Ansible module architecture¶
If you’re working on Ansible’s Core code, writing an Ansible module, or developing an action plugin, this deep dive helps you understand how Ansible’s program flow executes. If you’re just using Ansible Modules in playbooks, you can skip this section.
Types of modules¶
Ansible supports several different types of modules in its code base. Some of these are for backwards compatibility and others are to enable flexibility.
Action plugins¶
Action plugins look like modules to anyone writing a playbook. Usage documentation for most action plugins lives inside a module of the same name. Some action plugins do all the work, with the module providing only documentation. Some action plugins execute modules. The normal
action plugin executes modules that don’t have special action plugins. Action plugins always execute on the controller.
Some action plugins do all their work on the controller. For example, the debug action plugin (which prints text for the user to see) and the assert action plugin (which tests whether values in a playbook satisfy certain criteria) execute entirely on the controller.
Most action plugins set up some values on the controller, then invoke an actual module on the managed node that does something with these values. For example, the template action plugin takes values from the user to construct a file in a temporary location on the controller using variables from the playbook environment. It then transfers the temporary file to a temporary file on the remote system. After that, it invokes the copy module which operates on the remote system to move the file into its final location, sets file permissions, and so on.
New-style modules¶
All of the modules that ship with Ansible fall into this category. While you can write modules in any language, all official modules (shipped with Ansible) use either Python or PowerShell.
New-style modules have the arguments to the module embedded inside of them in some manner. Old-style modules must copy a separate file over to the managed node, which is less efficient as it requires two over-the-wire connections instead of only one.
Python¶
New-style Python modules use the Ansiballz framework framework for constructing
modules. These modules use imports from ansible.module_utils
to pull in
boilerplate module code, such as argument parsing, formatting of return
values as JSON, and various file operations.
Note
In Ansible, up to version 2.0.x, the official Python modules used the Module Replacer framework framework. For module authors, Ansiballz framework is largely a superset of Module Replacer framework functionality, so you usually do not need to know about one versus the other.
PowerShell¶
New-style PowerShell modules use the Module Replacer framework framework for constructing modules. These modules get a library of PowerShell code embedded in them before being sent to the managed node.
JSONARGS modules¶
These modules are scripts that include the string
<<INCLUDE_ANSIBLE_MODULE_JSON_ARGS>>
in their body.
This string is replaced with the JSON-formatted argument string. These modules typically set a variable to that value like this:
json_arguments = """<<INCLUDE_ANSIBLE_MODULE_JSON_ARGS>>"""
Which is expanded as:
json_arguments = """{"param1": "test's quotes", "param2": "\"To be or not to be\" - Hamlet"}"""
Note
Ansible outputs a JSON string with bare quotes. Double quotes are used to quote string values, double quotes inside of string values are backslash escaped, and single quotes may appear unescaped inside of a string value. To use JSONARGS, your scripting language must have a way to handle this type of string. The example uses Python’s triple quoted strings to do this. Other scripting languages may have a similar quote character that won’t be confused by any quotes in the JSON or it may allow you to define your own start-of-quote and end-of-quote characters. If the language doesn’t give you any of these then you’ll need to write a non-native JSON module or Old-style module instead.
These modules typically parse the contents of json_arguments
using a JSON
library and then use them as native variables throughout the code.
Non-native want JSON modules¶
If a module has the string WANT_JSON
in it anywhere, Ansible treats
it as a non-native module that accepts a filename as its only command line
parameter. The filename is for a temporary file containing a JSON
string containing the module’s parameters. The module needs to open the file,
read and parse the parameters, operate on the data, and print its return data
as a JSON encoded dictionary to stdout before exiting.
These types of modules are self-contained entities. As of Ansible 2.1, Ansible only modifies them to change a shebang line if present.
See also
Examples of Non-native modules written in ruby are in the Ansible for Rubyists repository.
Binary modules¶
From Ansible 2.2 onwards, modules may also be small binary programs. Ansible doesn’t perform any magic to make these portable to different systems so they may be specific to the system on which they were compiled or require other binary runtime dependencies. Despite these drawbacks, you may have to compile a custom module against a specific binary library if that’s the only way to get access to certain resources.
Binary modules take their arguments and return data to Ansible in the same way as want JSON modules.
See also
One example of a binary module written in go.
