = self.executor
for key, state in list(executor.get_event_buffer().items()):
... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L1979-L2007 | [
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"key... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | BackfillJob._get_dag_run | Returns a dag run for the given run date, which will be matched to an existing
dag run if available or create a new dag run otherwise. If the max_active_runs
limit is reached, this function will return None.
:param run_date: the execution date for the dag run
:type run_date: datetime.da... | airflow/jobs.py | def _get_dag_run(self, run_date, session=None):
"""
Returns a dag run for the given run date, which will be matched to an existing
dag run if available or create a new dag run otherwise. If the max_active_runs
limit is reached, this function will return None.
:param run_date: th... | def _get_dag_run(self, run_date, session=None):
"""
Returns a dag run for the given run date, which will be matched to an existing
dag run if available or create a new dag run otherwise. If the max_active_runs
limit is reached, this function will return None.
:param run_date: th... | [
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"# consider max_active_runs but ignore when running ... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | BackfillJob._task_instances_for_dag_run | Returns a map of task instance key to task instance object for the tasks to
run in the given dag run.
:param dag_run: the dag run to get the tasks from
:type dag_run: airflow.models.DagRun
:param session: the database session object
:type session: sqlalchemy.orm.session.Session | airflow/jobs.py | def _task_instances_for_dag_run(self, dag_run, session=None):
"""
Returns a map of task instance key to task instance object for the tasks to
run in the given dag run.
:param dag_run: the dag run to get the tasks from
:type dag_run: airflow.models.DagRun
:param session: ... | def _task_instances_for_dag_run(self, dag_run, session=None):
"""
Returns a map of task instance key to task instance object for the tasks to
run in the given dag run.
:param dag_run: the dag run to get the tasks from
:type dag_run: airflow.models.DagRun
:param session: ... | [
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"to",
"run",
"in",
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"given",
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"run",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L2071-L2101 | [
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"reset_state_fo... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | BackfillJob._process_backfill_task_instances | Process a set of task instances from a set of dag runs. Special handling is done
to account for different task instance states that could be present when running
them in a backfill process.
:param ti_status: the internal status of the job
:type ti_status: BackfillJob._DagRunTaskStatus
... | airflow/jobs.py | def _process_backfill_task_instances(self,
ti_status,
executor,
pickle_id,
start_date=None, session=None):
"""
Process a set of task instanc... | def _process_backfill_task_instances(self,
ti_status,
executor,
pickle_id,
start_date=None, session=None):
"""
Process a set of task instanc... | [
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"for",
"different",
"task",
"instance",
"states",
"that",
"could",
"be",
"present",
"when",
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"th... | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L2118-L2366 | [
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"ti_status... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | BackfillJob._execute_for_run_dates | Computes the dag runs and their respective task instances for
the given run dates and executes the task instances.
Returns a list of execution dates of the dag runs that were executed.
:param run_dates: Execution dates for dag runs
:type run_dates: list
:param ti_status: interna... | airflow/jobs.py | def _execute_for_run_dates(self, run_dates, ti_status, executor, pickle_id,
start_date, session=None):
"""
Computes the dag runs and their respective task instances for
the given run dates and executes the task instances.
Returns a list of execution dates o... | def _execute_for_run_dates(self, run_dates, ti_status, executor, pickle_id,
start_date, session=None):
"""
Computes the dag runs and their respective task instances for
the given run dates and executes the task instances.
