Developing plugins
Plugins augment Ansible’s core functionality with logic and features that are accessible to all modules. Ansible collections include a number of handy plugins, and you can easily write your own. All plugins must:
be written in Python
raise errors
return strings in unicode
conform to Ansible’s configuration and documentation standards
Once you’ve reviewed these general guidelines, you can skip to the particular type of plugin you want to develop.
Writing plugins in Python
You must write your plugin in Python so it can be loaded by the PluginLoader
and returned as a Python object that any module can use. Since your plugin will execute on the control node, you must write it in a compatible version of Python.
Raising errors
You should return errors encountered during plugin execution by raising AnsibleError()
or a similar class with a message describing the error. When wrapping other exceptions into error messages, you should always use the to_native
Ansible function to ensure proper string compatibility across Python versions:
from ansible.module_utils.common.text.converters import to_native
try:
cause_an_exception()
except Exception as e:
raise AnsibleError('Something happened, this was original exception: %s' % to_native(e))
Since Ansible evaluates variables only when they are needed, filter and test plugins should propagate the exceptions jinja2.exceptions.UndefinedError
and AnsibleUndefinedVariable
to ensure undefined variables are only fatal when necessary.
Check the different AnsibleError objects and see which one applies best to your situation. Check the section on the specific plugin type you’re developing for type-specific error handling details.
String encoding
You must convert any strings returned by your plugin into Python’s unicode type. Converting to unicode ensures that these strings can run through Jinja2. To convert strings:
from ansible.module_utils.common.text.converters import to_text
result_string = to_text(result_string)
Plugin configuration & documentation standards
To define configurable options for your plugin, describe them in the DOCUMENTATION
section of the python file. Callback and connection plugins have declared configuration requirements this way since Ansible version 2.4; most plugin types now do the same. This approach ensures that the documentation of your plugin’s options will always be correct and up-to-date. To add a configurable option to your plugin, define it in this format:
options:
option_name:
description: describe this config option
default: default value for this config option
env:
- name: NAME_OF_ENV_VAR
ini:
- section: section_of_ansible.cfg_where_this_config_option_is_defined
key: key_used_in_ansible.cfg
vars:
- name: name_of_ansible_var
- name: name_of_second_var
version_added: X.x
required: True/False
type: boolean/float/integer/list/none/path/pathlist/pathspec/string/tmppath
version_added: X.x
To access the configuration settings in your plugin, use self.get_option(<option_name>)
.
Some plugin types handle this differently:
Become, callback, connection and shell plugins are guaranteed to have the engine call
set_options()
.Lookup plugins always require you to handle it in the
run()
method.Inventory plugins are done automatically if you use the
base _read_config_file()
method. If not, you must useself.get_option(<option_name>)
.Cache plugins do it on load.
Cliconf, httpapi and netconf plugins indirectly piggy back on connection plugins.
Vars plugin settings are populated when first accessed (using the
self.get_option()
orself.get_options()
method.
If you need to populate settings explicitly, use a self.set_options()
call.
Configuration sources follow the precedence rules for values in Ansible. When there are multiple values from the same category, the value defined last takes precedence. For example, in the above configuration block, if both name_of_ansible_var
and name_of_second_var
are defined, the value of the option_name
option will be the value of name_of_second_var
. Refer to Controlling how Ansible behaves: precedence rules for further information.
Plugins that support embedded documentation (see ansible-doc for the list) should include well-formed doc strings. If you inherit from a plugin, you must document the options it takes, either through a documentation fragment or as a copy. See Module format and documentation for more information on correct documentation. Thorough documentation is a good idea even if you’re developing a plugin for local use.
- In ansible-core 2.14 we added support for documenting filter and test plugins. You have two options for providing documentation:
Define a Python file that includes inline documentation for each plugin.
Define a Python file for multiple plugins and create adjacent documentation files in YAML format.
Developing particular plugin types
Action plugins
Action plugins let you integrate local processing and local data with module functionality.
To create an action plugin, create a new class with the Base(ActionBase) class as the parent:
from ansible.plugins.action import ActionBase
class ActionModule(ActionBase):
pass
From there, execute the module using the _execute_module
method to call the original module.
