Python 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.
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
BaseSensorOperatorand run a poke method at a specifiedpoke_intervaluntil it returnsTrue.
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.
BaseSensorOperator¶
All sensors are derived from BaseSensorOperator. All sensors inherit
the timeout and poke_interval on top of the BaseOperator
attributes.
Hooks¶
Hooks are interfaces to external platforms and databases, implementing a common
interface when possible and acting as building blocks for operators. All hooks
are derived from BaseHook.
Executors¶
Executors are the mechanism by which task instances get run. All executors are
derived from BaseExecutor.
Models¶
Models are built on top of the SQLAlchemy ORM Base class, and instances are persisted in the database.
Exceptions¶
Secrets Backends¶
Airflow relies on secrets backends to retrieve Connection objects.
All secrets backends derive from BaseSecretsBackend.
Timetables¶
Custom timetable implementations provide Airflow’s scheduler additional logic to schedule DAG runs in ways not possible with built-in schedule expressions.