| :py:mod:`airflow.models.dagrun` |
| =============================== |
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| .. py:module:: airflow.models.dagrun |
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| Module Contents |
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| Classes |
| ~~~~~~~ |
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| .. autoapisummary:: |
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| airflow.models.dagrun.TISchedulingDecision |
| airflow.models.dagrun.DagRun |
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| .. py:class:: TISchedulingDecision |
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| Bases: :py:obj:`NamedTuple` |
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| Type of return for DagRun.task_instance_scheduling_decisions |
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| .. py:attribute:: tis |
| :annotation: :List[airflow.models.taskinstance.TaskInstance] |
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| .. py:attribute:: schedulable_tis |
| :annotation: :List[airflow.models.taskinstance.TaskInstance] |
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| .. py:attribute:: changed_tis |
| :annotation: :bool |
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| .. py:attribute:: unfinished_tis |
| :annotation: :List[airflow.models.taskinstance.TaskInstance] |
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| .. py:attribute:: finished_tis |
| :annotation: :List[airflow.models.taskinstance.TaskInstance] |
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| .. py:class:: DagRun(dag_id = None, run_id = None, queued_at = NOTSET, execution_date = None, start_date = None, external_trigger = None, conf = None, state = None, run_type = None, dag_hash = None, creating_job_id = None, data_interval = None) |
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| Bases: :py:obj:`airflow.models.base.Base`, :py:obj:`airflow.utils.log.logging_mixin.LoggingMixin` |
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| DagRun describes an instance of a Dag. It can be created |
| by the scheduler (for regular runs) or by an external trigger |
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| .. py:attribute:: __tablename__ |
| :annotation: = dag_run |
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| .. py:attribute:: id |
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| .. py:attribute:: dag_id |
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| .. py:attribute:: queued_at |
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| .. py:attribute:: execution_date |
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| .. py:attribute:: start_date |
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| .. py:attribute:: end_date |
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| .. py:attribute:: run_id |
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| .. py:attribute:: creating_job_id |
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| .. py:attribute:: external_trigger |
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| .. py:attribute:: run_type |
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| .. py:attribute:: conf |
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| .. py:attribute:: data_interval_start |
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| .. py:attribute:: data_interval_end |
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| .. py:attribute:: last_scheduling_decision |
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| .. py:attribute:: dag_hash |
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| .. py:attribute:: log_template_id |
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| .. py:attribute:: __table_args__ |
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| .. py:attribute:: task_instances |
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| .. py:attribute:: DEFAULT_DAGRUNS_TO_EXAMINE |
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| .. py:method:: __repr__(self) |
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| Return repr(self). |
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| .. py:method:: logical_date(self) |
| :property: |
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| .. py:method:: get_state(self) |
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| .. py:method:: set_state(self, state) |
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| .. py:method:: state(self) |
| :property: |
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| .. py:method:: refresh_from_db(self, session = NEW_SESSION) |
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| Reloads the current dagrun from the database |
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| :param session: database session |
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| .. py:method:: active_runs_of_dags(cls, dag_ids=None, only_running=False, session=None) |
| :classmethod: |
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| Get the number of active dag runs for each dag. |
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| .. py:method:: next_dagruns_to_examine(cls, state, session, max_number = None) |
| :classmethod: |
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| Return the next DagRuns that the scheduler should attempt to schedule. |
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| This will return zero or more DagRun rows that are row-level-locked with a "SELECT ... FOR UPDATE" |
| query, you should ensure that any scheduling decisions are made in a single transaction -- as soon as |
| the transaction is committed it will be unlocked. |
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| :rtype: list[airflow.models.DagRun] |
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| .. py:method:: find(cls, dag_id = None, run_id = None, execution_date = None, state = None, external_trigger = None, no_backfills = False, run_type = None, session = NEW_SESSION, execution_start_date = None, execution_end_date = None) |
