Public Interface of Airflow¶
The Public Interface of Apache Airflow is a set of interfaces that allow developers to interact with and access certain features of the Apache Airflow system. This includes operations such as creating and managing DAGs (Directed Acyclic Graphs), managing tasks and their dependencies, and extending Airflow capabilities by writing new executors, plugins, operators and providers. The Public Interface can be useful for building custom tools and integrations with other systems, and for automating certain aspects of the Airflow workflow.
Using Airflow Public Interfaces¶
Using Airflow Public Interfaces is needed when you want to interact with Airflow programmatically:
When you are extending Airflow classes such as Operators and Hooks. This can be done by DAG authors to add missing functionality in their DAGs or by those who write reusable custom operators for other DAG authors.
When writing new Plugins that extend Airflow’s functionality beyond DAG building blocks. Secrets, Timetables, Triggers, Listeners are all examples of such functionality. This is usually done by users who manage Airflow instances.
Bundling custom Operators, Hooks, Plugins and releasing them together via provider packages - this is usually done by those who intend to provide a reusable set of functionality for external services or applications Airflow integrates with.
All the ways above involve extending or using Airflow Python classes and functions. The classes
and functions mentioned below can be relied on to keep backwards-compatible signatures and behaviours within
MAJOR version of Airflow. On the other hand, classes and methods starting with
_ (also known
as protected Python methods) and
__ (also known as private Python methods) are not part of the Public
Airflow Interface and might change at any time.
You can also use Airflow’s Public Interface via the Stable REST API (based on the OpenAPI specification). For specific needs you can also use the Airflow Command Line Interface (CLI) though its behaviour might change in details (such as output format and available flags) so if you want to rely on those in programmatic way, the Stable REST API is recommended.
Using Public Interface to extend Airflow capabilities¶
Airflow uses Plugin mechanism to extend Airflow platform capabilities. They allow to extend Airflow UI but also they are the way to expose the below customizations (Triggers, Timetables, Listeners, etc.). Providers can also implement plugin endpoints and customize Airflow UI and the customizations.
You can read more about plugins in Plugins. You can read how to extend Airflow UI in Customize view of Apache from Airflow web UI. Note that there are some simple customizations of the UI that do not require plugins - you can read more about them in Customizing the UI.
Here are the ways how Plugins can be used to extend Airflow:
Airflow uses Triggers to implement
asyncio compatible Deferrable Operators.
All Triggers derive from
Airflow has a set of Triggers that are considered public. You are free to extend their functionality by extending them:
You can read more about Triggers in Deferrable Operators & Triggers.
Custom timetable implementations provide Airflow’s scheduler additional logic to
schedule DAG runs in ways not possible with built-in schedule expressions.
All Timetables derive from
Airflow has a set of Timetables that are considered public. You are free to extend their functionality by extending them:
You can read more about Timetables in Customizing DAG Scheduling with Timetables.
Listeners enable you to respond to DAG/Task lifecycle events.
This is implemented via
ListenerManager class that provides hooks that
can be implemented to respond to DAG/Task lifecycle events.
New in version 2.5: Listener public interface has been added in version 2.5.
You can read more about Listeners in Listeners.
Using Public Interface to integrate with external services and applications¶
Tasks in Airflow can orchestrate external services via Hooks and Operators. The core functionality of Airflow (such as authentication) can also be extended to leverage external services. You can read more about providers provider packages and core extensions they can provide in provider packages.
Executors are the mechanism by which task instances get run. All executors are
BaseExecutor. There are several
executor implementations built-in Airflow, each with its own unique characteristics and capabilities.
The executor interface itself (the BaseExecutor class) is public, but the built-in executors are not (i.e. KubernetesExecutor, LocalExecutor, etc). This means that, to use KubernetesExecutor as an example, we may make changes to KubernetesExecutor in minor or patch Airflow releases which could break an executor that subclasses KubernetesExecutor. This is necessary to allow Airflow developers sufficient freedom to continue to improve the executors we offer. Accordingly if you want to modify or extend a built-in executor, you should incorporate the full executor code into your project so that such changes will not break your derivative executor.
You can read more about executors in Executor.
New in version 2.6: The executor interface has been present in Airflow for quite some time but prior to 2.6, there was executor-specific code elsewhere in the codebase. As of version 2.6 executors are fully decoupled, in the sense that Airflow core no longer needs to know about the behavior of specific executors. You could have succeeded with implementing a custom executor before Airflow 2.6, and a number of people did, but there were some hard-coded behaviours that preferred in-built executors, and custom executors could not provide full functionality that built-in executors had.
All Secrets Backend implementations are public. You can extend their functionality:
Authentication backends can extend the way how Airflow authentication mechanism works. You can find out more about authentication in Auth backends that also shows available Authentication backends implemented in the community providers.
When creating Hooks, you can add custom Connections. You can read more about connections in Connections for available Connections implemented in the community providers.
When creating Hooks, you can add custom Extra Links that are displayed when the tasks are run. You can find out more about extra links in Extra Links that also shows available extra links implemented in the community providers.
Logging and Monitoring¶
You can extend the way how logs are written by Airflow. You can find out more about log writing in Logging & Monitoring.
The Writing logs that also shows available log writers implemented in the community providers.
Airflow has a set of Decorators that are considered public. You are free to extend their functionality by extending them:
You can read more about creating custom Decorators in Creating Custom @task Decorators.
Airflow has a built-in way of sending email notifications and it allows to extend it by adding custom email notification classes. You can read more about email notifications in Email Configuration.
Airflow has a built-in extensible way of sending notifications using the various
on_*_callback. You can read more
about notifications in Creating a notifier.
Cluster Policies are the way to dynamically apply cluster-wide policies to the DAGs being parsed or tasks being executed. You can read more about Cluster Policies in Cluster Policies.
What is not part of the Public Interface of Apache Airflow?¶
Everything not mentioned in this document should be considered as non-Public Interface.
Sometimes in other applications those components could be relied on to keep backwards compatibility, but in Airflow they are not parts of the Public Interface and might change any time:
Database structure is considered to be an internal implementation detail and you should not assume the structure is going to be maintained in a backwards-compatible way.
Web UI is continuously evolving and there are no backwards compatibility guarantees on HTML elements.
Python classes except those explicitly mentioned in this document, are considered an internal implementation detail and you should not assume they will be maintained in a backwards-compatible way.