Developing Modules

• Tutorial
• Testing Modules
• Reading Input
  • Binary Modules Input
• Module Provided ‘Facts’
• Common Module Boilerplate
• Check Mode
• Common Pitfalls
• Conventions/Recommendations
• Documenting Your Module
  • Example
  • Building & Testing
• Debugging AnsibleModule-based modules
• Module Paths
• Getting Your Module Into Ansible
• Module checklist
• Windows modules checklist
• Deprecating and making module aliases
• Appendix: Module Utilities

Ansible modules are reusable, standalone scripts that can be used by the Ansible API, or by the ansible or ansible-playbook programs. They return information to ansible by printing a JSON string to stdout before exiting. They take arguments in in one of several ways which we’ll go into as we work through this tutorial.

See modules for a list of various ones developed in core.

Modules can be written in any language and are found in the path specified by ANSIBLE_LIBRARY or the --module-path command line option.

By default, everything that ships with Ansible is pulled from its source tree, but additional paths can be added.

The directory i:file:./library, alongside your top level playbooks, is also automatically added as a search directory.

Should you develop an interesting Ansible module, consider sending a pull request to the modules-extras project. There’s also a core repo for more established and widely used modules. “Extras” modules may be promoted to core periodically, but there’s no fundamental difference in the end - both ship with Ansible, all in one package, regardless of how you acquire Ansible.

Tutorial

Let’s build a very-basic module to get and set the system time. For starters, let’s build a module that just outputs the current time.

We are going to use Python here but any language is possible. Only File I/O and outputting to standard out are required. So, bash, C++, clojure, Python, Ruby, whatever you want is fine.

Now Python Ansible modules contain some extremely powerful shortcuts (that all the core modules use) but first we are going to build a module the very hard way. The reason we do this is because modules written in any language OTHER than Python are going to have to do exactly this. We’ll show the easy way later.

So, here’s an example. You would never really need to build a module to set the system time, the ‘command’ module could already be used to do this.

Reading the modules that come with Ansible (linked above) is a great way to learn how to write modules. Keep in mind, though, that some modules in Ansible’s source tree are internalisms, so look at service - Manage services. or yum - Manages packages with the yum package manager, and don’t stare too close into things like async_wrapper or you’ll turn to stone. Nobody ever executes async_wrapper directly.

Ok, let’s get going with an example. We’ll use Python. For starters, save this as a file named timetest.py:

#!/usr/bin/python

import datetime
import json

date = str(datetime.datetime.now())
print json.dumps({
    "time" : date
})

Testing Modules

There’s a useful test script in the source checkout for Ansible:

git clone git://github.com/ansible/ansible.git --recursive
source ansible/hacking/env-setup

For instructions on setting up Ansible from source, please see intro_installation.

Let’s run the script you just wrote with that:

ansible/hacking/test-module -m ./timetest.py

You should see output that looks something like this:

{'time': '2012-03-14 22:13:48.539183'}

If you did not, you might have a typo in your module, so recheck it and try again.

Reading Input

Let’s modify the module to allow setting the current time. We’ll do this by seeing if a key value pair in the form time=<string> is passed in to the module.

Ansible internally saves arguments to an arguments file. So we must read the file and parse it. The arguments file is just a string, so any form of arguments are legal. Here we’ll do some basic parsing to treat the input as key=value.

The example usage we are trying to achieve to set the time is:

time time="March 14 22:10"

If no time parameter is set, we’ll just leave the time as is and return the current time.

