pytest-ansible

pytest-ansible

The pytest-ansible plugin is designed to provide seamless integration between pytest and Ansible, allowing you to efficiently run and test Ansible-related tasks and scenarios within your pytest test suite. This plugin enhances the testing workflow by offering three distinct pieces of functionality:

1. Unit Testing for Ansible Collections: This feature aids in running unit tests for Ansible collections using pytest. It allows you to validate the behavior of your Ansible modules and roles in isolation, ensuring that each component functions as expected.

2. Molecule Scenario Integration: The plugin assists in running Molecule scenarios using pytest. This integration streamlines the testing of Ansible roles and playbooks across different environments, making it easier to identify and fix issues across diverse setups.

3. Ansible Integration for Pytest Tests: With this functionality, you can seamlessly use Ansible from within your pytest tests. This opens up possibilities to interact with Ansible components and perform tasks like provisioning resources, testing configurations, and more, all while leveraging the power and flexibility of pytest.

Supported Ansible

Pytest Ansible will only support versions of python and ansible-core which are under active upstream support which currently translates to:

• Python 3.10 or newer
• Ansible-core 2.14 or newer

Installation

Install this plugin using pip:

pip install pytest-ansible

Getting Started

Unit Testing for Ansible Collections

The pytest-ansible-units plugin allows ansible collection's unit tests to be run with only pytest. It offers a focused approach to testing individual Ansible modules. With this plugin, you can write and execute unit tests specifically for Ansible modules, ensuring the accuracy and reliability of your module code. This is particularly useful for verifying the correctness of module behavior in isolation.

To use pytest-ansible-units, follow these steps:

1. Install the plugin using pip:

pip install pytest-ansible

1. Ensure you have Python 3.10 or greater, ansible-core, and pyyaml installed.

2. Depending on your preferred directory structure, you can clone collections into the appropriate paths.

   • Collection Tree Approach: The preferred approach is to clone the collections being developed into it's proper collection tree path. This eliminates the need for any symlinks and other collections being developed can be cloned into the same tree structure.

     git clone <repo> collections/ansible_collections/<namespace>/<name>
     

     Note: Run pytest in the root of the collection directory, adjacent to the collection's galaxy.yml file.

   • Shallow Tree Approach:

     git clone <repo>
     

     Notes:

     • Run pytest in the root of the collection directory, adjacent to the collection's galaxy.yml file.
     • A collections directory will be created in the repository directory, and collection content will be linked into it.

3. Execute the unit tests using pytest: pytest tests

Help

The following may be added to the collections' pyproject.toml file to limit warnings and set the default path for the collection's tests

[tool.pytest.ini_options]
testpaths = [
    "tests",
]
filterwarnings = [
    'ignore:AnsibleCollectionFinder has already been configured',
]

Information from the galaxy.yml file is used to build the collections directory structure and link the contents. The galaxy.yml file should reflect the correct collection namespace and name.

One way to detect issues without running the tests is to run:

pytest --collect-only

The follow errors may be seen:

E   ModuleNotFoundError: No module named 'ansible_collections'

• Check the galaxy.yml file for an accurate namespace and name
• Ensure pytest is being run from the collection's root directory, adjacent to the galaxy.yml

HINT: remove __pycache__ / .pyc files and/or use a unique basename for your test file modules

Molecule Scenario Integration

This functionality assists in running Molecule scenarios using pytest. It enables pytest discovery of all molecule.yml files inside the codebase and runs them as pytest tests. It allows you to include Molecule scenarios as part of your pytest test suite, allowing you to thoroughly test your Ansible roles and playbooks across different scenarios and environments.

Running molecule scenarios using pytest

Molecule scenarios can be tested using 2 different methods if molecule is installed.

Recommended:

Add a test_integration.py file to the tests/integration directory of the ansible collection:

"""Tests for molecule scenarios."""
from __future__ import absolute_import, division, print_function

from pytest_ansible.molecule import MoleculeScenario


def test_integration(molecule_scenario: MoleculeScenario) -> None:
    """Run molecule for each scenario.