Old-style modules¶
Old-style modules are similar to
want JSON modules, except that the file that
they take contains key=value
pairs for their parameters instead of
JSON. Ansible decides that a module is old-style when it doesn’t have
any of the markers that would show that it is one of the other types.
How modules are executed¶
When a user uses ansible or ansible-playbook, they specify a task to execute. The task is usually the name of a module along with several parameters to be passed to the module. Ansible takes these values and processes them in various ways before they are finally executed on the remote machine.
Executor/task_executor¶
The TaskExecutor receives the module name and parameters that were parsed from the playbook (or from the command line in the case of /usr/bin/ansible). It uses the name to decide whether it’s looking at a module or an Action Plugin. If it’s a module, it loads the Normal Action Plugin and passes the name, variables, and other information about the task and play to that Action Plugin for further processing.
The normal
action plugin¶
The normal
action plugin executes the module on the remote host. It is
the primary coordinator of much of the work to actually execute the module on
the managed machine.
It loads the appropriate connection plugin for the task, which then transfers or executes as needed to create a connection to that host.
It adds any internal Ansible properties to the module’s parameters (for instance, the ones that pass along
no_log
to the module).It works with other plugins (connection, shell, become, other action plugins) to create any temporary files on the remote machine and cleans up afterwards.
It pushes the module and module parameters to the remote host, although the module_common code described in the next section decides which format those will take.
It handles any special cases regarding modules (for instance, async execution, or complications around Windows modules that must have the same names as Python modules, so that internal calling of modules from other Action Plugins work.)
Much of this functionality comes from the BaseAction class,
which lives in plugins/action/__init__.py
. It uses the
Connection
and Shell
objects to do its work.
Note
When tasks are run with the async:
parameter, Ansible
uses the async
Action Plugin instead of the normal
Action Plugin
to invoke it. That program flow is currently not documented. Read the
source for information on how that works.
Executor/module_common.py¶
Code in executor/module_common.py
assembles the module
to be shipped to the managed node. The module is first read in, then examined
to determine its type:
PowerShell and JSON-args modules are passed through Module Replacer.
New-style Python modules are assembled by Ansiballz framework.
Non-native-want-JSON, Binary modules, and Old-Style modules aren’t touched by either of these and pass through unchanged.
After the assembling step, one final
modification is made to all modules that have a shebang line. Ansible checks
whether the interpreter in the shebang line has a specific path configured via
an ansible_$X_interpreter
inventory variable. If it does, Ansible
substitutes that path for the interpreter path given in the module. After
this, Ansible returns the complete module data and the module type to the
Normal Action which continues execution of
the module.
Assembler frameworks¶
Ansible supports two assembler frameworks: Ansiballz and the older Module Replacer.
Module Replacer framework¶
The Module Replacer framework is the original framework implementing new-style modules, and is still used for PowerShell modules. It is essentially a preprocessor (like the C Preprocessor for those familiar with that programming language). It does straight substitutions of specific substring patterns in the module file. There are two types of substitutions:
Replacements that only happen in the module file. These are public replacement strings that modules can utilize to get helpful boilerplate or access to arguments.
from ansible.module_utils.MOD_LIB_NAME import *
is replaced with the contents of theansible/module_utils/MOD_LIB_NAME.py
These should only be used with new-style Python modules.#<<INCLUDE_ANSIBLE_MODULE_COMMON>>
is equivalent tofrom ansible.module_utils.basic import *
and should also only apply to new-style Python modules.# POWERSHELL_COMMON
substitutes the contents ofansible/module_utils/powershell.ps1
. It should only be used with new-style Powershell modules.