Let’s look at the code. Read the comments as we’ll explain as we go. Note that this is highly verbose because it’s intended as an educational example. You can write modules a lot shorter than this:

#!/usr/bin/python

# import some python modules that we'll use.  These are all
# available in Python's core

import datetime
import sys
import json
import os
import shlex

# read the argument string from the arguments file
args_file = sys.argv[1]
args_data = file(args_file).read()

# For this module, we're going to do key=value style arguments.
# Modules can choose to receive json instead by adding the string:
#   WANT_JSON
# Somewhere in the file.
# Modules can also take free-form arguments instead of key-value or json
# but this is not recommended.

arguments = shlex.split(args_data)
for arg in arguments:

    # ignore any arguments without an equals in it
    if "=" in arg:

        (key, value) = arg.split("=")

        # if setting the time, the key 'time'
        # will contain the value we want to set the time to

        if key == "time":

            # now we'll affect the change.  Many modules
            # will strive to be 'idempotent', meaning they
            # will only make changes when the desired state
            # expressed to the module does not match
            # the current state.  Look at 'service'
            # or 'yum' in the main git tree for an example
            # of how that might look.

            rc = os.system("date -s \"%s\"" % value)

            # always handle all possible errors
            #
            # when returning a failure, include 'failed'
            # in the return data, and explain the failure
            # in 'msg'.  Both of these conventions are
            # required however additional keys and values
            # can be added.

            if rc != 0:
                print json.dumps({
                    "failed" : True,
                    "msg"    : "failed setting the time"
                })
                sys.exit(1)

            # when things do not fail, we do not
            # have any restrictions on what kinds of
            # data are returned, but it's always a
            # good idea to include whether or not
            # a change was made, as that will allow
            # notifiers to be used in playbooks.

            date = str(datetime.datetime.now())
            print json.dumps({
                "time" : date,
                "changed" : True
            })
            sys.exit(0)

# if no parameters are sent, the module may or
# may not error out, this one will just
# return the time

date = str(datetime.datetime.now())
print json.dumps({
    "time" : date
})

Let’s test that module:

ansible/hacking/test-module -m ./timetest.py -a "time=\"March 14 12:23\""

This should return something like:

{"changed": true, "time": "2012-03-14 12:23:00.000307"}

Binary Modules Input

Support for binary modules was added in Ansible 2.2. When Ansible detects a binary module, it will proceed to supply the argument input as a file on argv[1] that is formatted as JSON. The JSON contents of that file would resemble something similar to the following payload for a module accepting the same arguments as the ping module:

{
    "data": "pong",
    "_ansible_verbosity": 4,
    "_ansible_diff": false,
    "_ansible_debug": false,
    "_ansible_check_mode": false,
    "_ansible_no_log": false
}

Module Provided ‘Facts’

The setup - Gathers facts about remote hosts module that ships with Ansible provides many variables about a system that can be used in playbooks and templates. However, it’s possible to also add your own facts without modifying the system module. To do this, just have the module return a ansible_facts key, like so, along with other return data:

{
    "changed" : True,
    "rc" : 5,
    "ansible_facts" : {
        "leptons" : 5000,
        "colors" : {
            "red"   : "FF0000",
            "white" : "FFFFFF"
        }
    }
}

These ‘facts’ will be available to all statements called after that module (but not before) in the playbook. A good idea might be to make a module called ‘site_facts’ and always call it at the top of each playbook, though we’re always open to improving the selection of core facts in Ansible as well.

Common Module Boilerplate

As mentioned, if you are writing a module in Python, there are some very powerful shortcuts you can use. Modules are still transferred as one file, but an arguments file is no longer needed, so these are not only shorter in terms of code, they are actually FASTER in terms of execution time.

Rather than mention these here, the best way to learn is to read some of the source of the modules that come with Ansible.

The ‘group’ and ‘user’ modules are reasonably non-trivial and showcase what this looks like.

Key parts include always importing the boilerplate code from ansible.module_utils.basic like this:

from ansible.module_utils.basic import AnsibleModule
if __name__ == '__main__':
    main()

from ansible.module_utils.basic import *

And instantiating the module class like:

def main():
    module = AnsibleModule(
        argument_spec = dict(
            state     = dict(default='present', choices=['present', 'absent']),
            name      = dict(required=True),
            enabled   = dict(required=True, type='bool'),
            something = dict(aliases=['whatever'])
        )
    )

The AnsibleModule provides lots of common code for handling returns, parses your arguments for you, and allows you to check inputs.

