salt/doc/topics/development/tests/unit.rst

Writing Unit Tests

Introduction

Like many software projects, Salt has two broad-based testing approaches --integration testing and unit testing. While integration testing focuses on the interaction between components in a sandboxed environment, unit testing focuses on the singular implementation of individual functions.

Unit tests should be used specifically to test a function's logic. Unit tests rely on mocking external resources.

While unit tests are good for ensuring consistent results, they are most useful when they do not require more than a few mocks. Effort should be made to mock as many external resources as possible. This effort is encouraged, but not required. Sometimes the isolation provided by completely mocking the external dependencies is not worth the effort of mocking those dependencies.

In these cases, requiring an external library to be installed on the system before running the test file is a useful way to strike this balance. For example, the unit tests for the MySQL execution module require the presence of the MySQL python bindings on the system running the test file before proceeding to run the tests.

Overly detailed mocking can also result in decreased test readability and brittleness as the tests are more likely to fail when the code or its dependencies legitimately change. In these cases, it is better to add dependencies to the test runner dependency state.

Preparing to Write a Unit Test

This guide assumes 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 Installing Salt for Development<installing-for-development> and the Contributing<contributing> pages, respectively.

This documentation also assumes that you have an understanding of how to run Salt's test suite<running-the-tests>, including running the unit test subsection<running-test-subsections>, running the unit tests without testing daemons<running-unit-tests-no-daemons> to speed up development wait times, and running a unit test file, class, or individual test.

Best Practices

Unit tests should be written to the following specifications.

What to Test?

Since unit testing focuses on the singular implementation of individual functions, unit tests should be used specifically to test a function's logic. The following guidelines should be followed when writing unit tests for Salt's test suite:

• Each raise and return statement needs to be independently tested.
• Isolate testing functionality. Don't rely on the pass or failure of other, separate tests.
• Test functions should contain only one assertion.
• Many Salt execution modules are merely wrappers for distribution-specific functionality. If there isn't any logic present in a simple execution module, consider writing an integration test<integration-tests> instead of heavily mocking a call to an external dependency.

Mocking Test Data

A reasonable effort needs to be made to mock external resources used in the code being tested, such as APIs, function calls, external data either globally available or passed in through function arguments, file data, etc.

• Test functions should contain only one assertion and all necessary mock code and data for that assertion.
• External resources should be mocked in order to "block all of the exits". If a test function fails because something in an external library wasn't mocked properly (or at all), this test is not addressing all of the "exits" a function may experience. We want the Salt code and logic to be tested, specifically.
• Consider the fragility and longevity of a test. If the test is so tightly coupled to the code being tested, this makes a test unnecessarily fragile.
• Make sure you are not mocking the function to be tested so vigorously that the test return merely tests the mocked output. The test should always be testing a function's logic.

Mocking Loader Modules

Salt loader modules use a series of globally available dunder variables, __salt__, __opts__, __pillar__, etc. To facilitate testing these modules a mixin class was created, LoaderModuleMockMixin which can be found in tests/support/mixins.py. The reason for the existence of this class is because historically one would add these dunder variables directly on the imported module. This, however, introduces unexpected behavior when running the full test suite since those attributes would not be removed once we were done testing the module and would therefore leak to other modules being tested with unpredictable results. This is the kind of work that should be deferred to mock, and that's exactly what this mixin class does.

