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Plugins
=======
Airflow has a simple plugin manager built-in that can integrate external
features to its core by simply dropping files in your
``$AIRFLOW_HOME/plugins`` folder.
The python modules in the ``plugins`` folder get imported,
and **hooks**, **operators**, **sensors**, **macros**, **executors** and web **views**
get integrated to Airflow's main collections and become available for use.
What for?
---------
Airflow offers a generic toolbox for working with data. Different
organizations have different stacks and different needs. Using Airflow
plugins can be a way for companies to customize their Airflow installation
to reflect their ecosystem.
Plugins can be used as an easy way to write, share and activate new sets of
features.
There's also a need for a set of more complex applications to interact with
different flavors of data and metadata.
Examples:
* A set of tools to parse Hive logs and expose Hive metadata (CPU /IO / phases/ skew /...)
* An anomaly detection framework, allowing people to collect metrics, set thresholds and alerts
* An auditing tool, helping understand who accesses what
* A config-driven SLA monitoring tool, allowing you to set monitored tables and at what time
they should land, alert people, and expose visualizations of outages
* ...
Why build on top of Airflow?
----------------------------
Airflow has many components that can be reused when building an application:
* A web server you can use to render your views
* A metadata database to store your models
* Access to your databases, and knowledge of how to connect to them
* An array of workers that your application can push workload to
* Airflow is deployed, you can just piggy back on its deployment logistics
* Basic charting capabilities, underlying libraries and abstractions
Interface
---------
To create a plugin you will need to derive the
``airflow.plugins_manager.AirflowPlugin`` class and reference the objects
you want to plug into Airflow. Here's what the class you need to derive
looks like:
.. code:: python
class AirflowPlugin(object):
# The name of your plugin (str)
name = None
# A list of class(es) derived from BaseOperator
operators = []
# A list of class(es) derived from BaseSensorOperator
sensors = []
# A list of class(es) derived from BaseHook
hooks = []
# A list of class(es) derived from BaseExecutor
executors = []
# A list of references to inject into the macros namespace
macros = []
# A list of objects created from a class derived
# from flask_admin.BaseView
admin_views = []
# A list of Blueprint object created from flask.Blueprint. For use with the flask_admin based GUI
flask_blueprints = []
# A list of menu links (flask_admin.base.MenuLink). For use with the flask_admin based GUI
menu_links = []
# A list of dictionaries containing FlaskAppBuilder BaseView object and some metadata. See example below
appbuilder_views = []
# A list of dictionaries containing FlaskAppBuilder BaseView object and some metadata. See example below
appbuilder_menu_items = []
# A list of global operator extra links that can redirect users to
# external systems. These extra links will be available on the
# task page in the form of buttons.
#
# Note: the global operator extra link can be overridden at each
# operator level.
global_operator_extra_links = []
You can derive it by inheritance (please refer to the example below).
Please note ``name`` inside this class must be specified.
After the plugin is imported into Airflow,
you can invoke it using statement like
.. code:: python
from airflow.{type, like "operators", "sensors"}.{name specificed inside the plugin class} import *
When you write your own plugins, make sure you understand them well.
There are some essential properties for each type of plugin.
For example,
* For ``Operator`` plugin, an ``execute`` method is compulsory.
* For ``Sensor`` plugin, a ``poke`` method returning a Boolean value is compulsory.
Make sure you restart the webserver and scheduler after making changes to plugins so that they take effect.
.. _plugin-example:
Example
-------
The code below defines a plugin that injects a set of dummy object
definitions in Airflow.
.. code:: python
# This is the class you derive to create a plugin
from airflow.plugins_manager import AirflowPlugin
from flask import Blueprint
from flask_admin import BaseView, expose
from flask_admin.base import MenuLink
# Importing base classes that we need to derive
from airflow.hooks.base_hook import BaseHook
from airflow.models import BaseOperator
from airflow.models.baseoperator import BaseOperatorLink
from airflow.sensors.base_sensor_operator import BaseSensorOperator
from airflow.executors.base_executor import BaseExecutor
# Will show up under airflow.hooks.test_plugin.PluginHook
class PluginHook(BaseHook):
pass
# Will show up under airflow.operators.test_plugin.PluginOperator
class PluginOperator(BaseOperator):
pass
# Will show up under airflow.sensors.test_plugin.PluginSensorOperator
class PluginSensorOperator(BaseSensorOperator):
pass
# Will show up under airflow.executors.test_plugin.PluginExecutor
class PluginExecutor(BaseExecutor):
pass
# Will show up under airflow.macros.test_plugin.plugin_macro
# and in templates through {{ macros.test_plugin.plugin_macro }}
def plugin_macro():
pass
# Creating a flask admin BaseView
class TestView(BaseView):
@expose('/')
def test(self):
# in this example, put your test_plugin/test.html template at airflow/plugins/templates/test_plugin/test.html
return self.render("test_plugin/test.html", content="Hello galaxy!")
