doc/topics/tutorials/writing_tests.rst
.. _tutorial-salt-testing:
.. note::
This tutorial makes a couple of assumptions. The first assumption is that
you have a basic knowledge of Salt. To get up to speed, check out the
:ref:`Salt Walkthrough <tutorial-salt-walk-through>`.
The second assumption is that your Salt development environment is already
configured and that you have a basic understanding of contributing to the
Salt codebase. If you're unfamiliar with either of these topics, please refer
to the :ref:`Installing Salt for Development<installing-for-development>`
and the :ref:`Contributing<contributing>` pages, respectively.
Salt comes with a powerful integration and unit test suite. The test suite allows for the fully automated run of integration and/or unit tests from a single interface.
Salt's test suite is located under the tests directory in the root of Salt's
code base and is divided into two main types of tests:
:ref:unit tests and integration tests <integration-vs-unit>. The unit and
integration sub-test-suites are located in the tests directory, which is
where the majority of Salt's test cases are housed.
.. _getting_set_up_for_tests:
First of all you will need to ensure you install nox.
.. code-block:: bash
pip install nox
As noted in the introduction to this tutorial, Salt's test suite is located in the
tests directory in the root of Salt's code base. From there, the tests are divided
into two groups integration and unit. Within each of these directories, the
directory structure roughly mirrors the directory structure of Salt's own codebase.
For example, the files inside tests/integration/modules contains tests for the
files located within salt/modules.
.. note::
``tests/integration`` and ``tests/unit`` are the only directories discussed in
this tutorial. With the exception of the ``tests/runtests.py`` file, which is
used below in the `Running the Test Suite`_ section, the other directories and
files located in ``tests`` are outside the scope of this tutorial.
.. _integration-vs-unit:
Given that Salt's test suite contains two powerful, though very different, testing approaches, when should you write integration tests and when should you write unit tests?
Integration tests use Salt masters, minions, and a syndic to test salt functionality directly and focus on testing the interaction of these components. Salt's integration test runner includes functionality to run Salt execution modules, runners, states, shell commands, salt-ssh commands, salt-api commands, and more. This provides a tremendous ability to use Salt to test itself and makes writing such tests a breeze. Integration tests are the preferred method of testing Salt functionality when possible.
Unit tests do not spin up any Salt daemons, but instead find their value in testing
singular implementations of individual functions. Instead of testing against specific
interactions, unit tests should be used to test a function's logic. Unit tests should
be used to test a function's exit point(s) such as any return or raises
statements.
Unit tests are also useful in cases where writing an integration test might not be possible. While the integration test suite is extremely powerful, unfortunately at this time, it does not cover all functional areas of Salt's ecosystem. For example, at the time of this writing, there is not a way to write integration tests for Proxy Minions. Since the test runner will need to be adjusted to account for Proxy Minion processes, unit tests can still provide some testing support in the interim by testing the logic contained inside Proxy Minion functions.
Once all of the :ref:requirements <getting_set_up_for_tests> are installed, the
nox command is used to instantiate Salt's test suite:
.. code-block:: bash
nox -e 'test-3(coverage=False)'
The command above, if executed without any options, will run the entire suite of integration and unit tests. Some tests require certain flags to run, such as destructive tests. If these flags are not included, then the test suite will only perform the tests that don't require special attention.
At the end of the test run, you will see a summary output of the tests that passed, failed, or were skipped.
You can pass any pytest options after the nox command like so:
.. code-block:: bash
nox -e 'test-3(coverage=False)' -- tests/unit/modules/test_ps.py
The above command will run the test_ps.py test with the zeromq transport, python3,
and pytest. Pass any pytest options after --
Salt's set of integration tests use Salt to test itself. The integration portion of the test suite includes some built-in Salt daemons that will spin up in preparation of the test run. This list of Salt daemon processes includes:
These various daemons are used to execute Salt commands and functionality within the test suite, allowing you to write tests to assert against expected or unexpected behaviors.
A simple example of a test utilizing a typical master/minion execution module command
is the test for the test_ping function in the
tests/integration/modules/test_test.py
file:
.. code-block:: python
def test_ping(self):
"""
test.ping
"""
self.assertTrue(self.run_function("test.ping"))
The test above is a very simple example where the test.ping function is
executed by Salt's test suite runner and is asserting that the minion returned
with a True response.
.. _test-selection-options:
Test Selection Options
If you want to run only a subset of tests, this is easily done with pytest. You only
need to point the test runner to the directory. For example if you want to run all
integration module tests:
.. code-block:: bash
nox -e 'test-3(coverage=False)' -- tests/integration/modules/
Running Unit Tests
------------------
If you want to run only the unit tests, you can just pass the unit test directory
as an option to the test runner.
The unit tests do not spin up any Salt testing daemons as the integration tests
do and execute very quickly compared to the integration tests.
.. code-block:: bash
nox -e 'test-3(coverage=False)' -- tests/unit/
.. _running-specific-tests:
Running Specific Tests
----------------------
There are times when a specific test file, test class, or even a single,
individual test need to be executed, such as when writing new tests. In these
situations, you should use the `pytest syntax`_ to select the specific tests.