    :param molecule_scenario: The molecule scenario object
    """
    proc = molecule_scenario.test()
    assert proc.returncode == 0

The molecule_scenario fixture provides parameterized molecule scenarios discovered in the collection's extensions/molecule directory, as well as other directories within the collection.

molecule test -s <scenario> will be run for each scenario and a completed subprocess returned from the test() call.

Legacy:

Run molecule with the --molecule command line parameter to inject each molecule directory found in the current working directory. Each scenario will be injected as an external test in the the tests available for pytest. Due to the nature of this approach, the molecule scenarios are not represented as python tests and may not show in the IDE's pytest test tree.

To run Molecule scenarios using pytest, follow these steps:

1. Install the pytest-ansible plugin using pip:

pip install pytest-ansible

1. Execute pytest to run Molecule scenarios: pytest

Ansible Integration for Pytest Tests

The ansible_module, ansible_adhoc, localhost, and ansible_facts fixtures are provided to help you integrate Ansible functionalities into your pytest tests. These fixtures allow you to interact with Ansible modules, run commands on localhost, fetch Ansible facts, and more.

Fixtures and helpers for use in tests

Here's a quick overview of the available fixtures:

• ansible_module: Allows you to call Ansible modules directly within your test functions.
• ansible_adhoc: Provides a function to initialize a HostManager object to work with Ansible inventory.
• localhost: A convenience fixture for running Ansible modules that typically run on the local machine.
• ansible_facts: Returns a JSON structure representing system facts for the associated inventory.

Usage

Once installed, the following pytest command-line parameters are available:

pytest \
    [--inventory <path_to_inventory>] \
    [--extra-inventory <path_to_extra_inventory>] \
    [--host-pattern <host-pattern>] \
    [--connection <plugin>] \
    [--module-path <path_to_modules] \
    [--user <username>] \
    [--become] \
    [--become-user <username>] \
    [--become-method <method>] \
    [--ask-become-pass] \
    [--limit <limit>] \
    [--ansible-unit-inject-only] \
    [--molecule] \
    [--molecule-unavailable-driver] \
    [--skip-no-git-change] \
    [--check]

Inventory

Using ansible first starts with defining your inventory. This can be done in several ways, but to start, we'll use the ansible_adhoc fixture.

def test_my_inventory(ansible_adhoc):
    hosts = ansible_adhoc()

In the example above, the hosts variable is an instance of the HostManager class and describes your ansible inventory. For this to work, you'll need to tell ansible where to find your inventory. Inventory can be anything supported by ansible, which includes an INI file or an executable script that returns properly formatted JSON. For example,

pytest --inventory my_inventory.ini --host-pattern all

or

pytest --inventory path/to/my/script.py --host-pattern webservers

or

pytest --inventory one.example.com,two.example.com --host-pattern all

In the above examples, the inventory provided at runtime will be used in all tests that use the ansible_adhoc fixture. A more realistic scenario may involve using different inventory files (or host patterns) with different tests. To accomplish this, the fixture ansible_adhoc allows you to customize the inventory parameters. Read on for more detail on using the ansible_adhoc fixture.

Extra Inventory

Using ansible first starts with defining your extra inventory. This feature was added in version 2.3.0, and is intended to allow the user to work with two different inventories. This can be done in several ways, but to start, we'll use the ansible_adhoc fixture.

For example,

pytest --inventory my_inventory.ini --extra-inventory my_second_inventory.ini --host-pattern host_in_second_inventory

Fixture ansible_adhoc

The ansible_adhoc fixture returns a function used to initialize a HostManager object. The ansible_adhoc fixture will default to parameters supplied to the pytest command-line, but also allows one to provide keyword arguments used to initialize the inventory.