Returns a list of execution dates o... | [
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"and",
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"instances",
".",
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... | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L2405-L2442 | [
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"_get_... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | BackfillJob._set_unfinished_dag_runs_to_failed | 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 | airflow/jobs.py | 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
... | 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
... | [
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"state",
".",
"Then",
"set",
"DAG",
"runs",
"that",
"are",
"not",
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"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L2445-L2458 | [
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"... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | BackfillJob._execute | Initializes all components required to run a dag for a specified date range and
calls helper method to execute the tasks. | airflow/jobs.py | 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 betwee... | 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 betwee... | [
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"date",
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"and",
"calls",
"helper",
"method",
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"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L2461-L2536 | [
"def",
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"bf_start_date",
"# Get intervals between the start/end dates, which will turn into dag runs",
"ru... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | LocalTaskJob.heartbeat_callback | Self destruct task if state has been moved away from running externally | airflow/jobs.py | 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_... | 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_... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/jobs.py#L2637-L2673 | [
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"terminate",
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")",
"return",
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"task_inst... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | CloudSpannerHook._get_client | 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 | airflow/contrib/hooks/gcp_spanner_hook.py | 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... | 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... | [
"Provides",
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"client",
"for",
"interacting",
"with",
"the",
"Cloud",
"Spanner",
"API",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L41-L52 | [
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... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | CloudSpannerHook.get_instance | 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 Clo... | airflow/contrib/hooks/gcp_spanner_hook.py | 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.
... | 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.
... | [
"Gets",
"information",
"about",
"a",
"particular",
"instance",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L55-L70 | [
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"=",
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"n... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | CloudSpannerHook._apply_to_instance | 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_na... | airflow/contrib/hooks/gcp_spanner_hook.py | 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
... | 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
... | [
"Invokes",
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"method",
"on",
"a",
"given",
"instance",
"by",
"applying",
"a",
"specified",
"Callable",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L72-L106 | [
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"pro... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | CloudSpannerHook.create_instance | 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
... | airflow/contrib/hooks/gcp_spanner_hook.py | 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: Th... | 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: Th... | [
"Creates",
"a",
"new",
"Cloud",
"Spanner",
"instance",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L109-L133 | [
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"project_id",
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"instance_id",
",",
"configuration_na... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | CloudSpannerHook.update_instance | 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 vi... | airflow/contrib/hooks/gcp_spanner_hook.py | 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_na... | 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_na... | [
"Updates",
"an",
"existing",
"Cloud",
"Spanner",
"instance",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L136-L160 | [
"def",
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",",
"instance_id",
",",
"conf... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | CloudSpannerHook.delete_instance | 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 co... | airflow/contrib/hooks/gcp_spanner_hook.py | 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
... | 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
... | [
"Deletes",
"an",
"existing",
"Cloud",
"Spanner",
"instance",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L163-L181 | [
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"... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | CloudSpannerHook.get_database | 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
... | airflow/contrib/hooks/gcp_spanner_hook.py | 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
:para... | 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
:para... | [
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"does",
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"the",
"specified",
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L184-L209 | [
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"instance_id",
"=",
"instance_... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | CloudSpannerHook.create_database | 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... | airflow/contrib/hooks/gcp_spanner_hook.py | 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 dat... | 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 dat... | [
"Creates",
"a",
"new",
"database",
"in",
"Cloud",
"Spanner",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L212-L244 | [
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"(",
"ins... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | CloudSpannerHook.update_database | 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 c... | airflow/contrib/hooks/gcp_spanner_hook.py | 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.
... | 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.
... | [
"Updates",
"DDL",
"of",
"a",
"database",
"in",
"Cloud",
"Spanner",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L247-L288 | [
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"_get_client",
"(",
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"=",
"project_id",... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | CloudSpannerHook.delete_database | 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 p... | airflow/contrib/hooks/gcp_spanner_hook.py | 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... | 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... | [
"Drops",
"a",
"database",
"in",
"Cloud",
"Spanner",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L291-L325 | [
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"(",
"instance_id",
"=",
"instan... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | CloudSpannerHook.execute_dml | Executes an arbitrary DML query (INSERT, UPDATE, DELETE).
: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 queries: The queries to execute.
:type qu... | airflow/contrib/hooks/gcp_spanner_hook.py | def execute_dml(self, instance_id, database_id, queries, project_id=None):
"""
Executes an arbitrary DML query (INSERT, UPDATE, DELETE).
: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.
... | def execute_dml(self, instance_id, database_id, queries, project_id=None):
"""
Executes an arbitrary DML query (INSERT, UPDATE, DELETE).