As an example, if one needs to specify some options which should be available to the module being tested one should do:

import salt.modules.somemodule as somemodule


class SomeModuleTest(TestCase, LoaderModuleMockMixin):
    def setup_loader_modules(self):
        return {somemodule: {"__opts__": {"test": True}}}

Consider this more extensive example from tests/unit/modules/test_libcloud_dns.py:

# Import Python Libs
from __future__ import absolute_import

# Import Salt Testing Libs
from tests.support.mixins import LoaderModuleMockMixin
from tests.support.unit import TestCase
from tests.support.mock import patch, MagicMock
import salt.modules.libcloud_dns as libcloud_dns


class MockDNSDriver(object):
    def __init__(self):
        pass


def get_mock_driver():
    return MockDNSDriver()


@patch("salt.modules.libcloud_dns._get_driver", MagicMock(return_value=MockDNSDriver()))
class LibcloudDnsModuleTestCase(TestCase, LoaderModuleMockMixin):
    def setup_loader_modules(self):
        module_globals = {
            "__salt__": {
                "config.option": MagicMock(
                    return_value={"test": {"driver": "test", "key": "2orgk34kgk34g"}}
                )
            }
        }
        if libcloud_dns.HAS_LIBCLOUD is False:
            module_globals["sys.modules"] = {"libcloud": MagicMock()}

        return {libcloud_dns: module_globals}

What happens in the above example is we mock a call to __salt__['config.option'] to return the configuration needed for the execution of the tests. Additionally, if the libcloud library is not available, since that's not actually part of what's being tested, we mocked that import by patching sys.modules when tests are running.

Mocking Filehandles

Note

This documentation applies to the 2018.3 release cycle and newer. The extended functionality for mock_open described below does not exist in the 2017.7 and older release branches.

Opening files in Salt is done using salt.utils.files.fopen(). When testing code that reads from files, the mock_open helper can be used to mock filehandles. Note that is not the same mock_open as unittest.mock.mock_open from the Python standard library, but rather a separate implementation which has additional functionality.

from tests.support.unit import TestCase
from tests.support.mock import patch, mock_open

import salt.modules.mymod as mymod


class MyAwesomeTestCase(TestCase):
    def test_something(self):
        fopen_mock = mock_open(read_data="foo\nbar\nbaz\n")
        with patch("salt.utils.files.fopen", fopen_mock):
            result = mymod.myfunc()
            assert result is True

This will force any filehandle opened to mimic a filehandle which, when read, produces the specified contents.

Important

String Types

When running tests on Python 2, mock_open will convert any unicode types to str types to more closely reproduce Python 2 behavior (file reads are always str types in Python 2, irrespective of mode).

However, when configuring your read_data, make sure that you are using bytestrings (e.g. b'foo\nbar\nbaz\n') when the code you are testing is opening a file for binary reading, otherwise the tests will fail on Python 3. The mocked filehandles produced by mock_open will raise a TypeError if you attempt to read a bytestring when opening for non-binary reading, and similarly will not let you read a string when opening a file for binary reading. They will also not permit bytestrings to be "written" if the mocked filehandle was opened for non-binary writing, and vice-versa when opened for non-binary writing. These enhancements force test writers to write more accurate tests.

More Complex Scenarios

Multiple File Paths

What happens when the code being tested reads from more than one file? For those cases, you can pass read_data as a dictionary:

import textwrap

from tests.support.unit import TestCase
from tests.support.mock import patch, mock_open

import salt.modules.mymod as mymod


class MyAwesomeTestCase(TestCase):
    def test_something(self):
        contents = {
            "/etc/foo.conf": textwrap.dedent(
                """\
                foo
                bar
                baz
                """
            ),
            "/etc/b*.conf": textwrap.dedent(
                """\
                one
                two
                three
                """
            ),
        }
        fopen_mock = mock_open(read_data=contents)
        with patch("salt.utils.files.fopen", fopen_mock):
            result = mymod.myfunc()
            assert result is True

This would make salt.utils.files.fopen() produce filehandles with different contents depending on which file was being opened by the code being tested. /etc/foo.conf and any file matching the pattern /etc/b*.conf would work, while opening any other path would result in a FileNotFoundError being raised (in Python 2, an IOError).