After successful execution of the module, you can modify the module return data.
module_return = self._execute_module(module_name='<NAME_OF_MODULE>',
module_args=module_args,
task_vars=task_vars, tmp=tmp)
For example, if you wanted to check the time difference between your Ansible control node and your target machine(s), you could write an action plugin to check the local time and compare it to the return data from Ansible’s setup
module:
#!/usr/bin/python
# Make coding more python3-ish, this is required for contributions to Ansible
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
from ansible.plugins.action import ActionBase
from datetime import datetime
class ActionModule(ActionBase):
def run(self, tmp=None, task_vars=None):
super(ActionModule, self).run(tmp, task_vars)
module_args = self._task.args.copy()
module_return = self._execute_module(module_name='setup',
module_args=module_args,
task_vars=task_vars, tmp=tmp)
ret = dict()
remote_date = None
if not module_return.get('failed'):
for key, value in module_return['ansible_facts'].items():
if key == 'ansible_date_time':
remote_date = value['iso8601']
if remote_date:
remote_date_obj = datetime.strptime(remote_date, '%Y-%m-%dT%H:%M:%SZ')
time_delta = datetime.utcnow() - remote_date_obj
ret['delta_seconds'] = time_delta.seconds
ret['delta_days'] = time_delta.days
ret['delta_microseconds'] = time_delta.microseconds
return dict(ansible_facts=dict(ret))
This code checks the time on the control node, captures the date and time for the remote machine using the setup
module, and calculates the difference between the captured time and
the local time, returning the time delta in days, seconds and microseconds.
For practical examples of action plugins, see the source code for the action plugins included with Ansible Core
Cache plugins
Cache plugins store gathered facts and data retrieved by inventory plugins.
Import cache plugins using the cache_loader so you can use self.set_options()
and self.get_option(<option_name>)
. If you import a cache plugin directly in the code base, you can only access options by the ansible.constants
, and you break the cache plugin’s ability to be used by an inventory plugin.
from ansible.plugins.loader import cache_loader
[...]
plugin = cache_loader.get('custom_cache', **cache_kwargs)
There are two base classes for cache plugins, BaseCacheModule
for database-backed caches, and BaseCacheFileModule
for file-backed caches.
To create a cache plugin, start by creating a new CacheModule
class with the appropriate base class. If you’re creating a plugin using an __init__
method you should initialize the base class with any provided args and kwargs to be compatible with inventory plugin cache options. The base class calls self.set_options(direct=kwargs)
. After the base class __init__
method is called self.get_option(<option_name>)
should be used to access cache options.
New cache plugins should take the options _uri
, _prefix
, and _timeout
to be consistent with existing cache plugins.
from ansible.plugins.cache import BaseCacheModule
class CacheModule(BaseCacheModule):
def __init__(self, *args, **kwargs):
super(CacheModule, self).__init__(*args, **kwargs)
self._connection = self.get_option('_uri')
self._prefix = self.get_option('_prefix')
self._timeout = self.get_option('_timeout')
If you use the BaseCacheModule
, you must implement the methods get
, contains
, keys
, set
, delete
, flush
, and copy
. The contains
method should return a boolean that indicates if the key exists and has not expired. Unlike file-based caches, the get
method does not raise a KeyError if the cache has expired.
If you use the BaseFileCacheModule
, you must implement _load
and _dump
methods that will be called from the base class methods get
and set
.
If your cache plugin stores JSON, use AnsibleJSONEncoder
in the _dump
or set
method and AnsibleJSONDecoder
in the _load
or get
method.
For example cache plugins, see the source code for the cache plugins included with Ansible Core.
Callback plugins
Callback plugins add new behaviors to Ansible when responding to events. By default, callback plugins control most of the output you see when running the command line programs.
To create a callback plugin, create a new class with the Base(Callbacks) class as the parent:
from ansible.plugins.callback import CallbackBase
class CallbackModule(CallbackBase):
pass
From there, override the specific methods from the CallbackBase that you want to provide a callback for.
For plugins intended for use with Ansible version 2.0 and later, you should only override methods that start with v2
.
For a complete list of methods that you can override, please see __init__.py
in the
lib/ansible/plugins/callback directory.