Successful returns are made like this:

module.exit_json(changed=True, something_else=12345)

And failures are just as simple (where msg is a required parameter to explain the error):

module.fail_json(msg="Something fatal happened")

There are also other useful functions in the module class, such as module.sha1(path)(). See lib/ansible/module_utils/basic.py in the source checkout for implementation details.

Again, modules developed this way are best tested with the hacking/test-module script in the git source checkout. Because of the magic involved, this is really the only way the scripts can function outside of Ansible.

If submitting a module to Ansible’s core code, which we encourage, use of AnsibleModule is required.

Check Mode

Modules may optionally support check mode. If the user runs Ansible in check mode, the module should try to predict whether changes will occur.

For your module to support check mode, you must pass supports_check_mode=True when instantiating the AnsibleModule object. The AnsibleModule.check_mode attribute will evaluate to True when check mode is enabled. For example:

module = AnsibleModule(
    argument_spec = dict(...),
    supports_check_mode=True
)

if module.check_mode:
    # Check if any changes would be made but don't actually make those changes
    module.exit_json(changed=check_if_system_state_would_be_changed())

Remember that, as module developer, you are responsible for ensuring that no system state is altered when the user enables check mode.

If your module does not support check mode, when the user runs Ansible in check mode, your module will simply be skipped.

Common Pitfalls

You should also never do this in a module:

print "some status message"

Because the output is supposed to be valid JSON.

Modules must not output anything on standard error, because the system will merge standard out with standard error and prevent the JSON from parsing. Capturing standard error and returning it as a variable in the JSON on standard out is fine, and is, in fact, how the command module is implemented.

If a module returns stderr or otherwise fails to produce valid JSON, the actual output will still be shown in Ansible, but the command will not succeed.

Always use the hacking/test-module script when developing modules and it will warn you about these kind of things.

Conventions/Recommendations

As a reminder from the example code above, here are some basic conventions and guidelines:

• If the module is addressing an object, the parameter for that object should be called ‘name’ whenever possible, or accept ‘name’ as an alias.
• If you have a company module that returns facts specific to your installations, a good name for this module is site_facts.
• Modules accepting boolean status should generally accept ‘yes’, ‘no’, ‘true’, ‘false’, or anything else a user may likely throw at them. The AnsibleModule common code supports this with “type=’bool’”.
• Include a minimum of dependencies if possible. If there are dependencies, document them at the top of the module file, and have the module raise JSON error messages when the import fails.
• Modules must be self-contained in one file to be auto-transferred by ansible.
• If packaging modules in an RPM, they only need to be installed on the control machine and should be dropped into /usr/share/ansible. This is entirely optional and up to you.
• Modules must output valid JSON only. The toplevel return type must be a hash (dictionary) although they can be nested. Lists or simple scalar values are not supported, though they can be trivially contained inside a dictionary.
• In the event of failure, a key of ‘failed’ should be included, along with a string explanation in ‘msg’. Modules that raise tracebacks (stacktraces) are generally considered ‘poor’ modules, though Ansible can deal with these returns and will automatically convert anything unparseable into a failed result. If you are using the AnsibleModule common Python code, the ‘failed’ element will be included for you automatically when you call ‘fail_json’.
• Return codes from modules are actually not significant, but continue on with 0=success and non-zero=failure for reasons of future proofing.
• As results from many hosts will be aggregated at once, modules should return only relevant output. Returning the entire contents of a log file is generally bad form.

Documenting Your Module

All modules included in the CORE distribution must have a DOCUMENTATION string. This string MUST be a valid YAML document which conforms to the schema defined below. You may find it easier to start writing your DOCUMENTATION string in an editor with YAML syntax highlighting before you include it in your Python file.

Example

See an example documentation string in the checkout under examples/DOCUMENTATION.yml.