Since file patterns are supported, it is possible to use a pattern of '*' to define a fallback if no other patterns match the filename being opened. The below two mock_open calls would produce identical results:

mock_open(read_data="foo\n")
mock_open(read_data={"*": "foo\n"})

Note

Take care when specifying the read_data as a dictionary, in cases where the patterns overlap (e.g. when both /etc/b*.conf and /etc/bar.conf are in the read_data). Dictionary iteration order will determine which pattern is attempted first, second, etc., with the exception of * which is used when no other pattern matches. If your test case calls for specifying overlapping patterns, and you are not running Python 3.6 or newer, then an OrderedDict can be used to ensure matching is handled in the desired way:

contents = OrderedDict()
contents["/etc/bar.conf"] = "foo\nbar\nbaz\n"
contents["/etc/b*.conf"] = IOError(errno.EACCES, "Permission denied")
contents["*"] = 'This is a fallback for files not beginning with "/etc/b"\n'
fopen_mock = mock_open(read_data=contents)

Raising Exceptions

Instead of a string, an exception can also be used as the read_data:

import errno

from tests.support.unit import TestCase
from tests.support.mock import patch, mock_open

import salt.modules.mymod as mymod


class MyAwesomeTestCase(TestCase):
    def test_something(self):
        exc = IOError(errno.EACCES, "Permission denied")
        fopen_mock = mock_open(read_data=exc)
        with patch("salt.utils.files.fopen", fopen_mock):
            mymod.myfunc()

The above example would raise the specified exception when any file is opened. The expectation would be that mymod.myfunc() would gracefully handle the IOError, so a failure to do that would result in it being raised and causing the test to fail.

Multiple File Contents

For cases in which a file is being read more than once, and it is necessary to test a function's behavior based on what the file looks like the second (or third, etc.) time it is read, just specify the contents for that file as a list. Each time the file is opened, mock_open will cycle through the list and produce a mocked filehandle with the specified contents. For example:

import errno
import textwrap

from tests.support.unit import TestCase
from tests.support.mock import patch, mock_open

import salt.modules.mymod as mymod


class MyAwesomeTestCase(TestCase):
    def test_something(self):
        contents = {
            "/etc/foo.conf": [
                textwrap.dedent(
                    """\
                    foo
                    bar
                    """
                ),
                textwrap.dedent(
                    """\
                    foo
                    bar
                    baz
                    """
                ),
            ],
            "/etc/b*.conf": [
                IOError(errno.ENOENT, "No such file or directory"),
                textwrap.dedent(
                    """\
                    one
                    two
                    three
                    """
                ),
            ],
        }
        fopen_mock = mock_open(read_data=contents)
        with patch("salt.utils.files.fopen", fopen_mock):
            result = mymod.myfunc()
            assert result is True

Using this example, the first time /etc/foo.conf is opened, it will simulate a file with the first string in the list as its contents, while the second time it is opened, the simulated file's contents will be the second string in the list.

If no more items remain in the list, then attempting to open the file will raise a RuntimeError. In the example above, if /etc/foo.conf were to be opened a third time, a RuntimeError would be raised.

Note that exceptions can also be mixed in with strings when using this technique. In the above example, if /etc/bar.conf were to be opened twice, the first time would simulate the file not existing, while the second time would simulate a file with string defined in the second element of the list.

Note

Notice that the second path in the contents dictionary above (/etc/b*.conf) contains an asterisk. The items in the list are cycled through for each match of a given pattern (not separately for each individual file path), so this means that only two files matching that pattern could be opened before the next one would raise a RuntimeError.

Accessing the Mocked Filehandles in a Test

Note

The code for the MockOpen, MockCall, and MockFH classes (referenced below) can be found in tests/support/mock.py. There are extensive unit tests for them located in tests/unit/test_mock.py.

The above examples simply show how to mock salt.utils.files.fopen() to simulate files with the contents you desire, but you can also access the mocked filehandles (and more), and use them to craft assertions in your tests. To do so, just add an as clause to the end of the patch statement:

fopen_mock = mock_open(read_data="foo\nbar\nbaz\n")
with patch("salt.utils.files.fopen", fopen_mock) as m_open:
    # do testing here
    ...
    ...