The following is a modified example of how Ansible’s timer plugin is implemented, but with an extra option so you can see how configuration works in Ansible version 2.4 and later:
# Make coding more python3-ish, this is required for contributions to Ansible
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
# not only visible to ansible-doc, it also 'declares' the options the plugin requires and how to configure them.
DOCUMENTATION = '''
name: timer
callback_type: aggregate
requirements:
- enable in configuration
short_description: Adds time to play stats
version_added: "2.0" # for collections, use the collection version, not the Ansible version
description:
- This callback just adds total play duration to the play stats.
options:
format_string:
description: format of the string shown to user at play end
ini:
- section: callback_timer
key: format_string
env:
- name: ANSIBLE_CALLBACK_TIMER_FORMAT
default: "Playbook run took %s days, %s hours, %s minutes, %s seconds"
'''
from datetime import datetime
from ansible.plugins.callback import CallbackBase
class CallbackModule(CallbackBase):
"""
This callback module tells you how long your plays ran for.
"""
CALLBACK_VERSION = 2.0
CALLBACK_TYPE = 'aggregate'
CALLBACK_NAME = 'namespace.collection_name.timer'
# only needed if you ship it and don't want to enable by default
CALLBACK_NEEDS_ENABLED = True
def __init__(self):
# make sure the expected objects are present, calling the base's __init__
super(CallbackModule, self).__init__()
# start the timer when the plugin is loaded, the first play should start a few milliseconds after.
self.start_time = datetime.now()
def _days_hours_minutes_seconds(self, runtime):
''' internal helper method for this callback '''
minutes = (runtime.seconds // 60) % 60
r_seconds = runtime.seconds - (minutes * 60)
return runtime.days, runtime.seconds // 3600, minutes, r_seconds
# this is only event we care about for display, when the play shows its summary stats; the rest are ignored by the base class
def v2_playbook_on_stats(self, stats):
end_time = datetime.now()
runtime = end_time - self.start_time
# Shows the usage of a config option declared in the DOCUMENTATION variable. Ansible will have set it when it loads the plugin.
# Also note the use of the display object to print to screen. This is available to all callbacks, and you should use this over printing yourself
self._display.display(self._plugin_options['format_string'] % (self._days_hours_minutes_seconds(runtime)))
Note that the CALLBACK_VERSION
and CALLBACK_NAME
definitions are required for properly functioning plugins for Ansible version 2.0 and later. CALLBACK_TYPE
is mostly needed to distinguish ‘stdout’ plugins from the rest, since you can only load one plugin that writes to stdout.
For example callback plugins, see the source code for the callback plugins included with Ansible Core
New in ansible-core 2.11, callback plugins are notified (by the v2_playbook_on_task_start
) of meta tasks. By default, only explicit meta
tasks that users list in their plays are sent to callbacks.
There are also some tasks which are generated internally and implicitly at various points in execution. Callback plugins can opt-in to receiving these implicit tasks as well, by setting self.wants_implicit_tasks = True
. Any Task
object received by a callback hook will have an .implicit
attribute, which can be consulted to determine whether the Task
originated from within Ansible, or explicitly by the user.
Connection plugins
Connection plugins allow Ansible to connect to target hosts so it can execute tasks on them. Ansible ships with many connection plugins, but only one can be used per host at a time. The most commonly used connection plugins are native ssh
, paramiko
, and local
. All of these can be used with ad-hoc tasks and in playbooks.
To create a new connection plugin (for example, to support SNMP, Message bus, or other transports), copy the format of one of the existing connection plugins and drop it into connection
directory on your local plugin path.
Connection plugins can support common options (such as the --timeout
flag) by defining an entry in the documentation for the attribute name (in this case timeout
). If the common option has a non-null default, the plugin should define the same default since a different default would be ignored.
For example connection plugins, see the source code for the connection plugins included with Ansible Core.
Filter plugins
Filter plugins manipulate data. They are a feature of Jinja2 and are also available in Jinja2 templates used by the template
module. As with all plugins, they can be easily extended, but instead of having a file for each one you can have several per file. Most of the filter plugins shipped with Ansible reside in a core.py
.
Filter plugins do not use the standard configuration system described above, but since ansible-core 2.14 can use it as plain documentation.