Include it in your module file like this:

#!/usr/bin/python
# Copyright header....

DOCUMENTATION = '''
---
module: modulename
short_description: This is a sentence describing the module
# ... snip ...
'''

If an argument takes both C(True)/C(False) and C(Yes)/C(No), the documentation should use C(True) and C(False).

The description, and notes fields support formatting with some special macros.

These formatting functions are U(), M(), I(), and C() for URL, module, italic, and constant-width respectively. It is suggested to use C() for file and option names, and I() when referencing parameters; module names should be specified as M(module).

Examples should be written in YAML format in plain text in an EXAMPLES string within the module like this:

EXAMPLES = '''
- modulename:
    opt1: arg1
    opt2: arg2
'''

The EXAMPLES section, just like the documentation section, is required in all module pull requests for new modules.

The RETURN section documents what the module returns. For each value returned, provide a description, in what circumstances the value is returned, the type of the value and a sample. For example, from the copy module:

RETURN = '''
dest:
    description: destination file/path
    returned: success
    type: string
    sample: "/path/to/file.txt"
src:
    description: source file used for the copy on the target machine
    returned: changed
    type: string
    sample: "/home/httpd/.ansible/tmp/ansible-tmp-1423796390.97-147729857856000/source"
md5sum:
    description: md5 checksum of the file after running copy
    returned: when supported
    type: string
    sample: "2a5aeecc61dc98c4d780b14b330e3282"
...
'''

Building & Testing

Put your completed module file into the ‘library’ directory and then run the command: make webdocs. The new ‘modules.html’ file will be built and appear in the ‘docsite/’ directory.

Debugging AnsibleModule-based modules

Starting with Ansible-2.1.0, AnsibleModule-based modules are put together as a zip file consisting of the module file and the various python module boilerplate inside of a wrapper script instead of as a single file with all of the code concatenated together. Without some help, this can be harder to debug as the file needs to be extracted from the wrapper in order to see what’s actually going on in the module. Luckily the wrapper script provides some helper methods to do just that.

If you are using Ansible with the ANSIBLE_KEEP_REMOTE_FILES environment variables to keep the remote module file, here’s a sample of how your debugging session will start:

$ ANSIBLE_KEEP_REMOTE_FILES=1 ansible localhost -m ping -a 'data=debugging_session' -vvv
<127.0.0.1> ESTABLISH LOCAL CONNECTION FOR USER: badger
<127.0.0.1> EXEC /bin/sh -c '( umask 77 && mkdir -p "` echo $HOME/.ansible/tmp/ansible-tmp-1461434734.35-235318071810595 `" && echo "` echo $HOME/.ansible/tmp/ansible-tmp-1461434734.35-235318071810595 `" )'
<127.0.0.1> PUT /var/tmp/tmpjdbJ1w TO /home/badger/.ansible/tmp/ansible-tmp-1461434734.35-235318071810595/ping
<127.0.0.1> EXEC /bin/sh -c 'LANG=en_US.UTF-8 LC_ALL=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 /usr/bin/python /home/badger/.ansible/tmp/ansible-tmp-1461434734.35-235318071810595/ping'
localhost | SUCCESS => {
    "changed": false,
    "invocation": {
        "module_args": {
            "data": "debugging_session"
        },
        "module_name": "ping"
    },
    "ping": "debugging_session"
}

Setting ANSIBLE_KEEP_REMOTE_FILES to 1 tells Ansible to keep the remote module files instead of deleting them after the module finishes executing. Giving Ansible the -vvv optin makes Ansible more verbose. That way it prints the file name of the temporary module file for you to see.

