443 lines
15 KiB
ReStructuredText
443 lines
15 KiB
ReStructuredText
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Monkeypatching/mocking modules and environments
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================================================================
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.. currentmodule:: _pytest.monkeypatch
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Sometimes tests need to invoke functionality which depends
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on global settings or which invokes code which cannot be easily
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tested such as network access. The ``monkeypatch`` fixture
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helps you to safely set/delete an attribute, dictionary item or
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environment variable, or to modify ``sys.path`` for importing.
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The ``monkeypatch`` fixture provides these helper methods for safely patching and mocking
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functionality in tests:
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.. code-block:: python
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monkeypatch.setattr(obj, name, value, raising=True)
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monkeypatch.delattr(obj, name, raising=True)
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monkeypatch.setitem(mapping, name, value)
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monkeypatch.delitem(obj, name, raising=True)
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monkeypatch.setenv(name, value, prepend=False)
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monkeypatch.delenv(name, raising=True)
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monkeypatch.syspath_prepend(path)
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monkeypatch.chdir(path)
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All modifications will be undone after the requesting
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test function or fixture has finished. The ``raising``
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parameter determines if a ``KeyError`` or ``AttributeError``
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will be raised if the target of the set/deletion operation does not exist.
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Consider the following scenarios:
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1. Modifying the behavior of a function or the property of a class for a test e.g.
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there is an API call or database connection you will not make for a test but you know
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what the expected output should be. Use :py:meth:`monkeypatch.setattr` to patch the
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function or property with your desired testing behavior. This can include your own functions.
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Use :py:meth:`monkeypatch.delattr` to remove the function or property for the test.
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2. Modifying the values of dictionaries e.g. you have a global configuration that
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you want to modify for certain test cases. Use :py:meth:`monkeypatch.setitem` to patch the
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dictionary for the test. :py:meth:`monkeypatch.delitem` can be used to remove items.
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3. Modifying environment variables for a test e.g. to test program behavior if an
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environment variable is missing, or to set multiple values to a known variable.
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:py:meth:`monkeypatch.setenv` and :py:meth:`monkeypatch.delenv` can be used for
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these patches.
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4. Use ``monkeypatch.setenv("PATH", value, prepend=os.pathsep)`` to modify ``$PATH``, and
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:py:meth:`monkeypatch.chdir` to change the context of the current working directory
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during a test.
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5. Use py:meth:`monkeypatch.syspath_prepend` to modify ``sys.path`` which will also
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call :py:meth:`pkg_resources.fixup_namespace_packages` and :py:meth:`importlib.invalidate_caches`.
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See the `monkeypatch blog post`_ for some introduction material
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and a discussion of its motivation.
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.. _`monkeypatch blog post`: http://tetamap.wordpress.com/2009/03/03/monkeypatching-in-unit-tests-done-right/
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Simple example: monkeypatching functions
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----------------------------------------
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Consider a scenario where you are working with user directories. In the context of
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testing, you do not want your test to depend on the running user. ``monkeypatch``
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can be used to patch functions dependent on the user to always return a
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specific value.
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In this example, :py:meth:`monkeypatch.setattr` is used to patch ``Path.home``
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so that the known testing path ``Path("/abc")`` is always used when the test is run.
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This removes any dependency on the running user for testing purposes.
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:py:meth:`monkeypatch.setattr` must be called before the function which will use
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the patched function is called.
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After the test function finishes the ``Path.home`` modification will be undone.
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.. code-block:: python
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# contents of test_module.py with source code and the test
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from pathlib import Path
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def getssh():
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"""Simple function to return expanded homedir ssh path."""
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return Path.home() / ".ssh"
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def test_getssh(monkeypatch):
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# mocked return function to replace Path.home
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# always return '/abc'
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def mockreturn():
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return Path("/abc")
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# Application of the monkeypatch to replace Path.home
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# with the behavior of mockreturn defined above.
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monkeypatch.setattr(Path, "home", mockreturn)
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# Calling getssh() will use mockreturn in place of Path.home
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# for this test with the monkeypatch.
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x = getssh()
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assert x == Path("/abc/.ssh")
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Monkeypatching returned objects: building mock classes
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------------------------------------------------------
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:py:meth:`monkeypatch.setattr` can be used in conjunction with classes to mock returned
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objects from functions instead of values.
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Imagine a simple function to take an API url and return the json response.
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.. code-block:: python
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# contents of app.py, a simple API retrieval example
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import requests
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def get_json(url):
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"""Takes a URL, and returns the JSON."""
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r = requests.get(url)
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return r.json()
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We need to mock ``r``, the returned response object for testing purposes.