The example below demonstrates basic usage with options supplied at run-time to pytest.

def test_all_the_pings(ansible_adhoc):
    ansible_adhoc().all.ping()

The following example demonstrates available keyword arguments when creating a HostManager object.

def test_uptime(ansible_adhoc):
    # take down the database
    ansible_adhoc(inventory='db1.example.com,', user='ec2-user',
        become=True, become_user='root').all.command('reboot')

The HostManager object returned by the ansible_adhoc() function provides numerous ways of calling ansible modules against some, or all, of the inventory. The following demonstrates sample usage.

def test_host_manager(ansible_adhoc):
    hosts = ansible_adhoc()

    # __getitem__
    hosts['all'].ping()
    hosts['localhost'].ping()

    # __getattr__
    hosts.all.ping()
    hosts.localhost.ping()

    # Supports [ansible host patterns](http://docs.ansible.com/ansible/latest/intro_patterns.html)
    hosts['webservers:!phoenix'].ping()  # all webservers that are not in phoenix
    hosts[0].ping()
    hosts[0:2].ping()

    assert 'one.example.com' in hosts

    assert hasattr(hosts, 'two.example.com')

    for a_host in hosts:
        a_host.ping()

Fixture localhost

The localhost fixture is a convenience fixture that surfaces a ModuleDispatcher instance for ansible host running pytest. This is convenient when using ansible modules that typically run on the local machine, such as cloud modules (ec2, gce etc...).

def test_do_something_cloudy(localhost, ansible_adhoc):
    """Deploy an ec2 instance using multiple fixtures."""
    params = dict(
        key_name='some_key',
        instance_type='t2.micro',
        image='ami-123456',
        wait=True,
        group='webservers',
        count=1,
        vpc_subnet_id='subnet-29e63245',
        assign_public_ip=True,
    )

    # Deploy an ec2 instance from localhost using the `ansible_adhoc` fixture
    ansible_adhoc(inventory='localhost,', connection='local').localhost.ec2(**params)

    # Deploy an ec2 instance from localhost using the `localhost` fixture
    localhost.ec2(**params)

Fixture ansible_module

The ansible_module fixture allows tests and fixtures to call ansible modules. Unlike the ansible_adhoc fixture, this fixture only uses the options supplied to pytest at run time.

A very basic example demonstrating the ansible ping module:

def test_ping(ansible_module):
    ansible_module.ping()

A more involved example of updating the sshd configuration, and restarting the service.

def test_sshd_config(ansible_module):

    # update sshd MaxSessions
    contacted = ansible_module.lineinfile(
        dest="/etc/ssh/sshd_config",
        regexp="^#?MaxSessions .*",
        line="MaxSessions 150")
    )

    # assert desired outcome
    for (host, result) in contacted.items():
        assert 'failed' not in result, result['msg']
        assert 'changed' in result

    # restart sshd
    contacted = ansible_module.service(
        name="sshd",
        state="restarted"
    )

    # assert successful restart
    for (host, result) in contacted.items():
        assert 'changed' in result and result['changed']
        assert result['name'] == 'sshd'

    # do other stuff ...

Fixture ansible_facts

The ansible_facts fixture returns a JSON structure representing the system facts for the associated inventory. Sample fact data is available in the ansible documentation.

Note, this fixture is provided for convenience and could easily be called using ansible_module.setup().

A systems facts can be useful when deciding whether to skip a test ...

def test_something_with_amazon_ec2(ansible_facts):
    for facts in ansible_facts:
        if 'ec2.internal' != facts['ansible_domain']:
            pytest.skip("This test only applies to ec2 instances")

Additionally, since facts are just ansible modules, you could inspect the contents of the ec2_facts module for greater granularity ...

def test_terminate_us_east_1_instances(ansible_adhoc):

    for facts in ansible_adhoc().all.ec2_facts():
        if facts['ansible_ec2_placement_region'].startswith('us-east'):
            '''do some testing'''

Parameterize with pytest.mark.ansible

Perhaps the --ansible-inventory=<inventory> includes many systems, but you only wish to interact with a subset. The pytest.mark.ansible marker can be used to modify the pytest-ansible command-line parameters for a single test. Please note, the fixture ansible_adhoc is the prefer mechanism for interacting with ansible inventory within tests.

For example, to interact with the local system, you would adjust the host_pattern and connection parameters.