: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.
... | [
"Executes",
"an",
"arbitrary",
"DML",
"query",
"(",
"INSERT",
"UPDATE",
"DELETE",
")",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/gcp_spanner_hook.py#L328-L344 | [
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".",
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"instance_id... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | ImapAttachmentSensor.poke | 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 | airflow/contrib/sensors/imap_attachment_sensor.py | 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
"""
... | 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
"""
... | [
"Pokes",
"for",
"a",
"mail",
"attachment",
"on",
"the",
"mail",
"server",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/sensors/imap_attachment_sensor.py#L60-L76 | [
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... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | prepare_additional_parameters | Creates additional_properties parameter based on language_hints, web_detection_params and
additional_properties parameters specified by the user | airflow/contrib/operators/gcp_vision_operator.py | 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 ... | 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 ... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/gcp_vision_operator.py#L1221-L1244 | [
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"additional_properties",
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"additional... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | CassandraHook.get_conn | Returns a cassandra Session object | airflow/contrib/hooks/cassandra_hook.py | def get_conn(self):
"""
Returns a cassandra Session object
"""
if self.session and not self.session.is_shutdown:
return self.session
self.session = self.cluster.connect(self.keyspace)
return self.session | def get_conn(self):
"""
Returns a cassandra Session object
"""
if self.session and not self.session.is_shutdown:
return self.session
self.session = self.cluster.connect(self.keyspace)
return self.session | [
"Returns",
"a",
"cassandra",
"Session",
"object"
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/cassandra_hook.py#L108-L115 | [
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test | CassandraHook.table_exists | Checks if a table exists in Cassandra
:param table: Target Cassandra table.
Use dot notation to target a specific keyspace.
:type table: str | airflow/contrib/hooks/cassandra_hook.py | 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:
keyspac... | 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:
keyspac... | [
"Checks",
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/cassandra_hook.py#L164-L177 | [
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test | CassandraHook.record_exists | 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 | airflow/contrib/hooks/cassandra_hook.py | 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.
:t... | 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.
:t... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/cassandra_hook.py#L179-L200 | [
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test | SparkSubmitHook._build_spark_submit_command | Construct the spark-submit command to execute.
:param application: command to append to the spark-submit command
:type application: str
:return: full command to be executed | airflow/contrib/hooks/spark_submit_hook.py | def _build_spark_submit_command(self, application):
"""
Construct the spark-submit command to execute.
:param application: command to append to the spark-submit command
:type application: str
:return: full command to be executed
"""
connection_cmd = self._get_spar... | def _build_spark_submit_command(self, application):
"""
Construct the spark-submit command to execute.
:param application: command to append to the spark-submit command
:type application: str
:return: full command to be executed
"""
connection_cmd = self._get_spar... | [
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test | SparkSubmitHook._build_track_driver_status_command | Construct the command to poll the driver status.
:return: full command to be executed | airflow/contrib/hooks/spark_submit_hook.py | 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._connecti... | 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._connecti... | [
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test | SparkSubmitHook.submit | 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) | airflow/contrib/hooks/spark_submit_hook.py | 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 = sel... | 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 = sel... | [
"Remote",
"Popen",
"to",
"execute",
"the",
"spark",
"-",
"submit",
"job"
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/spark_submit_hook.py#L322-L376 | [
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test | SparkSubmitHook._process_spark_submit_log | 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... | airflow/contrib/hooks/spark_submit_hook.py | 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 tra... | 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 tra... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/spark_submit_hook.py#L378-L429 | [
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test | SparkSubmitHook._process_spark_status_log | parses the logs of the spark driver status query process
:param itr: An iterator which iterates over the input of the subprocess | airflow/contrib/hooks/spark_submit_hook.py | 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... | 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... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/spark_submit_hook.py#L431-L446 | [
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test | SparkSubmitHook._start_driver_status_tracking | Polls the driver based on self._driver_id to get the status.
Finish successfully when the status is FINISHED.
Finish failed when the status is ERROR/UNKNOWN/KILLED/FAILED.
