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Thin-wrapper around the mock package for easier use with pytest

Project description

This plugin provides a mocker fixture which is a thin-wrapper around the patching API provided by the mock package:

import os

class UnixFS:

    def rm(filename):

def test_unix_fs(mocker):

Besides undoing the mocking automatically after the end of the test, it also provides other nice utilities such as spy and stub, and uses pytest introspection when comparing calls.

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Professionally supported pytest-mock is now available


The mocker fixture has the same API as mock.patch, supporting the same arguments:

def test_foo(mocker):
    # all valid calls
    mocker.patch.object(os, 'listdir', autospec=True)
    mocked_isfile = mocker.patch('os.path.isfile')

The supported methods are:

Also, as a convenience, these names from the mock module are accessible directly from mocker:

It is also possible to use mocking functionality from fixtures of other scopes using the appropriate mock fixture:

  • class_mocker
  • module_mocker
  • package_mocker
  • session_mocker

Type Annotations

New in version 3.3.0.

pytest-mock is fully type annotated, letting users use static type checkers to test their code.

The mocker fixture returns pytest_mock.MockerFixture which can be used to annotate test functions:

from pytest_mock import MockerFixture

def test_foo(mocker: MockerFixture) -> None:

The type annotations have been checked with mypy, which is the only type checker supported at the moment; other type-checkers might work but are not currently tested.


The mocker.spy object acts exactly like the original method in all cases, except the spy also tracks function/method calls, return values and exceptions raised.

def test_spy_method(mocker):
    class Foo(object):
        def bar(self, v):
            return v * 2

    foo = Foo()
    spy = mocker.spy(foo, 'bar')
    assert == 42

    assert spy.spy_return == 42

def test_spy_function(mocker):
    # mymodule declares `myfunction` which just returns 42
    import mymodule

    spy = mocker.spy(mymodule, "myfunction")
    assert mymodule.myfunction() == 42
    assert spy.call_count == 1
    assert spy.spy_return == 42

The object returned by mocker.spy is a MagicMock object, so all standard checking functions are available (like assert_called_once_with or call_count in the examples above).

In addition, spy objects contain two extra attributes:

  • spy_return: contains the returned value of the spied function.
  • spy_exception: contain the last exception value raised by the spied function/method when it was last called, or None if no exception was raised.

Besides functions and normal methods, mocker.spy also works for class and static methods.

As of version 3.0.0, mocker.spy also works with async def functions.


In versions earlier than 2.0, the attributes were called return_value and side_effect respectively, but due to incompatibilities with unittest.mock they had to be renamed (see #175 for details).


The stub is a mock object that accepts any arguments and is useful to test callbacks. It may receive an optional name that is shown in its repr, useful for debugging.

def test_stub(mocker):
    def foo(on_something):
        on_something('foo', 'bar')

    stub = mocker.stub(name='on_something_stub')

    stub.assert_called_once_with('foo', 'bar')

Improved reporting of mock call assertion errors

This plugin monkeypatches the mock library to improve pytest output for failures of mock call assertions like Mock.assert_called_with() by hiding internal traceback entries from the mock module.

It also adds introspection information on differing call arguments when calling the helper methods. This features catches AssertionError raised in the method, and uses pytest’s own advanced assertions to return a better diff:

mocker = <pytest_mock.MockerFixture object at 0x0381E2D0>

    def test(mocker):
        m = mocker.Mock()
>       m.assert_called_once_with('', bar=4)
E       AssertionError: Expected call: mock('', bar=4)
E       Actual call: mock('fo')
E       pytest introspection follows:
E       Args:
E       assert ('fo',) == ('',)
E         At index 0 diff: 'fo' != ''
E         Use -v to get the full diff
E       Kwargs:
E       assert {} == {'bar': 4}
E         Right contains more items:
E         {'bar': 4}
E         Use -v to get the full diff AssertionError
========================== 1 failed in 0.03 seconds ===========================

This is useful when asserting mock calls with many/nested arguments and trying to quickly see the difference.

This feature is probably safe, but if you encounter any problems it can be disabled in your pytest.ini file:

mock_traceback_monkeypatch = false

Note that this feature is automatically disabled with the --tb=native option. The underlying mechanism used to suppress traceback entries from mock module does not work with that option anyway plus it generates confusing messages on Python 3.5 due to exception chaining

Use standalone “mock” package

New in version 1.4.0.

Python 3 users might want to use a newest version of the mock package as published on PyPI than the one that comes with the Python distribution.

mock_use_standalone_module = true

This will force the plugin to import mock instead of the unittest.mock module bundled with Python 3.4+. Note that this option is only used in Python 3+, as Python 2 users only have the option to use the mock package from PyPI anyway.

Note about usage as context manager

Although mocker’s API is intentionally the same as mock.patch’s, its use as context manager and function decorator is not supported through the fixture:

def test_context_manager(mocker):
    a = A()
    with mocker.patch.object(a, 'doIt', return_value=True, autospec=True):  # DO NOT DO THIS
        assert a.doIt() == True

The purpose of this plugin is to make the use of context managers and function decorators for mocking unnecessary, so it will emit a warning when used as such.

If you really intend to mock a context manager, mocker.patch.context_manager exists which won’t issue the above warning.


Install using pip:

$ pip install pytest-mock


Please consult the changelog page.

Why bother with a plugin?

There are a number of different patch usages in the standard mock API, but IMHO they don’t scale very well when you have more than one or two patches to apply.

It may lead to an excessive nesting of with statements, breaking the flow of the test:

import mock

def test_unix_fs():
    with mock.patch('os.remove'):

        with mock.patch('os.listdir'):
            assert'dir') == expected
            # ...

    with mock.patch('shutil.copy'):
        UnixFS.cp('src', 'dst')
        # ...

One can use patch as a decorator to improve the flow of the test:

def test_unix_fs(mocked_copy, mocked_listdir, mocked_remove):

    assert'dir') == expected
    # ...

    UnixFS.cp('src', 'dst')
    # ...

But this poses a few disadvantages:

  • test functions must receive the mock objects as parameter, even if you don’t plan to access them directly; also, order depends on the order of the decorated patch functions;
  • receiving the mocks as parameters doesn’t mix nicely with pytest’s approach of naming fixtures as parameters, or pytest.mark.parametrize;
  • you can’t easily undo the mocking during the test execution;

An alternative is to use contextlib.ExitStack to stack the context managers in a single level of indentation to improve the flow of the test:

import contextlib
import mock

def test_unix_fs():
    with contextlib.ExitStack() as stack:

        assert'dir') == expected
        # ...

        UnixFS.cp('src', 'dst')
        # ...

But this is arguably a little more complex than using pytest-mock.


Contributions are welcome! After cloning the repository, create a virtual env and install pytest-mock in editable mode with dev extras:

$ pip install --editable .[dev]
$ pre-commit install

Tests are run with tox, you can run the baseline environments before submitting a PR:

$ tox -e py38,linting

Style checks and formatting are done automatically during commit courtesy of pre-commit.


Distributed under the terms of the MIT license.

Security contact information

To report a security vulnerability, please use the Tidelift security contact. Tidelift will coordinate the fix and disclosure.

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