When doing this, m_open will be a MockOpen instance. It will contain several useful attributes:

• read_data - A dictionary containing the read_data passed when mock_open was invoked. In the event that multiple file paths <unit-tests-multiple-file-paths> are not used, then this will be a dictionary mapping * to the read_data passed to mock_open.

• call_count - An integer representing how many times salt.utils.files.fopen() was called to open a file.

• calls - A list of MockCall objects. A MockCall object is a simple class which stores the arguments passed to it, making the positional arguments available via its args attribute, and the keyword arguments available via its kwargs attribute.

  from tests.support.unit import TestCase
  from tests.support.mock import patch, mock_open, MockCall
  
  import salt.modules.mymod as mymod
  
  
  class MyAwesomeTestCase(TestCase):
      def test_something(self):
  
          with patch("salt.utils.files.fopen", mock_open(read_data=b"foo\n")) as m_open:
              mymod.myfunc()
              # Assert that only two opens attempted
              assert m_open.call_count == 2
              # Assert that only /etc/foo.conf was opened
              assert all(call.args[0] == "/etc/foo.conf" for call in m_open.calls)
              # Asser that the first open was for binary read, and the
              # second was for binary write.
              assert m_open.calls == [
                  MockCall("/etc/foo.conf", "rb"),
                  MockCall("/etc/foo.conf", "wb"),
              ]

  Note that MockCall is imported from tests.support.mock in the above example. Also, the second assert above is redundant since it is covered in the final assert, but both are included simply as an example.

• filehandles - A dictionary mapping the unique file paths opened, to lists of MockFH objects. Each open creates a unique MockFH object. Each MockFH object itself has a number of useful attributes:

  • filename - The path to the file which was opened using salt.utils.files.fopen()
  • call - A MockCall object representing the arguments passed to salt.utils.files.fopen(). Note that this MockCall is also available in the parent MockOpen instance's calls list.
  • The following methods are mocked using unittest.mock.Mock objects, and Mock's built-in asserts (as well as the call data) can be used as you would with any other Mock object:
    • .read()
    • .readlines()
    • .readline()
    • .close()
    • .write()
    • .writelines()
    • .seek()
  • The read functions (.read(), .readlines(), .readline()) all work as expected, as does iterating through the file line by line (i.e. for line in fh:).
  • The .tell() method is also implemented in such a way that it updates after each time the mocked filehandle is read, and will report the correct position. The one caveat here is that .seek() doesn't actually work (it's simply mocked), and will not change the position. Additionally, neither .write() or .writelines() will modify the mocked filehandle's contents.
  • The attributes .write_calls and .writelines_calls (no parenthesis) are available as shorthands and correspond to lists containing the contents passed for all calls to .write() and .writelines(), respectively.

Examples

with patch("salt.utils.files.fopen", mock_open(read_data=contents)) as m_open:
    # Run the code you are unit testing
    mymod.myfunc()
    # Check that only the expected file was opened, and that it was opened
    # only once.
    assert m_open.call_count == 1
    assert list(m_open.filehandles) == ["/etc/foo.conf"]
    # "opens" will be a list of all the mocked filehandles opened
    opens = m_open.filehandles["/etc/foo.conf"]
    # Check that we wrote the expected lines ("expected" here is assumed to
    # be a list of strings)
    assert opens[0].write_calls == expected

with patch("salt.utils.files.fopen", mock_open(read_data=contents)) as m_open:
    # Run the code you are unit testing
    mymod.myfunc()
    # Check that .readlines() was called (remember, it's a Mock)
    m_open.filehandles["/etc/foo.conf"][0].readlines.assert_called()

with patch("salt.utils.files.fopen", mock_open(read_data=contents)) as m_open:
    # Run the code you are unit testing
    mymod.myfunc()
    # Check that we read the file and also wrote to it
    m_open.filehandles["/etc/foo.conf"][0].read.assert_called_once()
    m_open.filehandles["/etc/foo.conf"][1].writelines.assert_called_once()

Naming Conventions

Test names and docstrings should indicate what functionality is being tested. Test functions are named test_<fcn>_<test-name> where <fcn> is the function being tested and <test-name> describes the raise or return being tested.