Possible status:
SUBMITTED
Submitted but not yet scheduled on a worker
RUNNING
Has... | airflow/contrib/hooks/spark_submit_hook.py | def _start_driver_status_tracking(self):
"""
Polls the driver based on self._driver_id to get the status.
Finish successfully when the status is FINISHED.
Finish failed when the status is ERROR/UNKNOWN/KILLED/FAILED.
Possible status:
SUBMITTED
Submitted but ... | def _start_driver_status_tracking(self):
"""
Polls the driver based on self._driver_id to get the status.
Finish successfully when the status is FINISHED.
Finish failed when the status is ERROR/UNKNOWN/KILLED/FAILED.
Possible status:
SUBMITTED
Submitted but ... | [
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"/"... | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/spark_submit_hook.py#L448-L511 | [
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"missed_job_status... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | SparkSubmitHook._build_spark_driver_kill_command | Construct the spark-submit command to kill a driver.
:return: full command to kill a driver | airflow/contrib/hooks/spark_submit_hook.py | def _build_spark_driver_kill_command(self):
"""
Construct the spark-submit command to kill a driver.
:return: full command to kill a driver
"""
# If the spark_home is passed then build the spark-submit executable path using
# the spark_home; otherwise assume that spark-s... | def _build_spark_driver_kill_command(self):
"""
Construct the spark-submit command to kill a driver.
:return: full command to kill a driver
"""
# If the spark_home is passed then build the spark-submit executable path using
# the spark_home; otherwise assume that spark-s... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/hooks/spark_submit_hook.py#L513-L537 | [
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"... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | get_task_runner | 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_t... | airflow/task/task_runner/__init__.py | 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 ... | 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 ... | [
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"runner",
"that",
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"used",
"to",
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"the",
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/task/task_runner/__init__.py#L27-L43 | [
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"contri... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | AWSBatchOperator._wait_for_task_ended | 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 | airflow/contrib/operators/awsbatch_operator.py | 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:... | 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:... | [
"Try",
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"a",
"waiter",
"from",
"the",
"below",
"pull",
"request"
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/awsbatch_operator.py#L117-L145 | [
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test | MySqlToGoogleCloudStorageOperator._query_mysql | Queries mysql and returns a cursor to the results. | airflow/contrib/operators/mysql_to_gcs.py | 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 | 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 | [
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"to",
"the",
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"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/mysql_to_gcs.py#L134-L142 | [
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"exec... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | MySqlToGoogleCloudStorageOperator._write_local_data_files | Takes a cursor, and writes results to a local file.
:return: A dictionary where keys are filenames to be used as object
names in GCS, and values are file handles to local files that
contain the data for the GCS objects. | airflow/contrib/operators/mysql_to_gcs.py | def _write_local_data_files(self, cursor):
"""
Takes a cursor, and writes results to a local file.
:return: A dictionary where keys are filenames to be used as object
names in GCS, and values are file handles to local files that
contain the data for the GCS objects.
... | def _write_local_data_files(self, cursor):
"""
Takes a cursor, and writes results to a local file.
:return: A dictionary where keys are filenames to be used as object
names in GCS, and values are file handles to local files that
contain the data for the GCS objects.
... | [
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"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/mysql_to_gcs.py#L144-L199 | [
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test | MySqlToGoogleCloudStorageOperator._configure_csv_file | Configure a csv writer with the file_handle and write schema
as headers for the new file. | airflow/contrib/operators/mysql_to_gcs.py | 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.w... | 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.w... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/mysql_to_gcs.py#L201-L208 | [
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".... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | MySqlToGoogleCloudStorageOperator._write_local_schema_file | 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 ... | airflow/contrib/operators/mysql_to_gcs.py | 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 file... | 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 file... | [
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"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/mysql_to_gcs.py#L210-L253 | [
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"schema",... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | MySqlToGoogleCloudStorageOperator._upload_to_gcs | Upload all of the file splits (and optionally the schema .json file) to
Google cloud storage. | airflow/contrib/operators/mysql_to_gcs.py | def _upload_to_gcs(self, files_to_upload):
"""
Upload all of the file splits (and optionally the schema .json file) to
Google cloud storage.