Replacements that are used by
ansible.module_utils
code. These are internal replacement patterns. They may be used internally, in the above public replacements, but shouldn’t be used directly by modules."<<ANSIBLE_VERSION>>"
is substituted with the Ansible version. In new-style Python modules under the Ansiballz framework framework the proper way is to instead instantiate an AnsibleModule and then access the version from :attr:AnsibleModule.ansible_version
."<<INCLUDE_ANSIBLE_MODULE_COMPLEX_ARGS>>"
is substituted with a string which is the Pythonrepr
of the JSON encoded module parameters. Usingrepr
on the JSON string makes it safe to embed in a Python file. In new-style Python modules under the Ansiballz framework this is better accessed by instantiating an AnsibleModule and then usingAnsibleModule.params
.<<SELINUX_SPECIAL_FILESYSTEMS>>
substitutes a string which is a comma separated list of file systems which have a file system dependent security context in SELinux. In new-style Python modules, if you really need this you should instantiate an AnsibleModule and then useAnsibleModule._selinux_special_fs
. The variable has also changed from a comma separated string of file system names to an actual python list of filesystem names.<<INCLUDE_ANSIBLE_MODULE_JSON_ARGS>>
substitutes the module parameters as a JSON string. Care must be taken to properly quote the string as JSON data may contain quotes. This pattern is not substituted in new-style Python modules as they can get the module parameters another way.The string
syslog.LOG_USER
is replaced wherever it occurs with thesyslog_facility
which was named inansible.cfg
or anyansible_syslog_facility
inventory variable that applies to this host. In new-style Python modules this has changed slightly. If you really need to access it, you should instantiate an AnsibleModule and then useAnsibleModule._syslog_facility
to access it. It is no longer the actual syslog facility and is now the name of the syslog facility. See the documentation on internal arguments for details.
Ansiballz framework¶
The Ansiballz framework was adopted in Ansible 2.1 and is used for all new-style Python modules. Unlike the Module Replacer, Ansiballz uses real Python imports of things in
ansible/module_utils
instead of merely preprocessing the module. It
does this by constructing a zipfile – which includes the module file, files
in ansible/module_utils
that are imported by the module, and some
boilerplate to pass in the module’s parameters. The zipfile is then Base64
encoded and wrapped in a small Python script which decodes the Base64 encoding
and places the zipfile into a temp directory on the managed node. It then
extracts just the Ansible module script from the zip file and places that in
the temporary directory as well. Then it sets the PYTHONPATH to find Python
modules inside of the zip file and imports the Ansible module as the special name, __main__
.
Importing it as __main__
causes Python to think that it is executing a script rather than simply
importing a module. This lets Ansible run both the wrapper script and the module code in a single copy of Python on the remote machine.
Note
Ansible wraps the zipfile in the Python script for two reasons:
for compatibility with Python 2.6 which has a less functional version of Python’s
-m
command line switch.so that pipelining will function properly. Pipelining needs to pipe the Python module into the Python interpreter on the remote node. Python understands scripts on stdin but does not understand zip files.
Prior to Ansible 2.7, the module was executed via a second Python interpreter instead of being executed inside of the same process. This change was made once Python-2.4 support was dropped to speed up module execution.
In Ansiballz, any imports of Python modules from the
ansible.module_utils
package trigger inclusion of that Python file
into the zipfile. Instances of #<<INCLUDE_ANSIBLE_MODULE_COMMON>>
in
the module are turned into from ansible.module_utils.basic import *
and ansible/module-utils/basic.py
is then included in the zipfile.
Files that are included from module_utils
are themselves scanned for
imports of other Python modules from module_utils
to be included in
the zipfile as well.
Warning
At present, the Ansiballz Framework cannot determine whether an import
should be included if it is a relative import. Always use an absolute
import that has ansible.module_utils
in it to allow Ansiballz to
determine that the file should be included.
Passing args¶
Arguments are passed differently by the two frameworks:
In Module Replacer framework, module arguments are turned into a JSON-ified string and substituted into the combined module file.
In Ansiballz framework, the JSON-ified string is part of the script which wraps the zipfile. Just before the wrapper script imports the Ansible module as
__main__
, it monkey-patches the private,_ANSIBLE_ARGS
variable inbasic.py
with the variable values. When aansible.module_utils.basic.AnsibleModule
is instantiated, it parses this string and places the args intoAnsibleModule.params
where it can be accessed by the module’s other code.
Warning
If you are writing modules, remember that the way we pass arguments is an internal implementation detail: it has changed in the past and will change again as soon as changes to the common module_utils
code allow Ansible modules to forgo using ansible.module_utils.basic.AnsibleModule
. Do not rely on the internal global _ANSIBLE_ARGS
variable.
Very dynamic custom modules which need to parse arguments before they
instantiate an AnsibleModule
may use _load_params
to retrieve those parameters.
Although _load_params
may change in breaking ways if necessary to support
changes in the code, it is likely to be more stable than either the way we pass parameters or the internal global variable.