Unit tests for salt/.../<module>.py are contained in a file called tests/unit/.../test_<module>.py, e.g. the tests for salt/modules/fib.py are in tests/unit/modules/test_fib.py.

In order for unit tests to get picked up during a run of the unit test suite, each unit test file must be prefixed with test_ and each individual test must be prepended with the test_ naming syntax, as described above.

If a function does not start with test_, then the function acts as a "normal" function and is not considered a testing function. It will not be included in the test run or testing output. The same principle applies to unit test files that do not have the test_*.py naming syntax. This test file naming convention is how the test runner recognizes that a test file contains unit tests.

Imports

Most commonly, the following imports are necessary to create a unit test:

from tests.support.unit import TestCase

If you need mock support to your tests, please also import:

from tests.support.mock import MagicMock, patch, call

Evaluating Truth

A longer discussion on the types of assertions one can make can be found by reading Python's documentation on unit testing.

Tests Using Mock Objects

In many cases, the purpose of a Salt module is to interact with some external system, whether it be to control a database, manipulate files on a filesystem or something else. In these varied cases, it's necessary to design a unit test which can test the function whilst replacing functions which might actually call out to external systems. One might think of this as "blocking the exits" for code under tests and redirecting the calls to external systems with our own code which produces known results during the duration of the test.

To achieve this behavior, Salt makes heavy use of the MagicMock package.

To understand how one might integrate Mock into writing a unit test for Salt, let's imagine a scenario in which we're testing an execution module that's designed to operate on a database. Furthermore, let's imagine two separate methods, here presented in pseduo-code in an imaginary execution module called 'db.py'.

def create_user(username):
    qry = "CREATE USER {0}".format(username)
    execute_query(qry)


def execute_query(qry):
    # Connect to a database and actually do the query...
    ...

Here, let's imagine that we want to create a unit test for the create_user function. In doing so, we want to avoid any calls out to an external system and so while we are running our unit tests, we want to replace the actual interaction with a database with a function that can capture the parameters sent to it and return pre-defined values. Therefore, our task is clear -- to write a unit test which tests the functionality of create_user while also replacing 'execute_query' with a mocked function.

To begin, we set up the skeleton of our class much like we did before, but with additional imports for MagicMock:

# Import Salt Testing libs
from tests.support.unit import TestCase

# Import Salt execution module to test
from salt.modules import db

# Import Mock libraries
from tests.support.mock import MagicMock, patch, call

# Create test case class and inherit from Salt's customized TestCase
# Skip this test case if we don't have access to mock!
class DbTestCase(TestCase):
    def test_create_user(self):
        # First, we replace 'execute_query' with our own mock function
        with patch.object(db, "execute_query", MagicMock()) as db_exq:

            # Now that the exits are blocked, we can run the function under test.
            db.create_user("testuser")

            # We could now query our mock object to see which calls were made
            # to it.
            ## print db_exq.mock_calls

            # Construct a call object that simulates the way we expected
            # execute_query to have been called.
            expected_call = call("CREATE USER testuser")

            # Compare the expected call with the list of actual calls.  The
            # test will succeed or fail depending on the output of this
            # assertion.
            db_exq.assert_has_calls(expected_call)

Modifying __salt__ In Place

At times, it becomes necessary to make modifications to a module's view of functions in its own __salt__ dictionary. Luckily, this process is quite easy.

Below is an example that uses MagicMock's patch functionality to insert a function into __salt__ that's actually a MagicMock instance.

def show_patch(self):
    with patch.dict(my_module.__salt__,
                    {'function.to_replace': MagicMock()}):
        # From this scope, carry on with testing, with a modified __salt__!