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The mock of ``r`` needs a ``.json()`` method which returns a dictionary.
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This can be done in our test file by defining a class to represent ``r``.
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.. code-block:: python
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# contents of test_app.py, a simple test for our API retrieval
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# import requests for the purposes of monkeypatching
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import requests
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# our app.py that includes the get_json() function
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# this is the previous code block example
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import app
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# custom class to be the mock return value
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# will override the requests.Response returned from requests.get
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class MockResponse:
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# mock json() method always returns a specific testing dictionary
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@staticmethod
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def json():
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return {"mock_key": "mock_response"}
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def test_get_json(monkeypatch):
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# Any arguments may be passed and mock_get() will always return our
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# mocked object, which only has the .json() method.
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def mock_get(*args, **kwargs):
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return MockResponse()
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# apply the monkeypatch for requests.get to mock_get
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monkeypatch.setattr(requests, "get", mock_get)
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# app.get_json, which contains requests.get, uses the monkeypatch
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result = app.get_json("https://fakeurl")
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assert result["mock_key"] == "mock_response"
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``monkeypatch`` applies the mock for ``requests.get`` with our ``mock_get`` function.
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The ``mock_get`` function returns an instance of the ``MockResponse`` class, which
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has a ``json()`` method defined to return a known testing dictionary and does not
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require any outside API connection.
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You can build the ``MockResponse`` class with the appropriate degree of complexity for
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the scenario you are testing. For instance, it could include an ``ok`` property that
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always returns ``True``, or return different values from the ``json()`` mocked method
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based on input strings.
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This mock can be shared across tests using a ``fixture``:
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.. code-block:: python
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# contents of test_app.py, a simple test for our API retrieval
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import pytest
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import requests
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# app.py that includes the get_json() function
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import app
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# custom class to be the mock return value of requests.get()
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class MockResponse:
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@staticmethod
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def json():
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return {"mock_key": "mock_response"}
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# monkeypatched requests.get moved to a fixture
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@pytest.fixture
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def mock_response(monkeypatch):
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"""Requests.get() mocked to return {'mock_key':'mock_response'}."""
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def mock_get(*args, **kwargs):
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return MockResponse()
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monkeypatch.setattr(requests, "get", mock_get)
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# notice our test uses the custom fixture instead of monkeypatch directly
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def test_get_json(mock_response):
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result = app.get_json("https://fakeurl")
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assert result["mock_key"] == "mock_response"
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Furthermore, if the mock was designed to be applied to all tests, the ``fixture`` could
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be moved to a ``conftest.py`` file and use the with ``autouse=True`` option.
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Global patch example: preventing "requests" from remote operations
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------------------------------------------------------------------
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If you want to prevent the "requests" library from performing http
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requests in all your tests, you can do:
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.. code-block:: python
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# contents of conftest.py
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import pytest
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@pytest.fixture(autouse=True)
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def no_requests(monkeypatch):
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"""Remove requests.sessions.Session.request for all tests."""
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monkeypatch.delattr("requests.sessions.Session.request")
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This autouse fixture will be executed for each test function and it
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will delete the method ``request.session.Session.request``
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so that any attempts within tests to create http requests will fail.
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.. note::
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Be advised that it is not recommended to patch builtin functions such as ``open``,
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``compile``, etc., because it might break pytest's internals. If that's
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unavoidable, passing ``--tb=native``, ``--assert=plain`` and ``--capture=no`` might
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help although there's no guarantee.
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.. note::
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Mind that patching ``stdlib`` functions and some third-party libraries used by pytest
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might break pytest itself, therefore in those cases it is recommended to use
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:meth:`MonkeyPatch.context` to limit the patching to the block you want tested:
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.. code-block:: python
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import functools
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def test_partial(monkeypatch):
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with monkeypatch.context() as m:
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m.setattr(functools, "partial", 3)
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assert functools.partial == 3
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See issue `#3290 <https://github.com/pytest-dev/pytest/issues/3290>`_ for details.
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Monkeypatching environment variables
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------------------------------------
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If you are working with environment variables you often need to safely change the values
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or delete them from the system for testing purposes. ``monkeypatch`` provides a mechanism
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to do this using the ``setenv`` and ``delenv`` method. Our example code to test:
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.. code-block:: python
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# contents of our original code file e.g. code.py
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import os
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def get_os_user_lower():
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"""Simple retrieval function.
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Returns lowercase USER or raises EnvironmentError."""
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username = os.getenv("USER")
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if username is None:
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raise OSError("USER environment is not set.")