If you want to examine the wrapper file you can. It will show a small python script with a large, base64 encoded string. The string contains the module that is going to be executed. Run the wrapper’s explode command to turn the string into some python files that you can work with:

$ python /home/badger/.ansible/tmp/ansible-tmp-1461434734.35-235318071810595/ping explode
Module expanded into:
/home/badger/.ansible/tmp/ansible-tmp-1461434734.35-235318071810595/debug_dir

When you look into the debug_dir you’ll see a directory structure like this:

├── ansible_module_ping.py
├── args
└── ansible
    ├── __init__.py
    └── module_utils
        ├── basic.py
        └── __init__.py

• ansible_module_ping.py is the code for the module itself. The name is based on the name of the module with a prefix so that we don’t clash with any other python module names. You can modify this code to see what effect it would have on your module.
• The args file contains a JSON string. The string is a dictionary containing the module arguments and other variables that Ansible passes into the module to change it’s behaviour. If you want to modify the parameters that are passed to the module, this is the file to do it in.
• The ansible directory contains code from ansible.module_utils that is used by the module. Ansible includes files for any :module:`ansible.module_utils imports in the module but not no files from any other module. So if your module uses ansible.module_utils.url Ansible will include it for you, but if your module includes requests then you’ll have to make sure that the python requests library is installed on the system before running the module. You can modify files in this directory if you suspect that the module is having a problem in some of this boilerplate code rather than in the module code you have written.

Once you edit the code or arguments in the exploded tree you need some way to run it. There’s a separate wrapper subcommand for this:

$ python /home/badger/.ansible/tmp/ansible-tmp-1461434734.35-235318071810595/ping execute
{"invocation": {"module_args": {"data": "debugging_session"}}, "changed": false, "ping": "debugging_session"}

This subcommand takes care of setting the PYTHONPATH to use the exploded debug_dir/ansible/module_utils directory and invoking the script using the arguments in the args file. You can continue to run it like this until you understand the problem. Then you can copy it back into your real module file and test that the real module works via ansible or ansible-playbook.

Module Paths

If you are having trouble getting your module “found” by ansible, be sure it is in the ANSIBLE_LIBRARY environment variable.

If you have a fork of one of the ansible module projects, do something like this:

ANSIBLE_LIBRARY=~/ansible-modules-core:~/ansible-modules-extras

And this will make the items in your fork be loaded ahead of what ships with Ansible. Just be sure to make sure you’re not reporting bugs on versions from your fork!

To be safe, if you’re working on a variant on something in Ansible’s normal distribution, it’s not a bad idea to give it a new name while you are working on it, to be sure you know you’re pulling your version.

Getting Your Module Into Ansible

High-quality modules with minimal dependencies can be included in Ansible, but modules (just due to the programming preferences of the developers) will need to be implemented in Python and use the AnsibleModule common code, and should generally use consistent arguments with the rest of the program. Stop by the mailing list to inquire about requirements if you like, and submit a github pull request to the extras project. Included modules will ship with ansible, and also have a chance to be promoted to ‘core’ status, which gives them slightly higher development priority (though they’ll work in exactly the same way).

Module checklist

The following checklist items are important guidelines for people who want to contribute to the development of modules to Ansible on GitHub. Please read the guidelines before you submit your PR/proposal.

• The shebang must always be #!/usr/bin/python. This allows ansible_python_interpreter to work
• Modules must be written to support Python 2.4. If this is not possible, required minimum python version and rationale should be explained in the requirements section in DOCUMENTATION. This minimum requirement will be advanced to Python-2.6 in Ansible-2.4.
• Modules must be written to use proper Python-3 syntax. At some point in the future we’ll come up with rules for running on Python-3 but we’re not there yet. See Ansible and Porting to Python 3 for help on how to do this.

