`airflow.models`¶

Airflow models

Package Contents¶

Classes¶

`BaseOperator`	Abstract base class for all operators. Since operators create objects that
`BaseOperatorLink`	Abstract base class that defines how we get an operator link.
`Connection`	Placeholder to store information about different database instances
`DAG`	A dag (directed acyclic graph) is a collection of tasks with directional
`DagModel`	Table containing DAG properties
`DagTag`	A tag name per dag, to allow quick filtering in the DAG view.
`DagBag`	A dagbag is a collection of dags, parsed out of a folder tree and has high
`DagPickle`	Dags can originate from different places (user repos, main repo, ...)
`DagRun`	DagRun describes an instance of a Dag. It can be created
`DbCallbackRequest`	Used to handle callbacks through database.
`ImportError`	A table to store all Import Errors. The ImportErrors are recorded when parsing DAGs.
`Log`	Used to actively log events to the database
`MappedOperator`	Object representing a mapped operator in a DAG.
`Param`	Class to hold the default value of a Param and rule set to do the validations. Without the rule set
`Pool`	the class to get Pool info.
`RenderedTaskInstanceFields`	Save Rendered Template Fields
`SensorInstance`	SensorInstance support the smart sensor service. It stores the sensor task states
`SkipMixin`	A Mixin to skip Tasks Instances
`SlaMiss`	Model that stores a history of the SLA that have been missed.
`TaskFail`	TaskFail tracks the failed run durations of each task instance.
`TaskInstance`	Task instances store the state of a task instance. This table is the
`TaskReschedule`	TaskReschedule tracks rescheduled task instances.
`Trigger`	Triggers are a workload that run in an asynchronous event loop shared with
`Variable`	Variables are a generic way to store and retrieve arbitrary content or settings

Functions¶

clear_task_instances(tis, session[, ...])

Clears a set of task instances, but makes sure the running ones

Attributes¶

`ID_LEN`
`Base`
`Operator`
`XCOM_RETURN_KEY`
`XCom`

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