For running a single test file, such as the pillar module test file in the
integration test directory, you must provide the file path.
.. code-block:: bash
nox -e 'test-3(coverage=False)' -- tests/pytests/integration/modules/test_pillar.py
Some test files contain only one test class while other test files contain multiple
test classes. To run a specific test class within the file, append the name of
the test class to the end of the file path:
.. code-block:: bash
nox -e 'test-3(coverage=False)' -- tests/pytests/integration/modules/test_pillar.py::PillarModuleTest
To run a single test within a file, append both the name of the test class the
individual test belongs to, as well as the name of the test itself:
.. code-block:: bash
nox -e 'test-3(coverage=False)' -- tests/pytests/integration/modules/test_pillar.py::PillarModuleTest::test_data
The following command is an example of how to execute a single test found in
the ``tests/unit/modules/test_cp.py`` file:
.. code-block:: bash
nox -e 'test-3(coverage=False)' -- tests/pytests/unit/modules/test_cp.py::CpTestCase::test_get_file_not_found
Writing Tests for Salt
======================
Once you're comfortable running tests, you can now start writing them! Be sure
to review the `Integration vs. Unit`_ section of this tutorial to determine what
type of test makes the most sense for the code you're testing.
.. note::
There are many decorators, naming conventions, and code specifications
required for Salt test files. We will not be covering all of the these specifics
in this tutorial. Please refer to the testing documentation links listed below
in the `Additional Testing Documentation`_ section to learn more about these
requirements.
In the following sections, the test examples assume the "new" test is added to
a test file that is already present and regularly running in the test suite and
is written with the correct requirements.
Writing Integration Tests
-------------------------
Since integration tests validate against a running environment, as explained in the
`Running Integration Tests`_ section of this tutorial, integration tests are very
easy to write and are generally the preferred method of writing Salt tests.
The following integration test is an example taken from the ``test.py`` file in the
``tests/integration/modules`` directory. This test uses the ``run_function`` method
to test the functionality of a traditional execution module command.
The ``run_function`` method uses the integration test daemons to execute a
``module.function`` command as you would with Salt. The minion runs the function and
returns. The test also uses `Python's Assert Functions`_ to test that the
minion's return is expected.
.. code-block:: python
def test_ping(self):
"""
test.ping
"""
self.assertTrue(self.run_function("test.ping"))
Args can be passed in to the ``run_function`` method as well:
.. code-block:: python
def test_echo(self):
"""
test.echo
"""
self.assertEqual(self.run_function("test.echo", ["text"]), "text")
The next example is taken from the
``tests/integration/modules/test_aliases.py`` file and
demonstrates how to pass kwargs to the ``run_function`` call. Also note that this
test uses another salt function to ensure the correct data is present (via the
``aliases.set_target`` call) before attempting to assert what the ``aliases.get_target``
call should return.
.. code-block:: python
def test_set_target(self):
"""
aliases.set_target and aliases.get_target
"""
set_ret = self.run_function("aliases.set_target", alias="fred", target="bob")
self.assertTrue(set_ret)
tgt_ret = self.run_function("aliases.get_target", alias="fred")
self.assertEqual(tgt_ret, "bob")
Using multiple Salt commands in this manner provides two useful benefits. The first is
that it provides some additional coverage for the ``aliases.set_target`` function.
The second benefit is the call to ``aliases.get_target`` is not dependent on the
presence of any aliases set outside of this test. Tests should not be dependent on
the previous execution, success, or failure of other tests. They should be isolated
from other tests as much as possible.
While it might be tempting to build out a test file where tests depend on one another
before running, this should be avoided. SaltStack recommends that each test should
test a single functionality and not rely on other tests. Therefore, when possible,
individual tests should also be broken up into singular pieces. These are not
hard-and-fast rules, but serve more as recommendations to keep the test suite simple.
This helps with debugging code and related tests when failures occur and problems
are exposed. There may be instances where large tests use many asserts to set up a
use case that protects against potential regressions.
.. note::
The examples above all use the ``run_function`` option to test execution module
functions in a traditional master/minion environment. To see examples of how to
test other common Salt components such as runners, salt-api, and more, please
refer to the :ref:`Integration Test Class Examples<integration-class-examples>`
documentation.
Destructive vs Non-destructive Tests
Since Salt is used to change the settings and behavior of systems, often, the best approach to run tests is to make actual changes to an underlying system. This is where the concept of destructive integration tests comes into play. Tests can be written to alter the system they are running on. This capability is what fills in the gap needed to properly test aspects of system management like package installation.
To write a destructive test, decorate the test function with the
destructive_test:
.. code-block:: python
@pytest.mark.destructive_test
def test_pkg_install(salt_cli):
ret = salt_cli.run("pkg.install", "finch")
assert ret
As explained in the Integration vs. Unit_ section above, unit tests should be
written to test the logic of a function. This includes focusing on testing
return and raises statements. Substantial effort should be made to mock
external resources that are used in the code being tested.