• Documentation: Make sure it exists

  • Module documentation should briefly and accurately define what each module and option does, and how it works with others in the underlying system. Documentation should be written for broad audience–readable both by experts and non-experts. This documentation is not meant to teach a total novice, but it also should not be reserved for the Illuminati (hard balance).
  • If an argument takes both C(True)/C(False) and C(Yes)/C(No), the documentation should use C(True) and C(False).
  • Descriptions should always start with a capital letter and end with a full stop. Consistency always helps.
  • The required setting is only required when true, otherwise it is assumed to be false.
  • If required is false/missing, default may be specified (assumed ‘null’ if missing). Ensure that the default parameter in docs matches default parameter in code.
  • Documenting default is not needed for required: true.
  • Remove unnecessary doc like aliases: [] or choices: [].
  • Do not use Boolean values in a choice list . For example, in the list choices: [‘no’, ‘verify’, ‘always], ‘no’ will be interpreted as a Boolean value (you can check basic.py for BOOLEANS_* constants to see the full list of Boolean keywords). If your option actually is a boolean, just use type=bool; there is no need to populate ‘choices’.
  • For new modules or options in a module add version_added. The version should match the value of the current development version and is a string (not a float), so be sure to enclose it in quotes.
  • Verify that arguments in doc and module spec dict are identical.
  • For password / secret arguments no_log=True should be set.
  • Requirements should be documented, using the requirements=[] field.
  • Author should be set, with their name and their github id, at the least.
  • Ensure that you make use of U() for urls, C() for files and options, I() for params, M() for modules.
  • If an optional parameter is sometimes required this need to be reflected in the documentation, e.g. “Required when C(state=present).”
  • Verify that a GPL 3 License header is included.
  • Does module use check_mode? Could it be modified to use it? Document it. Documentation is everyone’s friend.
  • Examples–include them whenever possible and make sure they are reproducible.
  • Document the return structure of the module. Refer to Common Return Values and Documenting Your Module for additional information.

• Predictable user interface: This is a particularly important section as it is also an area where we need significant improvements.

  • Name consistency across modules (we’ve gotten better at this, but we still have many deviations).
  • Declarative operation (not CRUD)–this makes it easy for a user not to care what the existing state is, just about the final state. started/stopped, present/absent–don’t overload options too much. It is preferable to add a new, simple option than to add choices/states that don’t fit with existing ones.
  • Keep options small, having them take large data structures might save us a few tasks, but adds a complex requirement that we cannot easily validate before passing on to the module.
  • Allow an “expert mode”. This may sound like the absolute opposite of the previous one, but it is always best to let expert users deal with complex data. This requires different modules in some cases, so that you end up having one (1) expert module and several ‘piecemeal’ ones (ec2_vpc_net?). The reason for this is not, as many users express, because it allows a single task and keeps plays small (which just moves the data complexity into vars files, leaving you with a slightly different structure in another YAML file). It does, however, allow for a more ‘atomic’ operation against the underlying APIs and services.

• Informative responses: Please note, that for >= 2.0, it is required that return data to be documented.

  • Always return useful data, even when there is no change.
  • Be consistent about returns (some modules are too random), unless it is detrimental to the state/action.
  • Make returns reusable–most of the time you don’t want to read it, but you do want to process it and re-purpose it.
  • Return diff if in diff mode. This is not required for all modules, as it won’t make sense for certain ones, but please attempt to include this when applicable).

• Code: This applies to all code in general, but often seems to be missing from modules, so please keep the following in mind as you work.

  • Validate upfront–fail fast and return useful and clear error messages.
  • Defensive programming–modules should be designed simply enough that this should be easy. Modules should always handle errors gracefully and avoid direct stacktraces. Ansible deals with this better in 2.0 and returns them in the results.
  • Fail predictably–if we must fail, do it in a way that is the most expected. Either mimic the underlying tool or the general way the system works.
  • Modules should not do the job of other modules, that is what roles are for. Less magic is more.
  • Don’t reinvent the wheel. Part of the problem is that code sharing is not that easy nor documented, we also need to expand our base functions to provide common patterns (retry, throttling, etc).
  • Support check mode. This is not required for all modules, as it won’t make sense for certain ones, but please attempt to include this when applicable). For more information, refer to Check Mode As A Drift Test and Check Mode (“Dry Run”).