"""
hook = GoogleCloudStorageHook(
google_cloud_storage_conn_id=self.google_cloud_storage_conn_id,
delegate_to=self... | def _upload_to_gcs(self, files_to_upload):
"""
Upload all of the file splits (and optionally the schema .json file) to
Google cloud storage.
"""
hook = GoogleCloudStorageHook(
google_cloud_storage_conn_id=self.google_cloud_storage_conn_id,
delegate_to=self... | [
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"to",
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"cloud",
"storage",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/mysql_to_gcs.py#L255-L266 | [
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"tm... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | MySqlToGoogleCloudStorageOperator._convert_types | Takes a value from MySQLdb, and converts it to a value that's safe for
JSON/Google cloud storage/BigQuery. Dates are converted to UTC seconds.
Decimals are converted to floats. Binary type fields are encoded with base64,
as imported BYTES data must be base64-encoded according to Bigquery SQL
... | airflow/contrib/operators/mysql_to_gcs.py | def _convert_types(schema, col_type_dict, row):
"""
Takes a value from MySQLdb, and converts it to a value that's safe for
JSON/Google cloud storage/BigQuery. Dates are converted to UTC seconds.
Decimals are converted to floats. Binary type fields are encoded with base64,
as impo... | def _convert_types(schema, col_type_dict, row):
"""
Takes a value from MySQLdb, and converts it to a value that's safe for
JSON/Google cloud storage/BigQuery. Dates are converted to UTC seconds.
Decimals are converted to floats. Binary type fields are encoded with base64,
as impo... | [
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"/",
"BigQuery",
".",
"Dates",
"are",
"converted",
"to",
"UTC",
"seconds",
".",
"Decimals",
"are... | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/mysql_to_gcs.py#L269-L288 | [
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"da... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | MySqlToGoogleCloudStorageOperator._get_col_type_dict | Return a dict of column name and column type based on self.schema if not None. | airflow/contrib/operators/mysql_to_gcs.py | 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 =... | 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 =... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/mysql_to_gcs.py#L290-L310 | [
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"(",... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | MySqlToGoogleCloudStorageOperator.type_map | Helper function that maps from MySQL fields to BigQuery fields. Used
when a schema_filename is set. | airflow/contrib/operators/mysql_to_gcs.py | 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',
FIE... | 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',
FIE... | [
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"fields",
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"Used",
"when",
"a",
"schema_filename",
"is",
"set",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/mysql_to_gcs.py#L313-L334 | [
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"'INTEGER'",
",",
"FIELD_TYPE",
".",
"DATETIME"... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | authenticate | Authenticate a PasswordUser with the specified
username/password.
:param session: An active SQLAlchemy session
:param username: The username
:param password: The password
:raise AuthenticationError: if an error occurred
:return: a PasswordUser | airflow/contrib/auth/backends/password_auth.py | def authenticate(session, username, password):
"""
Authenticate a PasswordUser with the specified
username/password.
:param session: An active SQLAlchemy session
:param username: The username
:param password: The password
:raise AuthenticationError: if an error occurred
:return: a Pass... | def authenticate(session, username, password):
"""
Authenticate a PasswordUser with the specified
username/password.
:param session: An active SQLAlchemy session
:param username: The username
:param password: The password
:raise AuthenticationError: if an error occurred
:return: a Pass... | [
"Authenticate",
"a",
"PasswordUser",
"with",
"the",
"specified",
"username",
"/",
"password",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/auth/backends/password_auth.py#L107-L132 | [
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"filter... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | SqoopOperator.execute | Execute sqoop job | airflow/contrib/operators/sqoop_operator.py | 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,... | 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,... | [
"Execute",
"sqoop",
"job"
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/contrib/operators/sqoop_operator.py#L166-L234 | [
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"num_mappers",
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"hcatalo... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | apply_lineage | Saves the lineage to XCom and if configured to do so sends it
to the backend. | airflow/lineage/__init__.py | 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",
... | 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",
... | [
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"so",
"sends",
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"to",
"the",
"backend",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/lineage/__init__.py#L48-L82 | [
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... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | prepare_lineage | Prepares the lineage inlets and outlets. Inlets can be:
* "auto" -> picks up any outlets from direct upstream tasks that have outlets defined, as such that
if A -> B -> C and B does not have outlets but A does, these are provided as inlets.