External resources that should be mocked include, but are not limited to, APIs,
function calls, external data either globally available or passed in through
function arguments, file data, etc. This practice helps to isolate unit tests to
test Salt logic. One handy way to think about writing unit tests is to "block
all of the exits". More information about how to properly mock external resources
can be found in Salt's :ref:Unit Test<unit-tests> documentation.
Salt's unit tests utilize Python's mock class as well as MagicMock_. The
@patch decorator is also heavily used when "blocking all the exits".
A simple example of a unit test currently in use in Salt is the
test_get_file_not_found test in the tests/pytests/unit/modules/test_cp.py file.
This test uses the @patch decorator and MagicMock to mock the return
of the call to Salt's cp.hash_file execution module function. This ensures
that we're testing the cp.get_file function directly, instead of inadvertently
testing the call to cp.hash_file, which is used in cp.get_file.
.. code-block:: python
def test_get_file_not_found(self):
"""
Test if get_file can't find the file.
"""
with patch("salt.modules.cp.hash_file", MagicMock(return_value=False)):
path = "salt://saltines"
dest = "/srv/salt/cheese"
ret = ""
assert cp.get_file(path, dest) == ret
Note that Salt's cp module is imported at the top of the file, along with all
of the other necessary testing imports. The get_file function is then called
directed in the testing function, instead of using the run_function method as
the integration test examples do above.
The call to cp.get_file returns an empty string when a hash_file isn't found.
Therefore, the example above is a good illustration of a unit test "blocking
the exits" via the @patch decorator, as well as testing logic via asserting
against the return statement in the if clause. In this example we used the
python assert to verify the return from cp.get_file. Pytest allows you to use
these asserts_ when writing your tests and, in fact, plain asserts_ is the preferred
way to assert anything in your tests. As Salt dives deeper into Pytest, the use of
unittest.TestClass will be replaced by plain test functions, or test functions grouped
in a class, which does not subclass unittest.TestClass, which, of course, doesn't
work with unittest assert functions.
There are more examples of writing unit tests of varying complexities available in the following docs:
Simple Unit Test Example<simple-unit-example>Complete Unit Test Example<complete-unit-example>Complex Unit Test Example<complex-unit-example>.. note::
Considerable care should be made to ensure that you're testing something
useful in your test functions. It is very easy to fall into a situation
where you have mocked so much of the original function that the test
results in only asserting against the data you have provided. This results
in a poor and fragile unit test.
The test dependencies for python modules are managed under the requirements/static/ci
directory. You will need to add your module to the appropriate file under requirements/static/ci.
When pre-commit is run it will create all of the needed requirement files
under requirements/static/ci/py3{6,7,8,9}. Nox will then use these files to install
the requirements for the tests.
If you need to add a system dependency for the test run, this will need to be added in
the salt-ci-images_ repo. This repo uses salt states to install system dependencies.
You need to update the state-tree/golden-images-provision.sls file with
your dependency to ensure it is installed. Once your PR is merged the core team
will need to promote the new images with your new dependency installed.
To test to see if a given log message has been emitted, the following pattern can be used
.. code-block:: python
def test_issue_58763_a(tmp_path, modules, state_tree, caplog):
venv_dir = tmp_path / "issue-2028-pip-installed"
sls_contents = """
test.random_hash:
module.run:
- size: 10
- hash_type: md5
"""
with pytest.helpers.temp_file("issue-58763.sls", sls_contents, state_tree):
with caplog.at_level(logging.DEBUG):
ret = modules.state.sls(
mods="issue-58763",
)
assert len(ret.raw) == 1
for k in ret.raw:
assert ret.raw[k]["result"] is True
assert (
"Detected legacy module.run syntax: test.random_hash" in caplog.messages
)
Salt has four groups
Pytest Decorators
.. code-block:: python
@pytest.mark.core_test
def test_ping(self):
"""
test.ping
"""
self.assertTrue(self.run_function("test.ping"))
You can also mark all the tests in file.
.. code-block:: python
pytestmark = [
pytest.mark.core_test,
]
def test_ping(self):
"""
test.ping
"""
self.assertTrue(self.run_function("test.ping"))
def test_ping2(self):
"""
test.ping
"""
for _ in range(10):
self.assertTrue(self.run_function("test.ping"))
You can enable or disable test groups locally by passing there respected flag:
In your PR you can enable or disable test groups by setting a label. All thought the fast, slow and core tests specified in the change file will always run.
In addition to this tutorial, there are some other helpful resources and documentation that go into more depth on Salt's test runner, writing tests for Salt code, and general Python testing documentation. Please see the follow references for more information:
Salt's Test Suite Documentation<salt-test-suite>Integration Tests<integration-tests>Unit Tests<unit-tests>MagicMock_Python Unittest_Python's Assert Functions_.. _asserts: https://docs.pytest.org/en/latest/assert.html .. _pytest syntax: https://docs.pytest.org/en/latest/usage.html#specifying-tests-selecting-tests .. _MagicMock: https://docs.python.org/3/library/unittest.mock.html .. _Python Unittest: https://docs.python.org/3/library/unittest.html .. _Python's Assert Functions: https://docs.python.org/3/library/unittest.html#assert-methods .. _salt-ci-images: https://github.com/saltstack/salt-ci-images