Note
Prior to Ansible 2.7, the Ansible module was invoked in a second Python interpreter and the arguments were then passed to the script over the script’s stdin.
Internal arguments¶
Both Module Replacer framework and Ansiballz framework send additional arguments to
the module beyond those which the user specified in the playbook. These
additional arguments are internal parameters that help implement global
Ansible features. Modules often do not need to know about these explicitly as
the features are implemented in ansible.module_utils.basic
but certain
features need support from the module so it’s good to know about them.
The internal arguments listed here are global. If you need to add a local internal argument to a custom module, create an action plugin for that specific module - see _original_basename
in the copy action plugin for an example.
_ansible_no_log¶
Boolean. Set to True whenever a parameter in a task or play specifies no_log
. Any module that calls AnsibleModule.log()
handles this automatically. If a module implements its own logging then
it needs to check this value. To access in a module, instantiate an
AnsibleModule
and then check the value of AnsibleModule.no_log
.
Note
no_log
specified in a module’s argument_spec is handled by a different mechanism.
_ansible_debug¶
Boolean. Turns more verbose logging on or off and turns on logging of
external commands that the module executes. If a module uses
AnsibleModule.debug()
rather than AnsibleModule.log()
then
the messages are only logged if _ansible_debug
is set to True
.
To set, add debug: True
to ansible.cfg
or set the environment
variable ANSIBLE_DEBUG
. To access in a module, instantiate an
AnsibleModule
and access AnsibleModule._debug
.
_ansible_diff¶
Boolean. If a module supports it, tells the module to show a unified diff of
changes to be made to templated files. To set, pass the --diff
command line
option. To access in a module, instantiate an AnsibleModule and access
AnsibleModule._diff
.
_ansible_verbosity¶
Unused. This value could be used for finer grained control over logging.
_ansible_selinux_special_fs¶
List. Names of filesystems which should have a special SELinux
context. They are used by the AnsibleModule methods which operate on
files (changing attributes, moving, and copying). To set, add a comma separated string of filesystem names in ansible.cfg
:
# ansible.cfg
[selinux]
special_context_filesystems=nfs,vboxsf,fuse,ramfs,vfat
Most modules can use the built-in AnsibleModule
methods to manipulate
files. To access in a module that needs to know about these special context filesystems, instantiate an AnsibleModule
and examine the list in
AnsibleModule._selinux_special_fs
.
This replaces ansible.module_utils.basic.SELINUX_SPECIAL_FS
from
Module Replacer framework. In module replacer it was a comma separated string of
filesystem names. Under Ansiballz it’s an actual list.
New in version 2.1.
_ansible_syslog_facility¶
This parameter controls which syslog facility Ansible module logs to. To set, change the syslog_facility
value in ansible.cfg
. Most
modules should just use AnsibleModule.log()
which will then make use of
this. If a module has to use this on its own, it should instantiate an
AnsibleModule and then retrieve the name of the syslog facility from
AnsibleModule._syslog_facility
. The Ansiballz code is less hacky than the old Module Replacer framework code:
# Old module_replacer way
import syslog
syslog.openlog(NAME, 0, syslog.LOG_USER)
# New Ansiballz way
import syslog
facility_name = module._syslog_facility
facility = getattr(syslog, facility_name, syslog.LOG_USER)
syslog.openlog(NAME, 0, facility)
New in version 2.1.
_ansible_version¶
This parameter passes the version of Ansible that runs the module. To access
it, a module should instantiate an AnsibleModule and then retrieve it
from AnsibleModule.ansible_version
. This replaces
ansible.module_utils.basic.ANSIBLE_VERSION
from
Module Replacer framework.
New in version 2.1.
Module return values & Unsafe strings¶
At the end of a module’s execution, it formats the data that it wants to return as a JSON string and prints the string to its stdout. The normal action plugin receives the JSON string, parses it into a Python dictionary, and returns it to the executor.
If Ansible templated every string return value, it would be vulnerable to an attack from users with access to managed nodes. If an unscrupulous user disguised malicious code as Ansible return value strings, and if those strings were then templated on the controller, Ansible could execute arbitrary code. To prevent this scenario, Ansible marks all strings inside returned data as Unsafe
, emitting any Jinja2 templates in the strings verbatim, not expanded by Jinja2.