Since Ansible evaluates variables only when they are needed, filter plugins should propagate the exceptions jinja2.exceptions.UndefinedError
and AnsibleUndefinedVariable
to ensure undefined variables are only fatal when necessary.
try:
cause_an_exception(with_undefined_variable)
except jinja2.exceptions.UndefinedError as e:
raise AnsibleUndefinedVariable("Something happened, this was the original exception: %s" % to_native(e))
except Exception as e:
raise AnsibleFilterError("Something happened, this was the original exception: %s" % to_native(e))
For example filter plugins, see the source code for the filter plugins included with Ansible Core.
Inventory plugins
Inventory plugins parse inventory sources and form an in-memory representation of the inventory. Inventory plugins were added in Ansible version 2.4.
You can see the details for inventory plugins in the Developing dynamic inventory page.
Lookup plugins
Lookup plugins pull in data from external data stores. Lookup plugins can be used within playbooks both for looping — playbook language constructs like with_fileglob
and with_items
are implemented through lookup plugins — and to return values into a variable or parameter.
Lookup plugins are expected to return lists, even if just a single element.
Ansible includes many filters which can be used to manipulate the data returned by a lookup plugin. Sometimes it makes sense to do the filtering inside the lookup plugin, other times it is better to return results that can be filtered in the playbook. Keep in mind how the data will be referenced when determining the appropriate level of filtering to be done inside the lookup plugin.
Here’s a simple lookup plugin implementation — this lookup returns the contents of a text file as a variable:
# python 3 headers, required if submitting to Ansible
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
DOCUMENTATION = r"""
name: file
author: Daniel Hokka Zakrisson (@dhozac) <[email protected]>
version_added: "0.9" # for collections, use the collection version, not the Ansible version
short_description: read file contents
description:
- This lookup returns the contents from a file on the Ansible control node's file system.
options:
_terms:
description: path(s) of files to read
required: True
option1:
description:
- Sample option that could modify plugin behavior.
- This one can be set directly ``option1='x'`` or in ansible.cfg, but can also use vars or environment.
type: string
ini:
- section: file_lookup
key: option1
notes:
- if read in variable context, the file can be interpreted as YAML if the content is valid to the parser.
- this lookup does not understand globbing --- use the fileglob lookup instead.
"""
from ansible.errors import AnsibleError, AnsibleParserError
from ansible.plugins.lookup import LookupBase
from ansible.utils.display import Display
display = Display()
class LookupModule(LookupBase):
def run(self, terms, variables=None, **kwargs):
# First of all populate options,
# this will already take into account env vars and ini config
self.set_options(var_options=variables, direct=kwargs)
# lookups in general are expected to both take a list as input and output a list
# this is done so they work with the looping construct 'with_'.
ret = []
for term in terms:
display.debug("File lookup term: %s" % term)
# Find the file in the expected search path, using a class method
# that implements the 'expected' search path for Ansible plugins.
lookupfile = self.find_file_in_search_path(variables, 'files', term)
# Don't use print or your own logging, the display class
# takes care of it in a unified way.
display.vvvv(u"File lookup using %s as file" % lookupfile)
try:
if lookupfile:
contents, show_data = self._loader._get_file_contents(lookupfile)
ret.append(contents.rstrip())
else:
# Always use ansible error classes to throw 'final' exceptions,
# so the Ansible engine will know how to deal with them.
# The Parser error indicates invalid options passed
raise AnsibleParserError()
except AnsibleParserError:
raise AnsibleError("could not locate file in lookup: %s" % term)
# consume an option: if this did something useful, you can retrieve the option value here
if self.get_option('option1') == 'do something':
pass
return ret
The following is an example of how this lookup is called:
---
- hosts: all
vars:
contents: "{{ lookup('namespace.collection_name.file', '/etc/foo.txt') }}"
contents_with_option: "{{ lookup('namespace.collection_name.file', '/etc/foo.txt', option1='donothing') }}"
tasks:
- debug:
msg: the value of foo.txt is {{ contents }} as seen today {{ lookup('pipe', 'date +"%Y-%m-%d"') }}
For example lookup plugins, see the source code for the lookup plugins included with Ansible Core.
For more usage examples of lookup plugins, see Using Lookups.