* "list of task_ids" -> picks up outlets from the upstream task_... | airflow/lineage/__init__.py | def prepare_lineage(func):
"""
Prepares the lineage inlets and outlets. Inlets can be:
* "auto" -> picks up any outlets from direct upstream tasks that have outlets defined, as such that
if A -> B -> C and B does not have outlets but A does, these are provided as inlets.
* "list of task_ids" -> p... | def prepare_lineage(func):
"""
Prepares the lineage inlets and outlets. Inlets can be:
* "auto" -> picks up any outlets from direct upstream tasks that have outlets defined, as such that
if A -> B -> C and B does not have outlets but A does, these are provided as inlets.
* "list of task_ids" -> p... | [
"Prepares",
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"lineage",
"inlets",
"and",
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".",
"Inlets",
"can",
"be",
":"
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/lineage/__init__.py#L85-L140 | [
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"\"Preparing lineage inlets and ... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | Connection.extra_dejson | Returns the extra property by deserializing json. | airflow/models/connection.py | def extra_dejson(self):
"""Returns the extra property by deserializing json."""
obj = {}
if self.extra:
try:
obj = json.loads(self.extra)
except Exception as e:
self.log.exception(e)
self.log.error("Failed parsing the json f... | def extra_dejson(self):
"""Returns the extra property by deserializing json."""
obj = {}
if self.extra:
try:
obj = json.loads(self.extra)
except Exception as e:
self.log.exception(e)
self.log.error("Failed parsing the json f... | [
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"deserializing",
"json",
"."
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/models/connection.py#L286-L296 | [
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"... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | date_range | 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), date... | airflow/utils/dates.py | 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... | 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... | [
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"... | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/dates.py#L36-L111 | [
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"... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | round_time | Returns the datetime of the form start_date + i * delta
which is closest to dt for any non-negative integer i.
Note that delta may be a datetime.timedelta or a dateutil.relativedelta
>>> round_time(datetime(2015, 1, 1, 6), timedelta(days=1))
datetime.datetime(2015, 1, 1, 0, 0)
>>> round_time(datetim... | airflow/utils/dates.py | def round_time(dt, delta, start_date=timezone.make_aware(datetime.min)):
"""
Returns the datetime of the form start_date + i * delta
which is closest to dt for any non-negative integer i.
Note that delta may be a datetime.timedelta or a dateutil.relativedelta
>>> round_time(datetime(2015, 1, 1, 6), ... | def round_time(dt, delta, start_date=timezone.make_aware(datetime.min)):
"""
Returns the datetime of the form start_date + i * delta
which is closest to dt for any non-negative integer i.
Note that delta may be a datetime.timedelta or a dateutil.relativedelta
>>> round_time(datetime(2015, 1, 1, 6), ... | [
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... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | infer_time_unit | Determine the most appropriate time unit for an array of time durations
specified in seconds.
e.g. 5400 seconds => 'minutes', 36000 seconds => 'hours' | airflow/utils/dates.py | def infer_time_unit(time_seconds_arr):
"""
Determine the most appropriate time unit for an array of time durations
specified in seconds.
e.g. 5400 seconds => 'minutes', 36000 seconds => 'hours'
"""
if len(time_seconds_arr) == 0:
return 'hours'
max_time_seconds = max(time_seconds_arr)... | def infer_time_unit(time_seconds_arr):
"""
Determine the most appropriate time unit for an array of time durations
specified in seconds.