• Exceptions: The module must handle them. (exceptions are bugs)

  • Give out useful messages on what you were doing and you can add the exception message to that.
  • Avoid catchall exceptions, they are not very useful unless the underlying API gives very good error messages pertaining the attempted action.

• Module-dependent guidelines: Additional module guidelines may exist for certain families of modules.

  • Be sure to check out the modules themselves for additional information.

    • Amazon: https://github.com/ansible/ansible-modules-extras/blob/devel/cloud/amazon/GUIDELINES.md

  • Modules should make use of the “extends_documentation_fragment” to ensure documentation available. For example, the AWS module should include:

    extends_documentation_fragment:
        - aws
        - ec2
    

• The module must not use sys.exit() –> use fail_json() from the module object.

• Import custom packages in try/except and handled with fail_json() in main() e.g.:

  try:
      import foo
      HAS_LIB=True
  except:
      HAS_LIB=False
  

• The return structure should be consistent, even if NA/None are used for keys normally returned under other options.
• Are module actions idempotent? If not document in the descriptions or the notes.
• Import module snippets from ansible.module_utils.basic import * at the bottom, conserves line numbers for debugging.
• The module must have a main function that wraps the normal execution.

• Call your main() from a conditional so that it would be possible to import them into unittests in the future example:

  if __name__ == '__main__':
      main()
  

• Try to normalize parameters with other modules, you can have aliases for when user is more familiar with underlying API name for the option
• Being pep8 compliant is nice, but not a requirement. Specifically, the 80 column limit now hinders readability more that it improves it
• Avoid ‘action/command‘, they are imperative and not declarative, there are other ways to express the same thing
• Do not add list or info state options to an existing module - create a new _facts module.
• If you are asking ‘how can I have a module execute other modules’ ... you want to write a role
• Return values must be able to be serialized as json via the python stdlib json library. basic python types (strings, int, dicts, lists, etc) are serializable. A common pitfall is to try returning an object via exit_json(). Instead, convert the fields you need from the object into the fields of a dictionary and return the dictionary.
• When fetching URLs, please use either fetch_url or open_url from ansible.module_utils.urls rather than urllib2; urllib2 does not natively verify TLS certificates and so is insecure for https.

Windows modules checklist

• Favour native powershell and .net ways of doing things over calls to COM libraries or calls to native executables which may or may not be present in all versions of windows
• modules are in powershell (.ps1 files) but the docs reside in same name python file (.py)
• look at ansible/lib/ansible/module_utils/powershell.ps1 for common code, avoid duplication
• Ansible uses strictmode version 2.0 so be sure to test with that enabled

• start with:

  #!powershell
  

  then:

  <GPL header>
  

  then:

  # WANT_JSON
  # POWERSHELL_COMMON
  

  then, to parse all arguments into a variable modules generally use:

  $params = Parse-Args $args
  

• Arguments:

  • Try and use state present and state absent like other modules
  • You need to check that all your mandatory args are present. You can do this using the builtin Get-AnsibleParam function.

  • Required arguments:

    $package =  Get-AnsibleParam -obj $params -name name -failifempty $true
    

  • Required arguments with name validation:

    $state = Get-AnsibleParam -obj $params -name "State" -ValidateSet "Present","Absent" -resultobj $resultobj -failifempty $true
    

  • Optional arguments with name validation:

    $state = Get-AnsibleParam -obj $params -name "State" -default "Present" -ValidateSet "Present","Absent"
    

  • the If “FailIfEmpty” is true, the resultobj parameter is used to specify the object returned to fail-json. You can also override the default message using $emptyattributefailmessage (for missing required attributes) and $ValidateSetErrorMessage (for attribute validation errors)
  • Look at existing modules for more examples of argument checking.

