Timedelta object gets added to your latest task instance’sĮxecution_date to figure out the next schedule Schedule_interval ( datetime.timedelta orĭ or str that acts as a cronĮxpression) – Defines how often that DAG runs, this A task_id can only beĭescription ( str) – The description for the DAG to e.g. Until their previous schedule (and upstream tasks) are completed.ĭAGs essentially act as namespaces for tasks. The property of depending on their own past, meaning that they can’t run For each schedule, (say daily or hourly), the DAG needs to runĮach individual tasks as their dependencies are met. A dag also has a schedule, a start date and an end date DAG ( dag_id, description = None, schedule_interval = timedelta(days=1), start_date = None, end_date = None, full_filepath = None, template_searchpath = None, template_undefined = jinja2.Undefined, user_defined_macros = None, user_defined_filters = None, default_args = None, concurrency = conf.getint('core', 'dag_concurrency'), max_active_runs = conf.getint('core', 'max_active_runs_per_dag'), dagrun_timeout = None, sla_miss_callback = None, default_view = None, orientation = conf.get('webserver', 'dag_orientation'), catchup = conf.getboolean('scheduler', 'catchup_by_default'), on_success_callback = None, on_failure_callback = None, doc_md = None, params = None, access_control = None, is_paused_upon_creation = None, jinja_environment_kwargs = None, tags = None ) ¶īases: _dag.BaseDag, _mixin.LoggingMixinĪ dag (directed acyclic graph) is a collection of tasks with directionalĭependencies. get_last_dagrun ( dag_id, session, include_externally_triggered = False ) ¶ Returns the last dag run for a dag, None if there was none. Still have up to 3600 seconds in total for it to succeed.Module Contents ¶. It can retry up to 2 times as defined by retries. If the sensor fails due to other reasons such as network outages during the 3600 seconds interval, It will not retry when this error is raised. In other words, if the fileĭoes not appear on the SFTP server within 3600 seconds, the sensor will raise AirflowSensorTimeout. The sensor is allowed maximum 3600 seconds as defined by timeout.

It can retry up to 2 times as defined by retries.įrom the start of the first execution, till it eventually succeeds (i.e. The sensor is allowed to retry when this happens. If it takes the sensor more than 60 seconds to poke the SFTP server, AirflowTaskTimeout will be raised. Is periodically executed and rescheduled until it succeeds.Įach time the sensor pokes the SFTP server, it is allowed to take maximum 60 seconds as defined by execution_timeout. The sensor is in reschedule mode, meaning it The following SFTPSensor example illustrates this. If timeout is breached, AirflowSensorTimeout will be raised and the sensor fails immediately This only matters for sensors in reschedule mode. In addition, sensors have a timeout parameter. If execution_timeout is breached, the task times out and Maximum time allowed for every execution. This applies to all Airflow tasks, including sensors. If you want a task to have a maximum runtime, set its execution_timeout attribute to a datetime.timedelta value When any custom Task (Operator) is running, it will get a copy of the task instance passed to it as well as being able to inspect task metadata, it also contains methods for things like XComs. Ideally, a task should flow from none, to scheduled, to queued, to running, and finally to success. Removed: The task has vanished from the DAG since the run started Up_for_reschedule: The task is a Sensor that is in reschedule modeĭeferred: The task has been deferred to a trigger Up_for_retry: The task failed, but has retry attempts left and will be rescheduled. Upstream_failed: An upstream task failed and the Trigger Rule says we needed it Skipped: The task was skipped due to branching, LatestOnly, or similar. Restarting: The task was externally requested to restart when it was runningįailed: The task had an error during execution and failed to run Success: The task finished running without errors Running: The task is running on a worker (or on a local/synchronous executor) Queued: The task has been assigned to an Executor and is awaiting a worker

Scheduled: The scheduler has determined the Task’s dependencies are met and it should run None: The Task has not yet been queued for execution (its dependencies are not yet met) The possible states for a Task Instance are: They are also the representation of a Task that has state, representing what stage of the lifecycle it is in. Much in the same way that a DAG is instantiated into a DAG Run each time it runs, the tasks under a DAG are instantiated into Task Instances.Īn instance of a Task is a specific run of that task for a given DAG (and thus for a given data interval).

Airflow dag owner