e.g. 5400 seconds => 'minutes', 36000 seconds => 'hours'
"""
if len(time_seconds_arr) == 0:
return 'hours'
max_time_seconds = max(time_seconds_arr)... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/dates.py#L195-L211 | [
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":",
"r... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | scale_time_units | Convert an array of time durations in seconds to the specified time unit. | airflow/utils/dates.py | 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_s... | 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_s... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/dates.py#L214-L224 | [
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"==",... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | days_ago | Get a datetime object representing `n` days ago. By default the time is
set to midnight. | airflow/utils/dates.py | 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... | 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... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/utils/dates.py#L227-L237 | [
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"min... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | get_dag_runs | Returns a list of Dag Runs for a specific DAG ID.
:param dag_id: String identifier of a DAG
:param state: queued|running|success...
:return: List of DAG runs of a DAG with requested state,
or all runs if the state is not specified | airflow/api/common/experimental/get_dag_runs.py | def get_dag_runs(dag_id, state=None):
"""
Returns a list of Dag Runs for a specific DAG ID.
:param dag_id: String identifier of a DAG
:param state: queued|running|success...
:return: List of DAG runs of a DAG with requested state,
or all runs if the state is not specified
"""
dagbag = Da... | def get_dag_runs(dag_id, state=None):
"""
Returns a list of Dag Runs for a specific DAG ID.
:param dag_id: String identifier of a DAG
:param state: queued|running|success...
:return: List of DAG runs of a DAG with requested state,
or all runs if the state is not specified
"""
dagbag = Da... | [
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test | AirflowSecurityManager.init_role | Initialize the role with the permissions and related view-menus.
:param role_name:
:param role_vms:
:param role_perms:
:return: | airflow/www/security.py | 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()
... | 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()
... | [
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"-",
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L175-L202 | [
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test | AirflowSecurityManager.delete_role | Delete the given Role
:param role_name: the name of a role in the ab_role table | airflow/www/security.py | 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)\
.f... | 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)\
.f... | [
"Delete",
"the",
"given",
"Role"
] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L204-L219 | [
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"r... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | AirflowSecurityManager.get_user_roles | 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. | airflow/www/security.py | 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_... | 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_... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L221-L234 | [
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"'AUTH... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | AirflowSecurityManager.get_all_permissions_views | Returns a set of tuples with the perm name and view menu name | airflow/www/security.py | def get_all_permissions_views(self):
"""
Returns a set of tuples with the perm name and view menu name
"""
perms_views = set()
for role in self.get_user_roles():
perms_views.update({(perm_view.permission.name, perm_view.view_menu.name)
... | def get_all_permissions_views(self):
"""
Returns a set of tuples with the perm name and view menu name
"""
perms_views = set()
for role in self.get_user_roles():
perms_views.update({(perm_view.permission.name, perm_view.view_menu.name)
... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L236-L244 | [
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test | AirflowSecurityManager.get_accessible_dag_ids | Return a set of dags that user has access to(either read or write).
:param username: Name of the user.
:return: A set of dag ids that the user could access. | airflow/www/security.py | def get_accessible_dag_ids(self, username=None):
"""
Return a set of dags that user has access to(either read or write).
:param username: Name of the user.
:return: A set of dag ids that the user could access.
"""
if not username:
username = g.user
i... | def get_accessible_dag_ids(self, username=None):
"""
Return a set of dags that user has access to(either read or write).
:param username: Name of the user.
:return: A set of dag ids that the user could access.
"""
if not username:
username = g.user
i... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L246-L266 | [
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test | AirflowSecurityManager.has_access | Verify whether a given user could perform certain permission
(e.g can_read, can_write) on the given dag_id.
:param permission: permission on dag_id(e.g can_read, can_edit).
:type permission: str
:param view_name: name of view-menu(e.g dag id is a view-menu as well).
:type view_n... | airflow/www/security.py | def has_access(self, permission, view_name, user=None):
"""
Verify whether a given user could perform certain permission
(e.g can_read, can_write) on the given dag_id.