| :classmethod: |
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| Returns a set of dag runs for the given search criteria. |
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| :param dag_id: the dag_id or list of dag_id to find dag runs for |
| :param run_id: defines the run id for this dag run |
| :param run_type: type of DagRun |
| :param execution_date: the execution date |
| :param state: the state of the dag run |
| :param external_trigger: whether this dag run is externally triggered |
| :param no_backfills: return no backfills (True), return all (False). |
| Defaults to False |
| :param session: database session |
| :param execution_start_date: dag run that was executed from this date |
| :param execution_end_date: dag run that was executed until this date |
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| .. py:method:: find_duplicate(cls, dag_id, run_id, execution_date, session = NEW_SESSION) |
| :classmethod: |
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| Return an existing run for the DAG with a specific run_id or execution_date. |
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| *None* is returned if no such DAG run is found. |
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| :param dag_id: the dag_id to find duplicates for |
| :param run_id: defines the run id for this dag run |
| :param execution_date: the execution date |
| :param session: database session |
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| .. py:method:: generate_run_id(run_type, execution_date) |
| :staticmethod: |
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| Generate Run ID based on Run Type and Execution Date |
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| .. py:method:: get_task_instances(self, state = None, session = NEW_SESSION) |
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| Returns the task instances for this dag run |
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| .. py:method:: get_task_instance(self, task_id, session = NEW_SESSION, *, map_index = -1) |
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| Returns the task instance specified by task_id for this dag run |
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| :param task_id: the task id |
| :param session: Sqlalchemy ORM Session |
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| .. py:method:: get_dag(self) |
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| Returns the Dag associated with this DagRun. |
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| :return: DAG |
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| .. py:method:: get_previous_dagrun(self, state = None, session = NEW_SESSION) |
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| The previous DagRun, if there is one |
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| .. py:method:: get_previous_scheduled_dagrun(self, session = NEW_SESSION) |
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| The previous, SCHEDULED DagRun, if there is one |
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| .. py:method:: update_state(self, session = NEW_SESSION, execute_callbacks = True) |
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| Determines the overall state of the DagRun based on the state |
| of its TaskInstances. |
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| :param session: Sqlalchemy ORM Session |
| :param execute_callbacks: Should dag callbacks (success/failure, SLA etc) be invoked |
| directly (default: true) or recorded as a pending request in the ``callback`` property |
| :return: Tuple containing tis that can be scheduled in the current loop & `callback` that |
| needs to be executed |
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| .. py:method:: task_instance_scheduling_decisions(self, session = NEW_SESSION) |
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| .. py:method:: verify_integrity(self, session = NEW_SESSION) |
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| Verifies the DagRun by checking for removed tasks or tasks that are not in the |
| database yet. It will set state to removed or add the task if required. |
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| :param session: Sqlalchemy ORM Session |
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| .. py:method:: get_run(session, dag_id, execution_date) |
| :staticmethod: |
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| Get a single DAG Run |
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| :meta private: |
| :param session: Sqlalchemy ORM Session |
| :param dag_id: DAG ID |
| :param execution_date: execution date |
| :return: DagRun corresponding to the given dag_id and execution date |
| if one exists. None otherwise. |
| :rtype: airflow.models.DagRun |
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| .. py:method:: is_backfill(self) |
| :property: |
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| .. py:method:: get_latest_runs(cls, session=None) |
| :classmethod: |
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| Returns the latest DagRun for each DAG |
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| .. py:method:: schedule_tis(self, schedulable_tis, session = NEW_SESSION) |
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| Set the given task instances in to the scheduled state. |
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| Each element of ``schedulable_tis`` should have it's ``task`` attribute already set. |
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| Any EmptyOperator without callbacks is instead set straight to the success state. |
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| All the TIs should belong to this DagRun, but this code is in the hot-path, this is not checked -- it |
| is the caller's responsibility to call this function only with TIs from a single dag run. |
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| .. py:method:: get_log_filename_template(self, *, session = NEW_SESSION) |
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