v = TestView(category="Test Plugin", name="Test View")
# Creating a flask blueprint to integrate the templates and static folder
bp = Blueprint(
"test_plugin", __name__,
template_folder='templates', # registers airflow/plugins/templates as a Jinja template folder
static_folder='static',
static_url_path='/static/test_plugin')
ml = MenuLink(
category='Test Plugin',
name='Test Menu Link',
url='https://airflow.apache.org/')
# Creating a flask appbuilder BaseView
class TestAppBuilderBaseView(AppBuilderBaseView):
@expose("/")
def test(self):
return self.render("test_plugin/test.html", content="Hello galaxy!")
v_appbuilder_view = TestAppBuilderBaseView()
v_appbuilder_package = {"name": "Test View",
"category": "Test Plugin",
"view": v_appbuilder_view}
# Creating a flask appbuilder Menu Item
appbuilder_mitem = {"name": "Google",
"category": "Search",
"category_icon": "fa-th",
"href": "https://www.google.com"}
# A global operator extra link that redirect you to
# task logs stored in S3
class S3LogLink(BaseOperatorLink):
name = 'S3'
def get_link(self, operator, dttm):
return 'https://s3.amazonaws.com/airflow-logs/{dag_id}/{task_id}/{execution_date}'.format(
dag_id=operator.dag_id,
task_id=operator.task_id,
execution_date=dttm,
)
# Defining the plugin class
class AirflowTestPlugin(AirflowPlugin):
name = "test_plugin"
operators = [PluginOperator]
sensors = [PluginSensorOperator]
hooks = [PluginHook]
executors = [PluginExecutor]
macros = [plugin_macro]
admin_views = [v]
flask_blueprints = [bp]
menu_links = [ml]
appbuilder_views = [v_appbuilder_package]
appbuilder_menu_items = [appbuilder_mitem]
global_operator_extra_links = [S3LogLink(),]
Note on role based views
------------------------
Airflow 1.10 introduced role based views using FlaskAppBuilder. You can configure which UI is used by setting
rbac = True. To support plugin views and links for both versions of the UI and maintain backwards compatibility,
the fields appbuilder_views and appbuilder_menu_items were added to the AirflowTestPlugin class.
Plugins as Python packages
--------------------------
It is possible to load plugins via `setuptools entrypoint <https://packaging.python.org/guides/creating-and-discovering-plugins/#using-package-metadata>`_ mechanism. To do this link
your plugin using an entrypoint in your package. If the package is installed, airflow
will automatically load the registered plugins from the entrypoint list.
_Note_: Neither the entrypoint name (eg, `my_plugin`) nor the name of the
plugin class will contribute towards the module and class name of the plugin
itself. The structure is determined by
`airflow.plugins_manager.AirflowPlugin.name` and the class name of the plugin
component with the pattern `airflow.{component}.{name}.{component_class_name}`.
.. code-block:: python
# my_package/my_plugin.py
from airflow.plugins_manager import AirflowPlugin
from airflow.models import BaseOperator
from airflow.hooks.base_hook import BaseHook
class MyOperator(BaseOperator):
pass
class MyHook(BaseHook):
pass
class MyAirflowPlugin(AirflowPlugin):
name = 'my_namespace'
operators = [MyOperator]
hooks = [MyHook]
.. code-block:: python
from setuptools import setup
setup(
name="my-package",
...
entry_points = {
'airflow.plugins': [
'my_plugin = my_package.my_plugin:MyAirflowPlugin'
]
}
)
This will create a hook, and an operator accessible at:
- `airflow.hooks.my_namespace.MyHook`
- `airflow.operators.my_namespace.MyOperator`