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return username.lower()
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There are two potential paths. First, the ``USER`` environment variable is set to a
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value. Second, the ``USER`` environment variable does not exist. Using ``monkeypatch``
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both paths can be safely tested without impacting the running environment:
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.. code-block:: python
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# contents of our test file e.g. test_code.py
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import pytest
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def test_upper_to_lower(monkeypatch):
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"""Set the USER env var to assert the behavior."""
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monkeypatch.setenv("USER", "TestingUser")
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assert get_os_user_lower() == "testinguser"
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def test_raise_exception(monkeypatch):
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"""Remove the USER env var and assert EnvironmentError is raised."""
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monkeypatch.delenv("USER", raising=False)
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with pytest.raises(OSError):
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_ = get_os_user_lower()
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This behavior can be moved into ``fixture`` structures and shared across tests:
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.. code-block:: python
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# contents of our test file e.g. test_code.py
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import pytest
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@pytest.fixture
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def mock_env_user(monkeypatch):
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monkeypatch.setenv("USER", "TestingUser")
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@pytest.fixture
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def mock_env_missing(monkeypatch):
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monkeypatch.delenv("USER", raising=False)
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# notice the tests reference the fixtures for mocks
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def test_upper_to_lower(mock_env_user):
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assert get_os_user_lower() == "testinguser"
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def test_raise_exception(mock_env_missing):
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with pytest.raises(OSError):
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_ = get_os_user_lower()
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Monkeypatching dictionaries
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---------------------------
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:py:meth:`monkeypatch.setitem` can be used to safely set the values of dictionaries
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to specific values during tests. Take this simplified connection string example:
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.. code-block:: python
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# contents of app.py to generate a simple connection string
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DEFAULT_CONFIG = {"user": "user1", "database": "db1"}
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def create_connection_string(config=None):
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"""Creates a connection string from input or defaults."""
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config = config or DEFAULT_CONFIG
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return f"User Id={config['user']}; Location={config['database']};"
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For testing purposes we can patch the ``DEFAULT_CONFIG`` dictionary to specific values.
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.. code-block:: python
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# contents of test_app.py
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# app.py with the connection string function (prior code block)
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import app
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def test_connection(monkeypatch):
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# Patch the values of DEFAULT_CONFIG to specific
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# testing values only for this test.
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monkeypatch.setitem(app.DEFAULT_CONFIG, "user", "test_user")
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monkeypatch.setitem(app.DEFAULT_CONFIG, "database", "test_db")
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# expected result based on the mocks
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expected = "User Id=test_user; Location=test_db;"
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# the test uses the monkeypatched dictionary settings
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result = app.create_connection_string()
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assert result == expected
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You can use the :py:meth:`monkeypatch.delitem` to remove values.
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.. code-block:: python
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# contents of test_app.py
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import pytest
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# app.py with the connection string function
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import app
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def test_missing_user(monkeypatch):
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# patch the DEFAULT_CONFIG t be missing the 'user' key
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monkeypatch.delitem(app.DEFAULT_CONFIG, "user", raising=False)
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# Key error expected because a config is not passed, and the
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# default is now missing the 'user' entry.
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with pytest.raises(KeyError):
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_ = app.create_connection_string()
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The modularity of fixtures gives you the flexibility to define
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separate fixtures for each potential mock and reference them in the needed tests.
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.. code-block:: python
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# contents of test_app.py
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import pytest
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# app.py with the connection string function
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import app
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# all of the mocks are moved into separated fixtures
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@pytest.fixture
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def mock_test_user(monkeypatch):
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"""Set the DEFAULT_CONFIG user to test_user."""
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monkeypatch.setitem(app.DEFAULT_CONFIG, "user", "test_user")
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@pytest.fixture
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def mock_test_database(monkeypatch):
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"""Set the DEFAULT_CONFIG database to test_db."""
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monkeypatch.setitem(app.DEFAULT_CONFIG, "database", "test_db")
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@pytest.fixture
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def mock_missing_default_user(monkeypatch):
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"""Remove the user key from DEFAULT_CONFIG"""
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monkeypatch.delitem(app.DEFAULT_CONFIG, "user", raising=False)
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# tests reference only the fixture mocks that are needed
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def test_connection(mock_test_user, mock_test_database):
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expected = "User Id=test_user; Location=test_db;"
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result = app.create_connection_string()
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assert result == expected
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def test_missing_user(mock_missing_default_user):
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with pytest.raises(KeyError):
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_ = app.create_connection_string()
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.. currentmodule:: _pytest.monkeypatch
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API Reference
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-------------
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Consult the docs for the :class:`MonkeyPatch` class.
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