A Simple Example

Let's assume that we're testing a very basic function in an imaginary Salt execution module. Given a module called fib.py that has a function called calculate(num_of_results), which given a num_of_results, produces a list of sequential Fibonacci numbers of that length.

A unit test to test this function might be commonly placed in a file called tests/unit/modules/test_fib.py. The convention is to place unit tests for Salt execution modules in test/unit/modules/ and to name the tests module prefixed with test_*.py.

Tests are grouped around test cases, which are logically grouped sets of tests against a piece of functionality in the tested software. Test cases are created as Python classes in the unit test module. To return to our example, here's how we might write the skeleton for testing fib.py:

# Import Salt Testing libs
from tests.support.unit import TestCase

# Import Salt execution module to test
import salt.modules.fib as fib

# Create test case class and inherit from Salt's customized TestCase
class FibTestCase(TestCase):
    """
    This class contains a set of functions that test salt.modules.fib.
    """

    def test_fib(self):
        """
        To create a unit test, we should prefix the name with `test_' so
        that it's recognized by the test runner.
        """
        fib_five = (0, 1, 1, 2, 3)
        self.assertEqual(fib.calculate(5), fib_five)

At this point, the test can now be run, either individually or as a part of a full run of the test runner. To ease development, a single test can be executed:

tests/runtests.py -v -n unit.modules.test_fib

This will report the status of the test: success, failure, or error. The -v flag increases output verbosity.

tests/runtests.py -n unit.modules.test_fib -v

To review the results of a particular run, take a note of the log location given in the output for each test:

Logging tests on /var/folders/nl/d809xbq577l3qrbj3ymtpbq80000gn/T/salt-runtests.log

A More Complete Example

Consider the following function from salt/modules/linux_sysctl.py.

def get(name):
    """
    Return a single sysctl parameter for this minion

    CLI Example:

    .. code-block:: bash

        salt '*' sysctl.get net.ipv4.ip_forward
    """
    cmd = "sysctl -n {0}".format(name)
    out = __salt__["cmd.run"](cmd)
    return out

This function is very simple, comprising only four source lines of code and having only one return statement, so we know only one test is needed. There are also two inputs to the function, the name function argument and the call to __salt__['cmd.run'](), both of which need to be appropriately mocked.

Mocking a function parameter is straightforward, whereas mocking a function call will require, in this case, the use of MagicMock. For added isolation, we will also redefine the __salt__ dictionary such that it only contains 'cmd.run'.

# Import Salt Libs
import salt.modules.linux_sysictl as linux_sysctl

# Import Salt Testing Libs
from tests.support.mixins import LoaderModuleMockMixin
from tests.support.unit import TestCase
from tests.support.mock import MagicMock, patch


class LinuxSysctlTestCase(TestCase, LoaderModuleMockMixin):
    """
    TestCase for salt.modules.linux_sysctl module
    """

    def test_get(self):
        """
        Tests the return of get function
        """
        mock_cmd = MagicMock(return_value=1)
        with patch.dict(linux_sysctl.__salt__, {"cmd.run": mock_cmd}):
            self.assertEqual(linux_sysctl.get("net.ipv4.ip_forward"), 1)

Since get() has only one raise or return statement and that statement is a success condition, the test function is simply named test_get(). As described, the single function call parameter, name is mocked with net.ipv4.ip_forward and __salt__['cmd.run'] is replaced by a MagicMock function object. We are only interested in the return value of __salt__['cmd.run'], which MagicMock allows us by specifying via return_value=1. Finally, the test itself tests for equality between the return value of get() and the expected return of 1. This assertion is expected to succeed because get() will determine its return value from __salt__['cmd.run'], which we have mocked to return 1.