:param permission: permission on dag_id(e.g can_read, can_edit).
:type permission: str
:param view_name... | def has_access(self, permission, view_name, user=None):
"""
Verify whether a given user could perform certain permission
(e.g can_read, can_write) on the given dag_id.
:param permission: permission on dag_id(e.g can_read, can_edit).
:type permission: str
:param view_name... | [
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... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | AirflowSecurityManager._has_role | Whether the user has this role name | airflow/www/security.py | 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()]) | 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()]) | [
"Whether",
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"has",
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L294-L301 | [
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test | AirflowSecurityManager._has_perm | Whether the user has this perm | airflow/www/security.py | 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()
... | 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()
... | [
"Whether",
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L303-L312 | [
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test | AirflowSecurityManager.clean_perms | FAB leaves faulty permissions that need to be cleaned up | airflow/www/security.py | 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.Permiss... | 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.Permiss... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L326-L342 | [
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test | AirflowSecurityManager._merge_perm | 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 vie... | airflow/www/security.py | 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.
... | 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.
... | [
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test | AirflowSecurityManager.create_custom_dag_permission_view | Workflow:
1. Fetch all the existing (permissions, view-menu) from Airflow DB.
2. Fetch all the existing dag models that are either active or paused. Exclude the subdags.
3. Create both read and write permission view-menus relation for every dags from step 2
4. Find out all the dag specif... | airflow/www/security.py | def create_custom_dag_permission_view(self, session=None):
"""
Workflow:
1. Fetch all the existing (permissions, view-menu) from Airflow DB.
2. Fetch all the existing dag models that are either active or paused. Exclude the subdags.
3. Create both read and write permission view-m... | def create_custom_dag_permission_view(self, session=None):
"""
Workflow:
1. Fetch all the existing (permissions, view-menu) from Airflow DB.
2. Fetch all the existing dag models that are either active or paused. Exclude the subdags.
3. Create both read and write permission view-m... | [
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"'Fetching a set of all permission, view_menu from FAB meta-table'",
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"merge_pv",
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"perm",
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":... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | AirflowSecurityManager.update_admin_perm_view | Admin should have all the permission-views.
Add the missing ones to the table for admin.
:return: None. | airflow/www/security.py | 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_me... | 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_me... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L440-L453 | [
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"per... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | AirflowSecurityManager.sync_roles | 1. Init the default role(Admin, Viewer, User, Op, public)
with related permissions.
2. Init the custom role(dag-user) with related permissions.
:return: None. | airflow/www/security.py | def sync_roles(self):
"""
1. Init the default role(Admin, Viewer, User, Op, public)
with related permissions.
2. Init the custom role(dag-user) with related permissions.
:return: None.
"""
self.log.debug('Start syncing user roles.')
# Create global all... | def sync_roles(self):
"""
1. Init the default role(Admin, Viewer, User, Op, public)
with related permissions.
2. Init the custom role(dag-user) with related permissions.
:return: None.
"""
self.log.debug('Start syncing user roles.')
# Create global all... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L455-L477 | [
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".... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
test | AirflowSecurityManager.sync_perm_for_dag | Sync permissions for given dag id. The dag id surely exists in our dag bag
as only / refresh button or cli.sync_perm will call this function
: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 rolena... | airflow/www/security.py | def sync_perm_for_dag(self, dag_id, access_control=None):
"""
Sync permissions for given dag id. The dag id surely exists in our dag bag
as only / refresh button or cli.sync_perm will call this function
:param dag_id: the ID of the DAG whose permissions should be updated
:type d... | def sync_perm_for_dag(self, dag_id, access_control=None):
"""
Sync permissions for given dag id. The dag id surely exists in our dag bag
as only / refresh button or cli.sync_perm will call this function
:param dag_id: the ID of the DAG whose permissions should be updated
:type d... | [
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] | apache/airflow | python | https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/www/security.py#L479-L498 | [
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"... | b69c686ad8a0c89b9136bb4b31767257eb7b2597 |
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