• Results

  • The result object should allways contain an attribute called changed set to either $true or $false

  • Create your result object like this:

    $result = New-Object psobject @{
    changed = $false
    other_result_attribute = $some_value
    };
    
    If all is well, exit with a
    Exit-Json $result
    

  • Ensure anything you return, including errors can be converted to json.
  • Be aware that because exception messages could contain almost anything.
  • ConvertTo-Json will fail if it encounters a trailing in a string.
  • If all is not well use Fail-Json to exit.

• Have you tested for powershell 3.0 and 4.0 compliance?

Deprecating and making module aliases

Starting in 1.8, you can deprecate modules by renaming them with a preceding _, i.e. old_cloud.py to _old_cloud.py. This keeps the module available, but hides it from the primary docs and listing.

You can also rename modules and keep an alias to the old name by using a symlink that starts with _. This example allows the stat module to be called with fileinfo, making the following examples equivalent:

EXAMPLES = '''
ln -s stat.py _fileinfo.py
ansible -m stat -a "path=/tmp" localhost
ansible -m fileinfo -a "path=/tmp" localhost
'''

Appendix: Module Utilities

Ansible provides a number of module utilities that provide helper functions that you can use when developing your own modules. The basic.py module utility provides the main entry point for accessing the Ansible library, and all Ansible modules must, at minimum, import from basic.py:

from ansible.module_utils.basic import *

The following is a list of module_utils files and a general description. The module utility source code lives in the ./lib/module_utils directory under your main Ansible path - for more details on any specific module utility, please see the source code.

• a10.py - Utilities used by the a10_server module to manage A10 Networks devices.
• api.py - Adds shared support for generic API modules.
• asa.py - Module support utilities for managing Cisco ASA network devices.
• azure_rm_common.py - Definitions and utilities for Microsoft Azure Resource Manager template deployments.
• basic.py - General definitions and helper utilites for Ansible modules.
• cloudstack.py - Utilities for CloudStack modules.
• database.py - Miscellaneous helper functions for PostGRES and MySQL
• docker_common.py - Definitions and helper utilites for modules working with Docker.
• ec2.py - Definitions and utilites for modules working with Amazon EC2
• eos.py - Helper functions for modules working with EOS networking devices.
• f5.py - Helper functions for modules working with F5 networking devices.
• facts.py - Helper functions for modules that return facts.
• gce.py - Definitions and helper functions for modules that work with Google Compute Engine resources.
• ios.py - Definitions and helper functions for modules that manage Cisco IOS networking devices
• iosxr.py - Definitions and helper functions for modules that manage Cisco IOS-XR networking devices
• ismount.py - Contains single helper function that fixes os.path.ismount
• junos.py - Definitions and helper functions for modules that manage Junos networking devices
• known_hosts.py - Utilites for working with known_hosts file
• mysql.py - Allows modules to connect to a MySQL instance
• netcfg.py - Configuration utility functions for use by networking modules
• netcmd.py - Defines commands and comparison operators for use in networking modules
• network.py - Functions for running commands on networking devices
• nxos.py - Contains definitions and helper functions specific to Cisco NXOS networking devices
• openstack.py - Utilities for modules that work with Openstack instances.
• openswitch.py - Definitions and helper functions for modules that manage OpenSwitch devices
• powershell.ps1 - Utilities for working with Microsoft Windows clients
• pycompat24.py - Exception workaround for python 2.4
• rax.py - Definitions and helper functions for modules that work with Rackspace resources.
• redhat.py - Functions for modules that manage Red Hat Network registration and subscriptions
• service.py - Contains utilities to enable modules to work with Linux services (placeholder, not in use).
• shell.py - Functions to allow modules to create shells and work with shell commands
• six.py - Module utils for working with the Six python 2 and 3 compatibility library
• splitter.py - String splitting and manipulation utilites for working with Jinja2 templates
• urls.py - Utilities for working with http and https requests
• vca.py - Contains utilities for modules that work with VMware vCloud Air
• vmware.py - Contains utilities for modules that work with VMware vSphere VMs
• vyos.py - Definitions and functions for working with VyOS networking