API Reference ============= Operators --------- Operators allow for generation of certain types of tasks that become nodes in the DAG when instantiated. All operators derive from BaseOperator and inherit many attributes and methods that way. Refer to the BaseOperator documentation for more details. There are 3 main types of operators: - Operators that performs an **action**, or tell another system to perform an action - **Transfer** operators move data from one system to another - **Sensors** are a certain type of operator that will keep running until a certain criterion is met. Examples include a specific file landing in HDFS or S3, a partition appearing in Hive, or a specific time of the day. Sensors are derived from ``BaseSensorOperator`` and run a poke method at a specified ``poke_interval`` until it returns ``True``. BaseOperator '''''''''''' All operators are derived from ``BaseOperator`` and acquire much functionality through inheritance. Since this is the core of the engine, it's worth taking the time to understand the parameters of ``BaseOperator`` to understand the primitive features that can be leveraged in your DAGs. .. autoclass:: airflow.models.BaseOperator BaseSensorOperator ''''''''''''''''''' All sensors are derived from ``BaseSensorOperator``. All sensors inherit the ``timeout`` and ``poke_interval`` on top of the ``BaseOperator`` attributes. .. autoclass:: airflow.operators.sensors.BaseSensorOperator Operator API '''''''''''' .. automodule:: airflow.operators :show-inheritance: :members: BashOperator, BranchPythonOperator, TriggerDagRunOperator, DummyOperator, EmailOperator, ExternalTaskSensor, GenericTransfer, HdfsSensor, Hive2SambaOperator, HiveOperator, HivePartitionSensor, HiveToDruidTransfer, HiveToMySqlTransfer, SimpleHttpOperator, HttpSensor, MetastorePartitionSensor, MsSqlOperator, MsSqlToHiveTransfer, MySqlOperator, MySqlToHiveTransfer, NamedHivePartitionSensor, PostgresOperator, PrestoCheckOperator, PrestoIntervalCheckOperator, PrestoValueCheckOperator, PythonOperator, S3KeySensor, S3ToHiveTransfer, ShortCircuitOperator, SlackAPIOperator, SlackAPIPostOperator, SqlSensor, SubDagOperator, TimeSensor, WebHdfsSensor .. autoclass:: airflow.operators.docker_operator.DockerOperator Community-contributed Operators ''''''''''''''''''''''''''''''' .. automodule:: airflow.contrib.operators :show-inheritance: :members: SSHExecuteOperator, VerticaOperator, VerticaToHiveTransfer .. autoclass:: airflow.contrib.operators.bigquery_operator.BigQueryOperator .. autoclass:: airflow.contrib.operators.bigquery_to_gcs.BigQueryToCloudStorageOperator .. autoclass:: airflow.contrib.operators.ecs_operator.ECSOperator .. autoclass:: airflow.contrib.operators.file_to_wasb.FileToWasbOperator .. autoclass:: airflow.contrib.operators.gcs_download_operator.GoogleCloudStorageDownloadOperator .. autoclass:: airflow.contrib.operators.QuboleOperator .. autoclass:: airflow.contrib.operators.hipchat_operator.HipChatAPIOperator .. autoclass:: airflow.contrib.operators.hipchat_operator.HipChatAPISendRoomNotificationOperator .. _macros: Macros --------- Here's a list of variables and macros that can be used in templates Default Variables ''''''''''''''''' The Airflow engine passes a few variables by default that are accessible in all templates ================================= ==================================== Variable Description ================================= ==================================== ``{{ ds }}`` the execution date as ``YYYY-MM-DD`` ``{{ ds_nodash }}`` the execution date as ``YYYYMMDD`` ``{{ yesterday_ds }}`` yesterday's date as ``YYYY-MM-DD`` ``{{ yesterday_ds_nodash }}`` yesterday's date as ``YYYYMMDD`` ``{{ tomorrow_ds }}`` tomorrow's date as ``YYYY-MM-DD`` ``{{ tomorrow_ds_nodash }}`` tomorrow's date as ``YYYYMMDD`` ``{{ ts }}`` same as ``execution_date.isoformat()`` ``{{ ts_nodash }}`` same as ``ts`` without ``-`` and ``:`` ``{{ execution_date }}`` the execution_date, (datetime.datetime) ``{{ prev_execution_date }}`` the previous execution date (if available) (datetime.datetime) ``{{ next_execution_date }}`` the next execution date (datetime.datetime) ``{{ dag }}`` the DAG object ``{{ task }}`` the Task object ``{{ macros }}`` a reference to the macros package, described below ``{{ task_instance }}`` the task_instance object ``{{ end_date }}`` same as ``{{ ds }}`` ``{{ latest_date }}`` same as ``{{ ds }}`` ``{{ ti }}`` same as ``{{ task_instance }}`` ``{{ params }}`` a reference to the user-defined params dictionary ``{{ var.value.my_var }}`` global defined variables represented as a dictionary ``{{ var.json.my_var.path }}`` global defined variables represented as a dictionary with deserialized JSON object, append the path to the key within the JSON object ``{{ task_instance_key_str }}`` a unique, human-readable key to the task instance formatted ``{dag_id}_{task_id}_{ds}`` ``conf`` the full configuration object located at ``airflow.configuration.conf`` which represents the content of your ``airflow.cfg`` ``run_id`` the ``run_id`` of the current DAG run ``dag_run`` a reference to the DagRun object ``test_mode`` whether the task instance was called using the CLI's test subcommand ================================= ==================================== Note that you can access the object's attributes and methods with simple dot notation. Here are some examples of what is possible: ``{{ task.owner }}``, ``{{ task.task_id }}``, ``{{ ti.hostname }}``, ... Refer to the models documentation for more information on the objects' attributes and methods. The ``var`` template variable allows you to access variables defined in Airflow's UI. You can access them as either plain-text or JSON. If you use JSON, you are also able to walk nested structures, such as dictionaries like: ``{{ var.json.my_dict_var.key1 }}`` Macros '''''' Macros are a way to expose objects to your templates and live under the ``macros`` namespace in your templates. A few commonly used libraries and methods are made available. ================================= ==================================== Variable Description ================================= ==================================== ``macros.datetime`` The standard lib's ``datetime.datetime`` ``macros.timedelta`` The standard lib's ``datetime.timedelta`` ``macros.dateutil`` A reference to the ``dateutil`` package ``macros.time`` The standard lib's ``time`` ``macros.uuid`` The standard lib's ``uuid`` ``macros.random`` The standard lib's ``random`` ================================= ==================================== Some airflow specific macros are also defined: .. automodule:: airflow.macros :show-inheritance: :members: .. automodule:: airflow.macros.hive :show-inheritance: :members: .. _models_ref: Models ------ Models are built on top of the SQLAlchemy ORM Base class, and instances are persisted in the database. .. automodule:: airflow.models :show-inheritance: :members: DAG, BaseOperator, TaskInstance, DagBag, Connection Hooks ----- .. automodule:: airflow.hooks :show-inheritance: :members: DbApiHook, HiveCliHook, HiveMetastoreHook, HiveServer2Hook, HttpHook, DruidHook, MsSqlHook, MySqlHook, PostgresHook, PrestoHook, S3Hook, SqliteHook, WebHDFSHook Community contributed hooks ''''''''''''''''''''''''''' .. automodule:: airflow.contrib.hooks :show-inheritance: :members: BigQueryHook, GoogleCloudStorageHook, VerticaHook, FTPHook, SSHHook, CloudantHook .. autoclass:: airflow.contrib.hooks.gcs_hook.GoogleCloudStorageHook Executors --------- Executors are the mechanism by which task instances get run. .. automodule:: airflow.executors :show-inheritance: :members: LocalExecutor, CeleryExecutor, SequentialExecutor Community-contributed executors ''''''''''''''''''''''''''''''' .. autoclass:: airflow.contrib.executors.mesos_executor.MesosExecutor