@pytest.mark.ansible(host_pattern='local,', connection='local')
def test_copy_local(ansible_module):

    # create a file with random data
    contacted = ansible_module.copy(
        dest='/etc/motd',
        content='PyTest is amazing!',
        owner='root',
        group='root',
        mode='0644',
    )

    # assert only a single host was contacted
    assert len(contacted) == 1, \
        "Unexpected number of hosts contacted (%d != %d)" % \
        (1, len(contacted))

    assert 'local' in contacted

    # assert the copy module reported changes
    assert 'changed' in contacted['local']
    assert contacted['local']['changed']

Note, the parameters provided by pytest.mark.ansible will apply to all class methods.

@pytest.mark.ansible(host_pattern='local,', connection='local')
class Test_Local(object):
    def test_install(self, ansible_module):
        '''do some testing'''
    def test_template(self, ansible_module):
        '''do some testing'''
    def test_service(self, ansible_module):
        '''do some testing'''

Inspecting results

When using the ansible_adhoc, localhost or ansible_module fixtures, the object returned will be an instance of class AdHocResult. The AdHocResult class can be inspected as follows:

def test_adhoc_result(ansible_adhoc):
    contacted = ansible_adhoc(inventory=my_inventory).command("date")

    # As a dictionary
    for (host, result) in contacted.items():
        assert result.is_successful, "Failed on host %s" % host
    for result in contacted.values():
        assert result.is_successful
    for host in contacted.keys():
        assert host in ['localhost', 'one.example.com']

    assert contacted.localhost.is_successful

    # As a list
    assert len(contacted) > 0
    assert 'localhost' in contacted

    # As an iterator
    for result in contacted:
        assert result.is_successful

    # With __getattr__
    assert contacted.localhost.is_successful

    # Or __getitem__
    assert contacted['localhost'].is_successful

Using the AdHocResult object provides ways to conveniently access results for different hosts involved in the ansible adhoc command. Once the specific host result is found, you may inspect the result of the ansible adhoc command on that use by way of the ModuleResult interface. The ModuleResult class represents the dictionary returned by the ansible module for a particular host. The contents of the dictionary depend on the module called.

The ModuleResult interface provides some convenient properties to determine the success of the module call. Examples are included below.

def test_module_result(localhost):
    contacted = localhost.command("find /tmp")

    assert contacted.localhost.is_successful
    assert contacted.localhost.is_ok
    assert contacted.localhost.is_changed
    assert not contacted.localhost.is_failed

    contacted = localhost.shell("exit 1")
    assert contacted.localhost.is_failed
    assert not contacted.localhost.is_successful

The contents of the JSON returned by an ansible module differs from module to module. For guidance, consult the documentation and examples for the specific ansible module.

Exception handling

If ansible is unable to connect to any inventory, an exception will be raised.

@pytest.mark.ansible(inventory='unreachable.example.com,')
def test_shutdown(ansible_module):

    # attempt to ping a host that is down (or doesn't exist)
    pytest.raises(pytest_ansible.AnsibleHostUnreachable):
        ansible_module.ping()

Sometimes, only a single host is unreachable, and others will have properly returned data. The following demonstrates how to catch the exception, and inspect the results.

@pytest.mark.ansible(inventory='good:bad')
def test_inventory_unreachable(ansible_module):
    exc_info = pytest.raises(pytest_ansible.AnsibleHostUnreachable, ansible_module.ping)
    (contacted, dark) = exc_info.value.results

    # inspect the JSON result...
    for (host, result) in contacted.items():
        assert result['ping'] == 'pong'

    for (host, result) in dark.items():
        assert result['failed'] == True

Communication

Refer to the Communication section of the documentation to find out how to get in touch with us.

You can also find more information in the Ansible communication guide.

Contributing

Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.

Code of Conduct

Please see the Ansible Community Code of Conduct.

License

Distributed under the terms of the MIT license, "pytest-ansible" is free and open source software

Issues

If you encounter any problems, please file an issue along with a detailed description.