A Complex Example

Now consider the assign() function from the same salt/modules/linux_sysctl.py source file.

def assign(name, value):
    """
    Assign a single sysctl parameter for this minion

    CLI Example:

    .. code-block:: bash

        salt '*' sysctl.assign net.ipv4.ip_forward 1
    """
    value = str(value)
    sysctl_file = "/proc/sys/{0}".format(name.replace(".", "/"))
    if not os.path.exists(sysctl_file):
        raise CommandExecutionError("sysctl {0} does not exist".format(name))

    ret = {}
    cmd = 'sysctl -w {0}="{1}"'.format(name, value)
    data = __salt__["cmd.run_all"](cmd)
    out = data["stdout"]
    err = data["stderr"]

    # Example:
    #    # sysctl -w net.ipv4.tcp_rmem="4096 87380 16777216"
    #    net.ipv4.tcp_rmem = 4096 87380 16777216
    regex = re.compile(r"^{0}\s+=\s+{1}$".format(re.escape(name), re.escape(value)))

    if not regex.match(out) or "Invalid argument" in str(err):
        if data["retcode"] != 0 and err:
            error = err
        else:
            error = out
        raise CommandExecutionError("sysctl -w failed: {0}".format(error))
    new_name, new_value = out.split(" = ", 1)
    ret[new_name] = new_value
    return ret

This function contains two raise statements and one return statement, so we know that we will need (at least) three tests. It has two function arguments and many references to non-builtin functions. In the tests below you will see that MagicMock's patch() method may be used as a context manager or as a decorator. When patching the salt dunders however, please use the context manager approach.

There are three test functions, one for each raise and return statement in the source function. Each function is self-contained and contains all and only the mocks and data needed to test the raise or return statement it is concerned with.

# Import Salt Libs
import salt.modules.linux_sysctl as linux_sysctl
from salt.exceptions import CommandExecutionError

# Import Salt Testing Libs
from tests.support.mixins import LoaderModuleMockMixin
from tests.support.unit import TestCase
from tests.support.mock import MagicMock, patch


class LinuxSysctlTestCase(TestCase, LoaderModuleMockMixin):
    """
    TestCase for salt.modules.linux_sysctl module
    """

    @patch("os.path.exists", MagicMock(return_value=False))
    def test_assign_proc_sys_failed(self):
        """
        Tests if /proc/sys/<kernel-subsystem> exists or not
        """
        cmd = {
            "pid": 1337,
            "retcode": 0,
            "stderr": "",
            "stdout": "net.ipv4.ip_forward = 1",
        }
        mock_cmd = MagicMock(return_value=cmd)
        with patch.dict(linux_sysctl.__salt__, {"cmd.run_all": mock_cmd}):
            self.assertRaises(
                CommandExecutionError, linux_sysctl.assign, "net.ipv4.ip_forward", 1
            )

    @patch("os.path.exists", MagicMock(return_value=True))
    def test_assign_cmd_failed(self):
        """
        Tests if the assignment was successful or not
        """
        cmd = {
            "pid": 1337,
            "retcode": 0,
            "stderr": 'sysctl: setting key "net.ipv4.ip_forward": Invalid argument',
            "stdout": "net.ipv4.ip_forward = backward",
        }
        mock_cmd = MagicMock(return_value=cmd)
        with patch.dict(linux_sysctl.__salt__, {"cmd.run_all": mock_cmd}):
            self.assertRaises(
                CommandExecutionError,
                linux_sysctl.assign,
                "net.ipv4.ip_forward",
                "backward",
            )

    @patch("os.path.exists", MagicMock(return_value=True))
    def test_assign_success(self):
        """
        Tests the return of successful assign function
        """
        cmd = {
            "pid": 1337,
            "retcode": 0,
            "stderr": "",
            "stdout": "net.ipv4.ip_forward = 1",
        }
        ret = {"net.ipv4.ip_forward": "1"}
        mock_cmd = MagicMock(return_value=cmd)
        with patch.dict(linux_sysctl.__salt__, {"cmd.run_all": mock_cmd}):
            self.assertEqual(linux_sysctl.assign("net.ipv4.ip_forward", 1), ret)