Strings returned by invoking a module through ActionPlugin._execute_module()
are automatically marked as Unsafe
by the normal action plugin. If another action plugin retrieves information from a module through some other means, it must mark its return data as Unsafe
on its own.
In case a poorly-coded action plugin fails to mark its results as “Unsafe,” Ansible audits the results again when they are returned to the executor,
marking all strings as Unsafe
. The normal action plugin protects itself and any other code that it calls with the result data as a parameter. The check inside the executor protects the output of all other action plugins, ensuring that subsequent tasks run by Ansible will not template anything from those results either.
Special considerations¶
Pipelining¶
Ansible can transfer a module to a remote machine in one of two ways:
it can write out the module to a temporary file on the remote host and then use a second connection to the remote host to execute it with the interpreter that the module needs
or it can use what’s known as pipelining to execute the module by piping it into the remote interpreter’s stdin.
Pipelining only works with modules written in Python at this time because Ansible only knows that Python supports this mode of operation. Supporting pipelining means that whatever format the module payload takes before being sent over the wire must be executable by Python via stdin.
Why pass args over stdin?¶
Passing arguments via stdin was chosen for the following reasons:
When combined with ANSIBLE_PIPELINING, this keeps the module’s arguments from temporarily being saved onto disk on the remote machine. This makes it harder (but not impossible) for a malicious user on the remote machine to steal any sensitive information that may be present in the arguments.
Command line arguments would be insecure as most systems allow unprivileged users to read the full commandline of a process.
Environment variables are usually more secure than the commandline but some systems limit the total size of the environment. This could lead to truncation of the parameters if we hit that limit.
AnsibleModule¶
Argument spec¶
The argument_spec
provided to AnsibleModule
defines the supported arguments for a module, as well as their type, defaults and more.
Example argument_spec
:
module = AnsibleModule(argument_spec=dict(
top_level=dict(
type='dict',
options=dict(
second_level=dict(
default=True,
type='bool',
)
)
)
))
This section will discuss the behavioral attributes for arguments:
type¶
type
allows you to define the type of the value accepted for the argument. The default value for type
is str
. Possible values are:
str
list
dict
bool
int
float
path
raw
jsonarg
json
bytes
bits
The raw
type, performs no type validation or type casing, and maintains the type of the passed value.
elements¶
elements
works in combination with type
when type='list'
. elements
can then be defined as elements='int'
or any other type, indicating that each element of the specified list should be of that type.
default¶
The default
option allows sets a default value for the argument for the scenario when the argument is not provided to the module. When not specified, the default value is None
.
fallback¶
fallback
accepts a tuple
where the first argument is a callable (function) that will be used to perform the lookup, based on the second argument. The second argument is a list of values to be accepted by the callable.
The most common callable used is env_fallback
which will allow an argument to optionally use an environment variable when the argument is not supplied.
Example:
username=dict(fallback=(env_fallback, ['ANSIBLE_NET_USERNAME']))
choices¶
choices
accepts a list of choices that the argument will accept. The types of choices
should match the type
.
required¶
required
accepts a boolean, either True
or False
that indicates that the argument is required. This should not be used in combination with default
.
no_log¶
no_log
accepts a boolean, either True
or False
, that indicates explicitly whether or not the argument value should be masked in logs and output.
Note
In the absence of no_log
, if the parameter name appears to indicate that the argument value is a password or passphrase (such as “admin_password”), a warning will be shown and the value will be masked in logs but not output. To disable the warning and masking for parameters that do not contain sensitive information, set no_log
to False
.
aliases¶
aliases
accepts a list of alternative argument names for the argument, such as the case where the argument is name
but the module accepts aliases=['pkg']
to allow pkg
to be interchangeably with name
options¶
options
implements the ability to create a sub-argument_spec, where the sub options of the top level argument are also validated using the attributes discussed in this section. The example at the top of this section demonstrates use of options
. type
or elements
should be dict
is this case.
apply_defaults¶
apply_defaults
works alongside options
and allows the default
of the sub-options to be applied even when the top-level argument is not supplied.
In the example of the argument_spec
at the top of this section, it would allow module.params['top_level']['second_level']
to be defined, even if the user does not provide top_level
when calling the module.
removed_in_version¶
removed_in_version
indicates which version of Ansible a deprecated argument will be removed in.