Test plugins
Test plugins verify data. They are a feature of Jinja2 and are also available in Jinja2 templates used by the template
module. As with all plugins, they can be easily extended, but instead of having a file for each one you can have several per file. Most of the test plugins shipped with Ansible reside in a core.py
. These are specially useful in conjunction with some filter plugins like map
and select
; they are also available for conditional directives like when:
.
Test plugins do not use the standard configuration system described above. Since ansible-core 2.14 test plugins can use plain documentation.
Since Ansible evaluates variables only when they are needed, test plugins should propagate the exceptions jinja2.exceptions.UndefinedError
and AnsibleUndefinedVariable
to ensure undefined variables are only fatal when necessary.
try:
cause_an_exception(with_undefined_variable)
except jinja2.exceptions.UndefinedError as e:
raise AnsibleUndefinedVariable("Something happened, this was the original exception: %s" % to_native(e))
except Exception as e:
raise AnsibleFilterError("Something happened, this was the original exception: %s" % to_native(e))
For example test plugins, see the source code for the test plugins included with Ansible Core.
Vars plugins
Vars plugins inject additional variable data into Ansible runs that did not come from an inventory source, playbook, or command line. Playbook constructs like ‘host_vars’ and ‘group_vars’ work using vars plugins.
Vars plugins were partially implemented in Ansible 2.0 and rewritten to be fully implemented starting with Ansible 2.4. Vars plugins are supported by collections starting with Ansible 2.10.
Older plugins used a run
method as their main body/work:
def run(self, name, vault_password=None):
pass # your code goes here
Ansible 2.0 did not pass passwords to older plugins, so vaults were unavailable.
Most of the work now happens in the get_vars
method which is called from the VariableManager when needed.
def get_vars(self, loader, path, entities):
pass # your code goes here
The parameters are:
loader: Ansible’s DataLoader. The DataLoader can read files, auto-load JSON/YAML and decrypt vaulted data, and cache read files.
path: this is ‘directory data’ for every inventory source and the current play’s playbook directory, so they can search for data in reference to them.
get_vars
will be called at least once per available path.entities: these are host or group names that are pertinent to the variables needed. The plugin will get called once for hosts and again for groups.
This get_vars
method just needs to return a dictionary structure with the variables.
Since Ansible version 2.4, vars plugins only execute as needed when preparing to execute a task. This avoids the costly ‘always execute’ behavior that occurred during inventory construction in older versions of Ansible. Since Ansible version 2.10, vars plugin execution can be toggled by the user to run when preparing to execute a task or after importing an inventory source.
The user must explicitly enable vars plugins that reside in a collection. See Enabling vars plugins for details.
Legacy vars plugins are always loaded and run by default. You can prevent them from automatically running by setting REQUIRES_ENABLED
to True.
class VarsModule(BaseVarsPlugin):
REQUIRES_ENABLED = True
Include the vars_plugin_staging
documentation fragment to allow users to determine when vars plugins run.
DOCUMENTATION = '''
name: custom_hostvars
version_added: "2.10" # for collections, use the collection version, not the Ansible version
short_description: Load custom host vars
description: Load custom host vars
options:
stage:
ini:
- key: stage
section: vars_custom_hostvars
env:
- name: ANSIBLE_VARS_PLUGIN_STAGE
extends_documentation_fragment:
- vars_plugin_staging
'''
At times a value provided by a vars plugin will contain unsafe values. The utility function wrap_var provided by ansible.utils.unsafe_proxy should be used to ensure that Ansible handles the variable and value correctly. The use cases for unsafe data is covered in Unsafe or raw strings.
from ansible.plugins.vars import BaseVarsPlugin
from ansible.utils.unsafe_proxy import wrap_var
class VarsPlugin(BaseVarsPlugin):
def get_vars(self, loader, path, entities):
return dict(
something_unsafe=wrap_var("{{ SOMETHING_UNSAFE }}")
)
For example vars plugins, see the source code for the vars plugins included with Ansible Core.
See also
- Collection Index
Browse existing collections, modules, and plugins
- Python API
Learn about the Python API for task execution
- Developing dynamic inventory
Learn about how to develop dynamic inventory sources
- Developing modules
Learn about how to write Ansible modules
- Communication
Got questions? Need help? Want to share your ideas? Visit the Ansible communication guide
- Adjacent YAML documentation files
Alternate YAML files as documentation